diff --git a/pycorrfit/PyCorrFit.py b/pycorrfit/PyCorrFit.py
index d8985c60..d0bd9c90 100644
--- a/pycorrfit/PyCorrFit.py
+++ b/pycorrfit/PyCorrFit.py
@@ -1,11 +1,10 @@
+from pycorrfit.gui import main
"""PyCorrFit loader"""
from os.path import dirname, abspath, split
import sys
sys.path = [split(abspath(dirname(__file__)))[0]] + sys.path
-from pycorrfit.gui import main
-
if __name__ == "__main__":
main.Main()
diff --git a/pycorrfit/correlation.py b/pycorrfit/correlation.py
index 3b54efd8..de582806 100644
--- a/pycorrfit/correlation.py
+++ b/pycorrfit/correlation.py
@@ -12,6 +12,7 @@
class Correlation(object):
""" unifies correlation curve handling
"""
+
def __init__(self, backgrounds=[], correlation=None, corr_type="AC",
filename=None, fit_algorithm="Lev-Mar",
fit_model=6000, fit_ival=(0, 0),
@@ -93,7 +94,7 @@ def __repr__(self):
else:
c = "CC"
text = "{} correlation '{}' with {} traces".format(
- c, self.title, len(self._traces))
+ c, self.title, len(self._traces))
return text
def background_replace(self, channel, background):
@@ -144,7 +145,8 @@ def backgrounds(self, value):
elif isinstance(v, Trace):
backgrounds.append(v)
else:
- raise ValueError("Each background must be instance of Trace or ndarray")
+ raise ValueError(
+ "Each background must be instance of Trace or ndarray")
self._backgrounds = backgrounds
@property
@@ -321,12 +323,13 @@ def fit_model(self, value):
else:
raise NotImplementedError("Unknown model identifier")
- if newmodel != self._fit_model :
+ if newmodel != self._fit_model:
self._fit_model = newmodel
# overwrite fitting parameters
self._fit_parameters = self._fit_model.default_values
self._fit_parameters_variables = self._fit_model.default_variables
- self._fit_parameters_range = np.zeros((len(self._fit_parameters), 2))
+ self._fit_parameters_range = np.zeros(
+ (len(self._fit_parameters), 2))
self.normparm = None
@property
@@ -390,8 +393,8 @@ def fit_parameters_range(self, value):
expect_shape = (self.fit_parameters.shape[0], 2)
if value.shape != expect_shape:
msg = "Expected shape of fit parameters: {} (vs {})".format(
- expect_shape, value.shape
- )
+ expect_shape, value.shape
+ )
raise ValueError(msg)
self._fit_parameters_range = value
@@ -399,7 +402,8 @@ def fit_parameters_range(self, value):
def fit_parameters_variable(self):
"""which parameters are variable during fitting"""
if self._fit_parameters_variable is None:
- self._fit_parameters_variable = np.array(self.fit_model.default_variables, dtype=bool)
+ self._fit_parameters_variable = np.array(
+ self.fit_model.default_variables, dtype=bool)
return self._fit_parameters_variable
@fit_parameters_variable.setter
@@ -408,7 +412,7 @@ def fit_parameters_variable(self, value):
expect_size = self.fit_parameters.shape[0]
if value.shape[0] != expect_size:
msg = "Fit parameter variables must have size {}!".format(
- expect_size)
+ expect_size)
raise ValueError(msg)
self._fit_parameters_variable = value
@@ -416,17 +420,18 @@ def fit_parameters_variable(self, value):
def lag_time(self):
"""logarithmic lag time axis"""
if self.correlation is not None:
- return self._correlation[:,0].copy()
+ return self._correlation[:, 0].copy()
elif self._lag_time is not None:
return self._lag_time
else:
# some default lag time
- return 10**np.linspace(-6,8,1001)
+ return 10**np.linspace(-6, 8, 1001)
@lag_time.setter
def lag_time(self, value):
if self.correlation is not None:
- warnings.warn("Setting lag time not possible, because of existing correlation")
+ warnings.warn(
+ "Setting lag time not possible, because of existing correlation")
else:
self._lag_time = value
@@ -441,8 +446,8 @@ def modeled(self):
# perform parameter normalization
lag = self.lag_time
modeled = np.zeros((lag.shape[0], 2))
- modeled[:,0] = lag
- modeled[:,1] = self.fit_model(self.fit_parameters, lag)
+ modeled[:, 0] = lag
+ modeled[:, 1] = self.fit_model(self.fit_parameters, lag)
return modeled.copy()
@property
@@ -455,7 +460,7 @@ def modeled_fit(self):
def modeled_plot(self):
"""fitted data values, same shape as self.correlation_fit"""
toplot = self.modeled_fit
- toplot[:,1] *= self.normalize_factor
+ toplot[:, 1] *= self.normalize_factor
return toplot
@property
@@ -479,14 +484,14 @@ def residuals(self):
if self.correlation is None:
raise ValueError("Cannot compute residuals; No correlation given!")
residuals = self.correlation.copy()
- residuals[:,1] -= self.modeled[:,1]
+ residuals[:, 1] -= self.modeled[:, 1]
return residuals
@property
def residuals_fit(self):
"""fit residuals, same shape as self.correlation_fit"""
residuals_fit = self.correlation_fit.copy()
- residuals_fit[:,1] -= self.modeled_fit[:,1]
+ residuals_fit[:, 1] -= self.modeled_fit[:, 1]
return residuals_fit
@property
@@ -495,7 +500,7 @@ def residuals_plot(self):
cp = self.correlation_plot
if cp is not None:
residuals_plot = self.correlation_plot.copy()
- residuals_plot[:,1] -= self.modeled_plot[:,1]
+ residuals_plot[:, 1] -= self.modeled_plot[:, 1]
return residuals_plot
def set_weights(self, type_name, data):
@@ -532,7 +537,8 @@ def traces(self, value):
elif isinstance(v, Trace):
traces.append(v)
else:
- raise ValueError("Each trace must be instance of Trace or ndarray")
+ raise ValueError(
+ "Each trace must be instance of Trace or ndarray")
self._traces = traces
if len(self._traces) == 2:
diff --git a/pycorrfit/fit.py b/pycorrfit/fit.py
index 412d5fee..5286b4e5 100644
--- a/pycorrfit/fit.py
+++ b/pycorrfit/fit.py
@@ -10,6 +10,7 @@
class Constraint(object):
""" Class to translate fit constraints to lmfit syntax.
"""
+
def __init__(self, constraint, fit_bool, fit_bounds, fit_values):
"""
Parameters
@@ -45,7 +46,7 @@ def parameters(self):
"""
Returns list of dict for each parameter.
"""
- parms = [ it for it in self.constraint if isinstance(it, int)]
+ parms = [it for it in self.constraint if isinstance(it, int)]
id2 = self.constraint.index(parms[1])
p1 = {"id": parms[0],
@@ -56,7 +57,7 @@ def parameters(self):
p2 = {"id": parms[1],
"bool": self.fit_bool[parms[1]],
- "sign": ( +1 if id2==2 else -1),
+ "sign": (+1 if id2 == 2 else -1),
"value": self.fit_values[parms[1]]
}
@@ -64,7 +65,7 @@ def parameters(self):
@property
def operator(self):
- strval = [ it for it in self.constraint if not isinstance(it, int)]
+ strval = [it for it in self.constraint if not isinstance(it, int)]
return strval[0]
@property
@@ -153,46 +154,51 @@ def get_lmfit_parameter_kwargs(self):
if p1["bool"] and p2["bool"]:
if op == "<":
- #p1 < (-)p2 + 1.2
- #-> p1 = (-)p2 - d12 + 1.2
- #-> d12 = (-)p2 - p1 + 1.2
- #-> d12 > 0
+ # p1 < (-)p2 + 1.2
+ # -> p1 = (-)p2 - d12 + 1.2
+ # -> d12 = (-)p2 - p1 + 1.2
+ # -> d12 > 0
deltaname = "delta_{}_{}".format(p1["id"], p2["id"])
kwdelt = {}
kwdelt["name"] = deltaname
- kwdelt["value"] = p2["bool"]*self.fit_values[p2["id"]] - self.fit_values[p1["id"]]
+ kwdelt["value"] = p2["bool"] * \
+ self.fit_values[p2["id"]] - self.fit_values[p1["id"]]
kwdelt["vary"] = True
- kwdelt["min"] = 0 # note: enforces "<=" (not "<")
+ kwdelt["min"] = 0 # note: enforces "<=" (not "<")
kwdelt["max"] = np.inf
kwp1 = {}
kwp1["name"] = "parm{:04d}".format(p1["id"])
# this condition deals with negative numbers
kwp1["expr"] = "{MIN} if {COMP} < {MIN} else {MAX} if {COMP} > {MAX} else {COMP}".format(
- COMP="{}*parm{:04d}-{}+{:.14f}".format(p2["sign"], p2["id"], deltaname, ofs),
- MIN=self.fit_bounds[p1["id"]][0],
- MAX=self.fit_bounds[p1["id"]][1])
+ COMP="{}*parm{:04d}-{}+{:.14f}".format(
+ p2["sign"], p2["id"], deltaname, ofs),
+ MIN=self.fit_bounds[p1["id"]][0],
+ MAX=self.fit_bounds[p1["id"]][1])
kwargs = [kwdelt, kwp1]
elif op == ">":
- #p1 > (-)p2 + 1.2
- #-> p1 = (-)p2 + d12 + 1.2
- #-> d12 = p1 - (-)p2 - 1.2
- #-> d12 > 0
+ # p1 > (-)p2 + 1.2
+ # -> p1 = (-)p2 + d12 + 1.2
+ # -> d12 = p1 - (-)p2 - 1.2
+ # -> d12 > 0
deltaname = "delta_{}_{}".format(p1["id"], p2["id"])
kwdelt = {}
kwdelt["name"] = deltaname
- kwdelt["value"] = self.fit_values[p1["id"]] - p2["bool"]*self.fit_values[p2["id"]]
+ kwdelt["value"] = self.fit_values[p1["id"]] - \
+ p2["bool"]*self.fit_values[p2["id"]]
kwdelt["vary"] = True
- kwdelt["min"] = 0 # note: enforces ">=" (not ">")
- kwdelt["max"] = np.inf #self.fit_bounds[p1["id"]][1] + max(-p2["sign"]*self.fit_bounds[p2["id"]]) - ofs
+ kwdelt["min"] = 0 # note: enforces ">=" (not ">")
+ # self.fit_bounds[p1["id"]][1] + max(-p2["sign"]*self.fit_bounds[p2["id"]]) - ofs
+ kwdelt["max"] = np.inf
kwp1 = {}
kwp1["name"] = "parm{:04d}".format(p1["id"])
# this condition deals with negative numbers
kwp1["expr"] = "{MIN} if {COMP} < {MIN} else {MAX} if {COMP} > {MAX} else {COMP}".format(
- COMP="{}*parm{:04d}+{}+{:.14f}".format(p2["sign"], p2["id"], deltaname, ofs),
- MIN=self.fit_bounds[p1["id"]][0],
- MAX=self.fit_bounds[p1["id"]][1])
+ COMP="{}*parm{:04d}+{}+{:.14f}".format(
+ p2["sign"], p2["id"], deltaname, ofs),
+ MIN=self.fit_bounds[p1["id"]][0],
+ MAX=self.fit_bounds[p1["id"]][1])
kwargs = [kwdelt, kwp1]
@@ -202,10 +208,10 @@ def get_lmfit_parameter_kwargs(self):
return kwargs
-
class Fit(object):
""" Used for fitting FCS data to models.
"""
+
def __init__(self, correlations=[], global_fit=False,
global_fit_variables=[],
uselatex=False, verbose=0):
@@ -250,16 +256,16 @@ def __init__(self, correlations=[], global_fit=False,
# Set fitting options
self.fit_algorithm = corr.fit_algorithm
# Get the data required for fitting
- self.x = corr.correlation_fit[:,0]
- self.y = corr.correlation_fit[:,1]
+ self.x = corr.correlation_fit[:, 0]
+ self.y = corr.correlation_fit[:, 1]
# fit_bool: True for variable
self.fit_bool = corr.fit_parameters_variable.copy()
self.fit_parm = corr.fit_parameters.copy()
self.fit_bound = copy.copy(corr.fit_parameters_range)
self.is_weighted_fit = corr.is_weighted_fit
self.fit_weights = Fit.compute_weights(corr,
- verbose=verbose,
- uselatex=uselatex)
+ verbose=verbose,
+ uselatex=uselatex)
self.fit_parm_names = corr.fit_model.parameters[0]
self.func = corr.fit_model.function
self.check_parms = corr.check_parms
@@ -290,8 +296,8 @@ def __init__(self, correlations=[], global_fit=False,
varbound = [] # list of fitting boundaries
self.is_weighted_fit = None
for corr in self.correlations:
- xtemp.append(corr.correlation_fit[:,0])
- ytemp.append(corr.correlation_fit[:,1])
+ xtemp.append(corr.correlation_fit[:, 0])
+ ytemp.append(corr.correlation_fit[:, 1])
weights.append(Fit.compute_weights(corr))
ids.append(len(xtemp[-1])+ids[-1])
cmodels.append(corr.fit_model)
@@ -320,12 +326,12 @@ def __init__(self, correlations=[], global_fit=False,
self.fit_parm_names = varin
self.fit_bound = varbound
self.constraints = []
- warnings.warn("Constraints are not supported yet for global fitting.")
-
+ warnings.warn(
+ "Constraints are not supported yet for global fitting.")
def parameters_global_to_local(parameters, iicorr, varin=varin,
- initpar=initpar,
- correlations=correlations):
+ initpar=initpar,
+ correlations=correlations):
"""
With global `parameters` and an id `iicorr` pointing at
the correlation in `self.correlations`, return the
@@ -337,7 +343,8 @@ def parameters_global_to_local(parameters, iicorr, varin=varin,
for kk, pn in enumerate(mod.parameters[0]):
if pn in varin:
# edit that parameter
- fit_parm[kk] = parameters[np.where(np.array(varin)==pn)[0]]
+ fit_parm[kk] = parameters[np.where(
+ np.array(varin) == pn)[0]]
return fit_parm
def parameters_local_to_global(parameters, iicorr, fit_parm,
@@ -351,7 +358,8 @@ def parameters_local_to_global(parameters, iicorr, fit_parm,
for kk, pn in enumerate(mod.parameters[0]):
if pn in varin:
# edit that parameter
- parameters[np.where(np.array(varin)==pn)[0]] = fit_parm[kk]
+ parameters[np.where(np.array(varin) == pn)[
+ 0]] = fit_parm[kk]
return parameters
# Create function for fitting using ids
@@ -394,7 +402,6 @@ def global_check_parms(parameters,
# save fit data in correlation class
corr.fit_results = self.get_fit_results(corr)
-
def get_fit_results(self, correlation):
"""
Return a dictionary with all information about the performed fit.
@@ -403,14 +410,14 @@ def get_fit_results(self, correlation):
"""
c = correlation
d = {
- "chi2" : self.chi_squared,
- "chi2 type" : self.chi_squared_type,
- "weighted fit" : c.is_weighted_fit,
- "fit algorithm" : c.fit_algorithm,
- "fit result" : 1*c.fit_parameters,
- "fit parameters" : 1*np.where(c.fit_parameters_variable)[0],
- "fit weights" : 1*self.compute_weights(c)
- }
+ "chi2": self.chi_squared,
+ "chi2 type": self.chi_squared_type,
+ "weighted fit": c.is_weighted_fit,
+ "fit algorithm": c.fit_algorithm,
+ "fit result": 1*c.fit_parameters,
+ "fit parameters": 1*np.where(c.fit_parameters_variable)[0],
+ "fit weights": 1*self.compute_weights(c)
+ }
if c.is_weighted_fit:
d["weighted fit type"] = c.fit_weight_type
@@ -422,7 +429,6 @@ def get_fit_results(self, correlation):
return d
-
@property
def chi_squared(self):
""" Calculate displayed ChiĀ²
@@ -445,12 +451,11 @@ def chi_squared(self):
variance = self.fit_weights**2
chi2 = np.sum((self.y-fitted)**2/variance) / dof
else:
- chi2 = self.fit_function_scalar(self.fit_parm, self.x, self.y, self.fit_weights)
-
+ chi2 = self.fit_function_scalar(
+ self.fit_parm, self.x, self.y, self.fit_weights)
return chi2
-
@property
def chi_squared_type(self):
""" The type of ChiĀ² that currently applies.
@@ -470,7 +475,6 @@ def chi_squared_type(self):
else:
raise ValueError("Unknown weight type!")
-
@staticmethod
def compute_weights(correlation, verbose=0, uselatex=False):
""" computes and returns weights of the same length as
@@ -492,9 +496,9 @@ def compute_weights(correlation, verbose=0, uselatex=False):
if cdat is None:
raise ValueError("Cannot compute weights; No correlation given!")
cdatfit = corr.correlation_fit
- x_full = cdat[:,0]
- y_full = cdat[:,1]
- x_fit = cdatfit[:,0]
+ x_full = cdat[:, 0]
+ y_full = cdat[:, 1]
+ x_fit = cdatfit[:, 0]
#y_fit = cdatfit[:,1]
dataweights = np.ones_like(x_fit)
@@ -503,7 +507,8 @@ def compute_weights(correlation, verbose=0, uselatex=False):
weight_spread = int(weight_data)
except:
if verbose > 1:
- warnings.warn("Could not get weight spread for spline. Setting it to 3.")
+ warnings.warn(
+ "Could not get weight spread for spline. Setting it to 3.")
weight_spread = 3
if weight_type[:6] == "spline":
@@ -541,13 +546,13 @@ def compute_weights(correlation, verbose=0, uselatex=False):
ys = spintp.splev(xs, tck, der=0)
except:
if verbose > 0:
- raise ValueError("Could not find spline fit with "+\
+ raise ValueError("Could not find spline fit with " +
"{} knots.".format(knotnumber))
return
if verbose > 0:
- ## If plotting module is available:
+ # If plotting module is available:
#name = "spline fit: "+str(knotnumber)+" knots"
- #plotting.savePlotSingle(name, 1*x, 1*y, 1*ys,
+ # plotting.savePlotSingle(name, 1*x, 1*y, 1*ys,
# dirname=".",
# uselatex=uselatex)
# use matplotlib.pylab
@@ -560,7 +565,7 @@ def compute_weights(correlation, verbose=0, uselatex=False):
# Tell the user to install matplotlib
print("Couldn't import pylab! - not Plotting")
- ## Calculation of variance
+ # Calculation of variance
# In some cases, the actual cropping interval from ival[0]
# to ival[1] is chosen, such that the dataweights must be
# calculated from unknown datapoints.
@@ -571,7 +576,7 @@ def compute_weights(correlation, verbose=0, uselatex=False):
# Define start and end positions of the sections from
# where we wish to calculate the dataweights.
# Offset at beginning:
- if i + ival[0] < weight_spread:
+ if i + ival[0] < weight_spread:
# The offset that occurs
offsetstart = weight_spread - i - ival[0]
offsetcrop = 0
@@ -596,7 +601,7 @@ def compute_weights(correlation, verbose=0, uselatex=False):
dataweights[i] *= reference/dividor
# Do not substitute len(y[start:end]) with end-start!
# It is not the same!
- backset = 2*weight_spread + 1 - len(y[start:end]) - offsetstart
+ backset = 2*weight_spread + 1 - len(y[start:end]) - offsetstart
if backset != 0:
reference = 2*weight_spread + 1
dividor = reference - backset
@@ -607,7 +612,7 @@ def compute_weights(correlation, verbose=0, uselatex=False):
pmin = ival[0]
else:
pmin = weight_spread
- if x_full.shape[0] - ival[1] < weight_spread:
+ if x_full.shape[0] - ival[1] < weight_spread:
pmax = x_full.shape[0] - ival[1]
else:
pmax = weight_spread
@@ -618,7 +623,7 @@ def compute_weights(correlation, verbose=0, uselatex=False):
# Define start and end positions of the sections from
# where we wish to calculate the dataweights.
# Offset at beginning:
- if i + ival[0] < weight_spread:
+ if i + ival[0] < weight_spread:
# The offset that occurs
offsetstart = weight_spread - i - ival[0]
offsetcrop = 0
@@ -646,7 +651,8 @@ def compute_weights(correlation, verbose=0, uselatex=False):
dataweights[i] *= reference/dividor
# Do not substitute len(diff[start:end]) with end-start!
# It is not the same!
- backset = 2*weight_spread + 1 - len(diff[start:end]) - offsetstart
+ backset = 2*weight_spread + 1 - \
+ len(diff[start:end]) - offsetstart
if backset != 0:
reference = 2*weight_spread + 1
dividor = reference - backset
@@ -673,7 +679,6 @@ def compute_weights(correlation, verbose=0, uselatex=False):
return dataweights
-
def fit_function(self, params, x, y, weights=1):
"""
objective function that returns the residual (difference between
@@ -684,9 +689,9 @@ def fit_function(self, params, x, y, weights=1):
# Check dataweights for zeros and don't use these
# values for the least squares method.
with np.errstate(divide='ignore'):
- tominimize = np.where(weights!=0,
+ tominimize = np.where(weights != 0,
tominimize/weights, 0)
- ## There might be NaN values because of zero weights:
+ # There might be NaN values because of zero weights:
#tominimize = tominimize[~np.isinf(tominimize)]
return tominimize
@@ -716,14 +721,14 @@ def get_lmfitparm(self):
for pp in range(len(self.fit_parm)):
if not self.fit_bool[pp]:
if self.fit_bound[pp][0] == self.fit_bound[pp][1]:
- self.fit_bound[pp]=[-np.inf, np.inf]
+ self.fit_bound[pp] = [-np.inf, np.inf]
params.add(lmfit.Parameter(name="parm{:04d}".format(pp),
value=self.fit_parm[pp],
vary=self.fit_bool[pp],
min=self.fit_bound[pp][0],
max=self.fit_bound[pp][1],
- )
)
+ )
# Second, summarize the constraints in a dictionary, where
# keys are the parameter indexes of varied parameters.
@@ -743,7 +748,7 @@ def get_lmfitparm(self):
# [1, 0, "<", "2.3"]] -> parm1 + parm0 < 2.3
for pp in range(len(self.fit_parm)):
if self.fit_bool[pp]:
- inconstr = len([ cc for cc in self.constraints if pp in cc])
+ inconstr = len([cc for cc in self.constraints if pp in cc])
kwarglist = []
if inconstr:
@@ -760,10 +765,10 @@ def get_lmfitparm(self):
if len(kwarglist) == 0:
# normal parameter
kwarglist += [{"name": "parm{:04d}".format(pp),
- "value": self.fit_parm[pp],
- "vary": True,
- "min": self.fit_bound[pp][0],
- "max": self.fit_bound[pp][1],
+ "value": self.fit_parm[pp],
+ "vary": True,
+ "min": self.fit_bound[pp][0],
+ "max": self.fit_bound[pp][1],
}]
for kw in kwarglist:
params.add(lmfit.Parameter(**kw))
@@ -833,9 +838,9 @@ def minimize(self):
result = lmfit.minimize(fcn=self.fit_function,
params=params,
method=method,
- kws={"x":self.x,
- "y":self.y,
- "weights":self.fit_weights},
+ kws={"x": self.x,
+ "y": self.y,
+ "weights": self.fit_weights},
**methodkwargs
)
params = result.params
@@ -851,16 +856,16 @@ def minimize(self):
# the parameters that are varied during fitting
parmsbool = Fit.lmfitparm2array(params, attribute="vary")
# The parameters that are stuck
- parmstuck = parmsbool * (parmsinit==parmsres)
+ parmstuck = parmsbool * (parmsinit == parmsres)
parmsres[parmstuck] *= multby
# write changes
self.fit_parm = parmsres
params = self.get_lmfitparm()
- warnings.warn(u"PyCorrFit detected problems in fitting, "+\
- u"detected a stuck parameter, multiplied "+\
- u"it by {}, and fitted again. ".format(multby)+\
+ warnings.warn(u"PyCorrFit detected problems in fitting, " +
+ u"detected a stuck parameter, multiplied " +
+ u"it by {}, and fitted again. ".format(multby) +
u"The stuck parameters are: {}".format(
- np.array(self.fit_parm_names)[parmstuck]))
+ np.array(self.fit_parm_names)[parmstuck]))
elif diff < 1e-8:
# Experience tells us this is good enough.
break
@@ -876,24 +881,23 @@ def minimize(self):
# - lmfit <= 0.9.10: result.covar is None
# - lmfit >= 0.9.11: result.covar is not set
and hasattr(result, "covar")
- and result.covar is not None):
+ and result.covar is not None):
# This is the standard way to minimize the data. Therefore,
# we are a little bit more verbose.
covar = result.covar
try:
self.parmoptim_error = np.diag(covar)
except:
- warnings.warn("PyCorrFit Warning: Error estimate not "+\
- "possible, because we could not "+\
- "calculate covariance matrix. Please "+\
- "try reducing the number of fitting "+\
+ warnings.warn("PyCorrFit Warning: Error estimate not " +
+ "possible, because we could not " +
+ "calculate covariance matrix. Please " +
+ "try reducing the number of fitting " +
"parameters.")
self.parmoptim_error = None
else:
self.parmoptim_error = None
-
def GetAlgorithmStringList():
"""
Get supported fitting algorithms as strings.
@@ -920,10 +924,10 @@ def GetAlgorithmStringList():
# the original one is the least squares fit "leastsq"
Algorithms["Lev-Mar"] = ["leastsq",
"Levenberg-Marquardt",
- {"ftol" : 1.49012e-08,
- "xtol" : 1.49012e-08,
+ {"ftol": 1.49012e-08,
+ "xtol": 1.49012e-08,
}
- ]
+ ]
# simplex
Algorithms["Nelder-Mead"] = ["nelder",
diff --git a/pycorrfit/gui/doc.py b/pycorrfit/gui/doc.py
index b18ff329..75376fc4 100755
--- a/pycorrfit/gui/doc.py
+++ b/pycorrfit/gui/doc.py
@@ -90,19 +90,19 @@ def licence():
def SoftwareUsed():
"""Return some Information about the software used for this program"""
- text = "Python "+sys.version+\
- "\n\nModules:"+\
- "\n - cython "+\
- "\n - lmfit "+lmfit.__version__+\
- "\n - matplotlib "+matplotlib.__version__+\
- "\n - NumPy "+numpy.__version__+\
+ text = "Python "+sys.version +\
+ "\n\nModules:" +\
+ "\n - cython " +\
+ "\n - lmfit "+lmfit.__version__ +\
+ "\n - matplotlib "+matplotlib.__version__ +\
+ "\n - NumPy "+numpy.__version__ +\
"\n - PyYAML "+yaml.__version__ +\
- "\n - SciPy "+scipy.__version__+\
- "\n - simplejson "+simplejson.__version__+\
+ "\n - SciPy "+scipy.__version__ +\
+ "\n - simplejson "+simplejson.__version__ +\
"\n - sympy "+sympy.__version__ +\
"\n - wxPython "+wx.__version__
# Other software
- text += "\n\nOther software:"+\
+ text += "\n\nOther software:" +\
"\n - FCS_point_correlator ({})".format(read_pt3_scripts.version) +\
"\n PicoQuant file format for Python by Dominic Waithe"
if hasattr(sys, 'frozen'):
diff --git a/pycorrfit/gui/edclasses.py b/pycorrfit/gui/edclasses.py
index a0129646..57bb503f 100644
--- a/pycorrfit/gui/edclasses.py
+++ b/pycorrfit/gui/edclasses.py
@@ -7,15 +7,16 @@
import warnings
import matplotlib
-import wx
+import wx
# We do catch warnings about performing this before matplotlib.backends stuff
-#matplotlib.use('WXAgg') # Tells matplotlib to use WxWidgets
+# matplotlib.use('WXAgg') # Tells matplotlib to use WxWidgets
with warnings.catch_warnings():
warnings.simplefilter("ignore")
try:
- matplotlib.use('WXAgg') # Tells matplotlib to use WxWidgets for dialogs
+ # Tells matplotlib to use WxWidgets for dialogs
+ matplotlib.use('WXAgg')
except:
pass
@@ -24,10 +25,10 @@ class ChoicesDialog(wx.Dialog):
def __init__(self, parent, dropdownlist, title, text):
# parent is main frame
self.parent = parent
- #super(ChoicesDialog, self).__init__(parent=parent,
+ # super(ChoicesDialog, self).__init__(parent=parent,
# title=title)
wx.Dialog.__init__(self, parent, -1, title)
- ## Controls
+ # Controls
panel = wx.Panel(self)
# text1
textopen = wx.StaticText(panel, label=text)
@@ -35,7 +36,7 @@ def __init__(self, parent, dropdownlist, title, text):
btnabort = wx.Button(panel, wx.ID_CANCEL)
# Dropdown
self.dropdown = wx.ComboBox(panel, -1, "", (15, 30),
- wx.DefaultSize, dropdownlist, wx.CB_DROPDOWN|wx.CB_READONLY)
+ wx.DefaultSize, dropdownlist, wx.CB_DROPDOWN | wx.CB_READONLY)
self.dropdown.SetSelection(0)
# Bindings
self.Bind(wx.EVT_BUTTON, self.OnOK, btnok)
@@ -50,19 +51,17 @@ def __init__(self, parent, dropdownlist, title, text):
topSizer.Add(btnSizer)
panel.SetSizer(topSizer)
topSizer.Fit(self)
- #self.Show(True)
+ # self.Show(True)
self.SetFocus()
def OnOK(self, event=None):
self.SelcetedID = self.dropdown.GetSelection()
self.EndModal(wx.ID_OK)
-
def OnAbort(self, event=None):
self.EndModal(wx.ID_CANCEL)
-
def save_figure(self, evt=None):
"""
A substitude function for save in:
@@ -70,8 +69,8 @@ def save_figure(self, evt=None):
We want to be able to give parameters such as dirname and filename.
"""
try:
- parent=self.canvas.HACK_parent
- fig=self.canvas.HACK_fig
+ parent = self.canvas.HACK_parent
+ fig = self.canvas.HACK_fig
Page = self.canvas.HACK_Page
add = self.canvas.HACK_append
dirname = parent.dirname
@@ -89,8 +88,8 @@ def save_figure(self, evt=None):
fieltypestring += formats[key]+"(*."+key+")|*."+key+"|"
# remove last |
fieltypestring = fieltypestring[:-1]
- dlg = wx.FileDialog(parent, "Save figure", dirname, filename,
- fieltypestring, wx.FD_SAVE|wx.FD_OVERWRITE_PROMPT)
+ dlg = wx.FileDialog(parent, "Save figure", dirname, filename,
+ fieltypestring, wx.FD_SAVE | wx.FD_OVERWRITE_PROMPT)
# png is default
dlg.SetFilterIndex(keys.index("png"))
# user cannot do anything until he clicks "OK"
@@ -104,7 +103,7 @@ def save_figure(self, evt=None):
savename = filename
try:
self.canvas.figure.savefig(savename)
- except: # RuntimeError:
+ except: # RuntimeError:
# The file does not seem to be what it seems to be.
info = sys.exc_info()
errstr = "Could not latex output:\n"
@@ -113,8 +112,8 @@ def save_figure(self, evt=None):
errstr += str(info[1])+"\n"
for tb_item in traceback.format_tb(info[2]):
errstr += tb_item
- wx.MessageDialog(parent, errstr, "Error",
- style=wx.ICON_ERROR|wx.OK|wx.STAY_ON_TOP)
+ wx.MessageDialog(parent, errstr, "Error",
+ style=wx.ICON_ERROR | wx.OK | wx.STAY_ON_TOP)
else:
dirname = dlg.GetDirectory()
try:
@@ -127,37 +126,39 @@ class MyScrolledDialog(wx.Dialog):
def __init__(self, parent, overtext, readtext, title):
wx.Dialog.__init__(self, parent, title=title)
overtext = wx.StaticText(self, label=overtext)
- text = wx.TextCtrl(self, -1, readtext, size=(500,400),
+ text = wx.TextCtrl(self, -1, readtext, size=(500, 400),
style=wx.TE_MULTILINE | wx.TE_READONLY)
- sizer = wx.BoxSizer(wx.VERTICAL )
+ sizer = wx.BoxSizer(wx.VERTICAL)
btnsizer = wx.BoxSizer()
- btn = wx.Button(self, wx.ID_OK)#, "OK ")
+ btn = wx.Button(self, wx.ID_OK) # , "OK ")
btnsizer.Add(btn, 0, wx.ALL, 5)
- btnsizer.Add((5,-1), 0, wx.ALL, 5)
- btn = wx.Button(self, wx.ID_CANCEL)#, "Abort ")
+ btnsizer.Add((5, -1), 0, wx.ALL, 5)
+ btn = wx.Button(self, wx.ID_CANCEL) # , "Abort ")
btnsizer.Add(btn, 0, wx.ALL, 5)
- sizer.Add(overtext, 0, wx.EXPAND|wx.ALL, 5)
- sizer.Add(text, 0, wx.EXPAND|wx.ALL, 5)
- sizer.Add(btnsizer, 0, wx.EXPAND|wx.ALIGN_CENTER_VERTICAL|wx.ALL, 5)
+ sizer.Add(overtext, 0, wx.EXPAND | wx.ALL, 5)
+ sizer.Add(text, 0, wx.EXPAND | wx.ALL, 5)
+ sizer.Add(btnsizer, 0, wx.EXPAND |
+ wx.ALIGN_CENTER_VERTICAL | wx.ALL, 5)
self.SetSizerAndFit(sizer)
-
-
+
+
class MyOKAbortDialog(wx.Dialog):
def __init__(self, parent, text, title):
wx.Dialog.__init__(self, parent, title=title)
overtext = wx.StaticText(self, label=text)
- sizer = wx.BoxSizer(wx.VERTICAL )
+ sizer = wx.BoxSizer(wx.VERTICAL)
btnsizer = wx.BoxSizer()
- btn = wx.Button(self, wx.ID_OK)#, "OK ")
+ btn = wx.Button(self, wx.ID_OK) # , "OK ")
btnsizer.Add(btn, 0, wx.ALL, 5)
- btnsizer.Add((5,-1), 0, wx.ALL, 5)
- btn = wx.Button(self, wx.ID_CANCEL)#, "Abort ")
+ btnsizer.Add((5, -1), 0, wx.ALL, 5)
+ btn = wx.Button(self, wx.ID_CANCEL) # , "Abort ")
btnsizer.Add(btn, 0, wx.ALL, 5)
- sizer.Add(overtext, 0, wx.EXPAND|wx.ALL, 5)
- sizer.Add(btnsizer, 0, wx.EXPAND|wx.ALIGN_CENTER_VERTICAL|wx.ALL, 5)
+ sizer.Add(overtext, 0, wx.EXPAND | wx.ALL, 5)
+ sizer.Add(btnsizer, 0, wx.EXPAND |
+ wx.ALIGN_CENTER_VERTICAL | wx.ALL, 5)
self.SetSizerAndFit(sizer)
-
-
+
+
class MyYesNoAbortDialog(wx.Dialog):
def __init__(self, parent, text, title):
wx.Dialog.__init__(self, parent, title=title)
@@ -167,18 +168,19 @@ def __init__(self, parent, text, title):
btn1 = wx.Button(self, wx.ID_YES)
#btn1.Bind(wx.EVT_BTN, self.YES)
btnsizer.Add(btn1, 0, wx.ALL, 5)
- btnsizer.Add((1,-1), 0, wx.ALL, 5)
+ btnsizer.Add((1, -1), 0, wx.ALL, 5)
btn2 = wx.Button(self, wx.ID_NO)
btnsizer.Add(btn2, 0, wx.ALL, 5)
- btnsizer.Add((1,-1), 0, wx.ALL, 5)
+ btnsizer.Add((1, -1), 0, wx.ALL, 5)
btn3 = wx.Button(self, wx.ID_CANCEL)
btnsizer.Add(btn3, 0, wx.ALL, 5)
- sizer.Add(overtext, 0, wx.EXPAND|wx.ALL, 5)
- sizer.Add(btnsizer, 0, wx.EXPAND|wx.ALIGN_CENTER_VERTICAL|wx.ALL, 5)
+ sizer.Add(overtext, 0, wx.EXPAND | wx.ALL, 5)
+ sizer.Add(btnsizer, 0, wx.EXPAND |
+ wx.ALIGN_CENTER_VERTICAL | wx.ALL, 5)
self.SetSizerAndFit(sizer)
self.SetFocus()
self.Show()
-
+
def YES(self, e):
self.EndModal(wx.ID_YES)
diff --git a/pycorrfit/gui/frontend.py b/pycorrfit/gui/frontend.py
index 5036a508..90ad8dc4 100644
--- a/pycorrfit/gui/frontend.py
+++ b/pycorrfit/gui/frontend.py
@@ -37,10 +37,11 @@
########################################################################
class ExceptionDialog(wx.MessageDialog):
""""""
+
def __init__(self, msg):
"""Constructor"""
wx.MessageDialog.__init__(self, None, msg, "Error",
- wx.OK|wx.ICON_ERROR)
+ wx.OK | wx.ICON_ERROR)
########################################################################
@@ -48,17 +49,18 @@ class FlatNotebook(fnb.FlatNotebook):
"""
Flatnotebook class
"""
+
def __init__(self, parent):
"""Constructor"""
- style = fnb.FNB_SMART_TABS|fnb.FNB_NO_NAV_BUTTONS|\
- fnb.FNB_DROPDOWN_TABS_LIST|fnb.FNB_NODRAG|\
- fnb.FNB_TABS_BORDER_SIMPLE|\
- fnb.FNB_X_ON_TAB|fnb.FNB_NO_X_BUTTON
+ style = fnb.FNB_SMART_TABS | fnb.FNB_NO_NAV_BUTTONS |\
+ fnb.FNB_DROPDOWN_TABS_LIST | fnb.FNB_NODRAG |\
+ fnb.FNB_TABS_BORDER_SIMPLE |\
+ fnb.FNB_X_ON_TAB | fnb.FNB_NO_X_BUTTON
# Bugfix for Mac
if platform.system().lower() in ["windows", "linux"]:
- style = style|fnb.FNB_HIDE_ON_SINGLE_TAB
+ style = style | fnb.FNB_HIDE_ON_SINGLE_TAB
self.fnb = fnb.FlatNotebook.__init__(self, parent, wx.ID_ANY,
- agwStyle=style)
+ agwStyle=style)
class MyApp(wx.App):
@@ -68,7 +70,7 @@ def __init__(self, args):
# http://anonscm.debian.org/cgit/collab-maint/wx-migration-tools.git/tree/README#n30
self.SetAssertMode(wx.APP_ASSERT_SUPPRESS)
- def MacOpenFile(self,filename):
+ def MacOpenFile(self, filename):
"""
"""
if filename.endswith(".pcfs"):
@@ -85,17 +87,18 @@ def MacOpenFile(self,filename):
class MyFrame(wx.Frame):
def __init__(self, parent, anid, version):
sys.excepthook = MyExceptionHook
- ## Set initial variables that make sense
+ # Set initial variables that make sense
self.version = version
- ## Init of the superClass
- super(MyFrame, self).__init__(parent, anid, "PyCorrFit " + self.version)
+ # Init of the superClass
+ super(MyFrame, self).__init__(
+ parent, anid, "PyCorrFit " + self.version)
- self.CreateStatusBar() # A Statusbar in the bottom of the window
- self.StatusBar.SetStatusText("Find help and updates online:"+
+ self.CreateStatusBar() # A Statusbar in the bottom of the window
+ self.StatusBar.SetStatusText("Find help and updates online:" +
" 'Help > Update'")
- ## Properties of the Frame
- initial_size = (768,700)
+ # Properties of the Frame
+ initial_size = (768, 700)
self.SetSize(initial_size)
self.SetMinSize(initial_size)
@@ -108,7 +111,7 @@ def __init__(self, parent, anid, version):
self.SessionComment = "This is a session comment. It will be saved" +\
" as the session is saved."
- ## Set variables
+ # Set variables
# The model module that can be changed by importing user defined
# functions.
# These are only for compatibility.
@@ -136,7 +139,7 @@ def __init__(self, parent, anid, version):
# New as of 0.7.9
self.RangeSelector = None
- ## Setting up the menus.
+ # Setting up the menus.
# models, modeldict, modeltypes only for compatibility!
# I should use mdls for anything, since it's globally imported
# and modified by this program (e.g. adding new function)
@@ -147,16 +150,16 @@ def __init__(self, parent, anid, version):
self.modelmenudict = dict()
self.MakeMenu()
- ## Create the Flatnotebook (Tabs Tabs Tabs!)
+ # Create the Flatnotebook (Tabs Tabs Tabs!)
panel = wx.Panel(self)
self.panel = panel
self.notebook = FlatNotebook(panel)
self.notebook.SetRightClickMenu(self.curmenu)
- #self.notebook.SetAGWWindowStyleFlag(FNB_X_ON_TAB)
+ # self.notebook.SetAGWWindowStyleFlag(FNB_X_ON_TAB)
sizer = wx.BoxSizer(wx.VERTICAL)
- sizer.Add(self.notebook, 1, wx.ALL|wx.EXPAND, 5)
+ sizer.Add(self.notebook, 1, wx.ALL | wx.EXPAND, 5)
panel.SetSizer(sizer)
self.Layout()
@@ -188,7 +191,6 @@ def __init__(self, parent, anid, version):
if hasattr(sys, "frozen"):
self.OnSupport()
-
def add_fitting_tab(self, event=None, modelid=None, counter=None,
select=False):
""" This function creates a new page inside the notebook.
@@ -222,14 +224,14 @@ def add_fitting_tab(self, event=None, modelid=None, counter=None,
model = mdls.modeldict[modelid][1]
# Create New Tab
Newtab = page.FittingPanel(self, counter, modelid, active_parms)
- #self.Freeze()
+ # self.Freeze()
self.notebook.AddPage(Newtab, counter+model, select=select)
if select:
# A hack to have the last page displayed in the tab menu:
Npag = self.notebook.GetPageCount()
self.notebook.SetSelection(Npag-1)
- #self.Thaw()
+ # self.Thaw()
self.tabcounter = self.tabcounter + 1
# Enable the "Current" Menu
self.EnableToolCurrent(True)
@@ -243,7 +245,7 @@ def add_fitting_tab(self, event=None, modelid=None, counter=None,
# Find Tool Statistics
# Get open tools
#toolkeys = self.ToolsOpen.keys()
- #for key in toolkeys:
+ # for key in toolkeys:
# tool = self.ToolsOpen[key]
# try:
# if tool.MyName=="STATISTICS":
@@ -253,7 +255,6 @@ def add_fitting_tab(self, event=None, modelid=None, counter=None,
# pass
return Newtab
-
def EnableToolCurrent(self, enabled):
""" Independent on order of menus, enable or disable tools and
current menu.
@@ -264,7 +265,6 @@ def EnableToolCurrent(self, enabled):
cid = self.menuBar.FindMenu("Current &Page")
self.menuBar.EnableTop(cid, enabled)
-
def MakeMenu(self):
self.filemenu = wx.Menu()
# toolmenu and curmenu are public, because they need to be enabled/
@@ -279,44 +279,44 @@ def MakeMenu(self):
# wx.ID_ABOUT and wx.ID_EXIT are standard IDs provided by wxWidgets.
# self.filemenu
menuAddModel = self.filemenu.Append(wx.ID_ANY,
- "&Import model", "Add a user defined model.")
+ "&Import model", "Add a user defined model.")
menuLoadBatch = self.filemenu.Append(wx.ID_ANY,
- "&Load data\tCtrl+O", "Loads one or multiple data files")
+ "&Load data\tCtrl+O", "Loads one or multiple data files")
menuOpen = self.filemenu.Append(wx.ID_OPEN, "&Open session\tCtrl+Shift+O",
- "Restore a previously saved session")
+ "Restore a previously saved session")
self.filemenu.AppendSeparator()
self.menuComm = self.filemenu.Append(wx.ID_ANY, "Co&mment session",
- "Add a comment to this session", kind=wx.ITEM_CHECK)
+ "Add a comment to this session", kind=wx.ITEM_CHECK)
self.filemenu.Check(self.menuComm.GetId(), False)
menuClear = self.filemenu.Append(wx.ID_ANY, "&Clear session\tAlt+C",
- "Remove all pages but keep imported model functions.")
+ "Remove all pages but keep imported model functions.")
menuSave = self.filemenu.Append(wx.ID_SAVE, "&Save session\tCtrl+S",
- "Save entire Session")
+ "Save entire Session")
self.filemenu.AppendSeparator()
- menuExit = self.filemenu.Append(wx.ID_EXIT,"E&xit\tCtrl+Q",
- "Terminate the program")
+ menuExit = self.filemenu.Append(wx.ID_EXIT, "E&xit\tCtrl+Q",
+ "Terminate the program")
# prefmenu
self.MenuUseLatex = prefmenu.Append(wx.ID_ANY, "Use Latex",
- "Enables/Disables usage of Latex for image saving.",
- kind=wx.ITEM_CHECK)
+ "Enables/Disables usage of Latex for image saving.",
+ kind=wx.ITEM_CHECK)
self.MenuVerbose = prefmenu.Append(wx.ID_ANY, "Verbose mode",
- "Enables/Disables output of additional information.",
- kind=wx.ITEM_CHECK)
+ "Enables/Disables output of additional information.",
+ kind=wx.ITEM_CHECK)
self.MenuShowWeights = prefmenu.Append(wx.ID_ANY, "Show weights",
- "Enables/Disables displaying weights of fit.",
- kind=wx.ITEM_CHECK)
+ "Enables/Disables displaying weights of fit.",
+ kind=wx.ITEM_CHECK)
self.MenuShowWeights.Check()
self.MenuAutocloseTools = prefmenu.Append(wx.ID_ANY, "Autoclose tools",
- "Automatically close tools after usage.",
- kind=wx.ITEM_CHECK)
+ "Automatically close tools after usage.",
+ kind=wx.ITEM_CHECK)
# toolmenu
toolkeys = list(tools.ToolDict.keys())
toolkeys.sort()
for ttype in toolkeys:
for tool in np.arange(len(tools.ToolDict[ttype])):
menu = self.toolmenu.Append(wx.ID_ANY,
- tools.ToolName[ttype][tool][0],
- tools.ToolName[ttype][tool][1], kind=wx.ITEM_CHECK)
+ tools.ToolName[ttype][tool][0],
+ tools.ToolName[ttype][tool][1], kind=wx.ITEM_CHECK)
self.toolmenu.Check(menu.GetId(), False)
# Append tool to list of tools with menu ID
self.Tools[menu.GetId()] = tools.ToolDict[ttype][tool]
@@ -333,12 +333,12 @@ def MakeMenu(self):
"Save data (comma separated values)")
menuSavePlotCorr = self.curmenu.Append(wx.ID_ANY,
- "&Save correlation as image",
- "Export current plot as image.")
+ "&Save correlation as image",
+ "Export current plot as image.")
menuSavePlotTrace = self.curmenu.Append(wx.ID_ANY,
- "&Save trace as image",
- "Export current trace as image.")
+ "&Save trace as image",
+ "Export current trace as image.")
self.curmenu.AppendSeparator()
menuClPa = self.curmenu.Append(wx.ID_ANY, "&Close Page",
"Close Current Page")
@@ -358,25 +358,25 @@ def MakeMenu(self):
model = mdls.modeldict[modelid]
if platform.system().lower() == "darwin" and hasattr(sys, 'frozen'):
###
- ### Work-around for freezed mac version
+ # Work-around for freezed mac version
###
- ### (strange UTF-8 decoding error,
- ### would work with misc.removewrongUTF8)
+ # (strange UTF-8 decoding error,
+ # would work with misc.removewrongUTF8)
b = model[1].split("(")[0].strip()
c = misc.removewrongUTF8(model[2])
- menuentry = submenu.Append(model[0],b,c)
+ menuentry = submenu.Append(model[0], b, c)
else:
menuentry = submenu.Append(model[0], model[1], model[2])
self.Bind(wx.EVT_MENU, self.add_fitting_tab, menuentry)
# help menu
menuSupport = helpmenu.Append(wx.ID_ANY, "&Support",
- "How to (get) support (for) PyCorrFit")
+ "How to (get) support (for) PyCorrFit")
menuDocu = helpmenu.Append(wx.ID_ANY, "&Documentation",
- "PyCorrFit documentation")
+ "PyCorrFit documentation")
menuWiki = helpmenu.Append(wx.ID_ANY, "&Wiki",
- "PyCorrFit wiki pages by users for users (online)")
+ "PyCorrFit wiki pages by users for users (online)")
menuUpdate = helpmenu.Append(wx.ID_ANY, "&Update",
- "Check for new version"+
+ "Check for new version" +
" (Web access required)")
helpmenu.AppendSeparator()
menuShell = helpmenu.Append(wx.ID_ANY, "S&hell",
@@ -389,16 +389,17 @@ def MakeMenu(self):
# Create the menubar.
self.menuBar = wx.MenuBar()
# Adding all the menus to the MenuBar
- self.menuBar.Append(self.filemenu,"&File")
- self.menuBar.Append(self.toolmenu,"&Tools")
- self.menuBar.Append(self.curmenu,"Current &Page")
- self.menuBar.Append(modelmenu,"&Model")
- self.menuBar.Append(prefmenu,"&Preferences")
- self.menuBar.Append(helpmenu,"&Help")
- self.SetMenuBar(self.menuBar) # Adding the MenuBar to the Frame content.
+ self.menuBar.Append(self.filemenu, "&File")
+ self.menuBar.Append(self.toolmenu, "&Tools")
+ self.menuBar.Append(self.curmenu, "Current &Page")
+ self.menuBar.Append(modelmenu, "&Model")
+ self.menuBar.Append(prefmenu, "&Preferences")
+ self.menuBar.Append(helpmenu, "&Help")
+ # Adding the MenuBar to the Frame content.
+ self.SetMenuBar(self.menuBar)
self.EnableToolCurrent(False)
- ## Set events
- #File
+ # Set events
+ # File
#self.Bind(wx.EVT_MENU, self.OnLoadSingle, menuLoadSingle)
self.Bind(wx.EVT_MENU, self.OnLoadBatch, menuLoadBatch)
self.Bind(wx.EVT_MENU, self.OnAddModel, menuAddModel)
@@ -427,26 +428,38 @@ def MakeMenu(self):
# Add the shortcuts
# # For Tools first.
toolsitems = self.toolmenu.GetMenuItems()
- avg = filter(lambda x: x.GetItemLabelText() == 'Average data', toolsitems).__next__()
+ avg = filter(lambda x: x.GetItemLabelText() ==
+ 'Average data', toolsitems).__next__()
avg.SetItemLabel("{}\tAlt+A".format(avg.GetItemLabel()))
- bat = filter(lambda x: x.GetItemLabelText() == 'Batch control', toolsitems).__next__()
+ bat = filter(lambda x: x.GetItemLabelText() ==
+ 'Batch control', toolsitems).__next__()
bat.SetItemLabel("{}\tAlt+B".format(bat.GetItemLabel()))
- stat = filter(lambda x: x.GetItemLabelText() == 'Statistics view', toolsitems).__next__()
+ stat = filter(lambda x: x.GetItemLabelText() ==
+ 'Statistics view', toolsitems).__next__()
stat.SetItemLabel("{}\tAlt+S".format(stat.GetItemLabel()))
- view = filter(lambda x: x.GetItemLabelText() == 'Trace view', toolsitems).__next__()
+ view = filter(lambda x: x.GetItemLabelText() ==
+ 'Trace view', toolsitems).__next__()
view.SetItemLabel("{}\tAlt+V".format(view.GetItemLabel()))
self.accel_tbl = wx.AcceleratorTable([
- (wx.ACCEL_ALT, ord('A'), avg.GetId()),
- (wx.ACCEL_ALT, ord('B'), bat.GetId()),
- (wx.ACCEL_ALT, ord('V'), view.GetId()),
- (wx.ACCEL_ALT, ord('S'), stat.GetId()),
- (wx.ACCEL_CTRL, ord('O'), menuLoadBatch.GetId()),
- (wx.ACCEL_CTRL | wx.ACCEL_SHIFT, ord('O'), menuOpen.GetId()),
- (wx.ACCEL_CTRL, ord('S'), menuSave.GetId()),
- (wx.ACCEL_ALT, ord('C'), menuClear.GetId()),
- (wx.ACCEL_CTRL, ord('Q'), menuExit.GetId())
- ])
+ (wx.ACCEL_ALT, ord('A'), avg.GetId()),
+ (wx.ACCEL_ALT, ord(
+ 'B'), bat.GetId()),
+ (wx.ACCEL_ALT, ord(
+ 'V'), view.GetId()),
+ (wx.ACCEL_ALT, ord(
+ 'S'), stat.GetId()),
+ (wx.ACCEL_CTRL, ord('O'),
+ menuLoadBatch.GetId()),
+ (wx.ACCEL_CTRL | wx.ACCEL_SHIFT, ord(
+ 'O'), menuOpen.GetId()),
+ (wx.ACCEL_CTRL, ord('S'),
+ menuSave.GetId()),
+ (wx.ACCEL_ALT, ord('C'),
+ menuClear.GetId()),
+ (wx.ACCEL_CTRL, ord(
+ 'Q'), menuExit.GetId())
+ ])
self.SetAcceleratorTable(self.accel_tbl)
def OnAbout(self, event=None):
@@ -494,19 +507,19 @@ def OnAddModel(self, event=None, modfile=None):
NewModel = usermodel.UserModel(self)
try:
- NewModel.GetCode( os.path.join(dirname, filename) )
+ NewModel.GetCode(os.path.join(dirname, filename))
except NameError:
# sympy is probably not installed
# Warn the user
- text = ("SymPy not found.\n"+
- "In order to import user defined model\n"+
- "functions, please install Sympy\n"+
+ text = ("SymPy not found.\n" +
+ "In order to import user defined model\n" +
+ "functions, please install Sympy\n" +
"version 0.7.2 or higher.\nhttp://sympy.org/")
if platform.system().lower() == 'linux':
- text += ("\nSymPy is included in the package:\n"+
+ text += ("\nSymPy is included in the package:\n" +
" 'python-sympy'")
dlg = wx.MessageDialog(None, text, 'SymPy not found',
- wx.OK | wx.ICON_EXCLAMATION)
+ wx.OK | wx.ICON_EXCLAMATION)
dlg.ShowModal()
return
except:
@@ -519,7 +532,7 @@ def OnAddModel(self, event=None, modfile=None):
for tb_item in traceback.format_tb(info[2]):
errstr += tb_item
dlg = wx.MessageDialog(self, errstr, "Error",
- style=wx.ICON_ERROR|wx.OK|wx.STAY_ON_TOP)
+ style=wx.ICON_ERROR | wx.OK | wx.STAY_ON_TOP)
dlg.ShowModal()
return
# Test the code for sympy compatibility.
@@ -530,14 +543,14 @@ def OnAddModel(self, event=None, modfile=None):
except:
# This means that the imported model file could be
# contaminated. Ask the user how to proceed.
- text = "The model parsing check raised an Error.\n"+\
- "This could be the result of a wrong Syntax\n"+\
- "or an error of the parser.\n"+\
- "This might be dangerous. Procceed\n"+\
- "only, if you trust the source of the file.\n"+\
+ text = "The model parsing check raised an Error.\n" +\
+ "This could be the result of a wrong Syntax\n" +\
+ "or an error of the parser.\n" +\
+ "This might be dangerous. Procceed\n" +\
+ "only, if you trust the source of the file.\n" +\
"Try and import offensive file: "+filename+"?"
dlg2 = wx.MessageDialog(self, text, "Unsafe Operation",
- style=wx.ICON_EXCLAMATION|wx.YES_NO|wx.STAY_ON_TOP)
+ style=wx.ICON_EXCLAMATION | wx.YES_NO | wx.STAY_ON_TOP)
if dlg2.ShowModal() == wx.ID_YES:
NewModel.ImportModel()
else:
@@ -546,10 +559,8 @@ def OnAddModel(self, event=None, modfile=None):
# The model was loaded correctly
NewModel.ImportModel()
-
self.dirname = dirname
-
def OnClearSession(self, e=None, clearmodels=False):
"""
Clear the entire session
@@ -563,9 +574,9 @@ def OnClearSession(self, e=None, clearmodels=False):
# Ask, if user wants to save current session.
if numtabs > 0:
dial = wx.MessageDialog(self,
- 'Do you wish to save this session first?',
- 'Save current session?',
- wx.ICON_QUESTION | wx.CANCEL | wx.YES_NO | wx.NO_DEFAULT )
+ 'Do you wish to save this session first?',
+ 'Save current session?',
+ wx.ICON_QUESTION | wx.CANCEL | wx.YES_NO | wx.NO_DEFAULT)
# dial = edclasses.MyYesNoAbortDialog(self,
# 'Do you wish to save this session first?',
# 'Save current session?')
@@ -589,7 +600,7 @@ def OnClearSession(self, e=None, clearmodels=False):
self.SetTitleFCS(None)
self.SessionComment = "You may enter some information here."
self.Background = list()
- ## Do we want to keep user defined models after session clearing?
+ # Do we want to keep user defined models after session clearing?
if clearmodels == True:
# Also reset user defined models
for modelid in mdls.modeltypes["User"]:
@@ -599,13 +610,12 @@ def OnClearSession(self, e=None, clearmodels=False):
del mdls.modeldict[modelid]
mdls.modeltypes["User"] = list()
# Model Menu
- menu=self.modelmenudict["User"]
- for item in menu.GetMenuItems():
+ menu = self.modelmenudict["User"]
+ for item in menu.GetMenuItems():
menu.RemoveItem(item)
return "clear"
-
- def OnCommSession(self,e=None):
+ def OnCommSession(self, e=None):
""" Dialog for commenting on session. """
try:
self.EditCommentDlg.IsEnabled()
@@ -638,7 +648,6 @@ def OnDeletePage(self, event=None):
if self.notebook.GetPageCount() == 0:
self.OnFNBPageChanged()
-
def OnDocumentation(self, e=None):
""" Get the documentation and view it with browser"""
path = doc.GetLocationOfDocumentation()
@@ -659,8 +668,7 @@ def OnDocumentation(self, e=None):
cmd = 'xdg-open "{}" &'.format(path)
os.system(cmd)
-
- def OnExit(self,e=None):
+ def OnExit(self, e=None):
"""
Kindly asks the user if he wants to save the session and
then exit the program.
@@ -669,13 +677,13 @@ def OnExit(self,e=None):
# Ask, if user wants to save current session.
if numtabs > 0:
dial = wx.MessageDialog(self,
- 'Do you wish to save this session first?',
- 'Save current session?',
- wx.ICON_QUESTION | wx.CANCEL | wx.YES_NO | wx.NO_DEFAULT )
+ 'Do you wish to save this session first?',
+ 'Save current session?',
+ wx.ICON_QUESTION | wx.CANCEL | wx.YES_NO | wx.NO_DEFAULT)
result = dial.ShowModal()
dial.Destroy()
if result == wx.ID_CANCEL:
- return # stop this function - do nothing.
+ return # stop this function - do nothing.
elif result == wx.ID_YES:
filename = self.OnSaveSession()
if filename is None:
@@ -685,15 +693,12 @@ def OnExit(self,e=None):
# Exit the Program
self.Destroy()
-
- def OnFNBClosedPage(self,e=None):
+ def OnFNBClosedPage(self, e=None):
""" Called, when a page has been closed """
if self.notebook.GetPageCount() == 0:
# Grey out tools
self.EnableToolCurrent(False)
-
-
def OnFNBPageChanged(self, e=None, Page=None, trigger=None):
""" Called, when
- Page focus switches to another Page
@@ -705,8 +710,8 @@ def OnFNBPageChanged(self, e=None, Page=None, trigger=None):
"""
if (e is not None and
- e.GetEventType()==fnb.EVT_FLATNOTEBOOK_PAGE_CHANGED.typeId
- and trigger is None):
+ e.GetEventType() == fnb.EVT_FLATNOTEBOOK_PAGE_CHANGED.typeId
+ and trigger is None):
trigger = "tab_browse"
# Get the Page
if Page is None:
@@ -729,9 +734,7 @@ def OnFNBPageChanged(self, e=None, Page=None, trigger=None):
else:
self.notebook.Show()
-
-
- def OnImportData(self,e=None):
+ def OnImportData(self, e=None):
"""Import experimental data from all filetypes specified in
*readfiles.filetypes_dict*.
Is called by the curmenu and applies to currently opened model.
@@ -750,7 +753,7 @@ def OnImportData(self,e=None):
# This is wx widgets stuff.
filters = filters+"|"
dlg = wx.FileDialog(self, "Open data file",
- self.dirname, "", filters, wx.FD_OPEN)
+ self.dirname, "", filters, wx.FD_OPEN)
if dlg.ShowModal() == wx.ID_OK:
# The filename the page will get
path = dlg.GetPath() # Workaround since 0.7.5
@@ -769,7 +772,7 @@ def OnImportData(self,e=None):
for tb_item in traceback.format_tb(info[2]):
errstr += tb_item
wx.MessageDialog(self, errstr, "Error",
- style=wx.ICON_ERROR|wx.OK|wx.STAY_ON_TOP)
+ style=wx.ICON_ERROR | wx.OK | wx.STAY_ON_TOP)
return
else:
dataexp = Stuff["Correlation"]
@@ -839,18 +842,18 @@ def OnImportData(self,e=None):
# pages title.
num = len(curvelist)
# Show a nice progress dialog:
- style = wx.PD_REMAINING_TIME|wx.PD_SMOOTH|wx.PD_AUTO_HIDE|\
- wx.PD_CAN_ABORT
+ style = wx.PD_REMAINING_TIME | wx.PD_SMOOTH | wx.PD_AUTO_HIDE |\
+ wx.PD_CAN_ABORT
dlg = wx.ProgressDialog("Import", "Loading pages...",
- maximum = num, parent=self, style=style)
+ maximum=num, parent=self, style=style)
# Get current page and populate
CurPage = self.notebook.GetCurrentPage()
for i in np.arange(num):
# Fill Page with data
self.ImportData(CurPage, dataexp[i], trace[i],
- curvetype=curvelist[i], filename=filename[i],
- weights=Weight[i], weight_type=WeightName[i],
- curveid=i)
+ curvetype=curvelist[i], filename=filename[i],
+ weights=Weight[i], weight_type=WeightName[i],
+ curveid=i)
# Let the user abort, if he wants to:
# We want to do this here before an empty page is added
# to the notebok.
@@ -861,8 +864,8 @@ def OnImportData(self,e=None):
# Create new page.
# (Add n-1 pages while importing.)
CurPage = self.add_fitting_tab(event=None,
- modelid=CurPage.corr.fit_model.id,
- counter=None)
+ modelid=CurPage.corr.fit_model.id,
+ counter=None)
# We are finished here:
dlg.Destroy()
return
@@ -872,7 +875,6 @@ def OnImportData(self,e=None):
dlg.Destroy()
return
-
def OnMyLeftUp(self, event):
"""
Wrapper for LeftUp:
@@ -907,7 +909,6 @@ def OnMyLeftUp(self, event):
# Call what should have been called.
pc.OnLeftUp(event)
-
def ImportData(self, Page, dataexp, trace, curvetype="",
filename="", curveid="", run="0",
weights=None, weight_type=None, trigger=None):
@@ -932,7 +933,7 @@ def ImportData(self, Page, dataexp, trace, curvetype="",
# It might be possible, that we want the channels to be
# fixed to some interval. This is the case if the
# checkbox on the "Channel selection" dialog is checked.
- #self.OnFNBPageChanged()
+ # self.OnFNBPageChanged()
# Enable Fitting Button
CurPage.Fit_enable_fitting()
# Set new tabtitle value and strip leading or trailing
@@ -960,10 +961,9 @@ def ImportData(self, Page, dataexp, trace, curvetype="",
# Call this function to allow the "Channel Selection" window that
# might be open to update itself.
# We are aware of the fact, that we just did that
- #self.OnFNBPageChanged()
-
+ # self.OnFNBPageChanged()
- def OnLatexCheck(self,e):
+ def OnLatexCheck(self, e):
""" Checks if we can use latex. If not, create a pop-up window
stating so.
"""
@@ -971,42 +971,41 @@ def OnLatexCheck(self,e):
if uselatex == False:
# do nothing
return
- ## Check if we can use latex for plotting:
+ # Check if we can use latex for plotting:
r1 = meta.find_program("latex")[0]
r2 = meta.find_program("dvipng")[0]
# Ghostscript
r31 = meta.find_program("gs")[0]
- r32 = meta.find_program("mgs")[0] # from miktex
- r3 = max(r31,r32)
+ r32 = meta.find_program("mgs")[0] # from miktex
+ r3 = max(r31, r32)
if r1+r2+r3 < 3:
# Warn the user
if platform.system().lower() == 'windows':
- text = ("Latex plotting features will not work.\n"+
- "Please install MiKTeX.\n"+
+ text = ("Latex plotting features will not work.\n" +
+ "Please install MiKTeX.\n" +
"http://miktex.org/")
elif platform.system().lower() == 'darwin':
- text = ("Latex plotting features will not work.\n"+
- "Please install MacTeX.\n"+
+ text = ("Latex plotting features will not work.\n" +
+ "Please install MacTeX.\n" +
"http://tug.org/mactex/")
else:
- text = ("Latex plotting features will not work.\n"+
- "Make sure you have these packages installed:\n"+
- " - dvipng\n"+
- " - ghostscript\n"+
- " - texlive-latex-base\n"+
+ text = ("Latex plotting features will not work.\n" +
+ "Make sure you have these packages installed:\n" +
+ " - dvipng\n" +
+ " - ghostscript\n" +
+ " - texlive-latex-base\n" +
" - texlive-science\n")
dlg = wx.MessageDialog(None, text, 'Latex not found',
- wx.OK | wx.ICON_EXCLAMATION)
+ wx.OK | wx.ICON_EXCLAMATION)
dlg.ShowModal()
-
def OnLoadBatch(self, e=None, dataname=None):
""" Open multiple data files and apply a single model to them
We will create a new window where the user may decide which
model to use.
"""
if dataname is None:
- ## Browse the file system
+ # Browse the file system
SupFiletypes = list(readfiles.filetypes_dict.keys())
# Sort them so we have "All suported filetypes" up front
SupFiletypes.sort()
@@ -1018,7 +1017,7 @@ def OnLoadBatch(self, e=None, dataname=None):
# Add a separator if item is not last item
filters = filters+"|"
dlg = wx.FileDialog(self, "Open data files",
- self.dirname, "", filters, wx.FD_OPEN|wx.FD_MULTIPLE)
+ self.dirname, "", filters, wx.FD_OPEN | wx.FD_MULTIPLE)
if dlg.ShowModal() == wx.ID_OK:
Datafiles = dlg.GetFilenames()
# We rely on sorted filenames
@@ -1044,8 +1043,8 @@ def OnLoadBatch(self, e=None, dataname=None):
self.dirname = os.path.split(dataname)[0]
Datafiles.sort()
- ## Get information from the data files and let the user choose
- ## which type of curves to load and the corresponding model.
+ # Get information from the data files and let the user choose
+ # which type of curves to load and the corresponding model.
# List of filenames that could not be opened
BadFiles = list()
Exceptions = list()
@@ -1054,19 +1053,19 @@ def OnLoadBatch(self, e=None, dataname=None):
Trace = list()
Type = list()
Filename = list() # there might be zipfiles with additional name info
- #Run = list() # Run number connecting AC1 AC2 CC12 CC21
+ # Run = list() # Run number connecting AC1 AC2 CC12 CC21
Curveid = list() # Curve ID of each curve in a file
Weight = list()
WeightName = list()
# Display a progress dialog for file import
N = len(Datafiles)
- style = wx.PD_REMAINING_TIME|wx.PD_SMOOTH|wx.PD_AUTO_HIDE|\
- wx.PD_CAN_ABORT
+ style = wx.PD_REMAINING_TIME | wx.PD_SMOOTH | wx.PD_AUTO_HIDE |\
+ wx.PD_CAN_ABORT
dlgi = wx.ProgressDialog("Import", "Loading data...",
- maximum = N, parent=self, style=style)
+ maximum=N, parent=self, style=style)
for j in np.arange(N):
- afile=Datafiles[j]
+ afile = Datafiles[j]
# Let the user abort, if he wants to:
if dlgi.Update(j, "Loading data: "+afile)[0] == False:
dlgi.Destroy()
@@ -1081,8 +1080,8 @@ def OnLoadBatch(self, e=None, dataname=None):
# Print exception
trb = traceback.format_exc(excpt)
trb = "..." + trb.replace("\n", "\n...")
- warnings.warn("Problem processing a file."+\
- " Reason:\n{}".format(trb))
+ warnings.warn("Problem processing a file." +
+ " Reason:\n{}".format(trb))
else:
for i in np.arange(len(Stuff["Type"])):
Correlation.append(Stuff["Correlation"][i])
@@ -1095,7 +1094,7 @@ def OnLoadBatch(self, e=None, dataname=None):
else:
Weight.append(None)
WeightName.append(None)
- #Curveid.append(str(i+1))
+ # Curveid.append(str(i+1))
dlgi.Destroy()
# Add number of the curve within a file.
@@ -1119,7 +1118,7 @@ def OnLoadBatch(self, e=None, dataname=None):
trb = " " + trb.replace("\n", "\n ")
errstr += " " + item + "\n" + trb
dlg = wx.MessageDialog(self, errstr, "Error",
- style=wx.ICON_WARNING|wx.OK|wx.CANCEL|wx.STAY_ON_TOP)
+ style=wx.ICON_WARNING | wx.OK | wx.CANCEL | wx.STAY_ON_TOP)
if dlg.ShowModal() == wx.ID_CANCEL:
return
# Abort, if there are no curves left
@@ -1182,7 +1181,7 @@ def OnLoadBatch(self, e=None, dataname=None):
# to import.
keys = curvetypes.keys()
# Start the dialog for choosing types and model functions
- labels=list()
+ labels = list()
for i in np.arange(len(Filename)):
if Run[i] != "":
labels.append("{} r{:03d}-{}".format(Filename[i],
@@ -1236,22 +1235,22 @@ def OnLoadBatch(self, e=None, dataname=None):
else:
return
Chosen.Destroy()
- ## Import the data into new pages
+ # Import the data into new pages
# curvelist is a list of numbers or labels that correspond
# to each item in dataexp or trace. Each curvelist/filename
# item will be converted to a string and then added to the
# pages title.
num = len(Type)
# Show a nice progress dialog:
- style = wx.PD_REMAINING_TIME|wx.PD_SMOOTH|wx.PD_AUTO_HIDE|\
- wx.PD_CAN_ABORT
- dlg = wx.ProgressDialog("Import", "Loading pages..."
- , maximum = num, parent=self, style=style)
+ style = wx.PD_REMAINING_TIME | wx.PD_SMOOTH | wx.PD_AUTO_HIDE |\
+ wx.PD_CAN_ABORT
+ dlg = wx.ProgressDialog(
+ "Import", "Loading pages...", maximum=num, parent=self, style=style)
for i in np.arange(num):
# create a new page
CurPage = self.add_fitting_tab(event=None,
- modelid=modelList[i],
- counter=None)
+ modelid=modelList[i],
+ counter=None)
# Fill Page with data
self.ImportData(CurPage, Correlation[i], Trace[i],
curvetype=Type[i], filename=Filename[i],
@@ -1268,7 +1267,6 @@ def OnLoadBatch(self, e=None, dataname=None):
# the dialog.
dlg.Destroy()
-
def OnOpenSession(self, e=None, sessionfile=None):
""" Displays a dialog for opening PyCorrFit sessions
@@ -1288,8 +1286,8 @@ def OnOpenSession(self, e=None, sessionfile=None):
# the session. Therefore, we cannot open a new session.
return "abort"
- ## Create user dialog
- wc = [ "*{}".format(w) for w in opf.session_wildcards ]
+ # Create user dialog
+ wc = ["*{}".format(w) for w in opf.session_wildcards]
wcstring = "PyCorrFit session (*.pcfs)|{}".format(";".join(wc))
if sessionfile is None:
dlg = wx.FileDialog(self, "Open session file",
@@ -1298,7 +1296,7 @@ def OnOpenSession(self, e=None, sessionfile=None):
if dlg.ShowModal() == wx.ID_OK:
sessionfile = dlg.GetPath()
(self.dirname, self.filename) = os.path.split(
- sessionfile)
+ sessionfile)
else:
# User did not press OK
# stop this function
@@ -1307,17 +1305,17 @@ def OnOpenSession(self, e=None, sessionfile=None):
dlg.Destroy()
Infodict = opf.LoadSessionData(sessionfile)
- ## Check for correct version
+ # Check for correct version
try:
arcv = LooseVersion(Infodict["Version"])
thisv = LooseVersion(self.version.strip())
if arcv > thisv:
- errstring = "Your version of Pycorrfit ("+str(thisv)+\
- ") is too old to open this session ("+\
- str(arcv).strip()+").\n"+\
- "Please download the lates version of "+\
- " PyCorrFit from \n"+doc.HomePage+".\n"+\
- "Continue opening this session?"
+ errstring = "Your version of Pycorrfit ("+str(thisv) +\
+ ") is too old to open this session (" +\
+ str(arcv).strip()+").\n" +\
+ "Please download the lates version of " +\
+ " PyCorrFit from \n"+doc.HomePage+".\n" +\
+ "Continue opening this session?"
dlg = edclasses.MyOKAbortDialog(self, errstring, "Warning")
returns = dlg.ShowModal()
if returns == wx.ID_OK:
@@ -1329,14 +1327,14 @@ def OnOpenSession(self, e=None, sessionfile=None):
pass
self.SetTitleFCS(self.filename)
- ## Background traces
+ # Background traces
try:
self.Background = Infodict["Backgrounds"]
except:
pass
- ## Preferences
- ## if Preferences is Not None:
- ## add them!
+ # Preferences
+ # if Preferences is Not None:
+ # add them!
# External functions
for key in Infodict["External Functions"].keys():
NewModel = usermodel.UserModel(self)
@@ -1351,10 +1349,10 @@ def OnOpenSession(self, e=None, sessionfile=None):
# Reset tabcounter
self.tabcounter = 1
# Show a nice progress dialog:
- style = wx.PD_REMAINING_TIME|wx.PD_SMOOTH|wx.PD_AUTO_HIDE|\
- wx.PD_CAN_ABORT
+ style = wx.PD_REMAINING_TIME | wx.PD_SMOOTH | wx.PD_AUTO_HIDE |\
+ wx.PD_CAN_ABORT
dlg = wx.ProgressDialog("Import", "Loading pages...",
- maximum = N, parent=self, style=style)
+ maximum=N, parent=self, style=style)
for i in np.arange(N):
# Let the user abort, if he wants to:
if dlg.Update(i+1, "Loading pages...")[0] == False:
@@ -1381,7 +1379,8 @@ def OnOpenSession(self, e=None, sessionfile=None):
# As of 0.7.3: Add external weights to page
try:
for key in Infodict["External Weights"][pageid].keys():
- Newtab.corr.set_weights(key, Infodict["External Weights"][pageid][key])
+ Newtab.corr.set_weights(
+ key, Infodict["External Weights"][pageid][key])
except KeyError:
pass
@@ -1410,7 +1409,7 @@ def OnOpenSession(self, e=None, sessionfile=None):
try:
Newtab.tabtitle.SetValue(Infodict["Comments"][pageid])
except:
- pass # no page title
+ pass # no page title
# Parameters
self.UnpackParameters(Infodict["Parameters"][i], Newtab,
@@ -1438,7 +1437,8 @@ def OnOpenSession(self, e=None, sessionfile=None):
except:
pass
# also set fit parameters
- fit_results["fit parameters"] = np.where(Infodict["Parameters"][i][3])[0]
+ fit_results["fit parameters"] = np.where(
+ Infodict["Parameters"][i][3])[0]
# set fit weights for plotting
if fit_results["weighted fit"]:
# these were already imported:
@@ -1480,8 +1480,7 @@ def OnOpenSession(self, e=None, sessionfile=None):
# Disable some menus and close some dialogs
self.EnableToolCurrent(False)
-
- def OnSaveData(self,e=None):
+ def OnSaveData(self, e=None):
""" Opens a dialog for saving correlation data of a Page
Also saves the parameters that are accessible in the Info
@@ -1493,9 +1492,9 @@ def OnSaveData(self,e=None):
filename = "#{:04d}_{}".format(int(Page.counter.strip(":# ")),
Page.title.strip())
dlg = wx.FileDialog(self, "Save curve", self.dirname, filename,
- "Correlation with trace (*.csv)|*.csv;*.*"+\
- "|Correlation only (*.csv)|*.csv;*.*",
- wx.FD_SAVE|wx.FD_OVERWRITE_PROMPT)
+ "Correlation with trace (*.csv)|*.csv;*.*" +
+ "|Correlation only (*.csv)|*.csv;*.*",
+ wx.FD_SAVE | wx.FD_OVERWRITE_PROMPT)
# user cannot do anything until he clicks "OK"
if dlg.ShowModal() == wx.ID_OK:
path = dlg.GetPath() # Workaround since 0.7.5
@@ -1503,7 +1502,6 @@ def OnSaveData(self,e=None):
path += ".csv"
(self.dirname, self.filename) = os.path.split(path)
-
if dlg.GetFilterIndex() == 0:
savetrace = True
else:
@@ -1516,7 +1514,6 @@ def OnSaveData(self,e=None):
dlg.Destroy()
-
def OnSavePlotCorr(self, e=None):
""" make some output """
# Saving dialog box.
@@ -1526,13 +1523,12 @@ def OnSavePlotCorr(self, e=None):
Page = self.notebook.GetCurrentPage()
try:
plotting.savePlotCorrelation(self, self.dirname, Page, uselatex,
- verbose, show_weights)
+ verbose, show_weights)
except NameError as excpt:
trb = traceback.format_exc(excpt)
trb = " " + trb.replace("\n", "\n ")
raise NameError("Please make sure matplotlib is installed:\n"+trb)
-
def OnSavePlotTrace(self, e=None):
""" make some output """
# Saving dialog box.
@@ -1546,8 +1542,7 @@ def OnSavePlotTrace(self, e=None):
trb = " " + trb.replace("\n", "\n ")
raise NameError("Please make sure matplotlib is installed:\n"+trb)
-
- def OnSaveSession(self,e=None):
+ def OnSaveSession(self, e=None):
""" Displays a dialog for saving PyCorrFit sessions
@@ -1563,15 +1558,17 @@ def OnSaveSession(self,e=None):
"""
# Parameters are all in one dictionary:
Infodict = dict()
- Infodict["Backgrounds"] = self.Background # Background list
- Infodict["Comments"] = dict() # Session comment "Session" and Pages int
- Infodict["Correlations"] = dict() # all correlation curves
- Infodict["External Functions"] = dict() # external model functions
- Infodict["External Weights"] = dict() # additional weights for the pages
- Infodict["Parameters"] = dict() # all parameters of all pages
- Infodict["Preferences"] = dict() # not used
- Infodict["Supplements"] = dict() # error estimates for fitting
- Infodict["Traces"] = dict() # all traces
+ Infodict["Backgrounds"] = self.Background # Background list
+ # Session comment "Session" and Pages int
+ Infodict["Comments"] = dict()
+ Infodict["Correlations"] = dict() # all correlation curves
+ Infodict["External Functions"] = dict() # external model functions
+ # additional weights for the pages
+ Infodict["External Weights"] = dict()
+ Infodict["Parameters"] = dict() # all parameters of all pages
+ Infodict["Preferences"] = dict() # not used
+ Infodict["Supplements"] = dict() # error estimates for fitting
+ Infodict["Traces"] = dict() # all traces
# Save each Page
N = self.notebook.GetPageCount()
# External functions
@@ -1579,7 +1576,7 @@ def OnSaveSession(self,e=None):
# Those models belong to external user functions.
doc = mdls.modeldict[usermodelid][-1].__doc__
doc = doc.splitlines()
- docnew=""
+ docnew = ""
for line in doc:
docnew = docnew+line.strip()+"\r\n"
Infodict["External Functions"][usermodelid] = docnew
@@ -1596,7 +1593,8 @@ def OnSaveSession(self,e=None):
if hasattr(corr, "fit_results"):
Infodict["Supplements"][counter] = dict()
if "chi2" in corr.fit_results:
- Infodict["Supplements"][counter]["Chi sq"] = float(corr.fit_results["chi2"])
+ Infodict["Supplements"][counter]["Chi sq"] = float(
+ corr.fit_results["chi2"])
else:
Infodict["Supplements"][counter]["Chi sq"] = 0
PageList = list()
@@ -1606,21 +1604,24 @@ def OnSaveSession(self,e=None):
# optimization error
Alist = list()
- if (# there is an error key
+ if ( # there is an error key
"fit error estimation" in corr.fit_results and
# the errors were computed
len(corr.fit_results["fit error estimation"]) != 0 and
# len(errors) matches len(fit parameters)
- len(corr.fit_results["fit error estimation"]) == len(corr.fit_results["fit parameters"])
- ):
+ len(corr.fit_results["fit error estimation"]) == len(
+ corr.fit_results["fit parameters"])
+ ):
for ii, fitpid in enumerate(corr.fit_results["fit parameters"]):
Alist.append([int(fitpid),
- float(corr.fit_results["fit error estimation"][ii])
- ])
+ float(
+ corr.fit_results["fit error estimation"][ii])
+ ])
Infodict["Supplements"][counter]["FitErr"] = Alist
# Set exp data
- Infodict["Correlations"][counter] = [corr.lag_time, corr.correlation]
+ Infodict["Correlations"][counter] = [
+ corr.lag_time, corr.correlation]
# Also save the trace
Infodict["Traces"][counter] = corr.traces
# Append title to Comments
@@ -1651,7 +1652,7 @@ def OnSaveSession(self,e=None):
# File dialog
dlg = wx.FileDialog(self, "Save session file", self.dirname, "",
"PyCorrFit session (*.pcfs)|*.pcfs|All files (*.*)|*.*",
- wx.FD_SAVE|wx.FD_OVERWRITE_PROMPT)
+ wx.FD_SAVE | wx.FD_OVERWRITE_PROMPT)
if dlg.ShowModal() == wx.ID_OK:
# Save everything
path = dlg.GetPath() # Workaround since 0.7.5
@@ -1662,35 +1663,31 @@ def OnSaveSession(self,e=None):
self.filename = None
# Set title of our window
if (self.filename is not None and
- not self.filename.endswith(".pcfs")):
+ not self.filename.endswith(".pcfs")):
self.filename += ".pcfs"
dlg.Destroy()
self.SetTitleFCS(self.filename)
return self.filename
-
def OnShell(self, e=None):
Shell = wx.py.shell.ShellFrame(self, title="PyCorrFit Shell",
- style=wx.DEFAULT_FRAME_STYLE|wx.FRAME_FLOAT_ON_PARENT,
- locals=locals())
+ style=wx.DEFAULT_FRAME_STYLE | wx.FRAME_FLOAT_ON_PARENT,
+ locals=locals())
# Set window icon
if self.MainIcon is not None:
wx.Frame.SetIcon(Shell, self.MainIcon)
Shell.Show(True)
-
def OnSoftware(self, event=None):
# Show About Information
text = doc.SoftwareUsed()
wx.MessageBox(text, 'Software', wx.OK | wx.ICON_INFORMATION)
-
def OnSupport(self, event=None):
# Show About Information
text = doc.support
wx.MessageBox(text, 'Support PyCorrFit', wx.OK | wx.ICON_INFORMATION)
-
def OnTool(self, event):
eid = event.GetId()
try:
@@ -1707,16 +1704,13 @@ def OnTool(self, event):
# We close it then
self.ToolsOpen[eid].OnClose()
-
def OnUpdate(self, event):
update.update(self)
-
def OnWiki(self, e=None):
""" Go to the GitHub Wiki page"""
webbrowser.open(doc.GitWiki)
-
def PackParameters(self, Page):
""" Gets all parameters from a page and returns a list object,
that can be used to save as e.g. a safe YAML file
@@ -1734,7 +1728,7 @@ def PackParameters(self, Page):
# Additional parameters as of v.0.2.0
# Splines and model function:
# Additional parameters as of v.6.4.0
- #self.Fitbox=[ fitbox, weightedfitdrop, fittext, fittext2,
+ # self.Fitbox=[ fitbox, weightedfitdrop, fittext, fittext2,
# fittextvar, fitspin, buttonfit ]
# Some fits like Spline have a number of knots of the spline
# that is important for fitting. If there is a number in the
@@ -1764,7 +1758,6 @@ def PackParameters(self, Page):
Parms.append(Page.corr.fit_parameters_range)
return Parms
-
def UnpackParameters(self, Parms, Page, init=False):
""" Apply the given parameters to the Page in question.
This function contains several *len(Parms) >= X* statements.
@@ -1804,7 +1797,7 @@ def UnpackParameters(self, Parms, Page, init=False):
NA = active_values[lindex+1]
sigma = 0.21*lamb/NA
active_values[lindex] = sigma
- active_values = np.delete(active_values,lindex+1)
+ active_values = np.delete(active_values, lindex+1)
active_fitting = np.delete(active_fitting, lindex+1)
# Cropping: What part of the correlation should be displayed.
Page.corr.fit_ival = Parms[4]
@@ -1871,13 +1864,11 @@ def UnpackParameters(self, Parms, Page, init=False):
Page.OnAmplitudeCheck("init")
if len(Parms) >= 10:
Page.corr.fit_parameters_range = np.array(Parms[9])
- ## If we want to add more stuff, we should do something like:
- ## if len(Parms) >= 11:
+ # If we want to add more stuff, we should do something like:
+ # if len(Parms) >= 11:
## nextvalue = Parms[10]
- ## Such that we are compatible to earlier versions of
- ## PyCorrFit sessions.
-
-
+ # Such that we are compatible to earlier versions of
+ # PyCorrFit sessions.
def SetTitleFCS(self, title):
if title is not None and len(title) != 0:
diff --git a/pycorrfit/gui/icon.py b/pycorrfit/gui/icon.py
index bfdf8e42..c35e8b43 100644
--- a/pycorrfit/gui/icon.py
+++ b/pycorrfit/gui/icon.py
@@ -1,4 +1,4 @@
-#----------------------------------------------------------------------
+# ----------------------------------------------------------------------
# This file was generated by /usr/bin/img2py
#
from wx.lib.embeddedimage import PyEmbeddedImage
diff --git a/pycorrfit/gui/main.py b/pycorrfit/gui/main.py
index abb4ad12..86b73749 100755
--- a/pycorrfit/gui/main.py
+++ b/pycorrfit/gui/main.py
@@ -1,3 +1,9 @@
+from . import frontend as gui # The actual program
+from . import doc
+import yaml
+import scipy
+import numpy as np # NumPy
+import warnings
"""Main execution script"""
from distutils.version import LooseVersion
import os
@@ -7,6 +13,7 @@
class Fake(object):
""" Fake module.
"""
+
def __init__(self):
self.__version__ = "0.0 unknown"
self.version = "0.0 unknown"
@@ -20,13 +27,10 @@ def __init__(self):
except ImportError:
matplotlib = Fake()
# We do catch warnings about performing this before matplotlib.backends stuff
-#matplotlib.use('WXAgg') # Tells matplotlib to use WxWidgets
-import warnings
+# matplotlib.use('WXAgg') # Tells matplotlib to use WxWidgets
with warnings.catch_warnings():
warnings.simplefilter("ignore")
- matplotlib.use('WXAgg') # Tells matplotlib to use WxWidgets for dialogs
-import numpy as np # NumPy
-import scipy
+ matplotlib.use('WXAgg') # Tells matplotlib to use WxWidgets for dialogs
# Sympy is optional:
@@ -41,14 +45,10 @@ def __init__(self):
# We must not import wx here. frontend/gui does that. If we do import wx here,
# somehow unicode characters will not be displayed correctly on windows.
# import wx
-import yaml
-## Continue with the import:
+# Continue with the import:
sys.path.append(os.path.abspath(os.path.dirname(__file__)))
-from . import doc
-from . import frontend as gui # The actual program
-
def CheckVersion(given, required, name):
""" For a given set of versions str *required* and str *given*,
@@ -62,22 +62,22 @@ def CheckVersion(given, required, name):
print(" WARNING: Could not verify version of "+name+".")
return
if req > giv:
- print(" WARNING: You are using "+name+" v. "+given+\
- " | Required: "+name+" "+ required)
+ print(" WARNING: You are using "+name+" v. "+given +
+ " | Required: "+name+" " + required)
else:
print(" OK: "+name+" v. "+given+" | "+required+" required")
-## Start gui
+# Start gui
def Main():
- ## VERSION
+ # VERSION
version = doc.__version__
__version__ = version
print(gui.doc.info(version))
- ## Check important module versions
+ # Check important module versions
print("\n\nChecking module versions...")
CheckVersion(matplotlib.__version__, "2.2.2", "matplotlib")
CheckVersion(np.__version__, "1.14.2", "NumPy")
@@ -86,7 +86,7 @@ def Main():
CheckVersion(sympy.__version__, "1.1.1", "sympy")
CheckVersion(gui.wx.__version__, "4.0.1", "wxPython")
- ## Start gui
+ # Start gui
app = gui.MyApp(False)
frame = gui.MyFrame(None, -1, version)
diff --git a/pycorrfit/gui/misc.py b/pycorrfit/gui/misc.py
index 53402466..5b31e778 100644
--- a/pycorrfit/gui/misc.py
+++ b/pycorrfit/gui/misc.py
@@ -31,12 +31,12 @@ def parseString2Pagenum(parent, string, nodialog=False):
return PageNumbers
except:
if nodialog is False:
- errstring = "Invalid syntax in page selection: "+string+\
- ". Please use a comma separated list with"+\
+ errstring = "Invalid syntax in page selection: "+string +\
+ ". Please use a comma separated list with" +\
" optional dashes, e.g. '1-3,6,8'."
try:
wx.MessageDialog(parent, errstring, "Error",
- style=wx.ICON_ERROR|wx.OK|wx.STAY_ON_TOP)
+ style=wx.ICON_ERROR | wx.OK | wx.STAY_ON_TOP)
except:
raise ValueError(errstring)
else:
@@ -110,4 +110,3 @@ def getMainIcon(pxlength=32):
iconBMP = wx.Bitmap(image)
iconICO = wx.Icon(iconBMP)
return iconICO
-
diff --git a/pycorrfit/gui/page.py b/pycorrfit/gui/page.py
index 7c9156db..b5c87e8a 100644
--- a/pycorrfit/gui/page.py
+++ b/pycorrfit/gui/page.py
@@ -19,11 +19,11 @@
from . import wxutils
-
class FittingPanel(wx.Panel):
"""
Those are the Panels that show the fitting dialogs with the Plots.
"""
+
def __init__(self, parent, counter, modelid, active_parms, tau=None):
""" Initialize with given parameters. """
wx.Panel.__init__(self, parent=parent, id=wx.ID_ANY)
@@ -42,11 +42,10 @@ def __init__(self, parent, counter, modelid, active_parms, tau=None):
self._bgselected = None
self._bg2selected = None
- self.FitKnots = 5 # number of knots for spline fit or similiars
-
- self.weighted_fittype_id = 0 # integer (drop down item)
- self.weighted_nuvar = 3 # bins for std-dev. (left and rigth)
+ self.FitKnots = 5 # number of knots for spline fit or similiars
+ self.weighted_fittype_id = 0 # integer (drop down item)
+ self.weighted_nuvar = 3 # bins for std-dev. (left and rigth)
# The weights that are plotted in the page
# This is set by the PlotAll function
@@ -66,7 +65,7 @@ def __init__(self, parent, counter, modelid, active_parms, tau=None):
# Tool statistics uses this list:
self.StatisticsCheckboxes = None
- ### Splitter window
+ # Splitter window
# Sizes
size = parent.notebook.GetSize()
tabsize = 33
@@ -78,11 +77,11 @@ def __init__(self, parent, counter, modelid, active_parms, tau=None):
self.sp = wx.SplitterWindow(self, size=size, style=wx.SP_3DSASH)
# This is necessary to prevent "Unsplit" of the SplitterWindow:
self.sp.SetMinimumPaneSize(1)
- ## Settings Section (left side)
+ # Settings Section (left side)
#self.panelsettings = wx.Panel(self.sp, size=sizepanel)
self.panelsettings = scrolled.ScrolledPanel(self.sp, size=sizepanel)
self.panelsettings.SetupScrolling(scroll_x=False)
- ## Setting up Plot (correlation + chi**2)
+ # Setting up Plot (correlation + chi**2)
self.spcanvas = wx.SplitterWindow(self.sp, size=sizecanvas,
style=wx.SP_3DSASH)
# This is necessary to prevent "Unsplit" of the SplitterWindow:
@@ -164,7 +163,7 @@ def bgselected(self):
@bgselected.setter
def bgselected(self, value):
if value is None:
- self.corr.backgrounds=[]
+ self.corr.backgrounds = []
return
# check paren.Background and get id
background = self.parent.Background[value]
@@ -179,7 +178,7 @@ def bg2selected(self):
def bg2selected(self, value):
if value is None:
if self.corr.is_cc:
- self.corr.backgrounds=[]
+ self.corr.backgrounds = []
return
# check paren.Background and get id
background = self.parent.Background[value]
@@ -207,7 +206,7 @@ def apply_parameters(self, event=None):
# Here: Convert human readable units to program internal
# units
parmsconv = mdls.GetInternalFromHumanReadableParm(
- modelid, np.array(parameters))[1]
+ modelid, np.array(parameters))[1]
self.corr.fit_parameters = parmsconv
# Fitting parameters
@@ -239,7 +238,7 @@ def apply_parameters(self, event=None):
elif self.weighted_fittype_id == 2:
fit_weight_type = "model function"
fit_weight_data = self.weighted_nuvar
- else: # fitbox_selection > 2:
+ else: # fitbox_selection > 2:
fit_weight_type = fitbox_value
self.corr.fit_weight_type = fitbox_value
fit_weight_data = self.corr.fit_weight_data
@@ -256,7 +255,6 @@ def apply_parameters(self, event=None):
# function, write them back.
self.apply_parameters_reverse()
-
def apply_parameters_reverse(self, event=None):
""" Read the values from the pages parameters and write
it to the GUI form.
@@ -270,7 +268,7 @@ def apply_parameters_reverse(self, event=None):
# Here: Convert program internal units to
# human readable units
parameters = mdls.GetHumanReadableParms(modelid,
- self.corr.fit_parameters)[1]
+ self.corr.fit_parameters)[1]
parameters_variable = self.corr.fit_parameters_variable
# Write parameters to the form on the Page
for i in np.arange(len(self.active_parms[1])):
@@ -295,17 +293,15 @@ def apply_parameters_reverse(self, event=None):
self.AlgorithmDropdown.SetSelection(idalg)
self.updateChi2()
-
def calculate_corr(self):
"""
Calculate model correlation function
"""
return self.corr.modeled
-
def Fit_enable_fitting(self):
""" Enable the fitting button and the weighted fit control"""
- #self.Fitbox = [ fitbox, weightedfitdrop, fittext, fittext2,
+ # self.Fitbox = [ fitbox, weightedfitdrop, fittext, fittext2,
# fittextvar, fitspin, buttonfit, textalg,
# self.AlgorithmDropdown]
self.Fitbox[0].Enable()
@@ -314,7 +310,6 @@ def Fit_enable_fitting(self):
self.Fitbox[7].Enable()
self.Fitbox[8].Enable()
-
def Fit_function(self, event=None, noplots=False, trigger=None):
""" Calls the fit function.
@@ -327,7 +322,6 @@ def Fit_function(self, event=None, noplots=False, trigger=None):
"""
tools.batchcontrol.FitProgressDlg(self, self)
-
def Fit_finalize(self, trigger):
""" Things that need be done after fitting
"""
@@ -350,12 +344,11 @@ def Fit_finalize(self, trigger):
# update displayed chi2
self.updateChi2()
-
def Fit_WeightedFitCheck(self, event=None):
""" Enable Or disable variance calculation, dependent on
"Weighted Fit" checkbox
"""
- #self.Fitbox=[ fitbox, weightedfitdrop, fittext, fittext2, fittextvar,
+ # self.Fitbox=[ fitbox, weightedfitdrop, fittext, fittext2, fittextvar,
# fitspin, buttonfit ]
weighted = (self.Fitbox[1].GetSelection() != 0)
# In the case of "Average" we do not enable the
@@ -371,7 +364,6 @@ def Fit_WeightedFitCheck(self, event=None):
self.Fitbox[4].Disable()
self.Fitbox[5].Disable()
-
def MakeStaticBoxSizer(self, boxlabel):
""" Create a Box with check boxes (fit yes/no) and possibilities to
change initial values for fitting.
@@ -410,26 +402,25 @@ def MakeStaticBoxSizer(self, boxlabel):
sizer.Add(sizerh)
return sizer, check, spin
-
def OnAmplitudeCheck(self, event=None):
""" Enable/Disable BG rate text line.
New feature introduced in 0.7.8
"""
modelid = self.corr.fit_model.id
- ## Normalization to a certain parameter in plots
+ # Normalization to a certain parameter in plots
# Find all parameters that start with an "N"
# ? and "C" ?
# Create List
normlist = list()
normlist.append("None")
- ## Add parameters
+ # Add parameters
parameterlist = list()
for i in np.arange(len(self.active_parms[0])):
label = self.active_parms[0][i]
if label[0].lower() == "n":
normlist.append("*"+label)
parameterlist.append(i)
- ## Add supplementary parameters
+ # Add supplementary parameters
# Get them from models
supplement = mdls.GetMoreInfo(modelid, self)
if supplement is not None:
@@ -457,9 +448,9 @@ def OnAmplitudeCheck(self, event=None):
# Set dropdown values
self.AmplitudeInfo[2].SetItems(normlist)
self.AmplitudeInfo[2].SetSelection(normsel)
- ## Plot intensities
+ # Plot intensities
# Quick reminder:
- #self.AmplitudeInfo = [ [intlabel1, intlabel2],
+ # self.AmplitudeInfo = [ [intlabel1, intlabel2],
# [bgspin1, bgspin2],
# normtoNDropdown, textnor]
# Signal
@@ -473,20 +464,20 @@ def OnAmplitudeCheck(self, event=None):
else:
self.AmplitudeInfo[0][1].Disable()
# Background
- ## self.parent.Background[self.bgselected][i]
- ## [0] average signal [kHz]
- ## [1] signal name (edited by user)
- ## [2] signal trace (tuple) ([ms], [kHz])
+ # self.parent.Background[self.bgselected][i]
+ # [0] average signal [kHz]
+ # [1] signal name (edited by user)
+ # [2] signal trace (tuple) ([ms], [kHz])
if len(self.corr.backgrounds) >= 1:
self.AmplitudeInfo[1][0].SetValue(
- self.corr.backgrounds[0].countrate)
+ self.corr.backgrounds[0].countrate)
else:
self.AmplitudeInfo[1][0].SetValue(0)
self.AmplitudeInfo[1][1].SetValue(0)
if len(self.corr.backgrounds) == 2:
self.AmplitudeInfo[1][1].SetValue(
- self.corr.backgrounds[1].countrate)
+ self.corr.backgrounds[1].countrate)
else:
self.AmplitudeInfo[1][1].SetValue(0)
# Disable the second line in amplitude correction, if we have
@@ -495,13 +486,12 @@ def OnAmplitudeCheck(self, event=None):
for item in self.WXAmplitudeCCOnlyStuff:
item.Enable(boolval)
-
def OnBGSpinChanged(self, e):
""" Calls tools.background.ApplyAutomaticBackground
to update background information
"""
# Quick reminder:
- #self.AmplitudeInfo = [ [intlabel1, intlabel2],
+ # self.AmplitudeInfo = [ [intlabel1, intlabel2],
# [bgspin1, bgspin2],
# normtoNDropdown, textnor]
if self.corr.is_cc:
@@ -509,7 +499,7 @@ def OnBGSpinChanged(self, e):
bg = [float(self.AmplitudeInfo[1][0].GetValue()),
float(self.AmplitudeInfo[1][1].GetValue())]
sig = [float(self.AmplitudeInfo[0][0].GetValue()),
- float(self.AmplitudeInfo[0][1].GetValue())]
+ float(self.AmplitudeInfo[0][1].GetValue())]
# Make sure bg < sig
for ii in range(len(bg)):
if sig[ii] != 0:
@@ -529,7 +519,6 @@ def OnBGSpinChanged(self, e):
self.parent)
e.Skip()
-
def OnTitleChanged(self, e):
modelid = self.corr.fit_model.id
pid = self.parent.notebook.GetPageIndex(self)
@@ -539,7 +528,7 @@ def OnTitleChanged(self, e):
# How many characters of the the page title should be displayed
# in the tab? We choose 9: AC1-012 plus 2 whitespaces
text = self.counter + self.tabtitle.GetValue()[-9:]
- self.parent.notebook.SetPageText(pid,text)
+ self.parent.notebook.SetPageText(pid, text)
def OnSetRange(self, e):
""" Open a new Frame where the parameter range can be set.
@@ -563,7 +552,6 @@ def OnSetRange(self, e):
pass
self.parent.RangeSelector = None
-
def OnSize(self, event):
""" Resize the fitting Panel, when Window is resized. """
size = self.parent.notebook.GetSize()
@@ -571,7 +559,6 @@ def OnSize(self, event):
size[1] = size[1] - tabsize
self.sp.SetSize(size)
-
def PlotAll(self, event=None, trigger=None):
"""
This function plots the whole correlation and residuals canvas.
@@ -598,18 +585,18 @@ def PlotAll(self, event=None, trigger=None):
return
else:
self.InitialPlot = True
- ## Enable/Disable, set values frontend normalization
+ # Enable/Disable, set values frontend normalization
self.OnAmplitudeCheck()
- ## Apply parameters
+ # Apply parameters
self.apply_parameters()
# Calculate correlation function from parameters
- ## Drawing of correlation plot
+ # Drawing of correlation plot
# Plots corr.correlation_fit and the calcualted correlation function
# self.datacorr into the upper canvas.
# Create a line @ y=zero:
zerostart = self.corr.lag_time_fit[0]
zeroend = self.corr.lag_time_fit[-1]
- datazero = [[zerostart, 0], [zeroend,0]]
+ datazero = [[zerostart, 0], [zeroend, 0]]
# Set plot colors
width = 1
colexp = "grey"
@@ -633,14 +620,15 @@ def PlotAll(self, event=None, trigger=None):
# if weights are from average or other, make sure that the
# dimensions are correct
if weights.shape[0] == self.corr.correlation.shape[0]:
- weights = weights[self.corr.fit_ival[0]:self.corr.fit_ival[1]]
+ weights = weights[self.corr.fit_ival[0] :self.corr.fit_ival[1]]
# perform some checks
if np.allclose(weights, np.ones_like(weights)):
weights = 0
elif weights.shape[0] != self.corr.modeled_fit.shape[0]:
# non-matching weigths
- warnings.warn("Unmatching weights found. Probably from previous data set.")
+ warnings.warn(
+ "Unmatching weights found. Probably from previous data set.")
weights = 0
# Add the weights to the graph.
@@ -653,24 +641,25 @@ def PlotAll(self, event=None, trigger=None):
w2[:, 1] = w[:, 1] - weights
# crop w1 and w2 if corr.correlation_fit does not include all
# data points.
- if np.all(w[:,0] == self.corr.correlation_fit[:,0]):
+ if np.all(w[:, 0] == self.corr.correlation_fit[:, 0]):
pass
else:
- raise ValueError("This should not have happened: size of weights is wrong.")
- ## Normalization with self.normfactor
- w1[:,1] *= self.corr.normalize_factor
- w2[:,1] *= self.corr.normalize_factor
- self.weights_plot_fill_area = [w1,w2]
+ raise ValueError(
+ "This should not have happened: size of weights is wrong.")
+ # Normalization with self.normfactor
+ w1[:, 1] *= self.corr.normalize_factor
+ w2[:, 1] *= self.corr.normalize_factor
+ self.weights_plot_fill_area = [w1, w2]
lineweight1 = plot.PolyLine(w1, legend='',
- colour=colweight, width=width)
+ colour=colweight, width=width)
lines.append(lineweight1)
lineweight2 = plot.PolyLine(w2, legend='',
- colour=colweight, width=width)
+ colour=colweight, width=width)
lines.append(lineweight2)
else:
self.weights_plot_fill_area = None
- ## Plot Correlation curves
+ # Plot Correlation curves
# Plot both, experimental and calculated data
# Normalization with self.normfactor, new feature in 0.7.8
datacorr_norm = self.corr.modeled_plot
@@ -683,10 +672,10 @@ def PlotAll(self, event=None, trigger=None):
lines.append(lineexp)
lines.append(linecorr)
PlotCorr = plot.PlotGraphics(lines,
- xLabel=u'lag time Ļ [ms]', yLabel=u'G(Ļ)')
+ xLabel=u'lag time Ļ [ms]', yLabel=u'G(Ļ)')
self.canvascorr.Draw(PlotCorr)
- ## Calculate residuals
+ # Calculate residuals
resid_norm = self.corr.residuals_plot
lineres = plot.PolyLine(resid_norm, legend='', colour=colfit,
width=width)
@@ -697,8 +686,8 @@ def PlotAll(self, event=None, trigger=None):
else:
yLabelRes = "residuals"
PlotRes = plot.PlotGraphics([linezero, lineres],
- xLabel=u'lag time Ļ [ms]',
- yLabel=yLabelRes)
+ xLabel=u'lag time Ļ [ms]',
+ yLabel=yLabelRes)
self.canvaserr.Draw(PlotRes)
else:
# Amplitude normalization, new feature in 0.7.8
@@ -706,12 +695,11 @@ def PlotAll(self, event=None, trigger=None):
linecorr = plot.PolyLine(datacorr_norm, legend='', colour='blue',
width=1)
PlotCorr = plot.PlotGraphics([linezero, linecorr],
- xLabel=u'Lag time Ļ [ms]', yLabel=u'G(Ļ)')
+ xLabel=u'Lag time Ļ [ms]', yLabel=u'G(Ļ)')
self.canvascorr.Draw(PlotCorr)
self.Refresh()
self.parent.OnFNBPageChanged(trigger=trigger)
-
def settings(self):
""" Here we define, what should be displayed at the left side
of the fitting page/tab.
@@ -724,7 +712,7 @@ def settings(self):
mddat = mdls.modeldict[modelid]
modelshort = mdls.GetModelType(modelid)
titlelabel = u"Data set {} ({} {})".format(
- self.counter.strip(" :"), modelshort, mddat[1])
+ self.counter.strip(" :"), modelshort, mddat[1])
boxti = wx.StaticBox(self.panelsettings, label=titlelabel)
sizerti = wx.StaticBoxSizer(boxti, wx.VERTICAL)
sizerti.SetMinSize((horizontalsize, -1))
@@ -743,7 +731,7 @@ def settings(self):
# in the Page info tool.
#
labels, parameters = mdls.GetHumanReadableParms(modelid,
- self.active_parms[1])
+ self.active_parms[1])
parameterstofit = self.active_parms[2]
# Set initial values given by user/programmer for Diffusion Model
for i in np.arange(len(labels)):
@@ -769,17 +757,18 @@ def settings(self):
box1.Add(horzs)
# Set horizontal size
box1.SetMinSize((horizontalsize, -1))
- ## More info
- normbox = wx.StaticBox(self.panelsettings, label="Amplitude corrections")
+ # More info
+ normbox = wx.StaticBox(
+ self.panelsettings, label="Amplitude corrections")
miscsizer = wx.StaticBoxSizer(normbox, wx.VERTICAL)
miscsizer.SetMinSize((horizontalsize, -1))
# Intensities and Background
sizeint = wx.FlexGridSizer(rows=3, cols=3, vgap=5, hgap=5)
sizeint.Add(wx.StaticText(self.panelsettings, label="[kHz]"))
sizeint.Add(wx.StaticText(self.panelsettings,
- label="Intensity"))
+ label="Intensity"))
sizeint.Add(wx.StaticText(self.panelsettings,
- label="Background"))
+ label="Background"))
sizeint.Add(wx.StaticText(self.panelsettings, label="Ch1"))
intlabel1 = wx.TextCtrl(self.panelsettings)
bgspin1 = wxutils.PCFFloatTextCtrl(self.panelsettings)
@@ -797,18 +786,18 @@ def settings(self):
sizeint.Add(intlabel2)
sizeint.Add(bgspin2)
miscsizer.Add(sizeint)
- ## Normalize to n?
+ # Normalize to n?
textnor = wx.StaticText(self.panelsettings, label="Plot normalization")
miscsizer.Add(textnor)
normtoNDropdown = wx.ComboBox(self.panelsettings)
self.Bind(wx.EVT_COMBOBOX, self.PlotAll, normtoNDropdown)
miscsizer.Add(normtoNDropdown)
- self.AmplitudeInfo = [ [intlabel1, intlabel2],
- [bgspin1, bgspin2],
- normtoNDropdown, textnor]
+ self.AmplitudeInfo = [[intlabel1, intlabel2],
+ [bgspin1, bgspin2],
+ normtoNDropdown, textnor]
self.WXAmplitudeCCOnlyStuff = [chtext2, intlabel2, bgspin2]
self.panelsettings.sizer.Add(miscsizer, 0, wx.EXPAND, 0)
- ## Add fitting Box
+ # Add fitting Box
fitbox = wx.StaticBox(self.panelsettings, label="Fitting options")
fitsizer = wx.StaticBoxSizer(fitbox, wx.VERTICAL)
fitsizer.SetMinSize((horizontalsize, -1))
@@ -834,7 +823,8 @@ def settings(self):
fitsizer.Add(fittext2)
fitsizerspin = wx.BoxSizer(wx.HORIZONTAL)
fittextvar = wx.StaticText(self.panelsettings, label="j = ")
- fitspin = wx.SpinCtrl(self.panelsettings, -1, initial=3, min=1, max=100)
+ fitspin = wx.SpinCtrl(self.panelsettings, -1,
+ initial=3, min=1, max=100)
fitsizerspin.Add(fittextvar)
fitsizerspin.Add(fitspin)
fitsizer.Add(fitsizerspin)
@@ -854,8 +844,9 @@ def settings(self):
self.Bind(wx.EVT_BUTTON, self.Fit_function, buttonfit)
fitbuttonsizer.Add(buttonfit)
- ## add shortcut
- acctbl = wx.AcceleratorTable([(wx.ACCEL_CTRL, ord('F'), buttonfit.GetId())])
+ # add shortcut
+ acctbl = wx.AcceleratorTable(
+ [(wx.ACCEL_CTRL, ord('F'), buttonfit.GetId())])
self.SetAcceleratorTable(acctbl)
##
@@ -870,16 +861,15 @@ def settings(self):
self.panelsettings.Layout()
self.panelsettings.Show()
# Make all the stuff available for everyone
- self.Fitbox = [ fitbox, weightedfitdrop, fittext, fittext2,
- fittextvar, fitspin, buttonfit, textalg,
- self.AlgorithmDropdown]
+ self.Fitbox = [fitbox, weightedfitdrop, fittext, fittext2,
+ fittextvar, fitspin, buttonfit, textalg,
+ self.AlgorithmDropdown]
# Disable Fitting since no data has been loaded yet
for element in self.Fitbox:
element.Disable()
self.panelsettings.sizer.Fit(self.panelsettings)
self.parent.Layout()
-
def updateChi2(self):
"""
updates the self.WXTextChi2 text control
@@ -892,5 +882,5 @@ def updateChi2(self):
chi2str = wxutils.nice_string(chi2str)
label = u" ĻĀ²={}".format(chi2str)
# This does not work with wxPython 2.8.12:
- #self.WXTextChi2.SetLabelMarkup(u"{}".format(label))
+ # self.WXTextChi2.SetLabelMarkup(u"{}".format(label))
self.WXTextChi2.SetLabel(u"{}".format(label))
diff --git a/pycorrfit/gui/plotting.py b/pycorrfit/gui/plotting.py
index 22b095be..e832facc 100644
--- a/pycorrfit/gui/plotting.py
+++ b/pycorrfit/gui/plotting.py
@@ -1,3 +1,9 @@
+from pycorrfit import models as mdls
+from pycorrfit.meta import find_program
+import unicodedata
+from matplotlib import rcParams
+import matplotlib.pyplot as plt
+import matplotlib.gridspec as gridspec
"""Module plotting
Everything about plotting with matplotlib is located here.
@@ -13,15 +19,9 @@
with warnings.catch_warnings():
warnings.simplefilter("ignore")
matplotlib.use('WXAgg') # Tells matplotlib to use WxWidgets for dialogs
-import matplotlib.gridspec as gridspec
-import matplotlib.pyplot as plt
# Text rendering with matplotlib
-from matplotlib import rcParams
-import unicodedata
# For finding latex tools
-from pycorrfit.meta import find_program
-from pycorrfit import models as mdls
def greek2tex(char):
@@ -103,7 +103,7 @@ def latexmath(string):
else:
anew += char
# lower case
- lcitems = anew.split("_",1)
+ lcitems = anew.split("_", 1)
if len(lcitems) > 1:
anew = lcitems[0]+"_{\\text{"+lcitems[1]+"}}"
return anew + r" \hspace{0.3em} \mathrm{"+b+r"}"
@@ -154,7 +154,7 @@ def savePlotCorrelation(parent, dirname, Page, uselatex=False,
weights = Page.weights_plot_fill_area
tabtitle = Page.tabtitle.GetValue()
- #fitlabel = ur"Fit model: "+str(mdls.modeldict[Page.modelid][0])
+ # fitlabel = ur"Fit model: "+str(mdls.modeldict[Page.modelid][0])
fitlabel = Page.corr.fit_model.name
labelweights = r"Weights of fit"
labels, parms = mdls.GetHumanReadableParms(Page.modelid,
@@ -168,22 +168,23 @@ def savePlotCorrelation(parent, dirname, Page, uselatex=False,
if tabtitle.strip() == "":
tabtitle = "page"+str(Page.counter).strip().strip(":")
if Page.corr.normparm is not None:
- fitlabel += r", normalized to "+Page.corr.fit_model.parameters[0][Page.corr.normparm]
+ fitlabel += r", normalized to " + \
+ Page.corr.fit_model.parameters[0][Page.corr.normparm]
- ## Check if we can use latex for plotting:
+ # Check if we can use latex for plotting:
r1 = find_program("latex")[0]
r2 = find_program("dvipng")[0]
# Ghostscript
r31 = find_program("gs")[0]
- r32 = find_program("mgs")[0] # from miktex
- r3 = max(r31,r32)
+ r32 = find_program("mgs")[0] # from miktex
+ r3 = max(r31, r32)
if r1+r2+r3 < 3:
uselatex = False
if uselatex == True:
rcParams['text.usetex'] = True
rcParams['text.latex.unicode'] = True
rcParams['font.family'] = 'serif'
- rcParams['text.latex.preamble']=[r"""\usepackage{amsmath}
+ rcParams['text.latex.preamble'] = [r"""\usepackage{amsmath}
\usepackage[utf8x]{inputenc}
\usepackage{amssymb}
\usepackage{siunitx}"""]
@@ -191,31 +192,31 @@ def savePlotCorrelation(parent, dirname, Page, uselatex=False,
tabtitle = r"{\normalsize "+escapechars(tabtitle)+r"}"
labelweights = r"{\normalsize "+escapechars(labelweights)+r"}"
else:
- rcParams['text.usetex']=False
+ rcParams['text.usetex'] = False
# create plot
# plt.plot(x, y, '.', label = 'original data', markersize=5)
- fig=plt.figure()
+ fig = plt.figure()
wtit = "Correlation #{:04d}_{}".format(int(Page.counter.strip(":# ")),
- Page.title.strip())
+ Page.title.strip())
fig.canvas.set_window_title(wtit)
if resid is not None:
- gs = gridspec.GridSpec(2, 1, height_ratios=[5,1])
+ gs = gridspec.GridSpec(2, 1, height_ratios=[5, 1])
ax = plt.subplot(gs[0])
else:
ax = plt.subplot(111)
# ax = plt.axes()
ax.semilogx()
# plot fit first
- plt.plot(fit[:,0], fit[:,1], '-', label=fitlabel, lw=1.5,
+ plt.plot(fit[:, 0], fit[:, 1], '-', label=fitlabel, lw=1.5,
color="blue")
if dataexp is not None:
- plt.plot(dataexp[:,0], dataexp[:,1], '-', color="black",
+ plt.plot(dataexp[:, 0], dataexp[:, 1], '-', color="black",
alpha=.7, label=tabtitle, lw=1)
else:
plt.xlabel(r'lag time $\tau$ [ms]')
if weights is not None and show_weights is True:
- plt.fill_between(weights[0][:,0],weights[0][:,1],weights[1][:,1],
+ plt.fill_between(weights[0][:, 0], weights[0][:, 1], weights[1][:, 1],
color='cyan')
# fake legend:
p = plt.Rectangle((0, 0), 0, 0, color='cyan',
@@ -223,16 +224,16 @@ def savePlotCorrelation(parent, dirname, Page, uselatex=False,
ax.add_patch(p)
plt.ylabel('correlation')
if dataexp is not None:
- mind = np.min([ dataexp[:,1], fit[:,1]])
- maxd = np.max([ dataexp[:,1], fit[:,1]])
+ mind = np.min([dataexp[:, 1], fit[:, 1]])
+ maxd = np.max([dataexp[:, 1], fit[:, 1]])
else:
- mind = np.min(fit[:,1])
- maxd = np.max(fit[:,1])
+ mind = np.min(fit[:, 1])
+ maxd = np.max(fit[:, 1])
ymin = mind - (maxd - mind)/20.
ymax = maxd + (maxd - mind)/20.
ax.set_ylim(bottom=ymin, top=ymax)
- xmin = np.min(fit[:,0])
- xmax = np.max(fit[:,0])
+ xmin = np.min(fit[:, 0])
+ xmax = np.max(fit[:, 0])
ax.set_xlim(xmin, xmax)
# Add some nice text:
if uselatex == True and len(parms) != 0:
@@ -240,8 +241,8 @@ def savePlotCorrelation(parent, dirname, Page, uselatex=False,
text += r'\['
text += r'\begin{split}'
text += genLatexText(parms, labels)
- ## According to issue #54, we remove fitting errors from plots
- #if errparms is not None:
+ # According to issue #54, we remove fitting errors from plots
+ # if errparms is not None:
# keys = errparms.keys()
# keys.sort()
# for key in keys:
@@ -252,21 +253,19 @@ def savePlotCorrelation(parent, dirname, Page, uselatex=False,
text = r""
for i in np.arange(len(parms)):
text += u"{} = {:.3g}\n".format(labels[i], parms[i])
- ## According to issue #54, we remove fitting errors from plots
- #if errparms is not None:
+ # According to issue #54, we remove fitting errors from plots
+ # if errparms is not None:
# keys = errparms.keys()
# keys.sort()
# for key in keys:
# text += "Err "+key+" = " + str(errparms[key]) +"\n"
-
-
logmax = np.log10(xmax)
logmin = np.log10(xmin)
logtext = 0.6*(logmax-logmin)+logmin
xt = 10**(logtext)
yt = 0.3*ymax
- plt.text(xt,yt,text, size=12)
+ plt.text(xt, yt, text, size=12)
if resid is not None:
ax2 = plt.subplot(gs[1])
#ax2 = plt.axes()
@@ -276,15 +275,15 @@ def savePlotCorrelation(parent, dirname, Page, uselatex=False,
lb = r"\newline \indent "
else:
lb = "\n"
- yLabelRes = "weighted "+ lb +"residuals"
+ yLabelRes = "weighted " + lb + "residuals"
else:
yLabelRes = "residuals"
- minx = np.min(resid[:,0])
- maxx = np.max(resid[:,0])
- miny = np.min(resid[:,1])
- maxy = np.max(resid[:,1])
+ minx = np.min(resid[:, 0])
+ maxx = np.max(resid[:, 0])
+ miny = np.min(resid[:, 1])
+ maxy = np.max(resid[:, 1])
plt.hlines(0, minx, maxx, colors="orange")
- plt.plot(resid[:,0], resid[:,1], '-', color="black",
+ plt.plot(resid[:, 0], resid[:, 1], '-', color="black",
alpha=.85, label=yLabelRes, lw=1)
plt.xlabel(r'lag time $\tau$ [ms]')
plt.ylabel(yLabelRes, multialignment='center')
@@ -294,14 +293,13 @@ def savePlotCorrelation(parent, dirname, Page, uselatex=False,
ax2.set_ylim(-maxy, maxy)
ticks = ax2.get_yticks()
ax2.set_yticks([ticks[0], ticks[-1], 0])
- ## Hack
+ # Hack
# We need this for hacking. See edclasses.
fig.canvas.HACK_parent = parent
fig.canvas.HACK_fig = fig
fig.canvas.HACK_Page = Page
fig.canvas.HACK_append = ".png"
-
# Legend outside of plot
# Decrease size of plot to fit legend
box = ax.get_position()
@@ -312,11 +310,10 @@ def savePlotCorrelation(parent, dirname, Page, uselatex=False,
if resid is not None:
box2 = ax2.get_position()
ax2.set_position([box2.x0, box2.y0 + box.height * 0.2,
- box2.width, box2.height])
+ box2.width, box2.height])
ax.legend(loc='upper center', bbox_to_anchor=(0.5, -0.55),
- prop={'size':9})
-
+ prop={'size': 9})
if verbose == True:
plt.show()
@@ -364,44 +361,44 @@ def savePlotTrace(parent, dirname, Page, uselatex=False, verbose=False):
for ii, tr in enumerate(traces):
labels.append("Channel {}: {}".format(ii+1, tr.name))
- ## Check if we can use latex for plotting:
+ # Check if we can use latex for plotting:
r1 = find_program("latex")[0]
r2 = find_program("dvipng")[0]
# Ghostscript
r31 = find_program("gs")[0]
r32 = find_program("mgs")[0]
- r3 = max(r31,r32)
+ r3 = max(r31, r32)
if r1+r2+r3 < 3:
uselatex = False
if uselatex == True:
- rcParams['text.usetex']=True
- rcParams['text.latex.unicode']=True
- rcParams['font.family']='serif'
- rcParams['text.latex.preamble']=[r"\usepackage{amsmath}"]
+ rcParams['text.usetex'] = True
+ rcParams['text.latex.unicode'] = True
+ rcParams['font.family'] = 'serif'
+ rcParams['text.latex.preamble'] = [r"\usepackage{amsmath}"]
for i in np.arange(len(labels)):
labels[i] = r"{\normalsize "+escapechars(labels[i])+r"}"
else:
- rcParams['text.usetex']=False
+ rcParams['text.usetex'] = False
# create plot
# plt.plot(x, y, '.', label = 'original data', markersize=5)
- fig=plt.figure(figsize=(10,3))
+ fig = plt.figure(figsize=(10, 3))
wtit = "Trace #{:04d}_{}".format(int(Page.counter.strip(":# ")),
Page.title.strip())
fig.canvas.set_window_title(wtit)
ax = plt.subplot(111)
for i in np.arange(len(traces)):
# Columns
- time = traces[i][:,0]*timefactor
- intensity = traces[i][:,1]
+ time = traces[i][:, 0]*timefactor
+ intensity = traces[i][:, 1]
plt.plot(time, intensity, '-',
- label = labels[i],
+ label=labels[i],
lw=1)
# set plot boundaries
maxy = -np.infty
miny = np.infty
for tr in traces:
- maxy = max(np.max(tr[:,1]), maxy)
- miny = min(np.min(tr[:,1]), miny)
+ maxy = max(np.max(tr[:, 1]), maxy)
+ miny = min(np.min(tr[:, 1]), miny)
ax.set_ylim(miny, maxy)
plt.ylabel('count rate [kHz]')
@@ -414,17 +411,17 @@ def savePlotTrace(parent, dirname, Page, uselatex=False, verbose=False):
box.width, box.height * 0.9])
plt.legend(loc='upper center',
bbox_to_anchor=(0.5, -0.35),
- prop={'size':9},
+ prop={'size': 9},
)
- ## Hack
+ # Hack
# We need this for hacking. See edclasses.
fig.canvas.HACK_parent = parent
fig.canvas.HACK_fig = fig
fig.canvas.HACK_Page = Page
fig.canvas.HACK_append = "_trace.png"
- plt.tight_layout(rect=(.001,.34,.999,1.0))
+ plt.tight_layout(rect=(.001, .34, .999, 1.0))
if verbose == True:
plt.show()
@@ -441,5 +438,6 @@ def savePlotTrace(parent, dirname, Page, uselatex=False, verbose=False):
except:
pass
+
# set dpi to 300
matplotlib.rcParams['savefig.dpi'] = 300
diff --git a/pycorrfit/gui/threaded_progress.py b/pycorrfit/gui/threaded_progress.py
index b78a9894..1d5029f3 100644
--- a/pycorrfit/gui/threaded_progress.py
+++ b/pycorrfit/gui/threaded_progress.py
@@ -20,6 +20,7 @@ class KThread(threading.Thread):
thread will not actually be killed until the next Python statement is
executed.
"""
+
def __init__(self, *args, **keywords):
threading.Thread.__init__(self, *args, **keywords)
self.killed = False
@@ -53,9 +54,9 @@ def kill(self):
self.killed = True
-
class WorkerThread(KThread):
"""Worker Thread Class."""
+
def __init__(self, target, args, kwargs):
"""Init Worker Thread Class."""
KThread.__init__(self)
@@ -134,21 +135,20 @@ def __init__(self, parent, targets, args=None, kwargs={},
elif isinstance(args, list):
# convenience-convert args to tuples
if not isinstance(args[0], tuple):
- args = [ (t,) for t in args ]
+ args = [(t,) for t in args]
if isinstance(kwargs, dict):
kwargs = [kwargs]*nums
if not messages:
- messages = [ "item {} of {}".format(a+1, nums) for a in range(nums) ]
-
+ messages = ["item {} of {}".format(a+1, nums) for a in range(nums)]
time1 = time.time()
- sty = wx.PD_SMOOTH|wx.PD_AUTO_HIDE|wx.PD_CAN_ABORT
+ sty = wx.PD_SMOOTH | wx.PD_AUTO_HIDE | wx.PD_CAN_ABORT
if len(targets) > 1:
- sty = sty|wx.PD_REMAINING_TIME
+ sty = sty | wx.PD_REMAINING_TIME
dlgargs = [title, "initializing..."]
- dlgkwargs = {"maximum":nums, "parent":parent, "style":sty }
+ dlgkwargs = {"maximum": nums, "parent": parent, "style": sty}
dlg = None
self.aborted = False
@@ -166,7 +166,7 @@ def __init__(self, parent, targets, args=None, kwargs={},
dlg = wx.ProgressDialog(*dlgargs, **dlgkwargs)
wx.EndBusyCursor()
- init=False
+ init = False
time.sleep(.01)
if dlg:
if len(targets) == 1:
@@ -207,25 +207,25 @@ def finalize(self):
pass
-
if __name__ == "__main__":
# GUI Frame class that spins off the worker thread
class MainFrame(wx.Frame):
"""Class MainFrame."""
+
def __init__(self, parent, aid):
"""Create the MainFrame."""
wx.Frame.__init__(self, parent, aid, 'Thread Test')
# Dumb sample frame with two buttons
- but = wx.Button(self, wx.ID_ANY, 'Start Progress', pos=(0,0))
-
+ but = wx.Button(self, wx.ID_ANY, 'Start Progress', pos=(0, 0))
self.Bind(wx.EVT_BUTTON, self.OnStart, but)
def OnStart(self, event):
"""Start Computation."""
# Trigger the worker thread unless it's already busy
- arguments = [ test_class(a) for a in range(10) ]
+ arguments = [test_class(a) for a in range(10)]
+
def method(x):
x.arg *= 1.1
time.sleep(1)
@@ -233,9 +233,9 @@ def method(x):
print(tp.index_aborted)
print([a.arg for a in arguments])
-
class MainApp(wx.App):
"""Class Main App."""
+
def OnInit(self):
"""Init Main App."""
self.frame = MainFrame(None, -1)
@@ -247,6 +247,5 @@ class test_class(object):
def __init__(self, arg):
self.arg = arg
-
app = MainApp(0)
- app.MainLoop()
\ No newline at end of file
+ app.MainLoop()
diff --git a/pycorrfit/gui/tools/__init__.py b/pycorrfit/gui/tools/__init__.py
index 4d9e68ea..4e48d82f 100644
--- a/pycorrfit/gui/tools/__init__.py
+++ b/pycorrfit/gui/tools/__init__.py
@@ -1,3 +1,7 @@
+from .parmrange import RangeSelector
+from .comment import EditComment
+from .chooseimport import ChooseImportTypesModel
+from .chooseimport import ChooseImportTypes
"""PyCorrFit - module "tools"
This file contains tools, such as dialog boxes and other stuff,
@@ -38,42 +42,40 @@
# Load all of the classes
# This also defines the order of the tools in the menu
ImpA = [
- ["datarange", "SelectChannels"],
- ["overlaycurves", "Wrapper_Tools"],
- ["batchcontrol", "BatchCtrl"],
- ["globalfit", "GlobalFit"],
- ["average", "Average"],
- ["background", "BackgroundCorrection"]
- ]
+ ["datarange", "SelectChannels"],
+ ["overlaycurves", "Wrapper_Tools"],
+ ["batchcontrol", "BatchCtrl"],
+ ["globalfit", "GlobalFit"],
+ ["average", "Average"],
+ ["background", "BackgroundCorrection"]
+]
ImpB = [
- ["trace", "ShowTrace"],
- ["statistics", "Stat"],
- ["info", "ShowInfo"],
- ["simulation", "Slide"]
- ]
+ ["trace", "ShowTrace"],
+ ["statistics", "Stat"],
+ ["info", "ShowInfo"],
+ ["simulation", "Slide"]
+]
ModuleActive = list()
ToolsActive = list()
for i in np.arange(len(ImpA)):
# We have to add "tools." because this is a relative import
- ModuleActive.append(__import__(ImpA[i][0], globals(), locals(), [ImpA[i][1]], 1))
+ ModuleActive.append(__import__(
+ ImpA[i][0], globals(), locals(), [ImpA[i][1]], 1))
ToolsActive.append(getattr(ModuleActive[i], ImpA[i][1]))
ModulePassive = list()
ToolsPassive = list()
for i in np.arange(len(ImpB)):
- ModulePassive.append(__import__(ImpB[i][0], globals(), locals(), [ImpB[i][1]], 1))
+ ModulePassive.append(__import__(
+ ImpB[i][0], globals(), locals(), [ImpB[i][1]], 1))
ToolsPassive.append(getattr(ModulePassive[i], ImpB[i][1]))
- #ModulePassive.append(importlib.import_module("tools."+ImpB[i][0]))
+ # ModulePassive.append(importlib.import_module("tools."+ImpB[i][0]))
#ToolsPassive.append(getattr(ModulePassive[i], ImpB[i][1]))
# This is in the file menu and not needed in the dictionaries below.
-from .chooseimport import ChooseImportTypes
-from .chooseimport import ChooseImportTypesModel
-from .comment import EditComment
# the "special" tool RangeSelector
-from .parmrange import RangeSelector
ToolDict = dict()
ToolDict["A"] = ToolsActive
@@ -93,4 +95,3 @@
ToolName = dict()
ToolName["A"] = NameActive
ToolName["P"] = NamePassive
-
diff --git a/pycorrfit/gui/tools/average.py b/pycorrfit/gui/tools/average.py
index 348202c2..9af1777d 100644
--- a/pycorrfit/gui/tools/average.py
+++ b/pycorrfit/gui/tools/average.py
@@ -10,51 +10,52 @@
# Menu entry name
MENUINFO = ["&Average data", "Create an average curve from whole session."]
+
class Average(wx.Frame):
# This tool is derived from a wx.frame.
def __init__(self, parent):
# Define a unique name that identifies this tool
# Do not change this value. It is important for the Overlay tool
# (selectcurves.py, *Wrapper_Tools*).
- self.MyName="AVERAGE"
+ self.MyName = "AVERAGE"
# parent is the main frame of PyCorrFit
self.parent = parent
# Get the window positioning correctly
pos = self.parent.GetPosition()
pos = (pos[0]+100, pos[1]+100)
wx.Frame.__init__(self, parent=self.parent, title="Average curves",
- pos=pos, style=wx.DEFAULT_FRAME_STYLE|wx.FRAME_FLOAT_ON_PARENT)
- ## MYID
+ pos=pos, style=wx.DEFAULT_FRAME_STYLE | wx.FRAME_FLOAT_ON_PARENT)
+ # MYID
# This ID is given by the parent for an instance of this class
self.MyID = None
# Page - the currently active page of the notebook.
self.Page = self.parent.notebook.GetCurrentPage()
- ## Content
+ # Content
self.panel = wx.Panel(self)
self.topSizer = wx.BoxSizer(wx.VERTICAL)
textinit = wx.StaticText(self.panel,
- label="Create an average from the following pages:")
+ label="Create an average from the following pages:")
self.topSizer.Add(textinit)
- ## Page selection
+ # Page selection
self.WXTextPages = wx.TextCtrl(self.panel, value="",
- size=(textinit.GetSize()[0],-1))
+ size=(textinit.GetSize()[0], -1))
self.topSizer.Add(self.WXTextPages)
- ## Chechbox asking for Mono-Model
+ # Chechbox asking for Mono-Model
self.WXCheckMono = wx.CheckBox(self.panel,
- label="Only use pages with the same model as the first page.")
+ label="Only use pages with the same model as the first page.")
self.WXCheckMono.SetValue(True)
self.topSizer.Add(self.WXCheckMono)
- ## Model selection Dropdown
+ # Model selection Dropdown
textinit2 = wx.StaticText(self.panel,
- label="Select a model for the average:")
+ label="Select a model for the average:")
self.topSizer.Add(textinit2)
- self.WXDropSelMod = wx.ComboBox(self.panel, -1, "", (15,30),
- wx.DefaultSize, [], wx.CB_DROPDOWN|wx.CB_READONLY)
+ self.WXDropSelMod = wx.ComboBox(self.panel, -1, "", (15, 30),
+ wx.DefaultSize, [], wx.CB_DROPDOWN | wx.CB_READONLY)
self.topSizer.Add(self.WXDropSelMod)
textinit3 = wx.StaticText(self.panel,
- label="This tool averages only over pages with the same type"+\
- "\n(auto- or cross-correlation). Intensity data are"+\
- "\nappended sequentially.")
+ label="This tool averages only over pages with the same type" +
+ "\n(auto- or cross-correlation). Intensity data are" +
+ "\nappended sequentially.")
self.topSizer.Add(textinit3)
# Set all values of Text and Strin
self.SetValues()
@@ -65,13 +66,12 @@ def __init__(self, parent):
self.panel.SetSizer(self.topSizer)
self.topSizer.Fit(self)
self.SetMinSize(self.topSizer.GetMinSize())
- #Icon
+ # Icon
if parent.MainIcon is not None:
wx.Frame.SetIcon(self, parent.MainIcon)
self.Show(True)
self.OnPageChanged(self.Page)
-
def OnClose(self, event=None):
# This is a necessary function for PyCorrFit.
# Do not change it.
@@ -79,7 +79,6 @@ def OnClose(self, event=None):
self.parent.ToolsOpen.__delitem__(self.MyID)
self.Destroy()
-
def OnPageChanged(self, page, trigger=None):
"""
This function is called, when something in the panel
@@ -102,12 +101,11 @@ def OnPageChanged(self, page, trigger=None):
#idsel = self.WXDropSelMod.GetSelection()
self.SetValues()
# Set back user selection:
- #self.WXDropSelMod.SetSelection(idsel)
+ # self.WXDropSelMod.SetSelection(idsel)
self.panel.Enable()
self.Page = page
-
def OnAverage(self, evt=None):
strFull = self.WXTextPages.GetValue()
PageNumbers = misc.parseString2Pagenum(self, strFull)
@@ -128,8 +126,8 @@ def OnAverage(self, evt=None):
if referencePage is None:
# If that did not work, we have to raise an error.
- raise IndexError("PyCorrFit could not find the first"+
- " page for averaging.")
+ raise IndexError("PyCorrFit could not find the first" +
+ " page for averaging.")
return
for i in np.arange(self.parent.notebook.GetPageCount()):
@@ -141,8 +139,8 @@ def OnAverage(self, evt=None):
# Get all pages with the same model?
if self.WXCheckMono.GetValue() == True:
if (model.id == referencePage.corr.fit_model.id and
- corr.is_cc == referencePage.corr.is_cc):
- ## Check if the page has experimental data:
+ corr.is_cc == referencePage.corr.is_cc):
+ # Check if the page has experimental data:
# If there is an empty page somewhere, don't bother
if corr.correlation is not None:
pages.append(Page)
@@ -155,14 +153,14 @@ def OnAverage(self, evt=None):
UsedPagenumbers.append(int(j))
# If there are no pages in the list, exit gracefully
if len(pages) <= 0:
- texterr_a = "At least one page with experimental data is\n"+\
- "required for averaging. Please check the pages\n"+\
+ texterr_a = "At least one page with experimental data is\n" +\
+ "required for averaging. Please check the pages\n" +\
"that you selected for averaging."
if self.WXCheckMono.GetValue() == True:
- texterr_a += " Note: You selected\n"+\
- "to only use pages with same model as the first page."
+ texterr_a += " Note: You selected\n" +\
+ "to only use pages with same model as the first page."
wx.MessageDialog(self, texterr_a, "Error",
- style=wx.ICON_ERROR|wx.OK|wx.STAY_ON_TOP)
+ style=wx.ICON_ERROR | wx.OK | wx.STAY_ON_TOP)
return
# Now get all the experimental data
explist = list()
@@ -170,7 +168,7 @@ def OnAverage(self, evt=None):
tracetime = [np.array([]), np.array([])]
tracerate = [np.array([]), np.array([])]
TraceNumber = 0
- TraceAvailable = False # turns True, if pages contain traces
+ TraceAvailable = False # turns True, if pages contain traces
for page in pages:
corr = page.corr
# experimental correlation curve
@@ -191,35 +189,35 @@ def OnAverage(self, evt=None):
# we assume that the first two points in a
# trace are equidistant and we will use their
# difference as an offset
- offset = trace[j][:,0][1] - 2*trace[j][:,0][0]
- newtracetime = 1.*trace[j][:,0] + offset
+ offset = trace[j][:, 0][1] - 2*trace[j][:, 0][0]
+ newtracetime = 1.*trace[j][:, 0] + offset
newtracetime = newtracetime + oldend
tracetime[j] = np.append(tracetime[j], newtracetime)
del newtracetime
- tracerate[j] = np.append(tracerate[j], trace[j][:,1])
+ tracerate[j] = np.append(tracerate[j], trace[j][:, 1])
else:
# Initiate the trace
- tracetime[j] = 1.*trace[j][:,0]
- tracerate[j] = 1.*trace[j][:,1]
+ tracetime[j] = 1.*trace[j][:, 0]
+ tracerate[j] = 1.*trace[j][:, 1]
# Now check if the length of the correlation arrays are the same:
len0 = len(explist[0])
for item in explist[1:]:
if len(item) != len0:
# print an error message
wx.MessageDialog(self,
- "Averaging over curves with different lengths is not"+\
- "\nsupported. When measuring, please make sure that"+\
- "\nthe measurement time for all curves is the same.",
- "Error", style=wx.ICON_ERROR|wx.OK|wx.STAY_ON_TOP)
+ "Averaging over curves with different lengths is not" +
+ "\nsupported. When measuring, please make sure that" +
+ "\nthe measurement time for all curves is the same.",
+ "Error", style=wx.ICON_ERROR | wx.OK | wx.STAY_ON_TOP)
return
# Now shorten the trace, because we want as little memory usage as
# possible. I used this algorithm in read_FCS_Confocor3.py as well.
newtraces = list()
if TraceAvailable:
for j in np.arange(TraceNumber):
- tracej = np.zeros((len(tracetime[j]),2))
- tracej[:,0] = tracetime[j]
- tracej[:,1] = tracerate[j]
+ tracej = np.zeros((len(tracetime[j]), 2))
+ tracej[:, 0] = tracetime[j]
+ tracej[:, 1] = tracerate[j]
if len(tracej) >= 500:
# We want about 500 bins
# We need to sum over intervals of length *teiler*
@@ -229,43 +227,43 @@ def OnAverage(self, evt=None):
# Simultaneously sum over all intervals
for k in np.arange(teiler):
newsignal = \
- newsignal+tracej[k:newlength*teiler:teiler][:,1]
- newsignal = 1.* newsignal / teiler
- newtimes = tracej[teiler-1:newlength*teiler:teiler][:,0]
- if len(tracej)%teiler != 0:
+ newsignal+tracej[k:newlength*teiler:teiler][:, 1]
+ newsignal = 1. * newsignal / teiler
+ newtimes = tracej[teiler-1:newlength*teiler:teiler][:, 0]
+ if len(tracej) % teiler != 0:
# We have a rest signal
# We average it and add it to the trace
- rest = tracej[newlength*teiler:][:,1]
+ rest = tracej[newlength*teiler:][:, 1]
lrest = len(rest)
rest = np.array([sum(rest)/lrest])
newsignal = np.concatenate((newsignal, rest), axis=0)
timerest = np.array([tracej[-1][0]])
newtimes = np.concatenate((newtimes, timerest), axis=0)
- newtrace=np.zeros((len(newtimes),2))
- newtrace[:,0] = newtimes
- newtrace[:,1] = newsignal
+ newtrace = np.zeros((len(newtimes), 2))
+ newtrace[:, 0] = newtimes
+ newtrace[:, 1] = newsignal
else:
# Declare newtrace -
# otherwise we have a problem down three lines ;)
newtrace = tracej
newtraces.append(newtrace)
else:
- newtraces=[None,None]
+ newtraces = [None, None]
# Everything is cleared for averaging
exparray = np.array(explist)
- averagedata = exparray.sum(axis=0)[:,1]/len(exparray)
+ averagedata = exparray.sum(axis=0)[:, 1]/len(exparray)
# Create a copy from the first page
average = 1*exparray[0]
# Set average data
- average[:,1] = averagedata
+ average[:, 1] = averagedata
# create new page
self.IsCrossCorrelation = self.Page.corr.is_cc
interval = self.Page.corr.fit_ival
# Obtain the model ID from the dropdown selection.
idsel = self.WXDropSelMod.GetSelection()
modelid = self.DropdownIndex[idsel]
- self.AvgPage = self.parent.add_fitting_tab(modelid = modelid,
- select = True)
+ self.AvgPage = self.parent.add_fitting_tab(modelid=modelid,
+ select=True)
self.AvgPage.corr.fit_ival = interval
self.AvgPage.corr.correlation = average
if self.IsCrossCorrelation is False:
@@ -287,12 +285,13 @@ def OnAverage(self, evt=None):
newtabti = referencePage.tabtitle.GetValue()
else:
# Create a new tab title
- newtabti = "Average ["+misc.parsePagenum2String(UsedPagenumbers)+"]"
+ newtabti = "Average [" + \
+ misc.parsePagenum2String(UsedPagenumbers)+"]"
self.AvgPage.tabtitle.SetValue(newtabti)
# Set the addition information about the variance from averaging
Listname = "Average"
listname = Listname.lower()
- standarddev = exparray.std(axis=0)[:,1]
+ standarddev = exparray.std(axis=0)[:, 1]
if np.sum(np.abs(standarddev)) == 0:
# The average sd is zero. We probably made an average
# from only one page. In this case we do not enable
@@ -310,7 +309,7 @@ def OnAverage(self, evt=None):
# TODO:
# find a cleaner solution
extTypes.remove("none")
- extTypes.sort() # sorting
+ extTypes.sort() # sorting
for key in extTypes:
try:
WeightKinds.remove(key)
@@ -339,8 +338,9 @@ def SetValues(self, e=None):
pagenumlist = list()
for i in np.arange(self.parent.notebook.GetPageCount()):
Page = self.parent.notebook.GetPage(i)
- pagenumlist.append(int("".join(filter(lambda x: x.isdigit(), Page.counter))))
- valstring=misc.parsePagenum2String(pagenumlist)
+ pagenumlist.append(
+ int("".join(filter(lambda x: x.isdigit(), Page.counter))))
+ valstring = misc.parsePagenum2String(pagenumlist)
self.WXTextPages.SetValue(valstring)
# Dropdown
modelkeys = list(mdls.modeltypes.keys())
@@ -351,7 +351,7 @@ def SetValues(self, e=None):
current_model = -1
i = 0
DropdownList = list()
- self.DropdownIndex = list() # Contains model ids with same index
+ self.DropdownIndex = list() # Contains model ids with same index
current_index = 0
for modeltype in modelkeys:
for modelid in mdls.modeltypes[modeltype]:
@@ -359,6 +359,6 @@ def SetValues(self, e=None):
self.DropdownIndex.append(str(modelid))
if str(current_model) == str(modelid):
current_index = i
- i+=1
+ i += 1
self.WXDropSelMod.SetItems(DropdownList)
self.WXDropSelMod.SetSelection(current_index)
diff --git a/pycorrfit/gui/tools/background.py b/pycorrfit/gui/tools/background.py
index ca10b969..e8709545 100644
--- a/pycorrfit/gui/tools/background.py
+++ b/pycorrfit/gui/tools/background.py
@@ -16,17 +16,18 @@
# Menu entry name
MENUINFO = ["&Background correction", "Open a file for background correction."]
+
class BackgroundCorrection(wx.Frame):
def __init__(self, parent):
- self.MyName="BACKGROUND"
+ self.MyName = "BACKGROUND"
# Parent is main frame
self.parent = parent
# Get the window positioning correctly
pos = self.parent.GetPosition()
pos = (pos[0]+100, pos[1]+100)
wx.Frame.__init__(self, parent=parent, title="Background correction",
- pos=pos, style=wx.DEFAULT_FRAME_STYLE|wx.FRAME_FLOAT_ON_PARENT)
- ## MYID
+ pos=pos, style=wx.DEFAULT_FRAME_STYLE | wx.FRAME_FLOAT_ON_PARENT)
+ # MYID
# This ID is given by the parent for an instance of this class
self.MyID = None
# Current trace we are looking at
@@ -37,65 +38,66 @@ def __init__(self, parent):
self.oldtrace = None
self.oldfilename = None
self.average = None
- ## Start drawing
+ # Start drawing
# Splitter Window
self.sp = wx.SplitterWindow(self, style=wx.SP_NOBORDER)
- ## Controls
+ # Controls
panel = wx.Panel(self.sp)
# text1
backgroundinit = (
- "Correct the amplitude for non-correlated background.\n"+
- "The background intensity can be either imported\n"+
+ "Correct the amplitude for non-correlated background.\n" +
+ "The background intensity can be either imported\n" +
"from a blank measurement or set manually.")
textinit = wx.StaticText(panel, label=backgroundinit)
# Radio buttons
self.rbtnfile = wx.RadioButton(panel, -1, 'Blank measurement: ',
- style = wx.RB_GROUP)
+ style=wx.RB_GROUP)
self.rbtnfile.SetValue(True)
self.btnbrowse = wx.Button(panel, wx.ID_ANY, 'Browse ...')
- self.rbtnhand = wx.RadioButton (panel, -1, 'Manual, [kHz]: ')
+ self.rbtnhand = wx.RadioButton(panel, -1, 'Manual, [kHz]: ')
# Spincontrol
self.spinctrl = floatspin.FloatSpin(panel, digits=4, min_val=0,
increment=.01)
self.spinctrl.Enable(False)
# Verbose text
self.textfile = wx.StaticText(panel,
- label="No blank measurement file selected.")
+ label="No blank measurement file selected.")
textmeanavg = wx.StaticText(panel,
label="Average background signal [kHz]: ")
self.textmean = wx.StaticText(panel, label="")
# name
textname = wx.StaticText(panel, label="User defined background name: ")
sizeTextn = textname.GetSize()[0]
- self.bgname = wx.TextCtrl(panel, value="", size=(sizeTextn,-1))
+ self.bgname = wx.TextCtrl(panel, value="", size=(sizeTextn, -1))
self.bgname.Enable(False)
self.btnimport = wx.Button(panel, wx.ID_ANY, 'Import into session')
self.btnimport.Enable(False)
# Dropdown
- self.BGlist = ["File/User"] # updated by self.UpdateDropdown()
+ self.BGlist = ["File/User"] # updated by self.UpdateDropdown()
textdropdown = wx.StaticText(panel, label="Show background: ")
self.dropdown = wx.ComboBox(panel, -1, "File/User", (15, -1),
- wx.DefaultSize, self.BGlist, wx.CB_DROPDOWN|wx.CB_READONLY)
+ wx.DefaultSize, self.BGlist, wx.CB_DROPDOWN | wx.CB_READONLY)
self.UpdateDropdown()
# Radio buttons Channel1 and 2
- self.rbtnCh1 = wx.RadioButton (panel, -1, 'Ch1 ',
- style = wx.RB_GROUP)
+ self.rbtnCh1 = wx.RadioButton(panel, -1, 'Ch1 ',
+ style=wx.RB_GROUP)
self.rbtnCh1.SetValue(True)
- self.rbtnCh2 = wx.RadioButton (panel, -1, 'Ch2')
+ self.rbtnCh2 = wx.RadioButton(panel, -1, 'Ch2')
# Apply buttons
self.btnapply = wx.Button(panel, wx.ID_ANY, 'Apply')
textor = wx.StaticText(panel, label=" or ")
self.btnrem = wx.Button(panel, wx.ID_ANY, 'Dismiss')
- textpages = wx.StaticText(panel, label=" correction for pages: ")
+ textpages = wx.StaticText(panel, label=" correction for pages: ")
self.WXTextPages = wx.TextCtrl(panel, value="")
# Initial value for WXTextPages
pagenumlist = list()
for i in np.arange(self.parent.notebook.GetPageCount()):
Page = self.parent.notebook.GetPage(i)
- pagenumlist.append(int("".join(filter(lambda x: x.isdigit(), Page.counter))))
- valstring=misc.parsePagenum2String(pagenumlist)
+ pagenumlist.append(
+ int("".join(filter(lambda x: x.isdigit(), Page.counter))))
+ valstring = misc.parsePagenum2String(pagenumlist)
self.WXTextPages.SetValue(valstring)
- textyma = wx.StaticText(panel, label="Shortcut - ")
+ textyma = wx.StaticText(panel, label="Shortcut - ")
self.btnapplyall = wx.Button(panel, wx.ID_ANY, 'Apply to all pages')
textor2 = wx.StaticText(panel, label=" or ")
self.btnremyall = wx.Button(panel, wx.ID_ANY, 'Dismiss from all pages')
@@ -126,7 +128,7 @@ def __init__(self, parent):
droprightsizer = wx.BoxSizer(wx.VERTICAL)
dropsizer.Add(droprightsizer)
droprightsizer.Add(self.dropdown)
- #droprightsizer.Add(self.textafterdropdown)
+ # droprightsizer.Add(self.textafterdropdown)
applysizer = wx.BoxSizer(wx.HORIZONTAL)
applysizer.Add(self.btnapply)
applysizer.Add(textor)
@@ -156,11 +158,11 @@ def __init__(self, parent):
topSizer.Fit(self)
self.SetMinSize(topSizer.GetMinSize())
self.Show(True)
- ## Canvas
+ # Canvas
self.canvas = plot.PlotCanvas(self.sp)
# Sizes
psize = panel.GetBestSize()
- initial_size = (psize[0],psize[1]+200)
+ initial_size = (psize[0], psize[1]+200)
self.SetSize(initial_size)
sashsize = psize[1]+3
# This is also necessary to prevent unsplitting
@@ -168,11 +170,10 @@ def __init__(self, parent):
self.sp.SplitHorizontally(panel, self.canvas, sashsize)
# If there is no page, disable ourselves:
self.OnPageChanged(self.parent.notebook.GetCurrentPage())
- #Icon
+ # Icon
if parent.MainIcon is not None:
wx.Frame.SetIcon(self, parent.MainIcon)
-
def Apply(self, Page, backgroundid):
if self.rbtnCh1.GetValue() == True:
Page.bgselected = backgroundid
@@ -182,7 +183,6 @@ def Apply(self, Page, backgroundid):
# Autocorrelation only has one background!
Page.bg2selected = None
-
def OnApply(self, event):
strFull = self.WXTextPages.GetValue()
PageNumbers = misc.parseString2Pagenum(self, strFull)
@@ -203,7 +203,6 @@ def OnApply(self, event):
# Clean up unused backgrounds
CleanupAutomaticBackground(self.parent)
-
def OnApplyAll(self, event):
self.btnrem.Enable(True)
self.btnremyall.Enable(True)
@@ -217,23 +216,21 @@ def OnApplyAll(self, event):
Page.OnAmplitudeCheck("init")
Page.PlotAll()
except OverflowError:
- errstr = "Could not apply background to Page "+Page.counter+\
- ". \n Check the value of the trace average and the background."
+ errstr = "Could not apply background to Page "+Page.counter +\
+ ". \n Check the value of the trace average and the background."
dlg = wx.MessageDialog(self, errstr, "Error",
- style=wx.ICON_ERROR|wx.OK|wx.STAY_ON_TOP)
+ style=wx.ICON_ERROR | wx.OK | wx.STAY_ON_TOP)
dlg.ShowModal()
Page.bgselected = None
Page.bg2selected = None
# Clean up unused backgrounds
CleanupAutomaticBackground(self.parent)
-
def OnClose(self, event=None):
self.parent.toolmenu.Check(self.MyID, False)
self.parent.ToolsOpen.__delitem__(self.MyID)
self.Destroy()
-
def OnBrowse(self, event):
# filetypes_bg_dict is a dictionary with filetypes that have some
# trace signal information.
@@ -247,7 +244,7 @@ def OnBrowse(self, event):
# Add a separator
filters = filters+"|"
dlg = wx.FileDialog(self, "Choose a data file",
- self.parent.dirname, "", filters, wx.FD_OPEN)
+ self.parent.dirname, "", filters, wx.FD_OPEN)
if dlg.ShowModal() == wx.ID_OK:
# Workaround since 0.7.5
(dirname, filename) = os.path.split(dlg.GetPath())
@@ -268,7 +265,7 @@ def OnBrowse(self, event):
for tb_item in traceback.format_tb(info[2]):
errstr += tb_item
wx.MessageDialog(self, errstr, "Error",
- style=wx.ICON_ERROR|wx.OK|wx.STAY_ON_TOP)
+ style=wx.ICON_ERROR | wx.OK | wx.STAY_ON_TOP)
return
# Usually we will get a bunch of traces. Let the user select which
# one to take.
@@ -288,12 +285,12 @@ def OnBrowse(self, event):
# If we accidentally recorded a cross correlation curve
# as the background, let the user choose which trace he wants:
channelindex = None
- if ( len(stuff["Type"][selindex]) >= 2 and
- stuff["Type"][selindex][0:2] == "CC" ):
+ if (len(stuff["Type"][selindex]) >= 2 and
+ stuff["Type"][selindex][0:2] == "CC"):
choices = ["Channel 1", "Channel 2"]
label = "From which channel do you want to use the trace?"
dlg = wx.SingleChoiceDialog(self, label,
- "Curve selection", choices=choices)
+ "Curve selection", choices=choices)
if dlg.ShowModal() == wx.ID_OK:
channelindex = dlg.GetSelection()
trace = stuff["Trace"][selindex][channelindex]
@@ -306,15 +303,15 @@ def OnBrowse(self, event):
return
# Display filename and some of the directory
self.textfile.SetLabel("File: ..."+dirname[-10:]+"/"+filename)
- name = str(selindex)+". "+stuff["Filename"][selindex]+" "+\
- stuff["Type"][selindex]
+ name = str(selindex)+". "+stuff["Filename"][selindex]+" " +\
+ stuff["Type"][selindex]
if channelindex is not None:
name += " "+str(channelindex+1)
self.bgname.SetValue(name)
self.trace = trace
# Calculate average
- self.average = self.trace[:,1].mean()
+ self.average = self.trace[:, 1].mean()
# Display average
self.textmean.SetLabel(str(self.average)+" kHz")
self.spinctrl.SetValue(self.average)
@@ -340,9 +337,9 @@ def OnDraw(self, event=None):
# Draw the trace that was just imported
if self.trace and self.trace.all(): # It is enougth to check that you have an array
# Calculate average
- self.average = self.trace[:,1].mean()
+ self.average = self.trace[:, 1].mean()
self.activetrace = self.trace
- #self.textafterdropdown.SetLabel(" Avg: "+str(self.average)+
+ # self.textafterdropdown.SetLabel(" Avg: "+str(self.average)+
# " kHz")
self.textmean.SetLabel(str(self.average))
self.spinctrl.SetValue(self.average)
@@ -350,7 +347,7 @@ def OnDraw(self, event=None):
# Clear the canvas. Looks better.
self.canvas.Clear()
# Don't show the average
- #self.textafterdropdown.SetLabel("")
+ # self.textafterdropdown.SetLabel("")
self.textmean.SetLabel("")
return
else:
@@ -361,18 +358,18 @@ def OnDraw(self, event=None):
self.activetrace = self.parent.Background[item-1].trace
# We want to have the trace in [s] here.
trace = 1.*self.activetrace
- trace[:,0] = trace[:,0]/1000
+ trace[:, 0] = trace[:, 0]/1000
linesig = plot.PolyLine(trace, legend='', colour='blue', width=1)
self.canvas.Draw(plot.PlotGraphics([linesig],
- xLabel='time [s]',
- yLabel='background signal [kHz]'))
-
+ xLabel='time [s]',
+ yLabel='background signal [kHz]'))
def OnImport(self, event):
- self.parent.Background.append(Trace(trace=self.trace, name=self.bgname.GetValue()))
+ self.parent.Background.append(
+ Trace(trace=self.trace, name=self.bgname.GetValue()))
# Next two lines are taken care of by UpdateDropdown
#name = "{} ({:.2f} kHz)".format(self.bgname.GetValue(), self.average)
- #self.BGlist.append(name)
+ # self.BGlist.append(name)
self.UpdateDropdown()
self.btnremyall.Enable(True)
self.btnrem.Enable(True)
@@ -383,7 +380,6 @@ def OnImport(self, event):
for i in np.arange(self.parent.notebook.GetPageCount()):
self.parent.notebook.GetPage(i).OnAmplitudeCheck()
-
def OnPageChanged(self, page=None, trigger=None):
"""
This function is called, when something in the panel
@@ -416,17 +412,16 @@ def OnPageChanged(self, page=None, trigger=None):
self.btnapply.Enable(True)
self.btnapplyall.Enable(True)
if (self.WXTextPages.GetValue() == ""
- and self.parent.notebook.GetPageCount() != 0):
+ and self.parent.notebook.GetPageCount() != 0):
# Initial value for WXTextPages
pagenumlist = list()
for i in np.arange(self.parent.notebook.GetPageCount()):
Page = self.parent.notebook.GetPage(i)
- pagenumlist.append(int("".join(filter(lambda x: x.isdigit(), Page.counter))))
- valstring=misc.parsePagenum2String(pagenumlist)
+ pagenumlist.append(
+ int("".join(filter(lambda x: x.isdigit(), Page.counter))))
+ valstring = misc.parsePagenum2String(pagenumlist)
self.WXTextPages.SetValue(valstring)
-
-
def OnRadioFile(self, event):
# Do not let the user change the spinctrl
# setting.
@@ -444,7 +439,6 @@ def OnRadioFile(self, event):
self.dropdown.SetSelection(0)
self.OnDraw()
-
def OnRadioHand(self, event):
# Let user enter a signal.
self.spinctrl.Enable(True)
@@ -463,7 +457,6 @@ def OnRadioHand(self, event):
# Enter something as name
self.bgname.SetValue("User")
-
def OnRemove(self, event):
strFull = self.WXTextPages.GetValue()
PageNumbers = misc.parseString2Pagenum(self, strFull)
@@ -488,7 +481,6 @@ def OnRemove(self, event):
# Clean up unused backgrounds
CleanupAutomaticBackground(self.parent)
-
def OnRemoveAll(self, event):
N = self.parent.notebook.GetPageCount()
for i in np.arange(N):
@@ -503,18 +495,16 @@ def OnRemoveAll(self, event):
def SetPageNumbers(self, pagestring):
self.WXTextPages.SetValue(pagestring)
-
def SpinCtrlChange(self, event=None):
# Let user see the continuous trace we will generate
self.average = self.spinctrl.GetValue()
- self.trace = np.array([[0,self.average],[1,self.average]])
+ self.trace = np.array([[0, self.average], [1, self.average]])
self.textmean.SetLabel(str(self.average))
self.OnDraw()
-
def UpdateDropdown(self, e=None):
self.BGlist = list()
- #self.BGlist.append("File/User")
+ # self.BGlist.append("File/User")
for item in self.parent.Background:
self.BGlist.append(item.name)
self.dropdown.SetItems(self.BGlist)
@@ -544,11 +534,12 @@ def ApplyAutomaticBackground(page, bg, parent):
# Check if exists:
for i in range(len(parent.Background)):
if (parent.Background[i].countrate == bglist[b] and
- parent.Background[i].name == bgname):
+ parent.Background[i].name == bgname):
bgid[b] = i
if bgid[b] == -1:
# Add new background
- parent.Background.append(Trace(countrate=bglist[b], name=bgname, duration=1))
+ parent.Background.append(
+ Trace(countrate=bglist[b], name=bgname, duration=1))
bgid[b] = len(parent.Background) - 1
# Apply background to page
diff --git a/pycorrfit/gui/tools/batchcontrol.py b/pycorrfit/gui/tools/batchcontrol.py
index b3031bd0..a606c5a4 100644
--- a/pycorrfit/gui/tools/batchcontrol.py
+++ b/pycorrfit/gui/tools/batchcontrol.py
@@ -22,19 +22,19 @@ def __init__(self, parent):
pos = self.parent.GetPosition()
pos = (pos[0]+100, pos[1]+100)
wx.Frame.__init__(self, parent=parent, title="Batch control",
- pos=pos, style=wx.DEFAULT_FRAME_STYLE|wx.FRAME_FLOAT_ON_PARENT)
- ## MYID
+ pos=pos, style=wx.DEFAULT_FRAME_STYLE | wx.FRAME_FLOAT_ON_PARENT)
+ # MYID
# This ID is given by the parent for an instance of this class
self.MyID = None
- ## Misc
+ # Misc
try:
self.curpage = self.parent.notebook.GetCurrentPage()
except:
self.curpage = None
- ## Controls
+ # Controls
panel = wx.Panel(self)
self.panel = panel
- #Icon
+ # Icon
self.Redraw()
if parent.MainIcon is not None:
wx.Frame.SetIcon(self, parent.MainIcon)
@@ -64,7 +64,7 @@ def GetProtectedParameterIDs(self):
""" The model parameters that are protected from batch control
"""
- pbool = [ not cb.GetValue() for cb in self.wxParameterCheckBoxes ]
+ pbool = [not cb.GetValue() for cb in self.wxParameterCheckBoxes]
return np.array(pbool, dtype=bool)
def OnApply(self, event):
@@ -75,7 +75,7 @@ def OnApply(self, event):
for i in np.arange(self.parent.notebook.GetPageCount()):
OtherPage = self.parent.notebook.GetPage(i)
if (OtherPage.corr.fit_model.id == modelid and
- OtherPage.corr.correlation is not None):
+ OtherPage.corr.correlation is not None):
# create a copy of the fitting parameters in
# case we want to protect them
proparms = OtherPage.corr.fit_parameters
@@ -116,7 +116,7 @@ def OnFit(self, event):
for ii in np.arange(self.parent.notebook.GetPageCount()):
pageii = self.parent.notebook.GetPage(ii)
if (pageii.corr.fit_model.id == modelid and
- pageii.corr.correlation is not None):
+ pageii.corr.correlation is not None):
fit_page_list.append(pageii)
FitProgressDlg(self, fit_page_list, trigger="fit_batch")
@@ -125,7 +125,6 @@ def OnFit(self, event):
# Autoclose
self.OnClose()
-
def OnPageChanged(self, Page=None, trigger=None):
"""
This function is called, when something in the panel
@@ -176,7 +175,7 @@ def OnRadioThere(self, event=None):
# to be changed.
wc = opf.session_wildcards
wcstring = "PyCorrFit session (*.pcfs)|*{};*{}".format(
- wc[0], wc[1])
+ wc[0], wc[1])
dlg = wx.FileDialog(self.parent, "Open session file",
self.parent.dirname, "", wcstring, wx.FD_OPEN)
# user cannot do anything until he clicks "OK"
@@ -184,7 +183,7 @@ def OnRadioThere(self, event=None):
sessionfile = dlg.GetPath()
self.dirname = os.path.split(sessionfile)[0]
else:
- self.parent.dirname=dlg.GetDirectory()
+ self.parent.dirname = dlg.GetDirectory()
self.rbtnhere.SetValue(True)
return
@@ -208,14 +207,14 @@ def Redraw(self, e=None):
panel.RemoveChild(child)
child.Destroy()
- ## Parameter source selection
+ # Parameter source selection
boxleft = wx.StaticBox(panel, label="Parameter source")
self.rbtnhere = wx.RadioButton(panel, -1, 'This session',
- style = wx.RB_GROUP)
+ style=wx.RB_GROUP)
self.rbtnhere.SetValue(True)
self.rbtnthere = wx.RadioButton(panel, -1, 'Other session')
self.dropdown = wx.ComboBox(panel, -1, "Current page", (15, 30),
- wx.DefaultSize, [], wx.CB_DROPDOWN|wx.CB_READONLY)
+ wx.DefaultSize, [], wx.CB_DROPDOWN | wx.CB_READONLY)
# Create the dropdownlist
text2 = wx.StaticText(panel, label="""Only data sets that have the
same model as the parameter
@@ -241,27 +240,27 @@ def Redraw(self, e=None):
leftSizer.Add(text2)
leftSizer.AddSpacer(5)
- ## Parameter selection
+ # Parameter selection
boxright = wx.StaticBox(panel, label="Selected parameters")
rightSizer = wx.StaticBoxSizer(boxright, wx.VERTICAL)
self.parameter_sizer = rightSizer
self.RedrawParameterBox()
- ## Buttons
+ # Buttons
btnapply = wx.Button(panel, wx.ID_ANY, 'Apply to applicable pages')
btnfit = wx.Button(panel, wx.ID_ANY, 'Fit applicable pages')
# Bindings
self.Bind(wx.EVT_BUTTON, self.OnApply, btnapply)
self.Bind(wx.EVT_BUTTON, self.OnFit, btnfit)
- ## Sizers
+ # Sizers
sizer_bag = wx.GridBagSizer(hgap=5, vgap=5)
- sizer_bag.Add(leftSizer, (0,0))
- sizer_bag.Add(rightSizer, (0,1))
+ sizer_bag.Add(leftSizer, (0, 0))
+ sizer_bag.Add(rightSizer, (0, 1))
horsizer = wx.BoxSizer(wx.HORIZONTAL)
horsizer.Add(btnapply)
horsizer.Add(btnfit)
- sizer_bag.Add(horsizer, (1,0), span=wx.GBSpan(1,2))
+ sizer_bag.Add(horsizer, (1, 0), span=wx.GBSpan(1, 2))
panel.SetSizer(sizer_bag)
sizer_bag.Fit(panel)
@@ -292,7 +291,7 @@ def RedrawParameterBox(self, e=None):
parms = self.GetParameters()
modelid = parms[1]
ptext, _pval = mdls.GetHumanReadableParms(modelid, parms[2])
- ptext = [ p.split()[0] for p in ptext ]
+ ptext = [p.split()[0] for p in ptext]
self.wxParameterCheckBoxes = []
for p in ptext:
cb = wx.CheckBox(panel, label=p)
@@ -316,6 +315,7 @@ def RedrawParameterBox(self, e=None):
except:
pass
+
class FitProgressDlg(ThreadedProgressDlg):
def __init__(self, parent, pages, trigger=None):
""" A progress dialog for fitting in PyCorrFit
@@ -337,11 +337,12 @@ def __init__(self, parent, pages, trigger=None):
self.pages = pages
self.trigger = trigger
title = "Fitting data"
- messages = [ "Fitting page #{}.".format(pi.counter.strip("# :")) for pi in pages ]
+ messages = ["Fitting page #{}.".format(
+ pi.counter.strip("# :")) for pi in pages]
targets = [Fit]*len(pages)
args = [pi.corr for pi in pages]
# write parameters from page instance to correlation
- [ pi.apply_parameters() for pi in self.pages ]
+ [pi.apply_parameters() for pi in self.pages]
super(FitProgressDlg, self).__init__(parent, targets, args,
title=title,
messages=messages)
@@ -351,8 +352,8 @@ def finalize(self):
cleanup of non-fitted pages.
"""
if self.aborted:
- ## we need to cleanup
- fin_index = max(0,self.index_aborted-1)
+ # we need to cleanup
+ fin_index = max(0, self.index_aborted-1)
pab = self.pages[self.index_aborted]
pab.fit_results = None
pab.apply_parameters()
@@ -360,4 +361,5 @@ def finalize(self):
fin_index = len(self.pages)
# finalize fitting
- [ pi.Fit_finalize(trigger=self.trigger) for pi in self.pages[:fin_index] ]
+ [pi.Fit_finalize(trigger=self.trigger)
+ for pi in self.pages[:fin_index]]
diff --git a/pycorrfit/gui/tools/chooseimport.py b/pycorrfit/gui/tools/chooseimport.py
index ac7c38ba..109192b1 100644
--- a/pycorrfit/gui/tools/chooseimport.py
+++ b/pycorrfit/gui/tools/chooseimport.py
@@ -15,21 +15,22 @@ class ChooseImportTypes(wx.Dialog):
The model function is defined by the model that is in use.
"""
# This tool is derived from a wx.Dialog.
+
def __init__(self, parent, curvedict):
# parent is the main frame of PyCorrFit
self.parent = parent
# init
- #super(ChooseImportTypes, self).__init__(parent=parent,
+ # super(ChooseImportTypes, self).__init__(parent=parent,
# title="Choose types", size=(250, 200))
wx.Dialog.__init__(self, parent, -1, "Choose models")
self.keys = list()
- ## Content
+ # Content
self.panel = wx.Panel(self)
self.sizer = wx.BoxSizer(wx.VERTICAL)
self.boxes = dict()
# For the selection of types to import when doing import Data
- chooseimport = ("Several types of data were found in\n"+
- "the chosen file. Please select what\n"+
+ chooseimport = ("Several types of data were found in\n" +
+ "the chosen file. Please select what\n" +
"type(s) you would like to import.")
textinit = wx.StaticText(self.panel, label=chooseimport)
self.sizer.Add(textinit)
@@ -47,21 +48,19 @@ def __init__(self, parent, curvedict):
self.sizer.Add(btnok)
self.panel.SetSizer(self.sizer)
self.sizer.Fit(self)
- #Icon
+ # Icon
if parent.MainIcon is not None:
wx.Dialog.SetIcon(self, parent.MainIcon)
- #self.Show(True)
+ # self.Show(True)
self.SetFocus()
-
def OnClose(self, event=None):
# This is a necessary function for PyCorrFit.
# Do not change it.
self.EndModal(wx.ID_OK)
- #self.Destroy()
+ # self.Destroy()
-
- def OnSetkeys(self, event = None):
+ def OnSetkeys(self, event=None):
self.keys = list()
for key in self.boxes.keys():
if self.boxes[key].Value == True:
@@ -73,6 +72,7 @@ class ChooseImportTypesModel(wx.Dialog):
model function on import of data
"""
# This tool is derived from a wx.frame.
+
def __init__(self, parent, curvedict, correlations, labels=None):
""" curvedict - dictionary, contains indexes to correlations and
labels. The keys are different types of curves
@@ -83,18 +83,18 @@ def __init__(self, parent, curvedict, correlations, labels=None):
# parent is the main frame of PyCorrFit
self.parent = parent
# init
- #super(ChooseImportTypesModel, self).__init__(parent=parent,
+ # super(ChooseImportTypesModel, self).__init__(parent=parent,
# title="Choose types", size=(250, 200))
wx.Dialog.__init__(self, parent, -1, "Choose models")
self.curvedict = curvedict
- self.kept_curvedict = curvedict.copy() # Can be edited by user
+ self.kept_curvedict = curvedict.copy() # Can be edited by user
self.correlations = correlations
self.labels = labels
# List of keys that will be imported by our *parent*
self.typekeys = list()
# Dictionary of modelids corresponding to indices in curvedict
self.modelids = dict()
- ## Content
+ # Content
self.panel = wx.Panel(self)
self.sizer = wx.BoxSizer(wx.VERTICAL)
self.boxes = dict()
@@ -105,7 +105,8 @@ def __init__(self, parent, curvedict, correlations, labels=None):
curvekeys.sort()
self.curvekeys = curvekeys
# Dropdown model selections:
- DropdownList = ["No model selected"] # Contains string in model dropdown
+ # Contains string in model dropdown
+ DropdownList = ["No model selected"]
self.DropdownIndex = [None] # Contains corresponsing model
modelkeys = list(mdls.modeltypes.keys())
modelkeys.sort()
@@ -114,22 +115,23 @@ def __init__(self, parent, curvedict, correlations, labels=None):
DropdownList.append(modeltype+": "+mdls.modeldict[modelid][1])
self.DropdownIndex.append(modelid)
self.ModelDropdown = dict()
- dropsizer = wx.FlexGridSizer(rows=len(modelkeys), cols=3, vgap=5, hgap=5)
+ dropsizer = wx.FlexGridSizer(
+ rows=len(modelkeys), cols=3, vgap=5, hgap=5)
self.Buttons = list()
i = 8000
for key in curvekeys:
# Text with keys and numer of curves
- dropsizer.Add( wx.StaticText(self.panel, label=str(key)) )
- label=" ("+str(len(curvedict[key]))+" curves)"
+ dropsizer.Add(wx.StaticText(self.panel, label=str(key)))
+ label = " ("+str(len(curvedict[key]))+" curves)"
button = wx.Button(self.panel, i, label)
i += 1
self.Bind(wx.EVT_BUTTON, self.OnSelectCurves, button)
self.Buttons.append(button)
dropsizer.Add(button)
# Model selection dropdown
- dropdown = wx.ComboBox(self.panel, -1, DropdownList[0], (15,30),
- wx.DefaultSize, DropdownList, wx.CB_DROPDOWN|wx.CB_READONLY)
- dropsizer.Add( dropdown )
+ dropdown = wx.ComboBox(self.panel, -1, DropdownList[0], (15, 30),
+ wx.DefaultSize, DropdownList, wx.CB_DROPDOWN | wx.CB_READONLY)
+ dropsizer.Add(dropdown)
self.ModelDropdown[key] = dropdown
self.Bind(wx.EVT_COMBOBOX, self.OnSetkeys, dropdown)
self.sizer.Add(dropsizer)
@@ -139,13 +141,11 @@ def __init__(self, parent, curvedict, correlations, labels=None):
self.sizer.Add(btnok)
self.panel.SetSizer(self.sizer)
self.sizer.Fit(self)
- #self.Show(True)
+ # self.Show(True)
self.SetFocus()
if parent.MainIcon is not None:
wx.Dialog.SetIcon(self, parent.MainIcon)
-
-
def OnClose(self, event=None):
# This is a necessary function for PyCorrFit.
# Do not change it.
@@ -156,9 +156,8 @@ def OnClose(self, event=None):
self.keepcurvesindex[i] = int(self.keepcurvesindex[i])
self.EndModal(wx.ID_OK)
- #self.Show
- #self.Destroy()
-
+ # self.Show
+ # self.Destroy()
def OnSelectCurves(self, buttonevent):
# Get the type of curves we want to look at
@@ -179,8 +178,8 @@ def OnSelectCurves(self, buttonevent):
for item in self.kept_curvedict.keys():
prev_selected += self.kept_curvedict[item]
overlaycurves.Wrapper_OnImport(self.parent, corrcurves,
- self.OnSelected, prev_selected,
- labels=labeldict)
+ self.OnSelected, prev_selected,
+ labels=labeldict)
def OnSelected(self, keep, remove):
# Set new button label
@@ -188,7 +187,7 @@ def OnSelected(self, keep, remove):
keep[i] = int(keep[i])
#button = self.Buttons[self.buttonindex]
label = " ("+str(len(keep))+" curves)"
- #button.SetLabel(label)
+ # button.SetLabel(label)
# Add new content to selected key
SelectedKey = self.curvekeys[self.buttonindex]
#self.kept_curvedict[SelectedKey] = keep
@@ -212,8 +211,7 @@ def OnSelected(self, keep, remove):
button = self.Buttons[j]
button.SetLabel(label)
-
- def OnSetkeys(self, event = None):
+ def OnSetkeys(self, event=None):
# initiate objects
self.typekeys = list()
self.modelids = dict()
@@ -232,8 +230,3 @@ def OnSetkeys(self, event = None):
# Set different model id for the curves
self.modelids[index] = modelid
self.typekeys.sort()
-
-
-
-
-
diff --git a/pycorrfit/gui/tools/comment.py b/pycorrfit/gui/tools/comment.py
index 2fd00c06..c0c60a8f 100755
--- a/pycorrfit/gui/tools/comment.py
+++ b/pycorrfit/gui/tools/comment.py
@@ -4,26 +4,27 @@
class EditComment(wx.Frame):
""" Little Dialog to edit the comment on the session. """
+
def __init__(self, parent):
- ## Variables
+ # Variables
# parent is main frame
self.parent = parent
# Get the window positioning correctly
pos = self.parent.GetPosition()
pos = (pos[0]+100, pos[1]+100)
wx.Frame.__init__(self, parent=parent, title="Session comment",
- pos=pos, style=wx.DEFAULT_FRAME_STYLE|wx.FRAME_FLOAT_ON_PARENT)
- initial_size = (400,300)
+ pos=pos, style=wx.DEFAULT_FRAME_STYLE | wx.FRAME_FLOAT_ON_PARENT)
+ initial_size = (400, 300)
initial_sizec = (initial_size[0], initial_size[1]-50)
self.SetSize(initial_size)
- self.SetMinSize((400,300))
- ## Content
+ self.SetMinSize((400, 300))
+ # Content
self.panel = wx.Panel(self)
self.control = wx.TextCtrl(self.panel, style=wx.TE_MULTILINE,
- size=initial_sizec, value=self.parent.SessionComment)
+ size=initial_sizec, value=self.parent.SessionComment)
self.Bind(wx.EVT_TEXT, self.OnTextChanged, self.control)
text = wx.StaticText(self.panel,
- label="Session comments will be saved in the session file.")
+ label="Session comments will be saved in the session file.")
# buttons
btnsave = wx.Button(self.panel, wx.ID_SAVE, 'Save Comment')
self.Bind(wx.EVT_BUTTON, self.OnSave, btnsave)
diff --git a/pycorrfit/gui/tools/datarange.py b/pycorrfit/gui/tools/datarange.py
index 1d5f1fac..3b465fa9 100644
--- a/pycorrfit/gui/tools/datarange.py
+++ b/pycorrfit/gui/tools/datarange.py
@@ -7,6 +7,7 @@
MENUINFO = ["&Data range",
"Select an interval of lag times to be used for fitting."]
+
class SelectChannels(wx.Frame):
def __init__(self, parent):
# parent is main frame
@@ -15,23 +16,23 @@ def __init__(self, parent):
pos = self.parent.GetPosition()
pos = (pos[0]+100, pos[1]+100)
wx.Frame.__init__(self, parent=self.parent, title="Data range selection",
- pos=pos, style=wx.DEFAULT_FRAME_STYLE|wx.FRAME_FLOAT_ON_PARENT)
- ## MYID
+ pos=pos, style=wx.DEFAULT_FRAME_STYLE | wx.FRAME_FLOAT_ON_PARENT)
+ # MYID
# This ID is given by the parent for an instance of this class
self.MyID = None
- ## Start drawing
+ # Start drawing
panel = wx.Panel(self)
self.panel = panel
# Page
self.Page = self.parent.notebook.GetCurrentPage()
self.Calc_init(self.Page)
- text1 = wx.StaticText(panel, label=u"The lag times Ļ are stored as an "+
+ text1 = wx.StaticText(panel, label=u"The lag times Ļ are stored as an " +
u"array of length ")
self.textend = wx.StaticText(panel, label="%d." % self.lentau)
text2 = wx.StaticText(panel,
- label=u"You may wish to confine this array. "+
+ label=u"You may wish to confine this array. " +
u"This can be done here.")
- ##Spincontrols:
+ # Spincontrols:
FlexSpinSizer = wx.FlexGridSizer(rows=2, cols=4, vgap=5, hgap=5)
FlexSpinSizer.Add(wx.StaticText(panel, label="Channels:"))
self.spinstart = wx.SpinCtrl(panel, -1, initial=self.left,
@@ -58,7 +59,7 @@ def __init__(self, parent):
self.Bind(wx.EVT_SPINCTRL, self.OnChangeChannels, self.spinstart)
# Checkbox
self.fixcheck = wx.CheckBox(panel, -1,
- label="Fix current channel selection for all pages.")
+ label="Fix current channel selection for all pages.")
self.Bind(wx.EVT_CHECKBOX, self.OnCheckbox, self.fixcheck)
# Text
channelsel = "Leave this window open for a fixed selection."
@@ -84,16 +85,15 @@ def __init__(self, parent):
self.SetMinSize(topSizer.GetMinSize())
# Get times.
self.OnChangeChannels()
- #Icon
+ # Icon
if parent.MainIcon is not None:
wx.Frame.SetIcon(self, parent.MainIcon)
# Show window
self.Show(True)
self.OnPageChanged(self.Page)
-
def Calc_init(self, parent):
- ## Variables
+ # Variables
# Parent should be the fitting panel -
# The tab, where the fitting is done.
self.Page = parent
@@ -118,14 +118,12 @@ def Calc_init(self, parent):
# set the maximum possible value
self.right = self.end0
else:
- self.right -=1
-
+ self.right -= 1
def OnApply(self, event=None):
self.SetValues()
self.Page.PlotAll()
-
def OnApplyAll(self, event=None):
N = self.parent.notebook.GetPageCount()
for i in np.arange(N):
@@ -141,7 +139,6 @@ def OnApplyAll(self, event=None):
# Autoclose
self.OnClose()
-
def OnChangeTimes(self, e=None):
""" Called, whenever data range in seconds is changed. This updates
the data range in channels in the window.
@@ -149,7 +146,6 @@ def OnChangeTimes(self, e=None):
"""
pass
-
def OnChangeChannels(self, e=None):
""" Called, whenever data range in channels is changed. This updates
the data range in seconds in the window.
@@ -169,7 +165,6 @@ def OnChangeChannels(self, e=None):
self.TextTimesEnd.SetLabel("%.4e" % t2)
self.OnCheckbox()
-
def OnCheckbox(self, event=None):
""" Set the correct value in the spincontrol, if the checkbox
is not checked.
@@ -182,15 +177,13 @@ def OnCheckbox(self, event=None):
else:
self.ButtonApply.Enable()
self.ButtonApplyAll.Enable()
- #self.OnPageChanged(self.Page)
-
+ # self.OnPageChanged(self.Page)
def OnClose(self, event=None):
self.parent.toolmenu.Check(self.MyID, False)
self.parent.ToolsOpen.__delitem__(self.MyID)
self.Destroy()
-
def OnPageChanged(self, page, trigger=None):
# We do not need the *Range* Commands here yet.
# We open and close the SelectChannelsFrame every time we
@@ -219,14 +212,12 @@ def OnPageChanged(self, page, trigger=None):
self.textend.SetLabel("%d." % self.lentau)
self.OnChangeChannels()
-
-
def SetValues(self, page=None):
if page is None:
page = self.Page
# Get interval
start = self.spinstart.GetValue()
- end = self.spinend.GetValue() + 1 # +1, [sic]
+ end = self.spinend.GetValue() + 1 # +1, [sic]
if start > end:
# swap the variables, we are not angry at the user
start, end = end, start
@@ -234,6 +225,6 @@ def SetValues(self, page=None):
maxlen = len(page.corr.lag_time)
# Use the smaller one of both, so we do not get an
# index out of bounds error
- page.corr.fit_ival = [ start*(start < maxlen - 1 ),
- min(end, maxlen)
- ]
\ No newline at end of file
+ page.corr.fit_ival = [start*(start < maxlen - 1),
+ min(end, maxlen)
+ ]
diff --git a/pycorrfit/gui/tools/example.py b/pycorrfit/gui/tools/example.py
index 8195708a..9d8e2107 100644
--- a/pycorrfit/gui/tools/example.py
+++ b/pycorrfit/gui/tools/example.py
@@ -16,13 +16,13 @@ def __init__(self, parent):
pos = self.parent.GetPosition()
pos = (pos[0]+100, pos[1]+100)
wx.Frame.__init__(self, parent=self.parent, title="Example tool",
- pos=pos, style=wx.DEFAULT_FRAME_STYLE|wx.FRAME_FLOAT_ON_PARENT)
- ## MYID
+ pos=pos, style=wx.DEFAULT_FRAME_STYLE | wx.FRAME_FLOAT_ON_PARENT)
+ # MYID
# This ID is given by the parent for an instance of this class
self.MyID = None
# Page - the currently active page of the notebook.
self.Page = self.parent.notebook.GetCurrentPage()
- ## Content
+ # Content
self.panel = wx.Panel(self)
btncopy = wx.Button(self.panel, wx.ID_ANY, 'Example button')
# Binds the button to the function - close the tool
@@ -37,7 +37,6 @@ def __init__(self, parent):
wx.Frame.SetIcon(self, parent.MainIcon)
self.Show(True)
-
def OnClose(self, event=None):
# This is a necessary function for PyCorrFit.
# Do not change it.
@@ -45,7 +44,6 @@ def OnClose(self, event=None):
self.parent.ToolsOpen.__delitem__(self.MyID)
self.Destroy()
-
def OnPageChanged(self, page, trigger=None):
"""
This function is called, when something in the panel
@@ -64,5 +62,3 @@ def OnPageChanged(self, page, trigger=None):
return
self.panel.Enable()
self.Page = page
-
-
diff --git a/pycorrfit/gui/tools/globalfit.py b/pycorrfit/gui/tools/globalfit.py
index 685ee2f6..74551e33 100644
--- a/pycorrfit/gui/tools/globalfit.py
+++ b/pycorrfit/gui/tools/globalfit.py
@@ -12,26 +12,27 @@
MENUINFO = ["&Global fitting",
"Interconnect parameters from different measurements."]
+
class GlobalFit(wx.Frame):
# This tool is derived from a wx.frame.
def __init__(self, parent):
# Define a unique name that identifies this tool
# Do not change this value. It is important for the Overlay tool
# (selectcurves.py, *Wrapper_Tools*).
- self.MyName="GLOBALFIT"
+ self.MyName = "GLOBALFIT"
# parent is the main frame of PyCorrFit
self.parent = parent
# Get the window positioning correctly
pos = self.parent.GetPosition()
pos = (pos[0]+100, pos[1]+100)
wx.Frame.__init__(self, parent=self.parent, title="Gobal fitting",
- pos=pos, style=wx.DEFAULT_FRAME_STYLE|wx.FRAME_FLOAT_ON_PARENT)
- ## MYID
+ pos=pos, style=wx.DEFAULT_FRAME_STYLE | wx.FRAME_FLOAT_ON_PARENT)
+ # MYID
# This ID is given by the parent for an instance of this class
self.MyID = None
# Page - the currently active page of the notebook.
self.Page = self.parent.notebook.GetCurrentPage()
- ## Content
+ # Content
self.panel = wx.Panel(self)
self.topSizer = wx.BoxSizer(wx.VERTICAL)
textinit = """Fitting of multiple data sets with different models.
@@ -39,17 +40,18 @@ def __init__(self, parent):
check parameters on each page and start 'Global fit'.
"""
self.topSizer.Add(wx.StaticText(self.panel, label=textinit))
- ## Page selection
- self.WXTextPages = wx.TextCtrl(self.panel, value="", size=(330,-1))
+ # Page selection
+ self.WXTextPages = wx.TextCtrl(self.panel, value="", size=(330, -1))
# Set initial value in text control
pagenumlist = list()
for i in np.arange(self.parent.notebook.GetPageCount()):
Page = self.parent.notebook.GetPage(i)
- pagenumlist.append(int("".join(filter(lambda x: x.isdigit(), Page.counter))))
- valstring=misc.parsePagenum2String(pagenumlist)
+ pagenumlist.append(
+ int("".join(filter(lambda x: x.isdigit(), Page.counter))))
+ valstring = misc.parsePagenum2String(pagenumlist)
self.WXTextPages.SetValue(valstring)
self.topSizer.Add(self.WXTextPages)
- ## Button
+ # Button
btnfit = wx.Button(self.panel, wx.ID_ANY, 'Global fit')
# Binds the button to the function - close the tool
self.Bind(wx.EVT_BUTTON, self.OnFit, btnfit)
@@ -79,7 +81,7 @@ def OnFit(self, e=None):
# Something went wrong and parseString2Pagenum already displayed
# an error message.
return
- ## Get the correlations
+ # Get the correlations
corrs = list()
for i in np.arange(self.parent.notebook.GetPageCount()):
Page = self.parent.notebook.GetPage(i)
@@ -103,7 +105,8 @@ def OnFit(self, e=None):
# update fit results
for corr in corrs:
corr.fit_results["global parms"] = u", ".join(fit_parm_names)
- corr.fit_results["global pages"] = u", ".join([str(g) for g in global_pages])
+ corr.fit_results["global pages"] = u", ".join(
+ [str(g) for g in global_pages])
# Plot resutls
for i in np.arange(self.parent.notebook.GetPageCount()):
@@ -116,7 +119,6 @@ def OnFit(self, e=None):
# Autoclose
self.OnClose()
-
def OnPageChanged(self, page, trigger=None):
"""
This function is called, when something in the panel
@@ -137,6 +139,5 @@ def OnPageChanged(self, page, trigger=None):
self.panel.Enable()
self.Page = page
-
def SetPageNumbers(self, pagestring):
self.WXTextPages.SetValue(pagestring)
diff --git a/pycorrfit/gui/tools/info.py b/pycorrfit/gui/tools/info.py
index 169ac04d..e2b94ad8 100644
--- a/pycorrfit/gui/tools/info.py
+++ b/pycorrfit/gui/tools/info.py
@@ -9,17 +9,18 @@
MENUINFO = ["Page &info",
"Display some information on the current page."]
+
class InfoClass(object):
""" This class get's all the Info possible from a Page and
makes it available through a dictionary with headings as keys.
"""
- def __init__(self, CurPage=None, Pagelist=None ):
+
+ def __init__(self, CurPage=None, Pagelist=None):
# A list of all Pages currently available:
self.Pagelist = Pagelist
# The current page we are looking at:
self.CurPage = CurPage
-
def GetAllInfo(self):
""" Get a dictionary with page titles and an InfoDict as value.
"""
@@ -29,19 +30,16 @@ def GetAllInfo(self):
MultiInfo[Page.counter[:-2]] = self.GetPageInfo(Page)
return MultiInfo
-
def GetCurInfo(self):
""" Get all the information about the current Page.
Added for convenience. You may use GetPageInfo.
"""
return self.GetPageInfo(self.CurPage)
-
def GetCurFancyInfo(self):
""" For convenience. """
return self.GetFancyInfo(self.CurPage)
-
def GetFancyInfo(self, Page):
""" Get a nice string representation of the Info """
InfoDict = self.GetPageInfo(Page)
@@ -50,16 +48,16 @@ def GetFancyInfo(self, Page):
# Title
Title = u"\n"
for item in InfoDict["title"]:
- Title = Title + item[0]+"\t"+ item[1]+"\n"
+ Title = Title + item[0]+"\t" + item[1]+"\n"
# Parameters
Parameters = u"\nParameters:\n"
for item in InfoDict["parameters"]:
- Parameters = Parameters + u" "+item[0]+"\t"+ str(item[1])+"\n"
+ Parameters = Parameters + u" "+item[0]+"\t" + str(item[1])+"\n"
# Supplementary parameters
Supplement = u"\nSupplementary parameters:\n"
try:
for item in InfoDict["supplement"]:
- Supplement = Supplement + " "+item[0]+"\t"+ str(item[1])+"\n"
+ Supplement = Supplement + " "+item[0]+"\t" + str(item[1])+"\n"
except KeyError:
Supplement = ""
# Fitting
@@ -84,11 +82,10 @@ def GetFancyInfo(self, Page):
SupDoc = u"\n"+8*" "+InfoDict["modelsupdoc"][0]
except:
SupDoc = u""
- PageInfo = Version+Title+Parameters+Supplement+Fitting+Background+\
- ModelDoc+SupDoc
+ PageInfo = Version+Title+Parameters+Supplement+Fitting+Background +\
+ ModelDoc+SupDoc
return PageInfo
-
def GetPageInfo(self, Page):
""" Needs a Page and gets all information from it """
Page.PlotAll("init")
@@ -115,13 +112,13 @@ def GetPageInfo(self, Page):
Title.append(["Model ID", str(model.id)])
Title.append(["Model function", fct])
Title.append(["Page number", Page.counter[1:-2]])
- ## Parameters
+ # Parameters
Parameters = list()
# Use this function to determine human readable parameters, if possible
Units, Newparameters = mdls.GetHumanReadableParms(model.id, parms)
# Add Parameters
for i in np.arange(len(parms)):
- Parameters.append([ Units[i], Newparameters[i] ])
+ Parameters.append([Units[i], Newparameters[i]])
InfoDict["parameters"] = Parameters
# Add some more information if available
# Info is a dictionary or None
@@ -138,8 +135,7 @@ def GetPageInfo(self, Page):
pass
else:
InfoDict["modelsupdoc"] = [func_info.__doc__]
- ## Fitting
-
+ # Fitting
if hasattr(corr, "fit_results"):
Fitting = list()
@@ -147,58 +143,63 @@ def GetPageInfo(self, Page):
if corr.correlation is not None:
# Mode AC vs CC
if corr.is_cc:
- Title.append(["Type AC/CC", "Cross-correlation" ])
+ Title.append(["Type AC/CC", "Cross-correlation"])
else:
- Title.append(["Type AC/CC", "Autocorrelation" ])
+ Title.append(["Type AC/CC", "Autocorrelation"])
if "chi2" in corr.fit_results:
- Fitting.append([ u"ĻĀ²", corr.fit_results["chi2"]])
+ Fitting.append([u"ĻĀ²", corr.fit_results["chi2"]])
if weightedfit:
try:
- Fitting.append(["Weighted fit", corr.fit_results["weighted fit type"]])
+ Fitting.append(
+ ["Weighted fit", corr.fit_results["weighted fit type"]])
except KeyError:
- Fitting.append(["Weighted fit", u""+Page.Fitbox[1].GetValue()])
+ Fitting.append(
+ ["Weighted fit", u""+Page.Fitbox[1].GetValue()])
if "chi2 type" in corr.fit_results:
ChiSqType = corr.fit_results["chi2 type"]
else:
ChiSqType = "unknown"
- Fitting.append([ u"ĻĀ²-type", ChiSqType])
- Fitting.append([ "Algorithm", fit.Algorithms[corr.fit_algorithm][1]])
+ Fitting.append([u"ĻĀ²-type", ChiSqType])
+ Fitting.append(
+ ["Algorithm", fit.Algorithms[corr.fit_algorithm][1]])
if len(Page.GlobalParameterShare) != 0:
shared = str(Page.GlobalParameterShare[0])
for item in Page.GlobalParameterShare[1:]:
shared += ", "+str(item)
Fitting.append(["Shared parameters with Pages", shared])
if "weighted fit bins" in corr.fit_results:
- Fitting.append(["Std. channels", 2*corr.fit_results["weighted fit bins"]+1])
+ Fitting.append(
+ ["Std. channels", 2*corr.fit_results["weighted fit bins"]+1])
# Fitting range:
t1 = 1.*corr.lag_time[corr.fit_ival[0]]
t2 = 1.*corr.lag_time[corr.fit_ival[1]-1]
- Fitting.append([ "Ival start [ms]", "%.4e" % t1 ])
- Fitting.append([ "Ival end [ms]", "%.4e" % t2 ])
+ Fitting.append(["Ival start [ms]", "%.4e" % t1])
+ Fitting.append(["Ival end [ms]", "%.4e" % t2])
# Fittet parameters
try:
fitparmsid = corr.fit_results["fit parameters"]
except:
fitparmsid = corr.fit_parameters_variable
fitparms = np.array(corr.fit_model.parameters[0])[fitparmsid]
- fitparms_short = [ f.split()[0] for f in fitparms ]
+ fitparms_short = [f.split()[0] for f in fitparms]
fitparms_short = u", ".join(fitparms_short)
Fitting.append(["Fit parm.", fitparms_short])
# global fitting
for key in corr.fit_results.keys():
if key.startswith("global"):
- Fitting.append([key.capitalize(), corr.fit_results[key]])
+ Fitting.append(
+ [key.capitalize(), corr.fit_results[key]])
# Fit errors
if "fit error estimation" in corr.fit_results:
errors = corr.fit_results["fit error estimation"]
for err, par in zip(errors, fitparms):
nam, val = mdls.GetHumanReadableParameterDict(
- model.id, [par], [err])
+ model.id, [par], [err])
Fitting.append(["Err "+nam[0], val[0]])
InfoDict["fitting"] = Fitting
- ## Normalization parameter id to name
+ # Normalization parameter id to name
if corr.normparm is None:
normparmtext = "None"
elif corr.normparm < len(corr.fit_parameters):
@@ -209,29 +210,29 @@ def GetPageInfo(self, Page):
normparmtext = MoreInfo[supnum][0]
Title.append(["Normalization", normparmtext])
- ## Background
+ # Background
Background = list()
if corr.is_cc:
if len(corr.backgrounds) == 2:
# Channel 1
- Background.append([ "bg name Ch1",
- corr.backgrounds[0].name])
- Background.append([ "bg rate Ch1 [kHz]",
- corr.backgrounds[0].countrate])
+ Background.append(["bg name Ch1",
+ corr.backgrounds[0].name])
+ Background.append(["bg rate Ch1 [kHz]",
+ corr.backgrounds[0].countrate])
# Channel 2
- Background.append([ "bg name Ch2",
- corr.backgrounds[1].name])
- Background.append([ "bg rate Ch2 [kHz]",
- corr.backgrounds[1].countrate])
+ Background.append(["bg name Ch2",
+ corr.backgrounds[1].name])
+ Background.append(["bg rate Ch2 [kHz]",
+ corr.backgrounds[1].countrate])
InfoDict["background"] = Background
else:
if len(corr.backgrounds) == 1:
- Background.append([ "bg name",
- corr.backgrounds[0].name])
- Background.append([ "bg rate [kHz]",
- corr.backgrounds[0].countrate])
+ Background.append(["bg name",
+ corr.backgrounds[0].name])
+ Background.append(["bg rate [kHz]",
+ corr.backgrounds[0].countrate])
InfoDict["background"] = Background
- ## Function doc string
+ # Function doc string
InfoDict["modeldoc"] = [corr.fit_model.description_long]
InfoDict["title"] = Title
@@ -246,23 +247,24 @@ def __init__(self, parent):
pos = self.parent.GetPosition()
pos = (pos[0]+100, pos[1]+100)
wx.Frame.__init__(self, parent=self.parent, title="Info",
- pos=pos, style=wx.DEFAULT_FRAME_STYLE|wx.FRAME_FLOAT_ON_PARENT)
- ## MYID
+ pos=pos, style=wx.DEFAULT_FRAME_STYLE | wx.FRAME_FLOAT_ON_PARENT)
+ # MYID
# This ID is given by the parent for an instance of this class
self.MyID = None
# Page
self.Page = self.parent.notebook.GetCurrentPage()
# Size
- initial_size = wx.Size(650,700)
+ initial_size = wx.Size(650, 700)
initial_sizec = (initial_size[0]-6, initial_size[1]-30)
- self.SetMinSize(wx.Size(200,200))
+ self.SetMinSize(wx.Size(200, 200))
self.SetSize(initial_size)
- ## Content
+ # Content
self.panel = wx.Panel(self)
self.control = wx.TextCtrl(self.panel, style=wx.TE_MULTILINE,
- size=initial_sizec)
+ size=initial_sizec)
self.control.SetEditable(False)
- font1 = wx.Font(10, wx.MODERN, wx.NORMAL, wx.NORMAL, False, u'Monospace')
+ font1 = wx.Font(10, wx.MODERN, wx.NORMAL,
+ wx.NORMAL, False, u'Monospace')
self.control.SetFont(font1)
btncopy = wx.Button(self.panel, wx.ID_CLOSE, 'Copy to clipboard')
self.Bind(wx.EVT_BUTTON, self.OnCopy, btncopy)
@@ -271,14 +273,13 @@ def __init__(self, parent):
self.topSizer.Add(self.control)
self.panel.SetSizer(self.topSizer)
self.topSizer.Fit(self)
- #Icon
+ # Icon
if parent.MainIcon is not None:
wx.Frame.SetIcon(self, parent.MainIcon)
self.Show(True)
wx.EVT_SIZE(self, self.OnSize)
self.Content()
-
def Content(self):
# Fill self.control with content.
# Parameters and models
@@ -292,13 +293,11 @@ def Content(self):
PageInfo = InfoMan.GetCurFancyInfo()
self.control.SetValue(PageInfo)
-
def OnClose(self, event=None):
self.parent.toolmenu.Check(self.MyID, False)
self.parent.ToolsOpen.__delitem__(self.MyID)
self.Destroy()
-
def OnCopy(self, event):
if not wx.TheClipboard.IsOpened():
clipdata = wx.TextDataObject()
@@ -309,7 +308,6 @@ def OnCopy(self, event):
else:
print("Other application has lock on clipboard.")
-
def OnPageChanged(self, page=None, trigger=None):
"""
This function is called, when something in the panel
@@ -324,7 +322,6 @@ def OnPageChanged(self, page=None, trigger=None):
self.Page = page
self.Content()
-
def OnSize(self, event):
size = event.GetSize()
sizec = wx.Size(size[0]-5, size[1]-30)
diff --git a/pycorrfit/gui/tools/overlaycurves.py b/pycorrfit/gui/tools/overlaycurves.py
index b9d5e400..b4637ff9 100644
--- a/pycorrfit/gui/tools/overlaycurves.py
+++ b/pycorrfit/gui/tools/overlaycurves.py
@@ -15,6 +15,7 @@
# Menu entry name
MENUINFO = ["&Overlay curves", "Select experimental curves."]
+
class Wrapper_OnImport(object):
""" Wrapper for import function.
parent: wx.Frame
@@ -24,6 +25,7 @@ class Wrapper_OnImport(object):
curvedict.
selkeys: preselected values for curves in curvedict
"""
+
def __init__(self, parent, curvedict, onselected,
selkeys=None, labels=None):
self.onselected = onselected
@@ -38,7 +40,6 @@ def OnClose(self, event=None):
self.parent.Enable()
self.Selector.Destroy()
-
def OnResults(self, keyskeep, keysrem):
""" Here we will close (or disable?) pages that are not wanted
by the user. It is important that we do not close pages that
@@ -46,7 +47,7 @@ def OnResults(self, keyskeep, keysrem):
because we ignored those pages during import.
"""
self.OnClose()
- self.onselected(keyskeep,keysrem)
+ self.onselected(keyskeep, keysrem)
class Wrapper_Tools(object):
@@ -57,10 +58,10 @@ def __init__(self, parent):
"""
# parent is the main frame of PyCorrFit
self.parent = parent
- ## MYID
+ # MYID
# This ID is given by the parent for an instance of this class
self.MyID = None
- ## Wrapping
+ # Wrapping
curvedict, labels = self.GetCurvedict()
self.labels = labels
self.Selector = UserSelectCurves(parent, curvedict,
@@ -71,7 +72,6 @@ def __init__(self, parent):
if self.parent.notebook.GetPageCount() == 0:
self.Selector.sp.Disable()
-
def Disable(self):
self.Selector.Disable()
@@ -98,7 +98,6 @@ def OnClose(self, event=None):
self.parent.ToolsOpen.__delitem__(self.MyID)
self.Selector.Destroy()
-
def OnPageChanged(self, page=None, trigger=None):
"""
This function is called, when something in the panel
@@ -128,12 +127,11 @@ def OnPageChanged(self, page=None, trigger=None):
self.labels = labels
if oldlabels != self.Selector.curvelabels:
self.Selector.SelectBox.SetItems(
- self.Selector.curvelabels)
+ self.Selector.curvelabels)
for i in np.arange(len(self.Selector.curvekeys)):
self.Selector.SelectBox.SetSelection(i)
self.Selector.OnUpdatePlot(trigger=trigger)
-
def OnResults(self, keyskeep, keysrem):
""" Here we will close (or disable?) pages that are not wanted
by the user. It is important that we do not close pages that
@@ -151,7 +149,7 @@ def OnResults(self, keyskeep, keysrem):
for key in keyskeep:
textlist += "- "+key+" "+self.labels[key]+"\n"
dlg = edclasses.MyScrolledDialog(self.parent,
- overtext, textlist, "Warning")
+ overtext, textlist, "Warning")
if dlg.ShowModal() == wx.ID_OK:
N = self.parent.notebook.GetPageCount()
pagerem = list()
@@ -217,7 +215,7 @@ def __init__(self, parent, curvedict, wrapper=None, selkeys=None,
self.curvedict = curvedict
self.selkeys = selkeys
self.labels = labels # can be None
- self.curvelabels = None # filled by self.ProcessDict()
+ self.curvelabels = None # filled by self.ProcessDict()
if self.selkeys is not None:
newselkeys = list()
for item in self.selkeys:
@@ -227,15 +225,16 @@ def __init__(self, parent, curvedict, wrapper=None, selkeys=None,
pos = self.parent.GetPosition()
pos = (pos[0]+100, pos[1]+100)
wx.Frame.__init__(self, parent=self.parent, title="Overlay curves",
- pos=pos, style=wx.DEFAULT_FRAME_STYLE|wx.FRAME_FLOAT_ON_PARENT,
- size=(800,500))
- ## Pre-process
+ pos=pos, style=wx.DEFAULT_FRAME_STYLE | wx.FRAME_FLOAT_ON_PARENT,
+ size=(800, 500))
+ # Pre-process
self.ProcessDict()
- ## Content
- self.sp = wx.SplitterWindow(self, size=(500,500), style=wx.SP_NOBORDER)
+ # Content
+ self.sp = wx.SplitterWindow(
+ self, size=(500, 500), style=wx.SP_NOBORDER)
self.sp.SetMinimumPaneSize(1)
# Top panel
- panel_top = wx.Panel(self.sp, size=(500,200))
+ panel_top = wx.Panel(self.sp, size=(500, 200))
self.upperSizer = wx.BoxSizer(wx.VERTICAL)
if platform.system().lower() == 'darwin':
ctrl = "Apple"
@@ -246,14 +245,15 @@ def __init__(self, parent, curvedict, wrapper=None, selkeys=None,
"to select groups."
self.upperSizer.Add(wx.StaticText(panel_top, label=text))
# Bottom Panel
- self.bottom_sp = wx.SplitterWindow(self.sp, size=(500,300), style=wx.SP_NOBORDER)
+ self.bottom_sp = wx.SplitterWindow(
+ self.sp, size=(500, 300), style=wx.SP_NOBORDER)
self.bottom_sp.SetMinimumPaneSize(1)
sizepanelx = 250
- panel_bottom = wx.Panel(self.bottom_sp, size=(sizepanelx,300))
+ panel_bottom = wx.Panel(self.bottom_sp, size=(sizepanelx, 300))
self.boxSizer = wx.BoxSizer(wx.VERTICAL)
# Box selection
style = wx.LB_EXTENDED
- self.SelectBox = wx.ListBox(panel_bottom, size=(sizepanelx,300),
+ self.SelectBox = wx.ListBox(panel_bottom, size=(sizepanelx, 300),
style=style, choices=self.curvelabels)
for i in np.arange(len(self.curvekeys)):
self.SelectBox.SetSelection(i)
@@ -290,7 +290,7 @@ def __init__(self, parent, curvedict, wrapper=None, selkeys=None,
np.array(self.upperSizer.GetMinSize()) +
np.array((300, 30)))
self.SetMinSize(minsize)
- #self.SetSize(minsize)
+ # self.SetSize(minsize)
#self.SetMaxSize((9999, self.boxSizer.GetMinSize()[1]))
# Canvas
self.canvas = plot.PlotCanvas(self.bottom_sp)
@@ -316,47 +316,44 @@ def GetSelection(self):
keysnosel.append(key)
return keyssel, keysnosel
-
def ProcessDict(self, e=None):
# Define the order of keys used.
# We want to sort the keys, such that #10: is not before #1:
self.curvekeys = list(self.curvedict.keys())
# Sorting key function applied to each key before sorting:
- page_num = lambda counter: int(counter.strip().strip(":").strip("#"))
+ def page_num(counter): return int(
+ counter.strip().strip(":").strip("#"))
try:
for item in self.curvekeys:
page_num(item)
except:
- fstr = lambda x: x
+ def fstr(x): return x
else:
fstr = page_num
- self.curvekeys.sort(key = fstr)
+ self.curvekeys.sort(key=fstr)
if self.labels is None:
self.curvelabels = self.curvekeys
else:
# Use given labels instead of curvekeys.
self.curvelabels = list()
for key in self.curvekeys:
- self.curvelabels.append("#"+str(key).strip(":# ")+" "+self.labels[key])
-
+ self.curvelabels.append(
+ "#"+str(key).strip(":# ")+" "+self.labels[key])
def OnCancel(self, e=None):
""" Close the tool """
self.wrapper.OnClose()
-
def OnPushResultsRemove(self, e=None):
# Get keys from selection
keysrem, keyskeep = self.GetSelection()
self.wrapper.OnResults(keyskeep, keysrem)
-
def OnPushResultsKeep(self, e=None):
# Get keys from selection
keyskeep, keysrem = self.GetSelection()
self.wrapper.OnResults(keyskeep, keysrem)
-
def OnUpdatePlot(self, e=None, trigger=None):
""" What should happen when the selection in *self.SelectBox*
is changed?
@@ -369,7 +366,7 @@ def OnUpdatePlot(self, e=None, trigger=None):
If `trigger` is something that occurs during loading of
data, then we will not replot everything.
"""
- #if e is not None and e.GetEventType() == 10007:
+ # if e is not None and e.GetEventType() == 10007:
# return
# Get selected curves
@@ -394,9 +391,9 @@ def OnUpdatePlot(self, e=None, trigger=None):
self.canvas.enableLegend = True
if len(curves) != 0:
self.canvas.Draw(plot.PlotGraphics(lines,
- xLabel=u'lag time Ļ [ms]',
- yLabel=u'G(Ļ)'))
- ## This is an addon for 0.7.8
+ xLabel=u'lag time Ļ [ms]',
+ yLabel=u'G(Ļ)'))
+ # This is an addon for 0.7.8
keyskeep = list()
for i in self.SelectBox.GetSelections():
keyskeep.append(self.curvekeys[i])
diff --git a/pycorrfit/gui/tools/parmrange.py b/pycorrfit/gui/tools/parmrange.py
index c8555362..20ed994f 100644
--- a/pycorrfit/gui/tools/parmrange.py
+++ b/pycorrfit/gui/tools/parmrange.py
@@ -18,29 +18,28 @@ def __init__(self, Page):
pos = self.parent.GetPosition()
pos = (pos[0]+100, pos[1]+100)
wx.Frame.__init__(self, parent=self.parent, title="Parameter Range",
- pos=pos, style=wx.DEFAULT_FRAME_STYLE|wx.FRAME_FLOAT_ON_PARENT)
+ pos=pos, style=wx.DEFAULT_FRAME_STYLE | wx.FRAME_FLOAT_ON_PARENT)
# Page - the currently active page of the notebook.
self.Page = self.parent.notebook.GetCurrentPage()
- ## Content
+ # Content
self.panel = wx.Panel(self)
self.topSizer = wx.BoxSizer(wx.VERTICAL)
self.WXboxsizerlist = list()
self.WXparmlist = list()
self.OnPageChanged(self.Page)
- #Icon
+ # Icon
if self.parent.MainIcon is not None:
wx.Frame.SetIcon(self, self.parent.MainIcon)
self.Show(True)
-
def FillPanel(self):
""" Fill the panel with parameters from the page
"""
corr = self.Page.corr
self.parameter_range = np.zeros_like(corr.fit_parameters_range)
leftbound = []
- for item in corr.fit_parameters_range[:,0]:
+ for item in corr.fit_parameters_range[:, 0]:
if item is None:
leftbound.append(-np.inf)
else:
@@ -48,7 +47,7 @@ def FillPanel(self):
labels, parmleft = mdls.GetHumanReadableParms(corr.fit_model.id, # @UnusedVariable
leftbound)
rightbound = []
- for item in corr.fit_parameters_range[:,1]:
+ for item in corr.fit_parameters_range[:, 1]:
if item is None:
rightbound.append(np.inf)
else:
@@ -56,11 +55,12 @@ def FillPanel(self):
labels, parmright = mdls.GetHumanReadableParms(corr.fit_model.id,
rightbound)
- self.parameter_range[:,0] = np.array(parmleft)
- self.parameter_range[:,1] = np.array(parmright)
+ self.parameter_range[:, 0] = np.array(parmleft)
+ self.parameter_range[:, 1] = np.array(parmright)
# create line
- self.WXboxsizer = wx.FlexGridSizer(rows=len(labels), cols=5, vgap=5, hgap=5)
+ self.WXboxsizer = wx.FlexGridSizer(
+ rows=len(labels), cols=5, vgap=5, hgap=5)
for i in range(len(labels)):
left = wxutils.PCFFloatTextCtrl(self.panel)
right = wxutils.PCFFloatTextCtrl(self.panel)
@@ -97,7 +97,6 @@ def OnClose(self, event=None):
self.parent.RangeSelector = None
self.Destroy()
-
def OnPageChanged(self, page=None, trigger=None):
"""
This function is called, when something in the panel
@@ -122,10 +121,10 @@ def OnPageChanged(self, page=None, trigger=None):
except:
pass
for i in np.arange(len(self.WXparmlist)):
- self.WXparmlist[i][0].Destroy() #start
- self.WXparmlist[i][1][0].Destroy() #pname
- self.WXparmlist[i][1][1].Destroy() #pname
- self.WXparmlist[i][2].Destroy() #end
+ self.WXparmlist[i][0].Destroy() # start
+ self.WXparmlist[i][1][0].Destroy() # pname
+ self.WXparmlist[i][1][1].Destroy() # pname
+ self.WXparmlist[i][2].Destroy() # end
del self.WXparmlist
for i in np.arange(len(self.WXboxsizerlist)):
self.WXboxsizer.Remove(0)
@@ -133,8 +132,6 @@ def OnPageChanged(self, page=None, trigger=None):
self.WXparmlist = list()
self.FillPanel()
-
-
def OnSetParmRange(self, e):
""" Called whenever something is edited in this frame.
Writes back parameter ranges to the page
@@ -145,13 +142,14 @@ def OnSetParmRange(self, e):
self.parameter_range[i][0] = self.WXparmlist[i][0].GetValue()
self.parameter_range[i][1] = self.WXparmlist[i][2].GetValue()
if self.parameter_range[i][0] > self.parameter_range[i][1]:
- self.parameter_range[i][1] = 1.01*np.abs(self.parameter_range[i][0])
+ self.parameter_range[i][1] = 1.01 * \
+ np.abs(self.parameter_range[i][0])
self.WXparmlist[i][2].SetValue(self.parameter_range[i][1])
# Set parameters
parm0 = mdls.GetInternalFromHumanReadableParm(corr.fit_model.id,
- self.parameter_range[:,0])[1]
+ self.parameter_range[:, 0])[1]
parm1 = mdls.GetInternalFromHumanReadableParm(corr.fit_model.id,
- self.parameter_range[:,1])[1]
+ self.parameter_range[:, 1])[1]
corr.fit_parameters_range = np.dstack((parm0, parm1))[0]
if self.parent.MenuAutocloseTools.IsChecked():
diff --git a/pycorrfit/gui/tools/plotexport.py b/pycorrfit/gui/tools/plotexport.py
index 566aa700..b8b69864 100644
--- a/pycorrfit/gui/tools/plotexport.py
+++ b/pycorrfit/gui/tools/plotexport.py
@@ -11,13 +11,13 @@ def __init__(self, parent):
pos = self.parent.GetPosition()
pos = (pos[0]+100, pos[1]+100)
wx.Frame.__init__(self, parent=self.parent, title="Example Tool",
- pos=pos, style=wx.DEFAULT_FRAME_STYLE|wx.FRAME_FLOAT_ON_PARENT)
- ## MYID
+ pos=pos, style=wx.DEFAULT_FRAME_STYLE | wx.FRAME_FLOAT_ON_PARENT)
+ # MYID
# This ID is given by the parent for an instance of this class
self.MyID = None
# Page - the currently active page of the notebook.
self.Page = self.parent.notebook.GetCurrentPage()
- ## Content
+ # Content
self.panel = wx.Panel(self)
btnexample = wx.Button(self.panel, wx.ID_ANY, 'Example button')
# Binds the button to the function - close the tool
@@ -27,12 +27,11 @@ def __init__(self, parent):
self.panel.SetSizer(self.topSizer)
self.topSizer.Fit(self)
self.SetMinSize(self.topSizer.GetMinSize())
- #Icon
+ # Icon
if parent.MainIcon is not None:
wx.Frame.SetIcon(self, parent.MainIcon)
self.Show(True)
-
def OnClose(self, event=None):
# This is a necessary function for PyCorrFit.
# Do not change it.
@@ -40,7 +39,6 @@ def OnClose(self, event=None):
self.parent.ToolsOpen.__delitem__(self.MyID)
self.Destroy()
-
def OnPageChanged(self, page, trigger=None):
"""
This function is called, when something in the panel
@@ -54,4 +52,3 @@ def OnPageChanged(self, page, trigger=None):
# This is stuff that should be done when the active page
# of the notebook changes.
self.Page = page
-
diff --git a/pycorrfit/gui/tools/simulation.py b/pycorrfit/gui/tools/simulation.py
index 782c747f..0f5e0c64 100644
--- a/pycorrfit/gui/tools/simulation.py
+++ b/pycorrfit/gui/tools/simulation.py
@@ -13,6 +13,7 @@
MENUINFO = ["S&lider simulation",
"Fast plotting for different parameters."]
+
class Slide(wx.Frame):
# This tool is derived from a wx.frame.
def __init__(self, parent):
@@ -22,44 +23,44 @@ def __init__(self, parent):
pos = self.parent.GetPosition()
pos = (pos[0]+100, pos[1]+100)
wx.Frame.__init__(self, parent=self.parent, title="Simulation",
- pos=pos, style=wx.DEFAULT_FRAME_STYLE|wx.FRAME_FLOAT_ON_PARENT)
+ pos=pos, style=wx.DEFAULT_FRAME_STYLE | wx.FRAME_FLOAT_ON_PARENT)
# Starting positions/factors for spinctrls and sliders
self.slidemax = 1000
self.slidestart = 500
self.spinstartfactor = 0.1
self.spinendfactor = 1.9
- ## MYID
+ # MYID
# This ID is given by the parent for an instance of this class
self.MyID = None
# Page - the currently active page of the notebook.
self.Page = self.parent.notebook.GetCurrentPage()
- ## Content
+ # Content
self.panel = wx.Panel(self)
- self.rbtnB = wx.RadioButton (self.panel, -1, 'Vary A and B',
- style = wx.RB_GROUP)
- self.rbtnOp = wx.RadioButton (self.panel, -1, 'Fix relation')
+ self.rbtnB = wx.RadioButton(self.panel, -1, 'Vary A and B',
+ style=wx.RB_GROUP)
+ self.rbtnOp = wx.RadioButton(self.panel, -1, 'Fix relation')
self.btnreset = wx.Button(self.panel, wx.ID_ANY, 'Reset')
# Set starting variables
self.SetStart()
# Populate panel
dropsizer = wx.FlexGridSizer(rows=2, cols=3, vgap=5, hgap=5)
- dropsizer.Add( wx.StaticText(self.panel, label="Parameter A"))
- dropsizer.Add( wx.StaticText(self.panel, label="Operator"))
- dropsizer.Add( wx.StaticText(self.panel, label="Parameter B"))
+ dropsizer.Add(wx.StaticText(self.panel, label="Parameter A"))
+ dropsizer.Add(wx.StaticText(self.panel, label="Operator"))
+ dropsizer.Add(wx.StaticText(self.panel, label="Parameter B"))
self.droppA = wx.ComboBox(self.panel, -1, self.labelA, (15, 20),
- wx.DefaultSize, self.parmAlist,
- wx.CB_DROPDOWN|wx.CB_READONLY)
+ wx.DefaultSize, self.parmAlist,
+ wx.CB_DROPDOWN | wx.CB_READONLY)
self.droppA.SetSelection(0)
self.Bind(wx.EVT_COMBOBOX, self.Ondrop, self.droppA)
self.dropop = wx.ComboBox(self.panel, -1, "", (10, 20),
- wx.DefaultSize, self.oplist,
- wx.CB_DROPDOWN|wx.CB_READONLY)
+ wx.DefaultSize, self.oplist,
+ wx.CB_DROPDOWN | wx.CB_READONLY)
self.dropop.SetSelection(0)
self.opfunc = self.opdict[list(self.opdict.keys())[0]]
self.Bind(wx.EVT_COMBOBOX, self.Ondrop, self.dropop)
self.droppB = wx.ComboBox(self.panel, -1, self.labelB, (15, 30),
- wx.DefaultSize, self.parmBlist,
- wx.CB_DROPDOWN|wx.CB_READONLY)
+ wx.DefaultSize, self.parmBlist,
+ wx.CB_DROPDOWN | wx.CB_READONLY)
self.Bind(wx.EVT_COMBOBOX, self.Ondrop, self.droppB)
self.droppB.SetSelection(1)
dropsizer.Add(self.droppA)
@@ -79,7 +80,7 @@ def __init__(self, parent):
slidesizer.Add(self.sliderA)
self.endspinA = floatspin.FloatSpin(self.panel, digits=7)
slidesizer.Add(self.endspinA)
- self.textvalueA = wx.StaticText(self.panel, label= "%.5e" % self.valueA)
+ self.textvalueA = wx.StaticText(self.panel, label="%.5e" % self.valueA)
slidesizer.Add(self.textvalueA)
# Parameter B
self.textstartB = wx.StaticText(self.panel, label=self.labelB)
@@ -92,7 +93,7 @@ def __init__(self, parent):
slidesizer.Add(self.sliderB)
self.endspinB = floatspin.FloatSpin(self.panel, digits=7)
slidesizer.Add(self.endspinB)
- self.textvalueB = wx.StaticText(self.panel, label= "%.5e" % self.valueB)
+ self.textvalueB = wx.StaticText(self.panel, label="%.5e" % self.valueB)
slidesizer.Add(self.textvalueB)
# Result of operation
self.textstartOp = wx.StaticText(self.panel, label=self.labelOp)
@@ -106,7 +107,7 @@ def __init__(self, parent):
self.endspinOp = floatspin.FloatSpin(self.panel, digits=7)
slidesizer.Add(self.endspinOp)
self.textvalueOp = wx.StaticText(self.panel,
- label= "%.5e" % self.valueOp)
+ label="%.5e" % self.valueOp)
slidesizer.Add(self.textvalueOp)
# Bindings for slider
self.Bind(wx.EVT_SLIDER, self.OnSlider, self.sliderA)
@@ -133,7 +134,7 @@ def __init__(self, parent):
self.Bind(wx.EVT_SPINCTRL, self.OnSlider, self.endspinOp)
# Set values
self.SetValues()
- ## Sizers
+ # Sizers
self.topSizer = wx.BoxSizer(wx.VERTICAL)
self.topSizer.Add(dropsizer)
self.topSizer.Add(self.rbtnB)
@@ -145,17 +146,16 @@ def __init__(self, parent):
self.topSizer.Fit(self)
self.OnRadio()
self.OnPageChanged(self.Page, init=True)
- #Icon
+ # Icon
if parent.MainIcon is not None:
wx.Frame.SetIcon(self, parent.MainIcon)
self.Show(True)
-
def CalcFct(self, A, B, C):
if self.rbtnB.Value == True:
func = self.opfunc[0]
try:
- C = func(A,B)
+ C = func(A, B)
except ZeroDivisionError:
pass
else:
@@ -163,25 +163,23 @@ def CalcFct(self, A, B, C):
else:
func = self.opfunc[1]
try:
- B = func(A,C)
+ B = func(A, C)
except ZeroDivisionError:
pass
else:
return B, C
-
def FillOpDict(self):
# Dictionaries: [Calculate C, Calculate B)
- self.opdict["A/B"] = [lambda A,B: A/B, lambda A,C: A/C]
- self.opdict["B/A"] = [lambda A,B: B/A, lambda A,C: C*A]
- self.opdict["A*B"] = [lambda A,B: A*B, lambda A,C: C/A]
- self.opdict["A+B"] = [lambda A,B: A+B, lambda A,C: C-A]
- self.opdict["A-B"] = [lambda A,B: A-B, lambda A,C: A-C]
- self.opdict["A*exp(B)"] = [lambda A,B: A*np.exp(B),
- lambda A,C: np.log(C/A)]
- self.opdict["B*exp(A)"] = [lambda A,B: B*np.exp(A),
- lambda A,C: C/np.exp(A)]
-
+ self.opdict["A/B"] = [lambda A, B: A/B, lambda A, C: A/C]
+ self.opdict["B/A"] = [lambda A, B: B/A, lambda A, C: C*A]
+ self.opdict["A*B"] = [lambda A, B: A*B, lambda A, C: C/A]
+ self.opdict["A+B"] = [lambda A, B: A+B, lambda A, C: C-A]
+ self.opdict["A-B"] = [lambda A, B: A-B, lambda A, C: A-C]
+ self.opdict["A*exp(B)"] = [lambda A, B: A*np.exp(B),
+ lambda A, C: np.log(C/A)]
+ self.opdict["B*exp(A)"] = [lambda A, B: B*np.exp(A),
+ lambda A, C: C/np.exp(A)]
def OnClose(self, event=None):
# This is a necessary function for PyCorrFit.
@@ -190,7 +188,6 @@ def OnClose(self, event=None):
self.parent.ToolsOpen.__delitem__(self.MyID)
self.Destroy()
-
def Ondrop(self, event=None):
self.labelOp = self.oplist[self.dropop.GetSelection()]
self.labelA = self.parmAlist[self.droppA.GetSelection()]
@@ -206,7 +203,6 @@ def Ondrop(self, event=None):
self.SetValues()
self.OnSize()
-
def OnPageChanged(self, page=None, trigger=None, init=False):
"""
This function is called, when something in the panel
@@ -216,7 +212,7 @@ def OnPageChanged(self, page=None, trigger=None, init=False):
`tools`.
'init' is used by this tool only.
"""
- #if init:
+ # if init:
# # Get the parameters of the current page.
# self.SavedParms = self.parent.PackParameters(self.Page)
# When parent changes
@@ -249,7 +245,6 @@ def OnPageChanged(self, page=None, trigger=None, init=False):
self.Page = page
self.panel.Enable()
-
def OnRadio(self, event=None):
if self.rbtnB.Value == True:
# Parameter B is vaiable
@@ -269,11 +264,10 @@ def OnRadio(self, event=None):
self.endspinB.Enable(False)
self.Ondrop()
-
def OnReset(self, e=None):
self.parent.UnpackParameters(self.SavedParms, self.Page)
self.Page.apply_parameters_reverse()
- #self.OnPageChanged(self.Page)
+ # self.OnPageChanged(self.Page)
self.SetStart()
self.Ondrop()
@@ -284,15 +278,14 @@ def OnSize(self, event=None):
self.topSizer.Fit(self)
self.panel.SetSize(self.GetSize())
-
def OnSlider(self, event=None):
- ## Set the slider vlaues
+ # Set the slider vlaues
idmax = self.sliderA.GetMax()
slideA = self.sliderA.GetValue()
startA = self.startspinA.GetValue()
endA = self.endspinA.GetValue()
self.valueA = startA + (endA-startA)*slideA/idmax
- self.textvalueA.SetLabel( "%.5e" % self.valueA)
+ self.textvalueA.SetLabel("%.5e" % self.valueA)
if self.rbtnB.Value == True:
slideB = self.sliderB.GetValue()
startB = self.startspinB.GetValue()
@@ -306,12 +299,11 @@ def OnSlider(self, event=None):
self.valueOp = startOp + (endOp-startOp)*slideOp/idmax
self.valueB, self.valueOp = self.CalcFct(self.valueA, self.valueB,
self.valueOp)
- self.textvalueB.SetLabel( "%.5e" % self.valueB)
- self.textvalueOp.SetLabel( "%.5e" % self.valueOp)
+ self.textvalueB.SetLabel("%.5e" % self.valueB)
+ self.textvalueOp.SetLabel("%.5e" % self.valueOp)
self.SetResult()
self.OnSize()
-
def SetResult(self, event=None):
if self.parent.notebook.GetPageCount() == 0:
# Nothing to do
@@ -327,8 +319,8 @@ def SetResult(self, event=None):
# only write back those that have been changed:
#
parms_0 = 1.*np.array(mdls.valuedict[self.modelid][1])
- parms_0[idA] = self.valueA # human readable units
- parms_0[idB] = self.valueB # human readable units
+ parms_0[idA] = self.valueA # human readable units
+ parms_0[idB] = self.valueB # human readable units
parms_i =\
mdls.GetInternalFromHumanReadableParm(self.modelid, parms_0)[1]
self.Page.active_parms[1][idA] = parms_i[idA]
@@ -336,21 +328,20 @@ def SetResult(self, event=None):
self.Page.apply_parameters_reverse()
self.Page.PlotAll()
-
def SetStart(self):
# Sets first and second variable of a page to
# Parameters A and B respectively.
if self.parent.notebook.GetPageCount() == 0:
self.modelid = 6000
ParmLabels, ParmValues = \
- mdls.GetHumanReadableParms(self.modelid,
- mdls.valuedict[6000][1])
+ mdls.GetHumanReadableParms(self.modelid,
+ mdls.valuedict[6000][1])
else:
self.SavedParms = self.parent.PackParameters(self.Page)
self.modelid = self.Page.modelid
ParmLabels, ParmValues = \
- mdls.GetHumanReadableParms(self.modelid,
- self.Page.active_parms[1])
+ mdls.GetHumanReadableParms(self.modelid,
+ self.Page.active_parms[1])
self.parmAlist = ParmLabels
self.parmBlist = ParmLabels
@@ -367,8 +358,7 @@ def SetStart(self):
self.valueA = ParmValues[0]
self.valueB = ParmValues[1]
self.valueB, self.valueOp = self.CalcFct(self.valueA,
- self.valueB, 0)
-
+ self.valueB, 0)
def SetValues(self, event=None):
# Set the values for spin and slider
@@ -385,13 +375,13 @@ def SetValues(self, event=None):
if self.parent.notebook.GetPageCount() == 0:
self.modelid = 6000
ParmValues = \
- mdls.GetHumanReadableParms(self.modelid,
- mdls.valuedict[6000][1])[1]
+ mdls.GetHumanReadableParms(self.modelid,
+ mdls.valuedict[6000][1])[1]
else:
self.modelid = self.Page.modelid
ParmValues = \
- mdls.GetHumanReadableParms(self.modelid,
- self.Page.active_parms[1])[1]
+ mdls.GetHumanReadableParms(self.modelid,
+ self.Page.active_parms[1])[1]
self.valueA = ParmValues[idA]
self.valueB = ParmValues[idB]
# Operator
@@ -416,8 +406,7 @@ def SetValues(self, event=None):
self.startspinOp.SetValue(startOp)
self.endspinOp.SetValue(endOp)
# Set text
- self.textvalueA.SetLabel( "%.5e" % self.valueA)
- self.textvalueB.SetLabel( "%.5e" % self.valueB)
- self.textvalueOp.SetLabel( "%.5e" % self.valueOp)
+ self.textvalueA.SetLabel("%.5e" % self.valueA)
+ self.textvalueB.SetLabel("%.5e" % self.valueB)
+ self.textvalueOp.SetLabel("%.5e" % self.valueOp)
self.SetResult()
-
diff --git a/pycorrfit/gui/tools/statistics.py b/pycorrfit/gui/tools/statistics.py
index 63756589..712740ab 100644
--- a/pycorrfit/gui/tools/statistics.py
+++ b/pycorrfit/gui/tools/statistics.py
@@ -19,6 +19,7 @@
# Menu entry name
MENUINFO = ["&Statistics view", "Show some session statistics."]
+
def run_once(f):
def wrapper(*args, **kwargs):
if not wrapper.has_run:
@@ -31,7 +32,7 @@ def wrapper(*args, **kwargs):
class Stat(wx.Frame):
# This tool is derived from a wx.frame.
def __init__(self, parent):
- self.MyName="STATISTICS"
+ self.MyName = "STATISTICS"
# parent is the main frame of PyCorrFit
self.boxsizerlist = list()
self.parent = parent
@@ -39,9 +40,9 @@ def __init__(self, parent):
pos = self.parent.GetPosition()
pos = (pos[0]+100, pos[1]+100)
wx.Frame.__init__(self, parent=self.parent, title="Statistics",
- pos=pos, size=(700,600),
- style=wx.DEFAULT_FRAME_STYLE|wx.FRAME_FLOAT_ON_PARENT)
- ## MYID
+ pos=pos, size=(700, 600),
+ style=wx.DEFAULT_FRAME_STYLE | wx.FRAME_FLOAT_ON_PARENT)
+ # MYID
# This ID is given by the parent for an instance of this class
self.MyID = None
self.MyName = "STATISTICS"
@@ -50,13 +51,13 @@ def __init__(self, parent):
# Page - the currently active page of the notebook.
self.Page = self.parent.notebook.GetCurrentPage()
# Pagenumbers
- self.PageNumbers =range(1,1+self.parent.notebook.GetPageCount())
- ## Splitter window. left side: checkboxes
- ## right side: plot with parameters
+ self.PageNumbers = range(1, 1+self.parent.notebook.GetPageCount())
+ # Splitter window. left side: checkboxes
+ # right side: plot with parameters
self.sp = wx.SplitterWindow(self, style=wx.SP_3DSASH)
# This is necessary to prevent "Unsplit" of the SplitterWindow:
self.sp.SetMinimumPaneSize(1)
- ## Content
+ # Content
# We will display a dialog that conains all the settings
# - Which model we want statistics on
# - What kind of parameters should be printed
@@ -74,38 +75,38 @@ def __init__(self, parent):
self.panel.Disable()
# A dropdown menu for the source Page:
text = wx.StaticText(self.panel,
- label="Create a table with all the selected\n"+
- "variables below from pages with the\n"+
- "same model as the current page.")
- ## Page selection as in average tool
+ label="Create a table with all the selected\n" +
+ "variables below from pages with the\n" +
+ "same model as the current page.")
+ # Page selection as in average tool
Pagetext = wx.StaticText(self.panel,
- label="Curves ")
+ label="Curves ")
Psize = text.GetSize()[0]/2
self.WXTextPages = wx.TextCtrl(self.panel, value="",
- size=(Psize,-1))
+ size=(Psize, -1))
# Set number of pages
pagenumlist = list()
for i in np.arange(self.parent.notebook.GetPageCount()):
Page = self.parent.notebook.GetPage(i)
pagenumlist.append(int("".join(filter(lambda x: x.isdigit(),
- Page.counter))))
- valstring=misc.parsePagenum2String(pagenumlist)
+ Page.counter))))
+ valstring = misc.parsePagenum2String(pagenumlist)
self.WXTextPages.SetValue(valstring)
- ## Plot parameter dropdown box
+ # Plot parameter dropdown box
self.PlotParms = self.GetListOfPlottableParms()
Parmlist = self.PlotParms
DDtext = wx.StaticText(self.panel, label="Plot parameter ")
self.WXDropdown = wx.ComboBox(self.panel, -1, "",
- size=(Psize,-1), choices=Parmlist,
- style=wx.CB_DROPDOWN|wx.CB_READONLY)
+ size=(Psize, -1), choices=Parmlist,
+ style=wx.CB_DROPDOWN | wx.CB_READONLY)
self.Bind(wx.EVT_COMBOBOX, self.OnDropDown, self.WXDropdown)
self.Bind(wx.EVT_TEXT, self.OnDropDown, self.WXTextPages)
self.WXDropdown.SetSelection(0)
- ## Show Average and SD
+ # Show Average and SD
textavg = wx.StaticText(self.panel, label="Average ")
textsd = wx.StaticText(self.panel, label="Standard deviation ")
- self.WXavg = wx.TextCtrl(self.panel, size=(Psize,-1))
- self.WXsd = wx.TextCtrl(self.panel, size=(Psize,-1))
+ self.WXavg = wx.TextCtrl(self.panel, size=(Psize, -1))
+ self.WXsd = wx.TextCtrl(self.panel, size=(Psize, -1))
self.WXavg.SetEditable(False)
self.WXsd.SetEditable(False)
# Create space for parameters
@@ -132,13 +133,13 @@ def __init__(self, parent):
GridAll.Add(textsd)
GridAll.Add(self.WXsd)
#Psizer = wx.BoxSizer(wx.HORIZONTAL)
- #Psizer.Add(Pagetext)
- #Psizer.Add(self.WXTextPages)
+ # Psizer.Add(Pagetext)
+ # Psizer.Add(self.WXTextPages)
#DDsizer = wx.BoxSizer(wx.HORIZONTAL)
- #DDsizer.Add(DDtext)
- #DDsizer.Add(self.WXDropdown)
- #self.topSizer.Add(Psizer)
- #self.topSizer.Add(DDsizer)
+ # DDsizer.Add(DDtext)
+ # DDsizer.Add(self.WXDropdown)
+ # self.topSizer.Add(Psizer)
+ # self.topSizer.Add(DDsizer)
self.topSizer.Add(GridAll)
self.topSizer.Add(self.masterboxsizer)
self.topSizer.Add(self.btnSave)
@@ -147,19 +148,18 @@ def __init__(self, parent):
self.topSizer.Fit(self.panel)
px = self.topSizer.GetMinSize()[0]
- ## Plotting panel
+ # Plotting panel
self.canvas = plot.PlotCanvas(self.sp)
self.canvas.enableZoom = True
self.sp.SplitVertically(self.panel, self.canvas, px+5)
- ## Icon
+ # Icon
if parent.MainIcon is not None:
wx.Frame.SetIcon(self, parent.MainIcon)
self.Show(True)
self.OnDropDown()
-
def GetListOfAllParameters(self, e=None, return_std_checked=False,
- page=None):
+ page=None):
""" Returns sorted list of parameters.
If return_std_checked is True, then a second list with
standart checked parameters is returned.
@@ -203,7 +203,8 @@ def GetListOfAllParameters(self, e=None, return_std_checked=False,
checked[ii] = True
# A list with additional strings that should be default checked
# if found somewhere in the data.
- checklist = ["cpp", "duration", "bg rate", "avg.", "Model name", "filename/title"]
+ checklist = ["cpp", "duration", "bg rate",
+ "avg.", "Model name", "filename/title"]
for i in range(len(Info)):
item = Info[i]
for checkitem in checklist:
@@ -217,13 +218,11 @@ def GetListOfAllParameters(self, e=None, return_std_checked=False,
if item[0].count(checkitem):
checked[i] = False
-
if return_std_checked:
return Info, checked
else:
return Info
-
def GetListOfPlottableParms(self, e=None, return_values=False,
page=None):
""" Returns list of parameters that can be plotted.
@@ -255,7 +254,6 @@ def GetListOfPlottableParms(self, e=None, return_values=False,
else:
return parmlist
-
def GetWantedParameters(self):
"""
Updates self.SaveInfo with all the information that will be
@@ -286,9 +284,9 @@ def GetWantedParameters(self):
# If pagenumber is larger than 10,
# pagekeys.sort will not work, because we have strings
# Define new compare function
- cmp_func = lambda a: int(a.strip().strip("#"))
+ def cmp_func(a): return int(a.strip().strip("#"))
pagekeys.sort(key=cmp_func)
- #for Info in pagekeys:
+ # for Info in pagekeys:
# pageinfo = list()
# for item in AllInfo[Info]:
# for subitem in AllInfo[Info][item]:
@@ -319,7 +317,6 @@ def GetWantedParameters(self):
pageinfo.append([label, "NaN"])
self.SaveInfo.append(pageinfo)
-
def OnCheckboxChecked(self, e="restore"):
"""
Write boolean data of checked checkboxes to Page variable
@@ -329,7 +326,7 @@ def OnCheckboxChecked(self, e="restore"):
# What happens if a checkbox has been checked?
# We write the data to the Page
# (it will not be saved in the session).
- if e=="restore":
+ if e == "restore":
checklist = self.Page.StatisticsCheckboxes
if checklist is not None:
if len(checklist) <= len(self.Checkboxes):
@@ -341,13 +338,12 @@ def OnCheckboxChecked(self, e="restore"):
checklist.append(cb.GetValue())
self.Page.StatisticsCheckboxes = checklist
-
def OnChooseValues(self, event=None):
"""
Plot the values for the parameter selected by the user.
"""
Info, checked = self.GetListOfAllParameters(
- return_std_checked=True)
+ return_std_checked=True)
#headcounter = 0
#headlen = len(head)
# We will sort the checkboxes in more than one column if there
@@ -363,10 +359,10 @@ def OnChooseValues(self, event=None):
#itemcount += 1
#headcounter += 1
checkbox = wx.CheckBox(self.panel, label=Info[i][0])
- #if headcounter <= headlen:
+ # if headcounter <= headlen:
# checkbox.SetValue(True)
# Additionally default checked items
- #for checkitem in checklist:
+ # for checkitem in checklist:
# if item[0].count(checkitem):
# checkbox.SetValue(True)
checkbox.SetValue(checked[i])
@@ -382,7 +378,6 @@ def OnChooseValues(self, event=None):
self.OnCheckboxChecked("restore")
self.AllPlotParms = Info
-
def OnClose(self, event=None):
# This is a necessary function for PyCorrFit.
# Do not change it.
@@ -390,7 +385,6 @@ def OnClose(self, event=None):
self.parent.ToolsOpen.__delitem__(self.MyID)
self.Destroy()
-
def OnDropDown(self, e=None):
""" Plot the parameter selected in WXDropdown
Uses info stored in self.PlotParms and self.InfoClass
@@ -403,7 +397,7 @@ def OnDropDown(self, e=None):
strFull = self.WXTextPages.GetValue()
try:
PageNumbers = misc.parseString2Pagenum(self, strFull,
- nodialog=True)
+ nodialog=True)
except:
PageNumbers = self.PageNumbers
else:
@@ -425,12 +419,12 @@ def OnDropDown(self, e=None):
plotcurve = list()
for page in pages:
pllabel, pldata = self.GetListOfPlottableParms(page=page,
- return_values=True)
+ return_values=True)
# Get the labels and make a plot of the parameters
if len(pllabel)-1 >= DDselid and pllabel[DDselid] == label:
x = int(page.counter.strip("#: "))
y = pldata[DDselid]
- plotcurve.append([x,y])
+ plotcurve.append([x, y])
else:
# try to get the label by searching for the first
# instance
@@ -438,16 +432,16 @@ def OnDropDown(self, e=None):
if pllabel[k] == label:
x = int(page.counter.strip("#: "))
y = pldata[k]
- plotcurve.append([x,y])
+ plotcurve.append([x, y])
# Prepare plotting
self.canvas.Clear()
linesig = plot.PolyMarker(plotcurve, size=1.5, marker='circle')
plotlist = [linesig]
# average line
try:
- avg = np.average(np.array(plotcurve)[:,1])
- maxpage = int(np.max(np.array(plotcurve)[:,0]) +1)
- minpage = int(np.min(np.array(plotcurve)[:,0]) -1)
+ avg = np.average(np.array(plotcurve)[:, 1])
+ maxpage = int(np.max(np.array(plotcurve)[:, 0]) + 1)
+ minpage = int(np.min(np.array(plotcurve)[:, 0]) - 1)
except:
minpage = 0
maxpage = 0
@@ -461,13 +455,13 @@ def OnDropDown(self, e=None):
plotlist.append(lineclear)
# Update Text control
self.WXavg.SetValue(str(avg))
- self.WXsd.SetValue(str(np.std(np.array(plotcurve)[:,1])))
+ self.WXsd.SetValue(str(np.std(np.array(plotcurve)[:, 1])))
# Draw
# This causes a memory leak after this function has been
# called several times with the same large data set.
# This goes away if only linesig OR lineclear are plotted.
#
- #graphics = plot.PlotGraphics(plotlist,
+ # graphics = plot.PlotGraphics(plotlist,
# xLabel='page number',
# yLabel=label)
graphics = plot.PlotGraphics([linesig],
@@ -477,8 +471,7 @@ def OnDropDown(self, e=None):
# Correctly set x-axis
minticks = 2
self.canvas.SetXSpec(max(maxpage-minpage, minticks))
- self.canvas.Draw(graphics, xAxis=(minpage,maxpage))
-
+ self.canvas.Draw(graphics, xAxis=(minpage, maxpage))
def OnPageChanged(self, page, trigger=None):
"""
@@ -500,10 +493,10 @@ def OnPageChanged(self, page, trigger=None):
if self.Page.corr.fit_model.id == page.corr.fit_model.id:
return
if (trigger in ["page_add_finalize"] and
- self.WXTextPages.GetValue() == "1"):
+ self.WXTextPages.GetValue() == "1"):
# We probably imported data with statistics window open
self.PageNumbers = range(1,
- 1+self.parent.notebook.GetPageCount())
+ 1+self.parent.notebook.GetPageCount())
setstring = misc.parsePagenum2String(self.PageNumbers)
self.WXTextPages.SetValue(setstring)
@@ -517,8 +510,8 @@ def OnPageChanged(self, page, trigger=None):
for i in np.arange(self.parent.notebook.GetPageCount()):
Page = self.parent.notebook.GetPage(i)
pagenumlist.append(int("".join(filter(lambda x: x.isdigit(),
- Page.counter))))
- valstring=misc.parsePagenum2String(pagenumlist)
+ Page.counter))))
+ valstring = misc.parsePagenum2String(pagenumlist)
self.WXTextPages.SetValue(valstring)
DDselection = self.WXDropdown.GetValue()
self.Page = page
@@ -536,7 +529,7 @@ def OnPageChanged(self, page, trigger=None):
for i in np.arange(len(self.Checkboxes)):
self.Checkboxes[i].Destroy()
del self.Checkboxes
- #self.Checklabels[i].Destroy() # those cannot be destroyed.
+ # self.Checklabels[i].Destroy() # those cannot be destroyed.
for i in np.arange(len(self.boxsizerlist)):
self.boxsizer.Remove(0)
self.boxsizer.Layout()
@@ -555,17 +548,16 @@ def OnPageChanged(self, page, trigger=None):
(px, py) = self.topSizer.GetMinSize()
self.sp.SetSashPosition(px+5)
self.SetMinSize((px+400, py))
- self.SetSize((np.max([px+400,ax,oldsize[0]]),
- np.max([py,ay,oldsize[1]])))
+ self.SetSize((np.max([px+400, ax, oldsize[0]]),
+ np.max([py, ay, oldsize[1]])))
# Replot
self.OnDropDown()
-
def OnSaveTable(self, event=None):
dirname = self.parent.dirname
dlg = wx.FileDialog(self.parent, "Choose file to save", dirname,
- "", "Text file (*.txt)|*.txt;*.TXT",
- wx.FD_SAVE|wx.FD_OVERWRITE_PROMPT)
+ "", "Text file (*.txt)|*.txt;*.TXT",
+ wx.FD_SAVE | wx.FD_OVERWRITE_PROMPT)
# user cannot do anything until he clicks "OK"
if dlg.ShowModal() == wx.ID_OK:
filename = dlg.GetPath()
@@ -646,18 +638,18 @@ def SortParameters(parms):
"""
startswith_sort = [
- u"avg. signal",
- u"n",
- u"T",
- u"Ļ_trip",
- u"F",
- u"C",
- u"D",
- u"Ļ",
- u"Ļ_diff",
- u"alpha",
- u"SP",
- ]
+ u"avg. signal",
+ u"n",
+ u"T",
+ u"Ļ_trip",
+ u"F",
+ u"C",
+ u"D",
+ u"Ļ",
+ u"Ļ_diff",
+ u"alpha",
+ u"SP",
+ ]
otherparms = list()
@@ -676,7 +668,6 @@ def SortParameters(parms):
# special offsets to distinguish "T" and "Type":
special_off_start = ["Type", "Fit"]
-
def rate_tuple(item):
x = item[0]
return rate(x)
@@ -726,13 +717,12 @@ def rate(x):
if x.startswith(p):
r += 300
- if r==0:
+ if r == 0:
r = 10000
return r
-
- def compare(x,y):
+ def compare(x, y):
"""
rates x and y.
returns -1, 0, 1 required for common list sort
@@ -742,4 +732,4 @@ def compare(x,y):
return rx-ry
- return sorted(parms, key=rate_tuple)
\ No newline at end of file
+ return sorted(parms, key=rate_tuple)
diff --git a/pycorrfit/gui/tools/trace.py b/pycorrfit/gui/tools/trace.py
index 6a926f01..df577e71 100644
--- a/pycorrfit/gui/tools/trace.py
+++ b/pycorrfit/gui/tools/trace.py
@@ -15,13 +15,13 @@ def __init__(self, parent):
pos = self.parent.GetPosition()
pos = (pos[0]+100, pos[1]+100)
wx.Frame.__init__(self, parent=self.parent, title="Trace view",
- pos=pos, style=wx.DEFAULT_FRAME_STYLE|wx.FRAME_FLOAT_ON_PARENT)
- ## MYID
+ pos=pos, style=wx.DEFAULT_FRAME_STYLE | wx.FRAME_FLOAT_ON_PARENT)
+ # MYID
# This ID is given by the parent for an instance of this class
self.MyID = None
# Page
self.Page = self.parent.notebook.GetCurrentPage()
- ## Canvas
+ # Canvas
self.canvas = plot.PlotCanvas(self)
self.canvas.enableZoom = True
if self.parent.notebook.GetPageCount() == 0:
@@ -29,53 +29,54 @@ def __init__(self, parent):
pass
else:
self.OnDraw()
- initial_size = (780,250)
+ initial_size = (780, 250)
self.SetSize(initial_size)
self.SetMinSize(initial_size)
- ## Icon
+ # Icon
if parent.MainIcon is not None:
wx.Frame.SetIcon(self, parent.MainIcon)
self.Show(True)
-
def OnClose(self, event=None):
self.parent.toolmenu.Check(self.MyID, False)
self.parent.ToolsOpen.__delitem__(self.MyID)
self.Destroy()
-
def OnDraw(self):
traces = self.Page.corr.traces
self.canvas.enableLegend = True
if len(traces) == 1:
self.trace = 1*traces[0].trace
# We want to have the trace in [s] here.
- self.trace[:,0] = self.trace[:,0]/1000
+ self.trace[:, 0] = self.trace[:, 0]/1000
line = plot.PolyLine(self.trace,
- legend='{:.2f}kHz'.format(traces[0].countrate),
- colour='blue', width=1)
+ legend='{:.2f}kHz'.format(
+ traces[0].countrate),
+ colour='blue', width=1)
lines = [line]
- xmax = np.max(self.trace[:,0])
- xmin = np.min(self.trace[:,0])
- ymax = np.max(self.trace[:,1])
- ymin = np.min(self.trace[:,1])
+ xmax = np.max(self.trace[:, 0])
+ xmin = np.min(self.trace[:, 0])
+ ymax = np.max(self.trace[:, 1])
+ ymin = np.min(self.trace[:, 1])
elif len(traces) == 2:
# This means that we have two (CC) traces to plot
self.tracea = 1*traces[0].trace
- self.tracea[:,0] = self.tracea[:,0]/1000
+ self.tracea[:, 0] = self.tracea[:, 0]/1000
self.traceb = 1*traces[1].trace
- self.traceb[:,0] = self.traceb[:,0]/1000
+ self.traceb[:, 0] = self.traceb[:, 0]/1000
linea = plot.PolyLine(self.tracea,
- legend='channel 1 {:.2f}kHz'.format(traces[0].countrate),
- colour='blue', width=1)
+ legend='channel 1 {:.2f}kHz'.format(
+ traces[0].countrate),
+ colour='blue', width=1)
lineb = plot.PolyLine(self.traceb,
- legend='channel 2 {:.2f}kHz'.format(traces[1].countrate),
- colour='red', width=1)
+ legend='channel 2 {:.2f}kHz'.format(
+ traces[1].countrate),
+ colour='red', width=1)
lines = [linea, lineb]
- xmax = max(np.max(self.tracea[:,0]), np.max(self.traceb[:,0]))
- xmin = min(np.min(self.tracea[:,0]), np.min(self.traceb[:,0]))
- ymax = max(np.max(self.tracea[:,1]), np.max(self.traceb[:,1]))
- ymin = min(np.min(self.tracea[:,1]), np.min(self.traceb[:,1]))
+ xmax = max(np.max(self.tracea[:, 0]), np.max(self.traceb[:, 0]))
+ xmin = min(np.min(self.tracea[:, 0]), np.min(self.traceb[:, 0]))
+ ymax = max(np.max(self.tracea[:, 1]), np.max(self.traceb[:, 1]))
+ ymin = min(np.min(self.tracea[:, 1]), np.min(self.traceb[:, 1]))
else:
self.canvas.Clear()
@@ -84,9 +85,8 @@ def OnDraw(self):
self.canvas.Draw(plot.PlotGraphics(lines,
xLabel='time [s]',
yLabel='count rate [kHz]'),
- xAxis=(xmin,xmax),
- yAxis=(ymin,ymax))
-
+ xAxis=(xmin, xmax),
+ yAxis=(ymin, ymax))
def OnPageChanged(self, page=None, trigger=None):
"""
@@ -108,4 +108,3 @@ def OnPageChanged(self, page=None, trigger=None):
pass
return
self.OnDraw()
-
diff --git a/pycorrfit/gui/update.py b/pycorrfit/gui/update.py
index ecdf1cad..4b521e48 100644
--- a/pycorrfit/gui/update.py
+++ b/pycorrfit/gui/update.py
@@ -1,5 +1,5 @@
"""PyCorrFit - update checking"""
-from distutils.version import LooseVersion # For version checking
+from distutils.version import LooseVersion # For version checking
import os
import tempfile
import traceback
@@ -18,7 +18,6 @@
from . import misc
-
class UpdateDlg(wx.Frame):
def __init__(self, parent, valuedict):
@@ -29,7 +28,7 @@ def __init__(self, parent, valuedict):
pos = parent.GetPosition()
pos = (pos[0]+100, pos[1]+100)
wx.Frame.__init__(self, parent, wx.ID_ANY, title="Update",
- size=(230,240), pos=pos)
+ size=(230, 240), pos=pos)
self.changelog = changelog
# Fill html content
html = wxHTML(self)
@@ -45,7 +44,7 @@ def __init__(self, parent, valuedict):
if changelog:
string = string + \
- 'Change Log'.format(changelog)
+ 'Change Log'.format(changelog)
string += ''
html.SetPage(string)
self.Bind(wx.EVT_CLOSE, self.Close)
@@ -53,7 +52,6 @@ def __init__(self, parent, valuedict):
ico = misc.getMainIcon()
wx.Frame.SetIcon(self, ico)
-
def Close(self, event):
if len(self.changelog) != 0:
# Cleanup downloaded file, if it was downloaded
@@ -93,11 +91,13 @@ def update(parent):
delayedresult.startWorker(_update_consumer, _update_worker,
wargs=(parent,), cargs=(parent,))
+
def _update_consumer(delayedresult, parent):
results = delayedresult.get()
dlg = UpdateDlg(parent, results)
dlg.Show()
- parent.StatusBar.SetStatusText("...update status: "+results["Description"][2])
+ parent.StatusBar.SetStatusText(
+ "...update status: "+results["Description"][2])
def _update_worker(parent):
@@ -110,7 +110,7 @@ def _update_worker(parent):
else:
changelog = responseVer.read()
- ghrepo="FCS-analysis/PyCorrFit"
+ ghrepo = "FCS-analysis/PyCorrFit"
if hasattr(pcf_version, "repo_tag"):
old = LooseVersion(pcf_version.repo_tag)
else:
@@ -132,7 +132,7 @@ def _update_worker(parent):
clfile.write(changelog)
clfile.close()
else:
- changelogfile=doc.StaticChangeLog
+ changelogfile = doc.StaticChangeLog
results = dict()
results["Description"] = description
results["Homepage"] = doc.HomePage
diff --git a/pycorrfit/gui/usermodel.py b/pycorrfit/gui/usermodel.py
index b25e4f8c..06e667ae 100644
--- a/pycorrfit/gui/usermodel.py
+++ b/pycorrfit/gui/usermodel.py
@@ -17,7 +17,7 @@
from sympy.core.function import Function
from sympy import sympify
except ImportError:
- warnings.warn("Importing sympy failed."+\
+ warnings.warn("Importing sympy failed." +
" Reason: {}.".format(sys.exc_info()[1].message))
# Define Function, so PyCorrFit will start, even if sympy is not there.
# wixi needs Function.
@@ -47,6 +47,7 @@ class CorrFunc(object):
Check the input code of a proposed user model function and
return a function for fitting via GetFunction.
"""
+
def __init__(self, labels, values, substitutes, funcstring):
self.values = values
# a --> a
@@ -58,10 +59,10 @@ def __init__(self, labels, values, substitutes, funcstring):
for key in substitutes.keys():
# Don't forget to insert the "(" and ")"'s
self.funcstring = self.funcstring.replace(key,
- "("+substitutes[key]+")")
+ "("+substitutes[key]+")")
for otherkey in substitutes.keys():
substitutes[otherkey] = substitutes[otherkey].replace(key,
- "("+substitutes[key]+")")
+ "("+substitutes[key]+")")
# Convert the function string to a simpification object
self.simpification = sympify(self.funcstring, sympyfuncdict)
self.simstring = str(self.simpification)
@@ -80,7 +81,7 @@ def G(parms, tau):
# symstring = symstring.replace(key, str(vardict[key]))
# symstring = symstring.replace("####", "tau")
g = eval(self.funcstring, self.vardict)
- ## This would be a safer way to do this, but it is too slow!
+ # This would be a safer way to do this, but it is too slow!
# Once simpy supports arrays, we can use these.
#
# g = np.zeros(len(tau))
@@ -106,6 +107,7 @@ def TestFunction(self):
class UserModel(object):
""" Class for importing txt files as models into PyCorrFit.
"""
+
def __init__(self, parent):
" Define all important constants and variables. "
# Current ID is the last model ID we gave away.
diff --git a/pycorrfit/gui/wxutils.py b/pycorrfit/gui/wxutils.py
index 673cbd93..bc4e4b99 100644
--- a/pycorrfit/gui/wxutils.py
+++ b/pycorrfit/gui/wxutils.py
@@ -15,20 +15,21 @@ def float2string_nsf(fval, n=7):
Returns:
String with only n s.f. and trailing zeros.
"""
- #sgn=np.sign(fval)
+ # sgn=np.sign(fval)
try:
if fval == 0:
- npoint=n
+ npoint = n
else:
- q=abs(fval)
- k=int(np.ceil(np.log10(q/n)))
+ q = abs(fval)
+ k = int(np.ceil(np.log10(q/n)))
# prevent negative significant digits
npoint = max(0, n-k)
- string="{:.{}f}".format(fval, npoint)
+ string = "{:.{}f}".format(fval, npoint)
except:
- string="{}".format(fval)
+ string = "{}".format(fval)
return string
+
def nice_string(string):
"""
Convert a string of a float created by `float2string_nsf`
@@ -44,9 +45,10 @@ def nice_string(string):
olen = len(string)
newstring = string.rstrip("0")
if olen > len(newstring):
- string=newstring+"0"
+ string = newstring+"0"
return string
+
class PCFFloatValidator(wx.PyValidator):
def __init__(self, flag=None, pyVar=None):
wx.PyValidator.__init__(self)
@@ -93,8 +95,8 @@ def OnChar(self, event):
# not allowed
return
- if ( char in string.digits or
- char in ["+", "-"]+onlyonce):
+ if (char in string.digits or
+ char in ["+", "-"]+onlyonce):
event.Skip()
return
@@ -108,7 +110,7 @@ def OnChar(self, event):
class PCFFloatTextCtrl(wx.TextCtrl):
def __init__(self, *args, **kwargs):
- wx.TextCtrl.__init__(self, *args, validator=PCFFloatValidator(), size=(110,-1),
+ wx.TextCtrl.__init__(self, *args, validator=PCFFloatValidator(), size=(110, -1),
style=wx.TE_PROCESS_ENTER, **kwargs)
self.Bind(wx.EVT_ENTER_WINDOW, self.OnMouseEnter)
self.Bind(wx.EVT_LEAVE_WINDOW, self.OnMouseLeave)
@@ -116,10 +118,10 @@ def __init__(self, *args, **kwargs):
def OnMouseEnter(self, e):
self.SetFocus()
- self.SetSelection(-1,0)
+ self.SetSelection(-1, 0)
def OnMouseLeave(self, e):
- self.SetSelection(0,0)
+ self.SetSelection(0, 0)
self.SetInsertionPoint(0)
def SetValue(self, value):
@@ -155,7 +157,7 @@ def string2float(string):
value.
"""
if string.count("inf"):
- if string[0]=="-":
+ if string[0] == "-":
return -np.inf
else:
return np.inf
diff --git a/pycorrfit/meta.py b/pycorrfit/meta.py
index 5941d32c..9a9197c0 100644
--- a/pycorrfit/meta.py
+++ b/pycorrfit/meta.py
@@ -27,16 +27,16 @@ def get_file_location(filename):
"""
dirname = os.path.dirname(os.path.abspath(__file__))
locations = ["/./", "/pycorrfit_doc/", "/doc/"]
- locations += [ "/.."+l for l in locations]
- locations = [ os.path.realpath(dirname+l) for l in locations]
+ locations += ["/.."+l for l in locations]
+ locations = [os.path.realpath(dirname+l) for l in locations]
for i in range(len(locations)):
# check /usr/lib64/32 -> /usr/lib
for larch in ["lib32", "lib64"]:
if dirname.count(larch):
locations.append(locations[i].replace(larch, "lib", 1))
-
- ## freezed binaries:
+
+ # freezed binaries:
if hasattr(sys, 'frozen'):
try:
adir = sys._MEIPASS + "/doc/" # @UndefinedVariable
@@ -44,10 +44,9 @@ def get_file_location(filename):
adir = "./"
locations.append(os.path.realpath(adir))
for loc in locations:
- thechl = os.path.join(loc,filename)
+ thechl = os.path.join(loc, filename)
if os.path.exists(thechl):
return thechl
break
# if this does not work:
return None
-
diff --git a/pycorrfit/models/MODEL_TIRF_1C.py b/pycorrfit/models/MODEL_TIRF_1C.py
index fa7c3c19..8995a492 100755
--- a/pycorrfit/models/MODEL_TIRF_1C.py
+++ b/pycorrfit/models/MODEL_TIRF_1C.py
@@ -14,9 +14,10 @@ def wixi(x):
wixi = sps.wofz(z)
# We should have a real solution. Make sure nobody complains about
# some zero-value imaginary numbers.
-
+
return np.real_if_close(wixi)
+
def CF_Gxy_TIR_square(parms, tau):
# Model 6000
u""" Two-dimensional diffusion with a square shaped lateral detection
@@ -33,7 +34,7 @@ def CF_Gxy_TIR_square(parms, tau):
Please refer to the documentation of PyCorrFit
for further information on this model function.
-
+
Returns: Normalized Lateral correlation function w/square pinhole.
"""
D = parms[0]
@@ -61,7 +62,7 @@ def CF_Gxyz_TIR_square(parms, tau, wixi=wixi):
detection area taking into account the size of the
point spread function; and an exponential decaying profile
in axial direction.
-
+
*parms* - a list of parameters.
Parameters (parms[i]):
[0] D Diffusion coefficient
@@ -74,7 +75,7 @@ def CF_Gxyz_TIR_square(parms, tau, wixi=wixi):
Please refer to the documentation of PyCorrFit
for further information on this model function.
-
+
Returns: 3D correlation function for TIR-FCS w/square pinhole
"""
D = parms[0]
@@ -82,18 +83,18 @@ def CF_Gxyz_TIR_square(parms, tau, wixi=wixi):
a = parms[2]
kappa = 1/parms[3]
Conc = parms[4]
- ### Calculate gxy
+ # Calculate gxy
- # Axial correlation
+ # Axial correlation
x = np.sqrt(D*tau)*kappa
w_ix = wixi(x)
gz = np.sqrt(D*tau/np.pi) - (2*D*tau*kappa**2 - 1)/(2*kappa) * w_ix
# Lateral correlation
gx1 = 2/(a**2*np.sqrt(np.pi)) * np.sqrt(sigma**2+D*tau) * \
- ( np.exp(-a**2/(4*(sigma**2+D*tau))) -1 )
- gx2 = 1/a * sps.erf( a / (2*np.sqrt(sigma**2 + D*tau)))
- gx = gx1 + gx2
+ (np.exp(-a**2/(4*(sigma**2+D*tau))) - 1)
+ gx2 = 1/a * sps.erf(a / (2*np.sqrt(sigma**2 + D*tau)))
+ gx = gx1 + gx2
gxy = gx**2
# Non normalized correlation function
@@ -120,10 +121,10 @@ def MoreInfo_6000(parms, countrate=None):
#sigma = parms[1]
a = parms[2]
Conc = parms[3]
- Info=list()
+ Info = list()
# Detection area:
- Aeff = a**2
+ Aeff = a**2
# Particel number
Neff = Aeff * Conc
# Correlation function at tau = 0
@@ -188,7 +189,6 @@ def MoreInfo_6010(parms, countrate):
return Info
-
# 2D Model Square
m_twodsq6000 = [6000, u"2D", u"2D diffusion w/ square pinhole",
CF_Gxy_TIR_square]
@@ -196,7 +196,7 @@ def MoreInfo_6010(parms, countrate):
u"Ļ [100 nm]",
u"a [100 nm]",
u"C_2D [100 /ĀµmĀ²]"]
-values_6000 = [0.054, 2.3, 7.5, .6] # [D,lamb,NA,a,conc]
+values_6000 = [0.054, 2.3, 7.5, .6] # [D,lamb,NA,a,conc]
# For user comfort we add values that are human readable.
# Theese will be used for output that only humans can read.
labels_human_readable_6000 = [u"D [ĀµmĀ²/s]",
@@ -230,7 +230,6 @@ def MoreInfo_6010(parms, countrate):
labels_human_readable_6010, values_factor_human_readable_6010]
-
# Pack the models
model1 = dict()
model1["Parameters"] = parms_6000
diff --git a/pycorrfit/models/MODEL_TIRF_2D2D.py b/pycorrfit/models/MODEL_TIRF_2D2D.py
index fb90a7ef..954ab4c0 100755
--- a/pycorrfit/models/MODEL_TIRF_2D2D.py
+++ b/pycorrfit/models/MODEL_TIRF_2D2D.py
@@ -14,11 +14,13 @@ def wixi(x):
wixi = sps.wofz(z)
# We should have a real solution. Make sure nobody complains about
# some zero-value imaginary numbers.
-
+
return np.real_if_close(wixi)
# model 6022
# 2D + 2D no binding TIRF
+
+
def CF_Gxy_TIR_square_2d2d(parms, tau, wixi=wixi):
u""" Two-component two-dimensional diffusion with a square-shaped
lateral detection area taking into account the size of the
@@ -45,7 +47,7 @@ def CF_Gxy_TIR_square_2d2d(parms, tau, wixi=wixi):
Conc_2D2 = parms[5]
alpha = parms[6]
- ## First the 2D-diffusion of species 1
+ # First the 2D-diffusion of species 1
var1 = sigma**2+D_2D1*tau
AA1 = 2*np.sqrt(var1)/(a**2*np.sqrt(np.pi))
BB1 = np.exp(-a**2/(4*(var1))) - 1
@@ -53,9 +55,9 @@ def CF_Gxy_TIR_square_2d2d(parms, tau, wixi=wixi):
# gx = AA*BB+CC
# gxy = gx**2
# g2D = Conc_2D * gxy
- g2D1 = Conc_2D1 * (AA1*BB1+CC1)**2
+ g2D1 = Conc_2D1 * (AA1*BB1+CC1)**2
- ## Second the 2D-diffusion of species 2
+ # Second the 2D-diffusion of species 2
var2 = sigma**2+D_2D2*tau
AA2 = 2*np.sqrt(var2)/(a**2*np.sqrt(np.pi))
BB2 = np.exp(-a**2/(4*(var2))) - 1
@@ -63,60 +65,60 @@ def CF_Gxy_TIR_square_2d2d(parms, tau, wixi=wixi):
# gx = AA*BB+CC
# gxy = gx**2
# g2D = Conc_2D * gxy
- g2D2 = alpha**2 * Conc_2D2 * (AA2*BB2+CC2)**2
+ g2D2 = alpha**2 * Conc_2D2 * (AA2*BB2+CC2)**2
- ## Finally the Prefactor
+ # Finally the Prefactor
F = Conc_2D1 + alpha * Conc_2D2
G = (g2D1 + g2D2) / F**2
return G
# 2D-2D Model TIR
-m_tir_2d_2d_mix_6022 = [6022, u"2D+2D","Separate 2D diffusion, TIR",
+m_tir_2d_2d_mix_6022 = [6022, u"2D+2D", "Separate 2D diffusion, TIR",
CF_Gxy_TIR_square_2d2d]
-labels_6022 = [ u"D"+u"\u2081"+u" [10 ĀµmĀ²/s]",
- u"D"+u"\u2082"+u" [10 ĀµmĀ²/s]",
- u"Ļ [100 nm]",
- u"a [100 nm]",
- u"C"+u"\u2081"+u" [100 /ĀµmĀ²]",
- u"C"+u"\u2082"+u" [100 /ĀµmĀ²]",
- u"\u03b1"+" (q"+u"\u2082"+"/q"+u"\u2081"+")"
- ]
+labels_6022 = [u"D"+u"\u2081"+u" [10 ĀµmĀ²/s]",
+ u"D"+u"\u2082"+u" [10 ĀµmĀ²/s]",
+ u"Ļ [100 nm]",
+ u"a [100 nm]",
+ u"C"+u"\u2081"+u" [100 /ĀµmĀ²]",
+ u"C"+u"\u2082"+u" [100 /ĀµmĀ²]",
+ u"\u03b1"+" (q"+u"\u2082"+"/q"+u"\u2081"+")"
+ ]
values_6022 = [
- 0.01, # D_2Dā [10 ĀµmĀ²/s]
- 0.90, # D_2Dā [10 ĀµmĀ²/s]
- 2.3, # Ļ [100 nm]
- 7.50, # a [100 nm]
- 0.01, # conc.2Dā [100 /ĀµmĀ²]
- 0.03, # conc.2Dā [100 /ĀµmĀ²]
- 1 # alpha
- ]
+ 0.01, # D_2Dā [10 ĀµmĀ²/s]
+ 0.90, # D_2Dā [10 ĀµmĀ²/s]
+ 2.3, # Ļ [100 nm]
+ 7.50, # a [100 nm]
+ 0.01, # conc.2Dā [100 /ĀµmĀ²]
+ 0.03, # conc.2Dā [100 /ĀµmĀ²]
+ 1 # alpha
+]
# For user comfort we add values that are human readable.
# Theese will be used for output that only humans can read.
labels_human_readable_6022 = [
- u"D"+u"\u2081"+u" [ĀµmĀ²/s]",
- u"D"+u"\u2082"+u" [ĀµmĀ²/s]",
- u"Ļ [nm]",
- u"a [nm]",
- u"C"+u"\u2081"+u" [1/ĀµmĀ²]",
- u"C"+u"\u2082"+u" [1/ĀµmĀ²]",
- u"\u03b1"+" (q"+u"\u2082"+"/q"+u"\u2081"+")"
- ]
+ u"D"+u"\u2081"+u" [ĀµmĀ²/s]",
+ u"D"+u"\u2082"+u" [ĀµmĀ²/s]",
+ u"Ļ [nm]",
+ u"a [nm]",
+ u"C"+u"\u2081"+u" [1/ĀµmĀ²]",
+ u"C"+u"\u2082"+u" [1/ĀµmĀ²]",
+ u"\u03b1"+" (q"+u"\u2082"+"/q"+u"\u2081"+")"
+]
values_factor_human_readable_6022 = [
- 10, # D_2Dā [10 ĀµmĀ²/s],
- 10, # D_2Dā [10 ĀµmĀ²/s]
- 100, # Ļ [100 nm]
- 100, # a [100 nm]
- 100, # conc.2Dā [100 /ĀµmĀ²]
- 100, # conc.2Dā [100 /ĀµmĀ²]
- 1
- ]
+ 10, # D_2Dā [10 ĀµmĀ²/s],
+ 10, # D_2Dā [10 ĀµmĀ²/s]
+ 100, # Ļ [100 nm]
+ 100, # a [100 nm]
+ 100, # conc.2Dā [100 /ĀµmĀ²]
+ 100, # conc.2Dā [100 /ĀµmĀ²]
+ 1
+]
valuestofit_6022 = [False, True, False, False, False, True, False]
-parms_6022 = [labels_6022, values_6022, valuestofit_6022,
+parms_6022 = [labels_6022, values_6022, valuestofit_6022,
labels_human_readable_6022, values_factor_human_readable_6022]
-boundaries = [ [0, np.inf] ] * len(values_6022)
+boundaries = [[0, np.inf]] * len(values_6022)
model1 = dict()
diff --git a/pycorrfit/models/MODEL_TIRF_3D2D.py b/pycorrfit/models/MODEL_TIRF_3D2D.py
index 1f3e2b8d..a6e084cf 100755
--- a/pycorrfit/models/MODEL_TIRF_3D2D.py
+++ b/pycorrfit/models/MODEL_TIRF_3D2D.py
@@ -14,7 +14,7 @@ def wixi(x):
wixi = sps.wofz(z)
# We should have a real solution. Make sure nobody complains about
# some zero-value imaginary numbers.
-
+
return np.real_if_close(wixi)
@@ -49,7 +49,7 @@ def CF_Gxyz_TIR_square_3d2d(parms, tau, wixi=wixi):
Conc_2D = parms[6]
alpha = parms[7]
- ## First the 2D-diffusion at z=0
+ # First the 2D-diffusion at z=0
var1 = sigma**2+D_2D*tau
AA = 2*np.sqrt(var1)/(a**2*np.sqrt(np.pi))
BB = np.exp(-a**2/(4*(var1))) - 1
@@ -57,23 +57,23 @@ def CF_Gxyz_TIR_square_3d2d(parms, tau, wixi=wixi):
# gx = AA*BB+CC
# gxy = gx**2
# g2D = Conc_2D * gxy
- g2D = Conc_2D * (AA*BB+CC)**2
+ g2D = Conc_2D * (AA*BB+CC)**2
- ## Second the 3D diffusion for z>0
- # Axial correlation
+ # Second the 3D diffusion for z>0
+ # Axial correlation
x = np.sqrt(D_3D*tau)*kappa
w_ix = wixi(x)
gz = np.sqrt(D_3D*tau/np.pi) - (2*D_3D*tau*kappa**2 - 1)/(2*kappa) * w_ix
# Lateral correlation
gx1 = 2/(a**2*np.sqrt(np.pi)) * np.sqrt(sigma**2+D_3D*tau) * \
- ( np.exp(-a**2/(4*(sigma**2+D_3D*tau))) -1 )
- gx2 = 1/a * sps.erf( a / (2*np.sqrt(sigma**2 + D_3D*tau)))
- gx = gx1 + gx2
+ (np.exp(-a**2/(4*(sigma**2+D_3D*tau))) - 1)
+ gx2 = 1/a * sps.erf(a / (2*np.sqrt(sigma**2 + D_3D*tau)))
+ gx = gx1 + gx2
gxy = gx**2
# Non normalized correlation function
g3D = alpha**2 * Conc_3D * gxy * gz
- ## Finally the Prefactor
+ # Finally the Prefactor
F = alpha * Conc_3D / kappa + Conc_2D
G = (g3D + g2D) / F**2
return G
@@ -86,46 +86,46 @@ def CF_Gxyz_TIR_square_3d2d(parms, tau, wixi=wixi):
labels_6020 = [u"D_3D [10 ĀµmĀ²/s]",
u"D_2D [10 ĀµmĀ²/s]",
u"Ļ [100 nm]",
- u"a [100 nm]",
- u"d_eva [100 nm]",
- u"C_3D [1000 /ĀµmĀ³]",
- u"C_2D [100 /ĀµmĀ²]",
+ u"a [100 nm]",
+ u"d_eva [100 nm]",
+ u"C_3D [1000 /ĀµmĀ³]",
+ u"C_2D [100 /ĀµmĀ²]",
u"\u03b1"+" (q3D/q2D)"
- ]
+ ]
values_6020 = [
- 50.0, # D_3D [10 ĀµmĀ²/s]
- 0.81, # D_2D [10 ĀµmĀ²/s]
- 2.3, # Ļ [100 nm]
- 7.50, # a [100 nm]
- 1.0, # d_eva [100 nm]
- 0.01, # conc.3D [1000 /ĀµmĀ³]
- 0.03, # conc.2D [100 /ĀµmĀ²]
- 1 # alpha
- ]
+ 50.0, # D_3D [10 ĀµmĀ²/s]
+ 0.81, # D_2D [10 ĀµmĀ²/s]
+ 2.3, # Ļ [100 nm]
+ 7.50, # a [100 nm]
+ 1.0, # d_eva [100 nm]
+ 0.01, # conc.3D [1000 /ĀµmĀ³]
+ 0.03, # conc.2D [100 /ĀµmĀ²]
+ 1 # alpha
+]
# For user comfort we add values that are human readable.
# Theese will be used for output that only humans can read.
labels_human_readable_6020 = [
- u"D_3D [ĀµmĀ²/s]",
- u"D_2D [ĀµmĀ²/s]",
- u"Ļ [nm]",
- u"a [nm]",
- u"d_eva [nm]",
- u"C_3D [1/ĀµmĀ³]",
- u"C_2D [1/ĀµmĀ²]",
- u"\u03b1"+" (q3D/q2D)"
- ]
+ u"D_3D [ĀµmĀ²/s]",
+ u"D_2D [ĀµmĀ²/s]",
+ u"Ļ [nm]",
+ u"a [nm]",
+ u"d_eva [nm]",
+ u"C_3D [1/ĀµmĀ³]",
+ u"C_2D [1/ĀµmĀ²]",
+ u"\u03b1"+" (q3D/q2D)"
+]
values_factor_human_readable_6020 = [
- 10, # D_3D [ĀµmĀ²/s]
- 10, # D_2D [10 ĀµmĀ²/s]
- 100, # Ļ [100 nm]
- 100, # a [100 nm]
- 100, # d_eva [100 nm]
- 1000, # conc.3D [1000 /ĀµmĀ³]
- 100, # conc.2D [100 /ĀµmĀ²]
- 1 # alpha
- ]
+ 10, # D_3D [ĀµmĀ²/s]
+ 10, # D_2D [10 ĀµmĀ²/s]
+ 100, # Ļ [100 nm]
+ 100, # a [100 nm]
+ 100, # d_eva [100 nm]
+ 1000, # conc.3D [1000 /ĀµmĀ³]
+ 100, # conc.2D [100 /ĀµmĀ²]
+ 1 # alpha
+]
valuestofit_6020 = [False, True, False, False, False, False, True, False]
-parms_6020 = [labels_6020, values_6020, valuestofit_6020,
+parms_6020 = [labels_6020, values_6020, valuestofit_6020,
labels_human_readable_6020, values_factor_human_readable_6020]
diff --git a/pycorrfit/models/MODEL_TIRF_3D2Dkin_Ries.py b/pycorrfit/models/MODEL_TIRF_3D2Dkin_Ries.py
index 12f8126f..7a80781e 100755
--- a/pycorrfit/models/MODEL_TIRF_3D2Dkin_Ries.py
+++ b/pycorrfit/models/MODEL_TIRF_3D2Dkin_Ries.py
@@ -9,6 +9,7 @@
import scipy.special as sps
import numpy.lib.scimath as nps
+
def wixi(x):
""" Complex Error Function (Faddeeva/Voigt).
w(i*x) = exp(x**2) * ( 1-erf(x) )
@@ -93,15 +94,15 @@ def CF_gz_CC(parms, tau, wixi=wixi):
k_d = parms[10]
# Define some other constants:
K = k_a/k_d # equilibrium constant
- Beta = 1/(1 + K*Conc_3D) # This is wrong in the Ries paper
+ Beta = 1/(1 + K*Conc_3D) # This is wrong in the Ries paper
#Re = D / d_eva**2
Rt = D * (Conc_3D / (Beta * Conc_2D))**2
Rr = k_a * Conc_3D + k_d
# Define even more constants:
- sqrtR1 = -Rr/(2*nps.sqrt(Rt)) + nps.sqrt( Rr**2/(4*Rt) - Rr )
- sqrtR2 = -Rr/(2*nps.sqrt(Rt)) - nps.sqrt( Rr**2/(4*Rt) - Rr )
- R1 = sqrtR1 **2
- R2 = sqrtR2 **2
+ sqrtR1 = -Rr/(2*nps.sqrt(Rt)) + nps.sqrt(Rr**2/(4*Rt) - Rr)
+ sqrtR2 = -Rr/(2*nps.sqrt(Rt)) - nps.sqrt(Rr**2/(4*Rt) - Rr)
+ R1 = sqrtR1 ** 2
+ R2 = sqrtR2 ** 2
# Calculate return function
A1 = eta_2D * Conc_2D / (eta_3D * Conc_3D) * Beta
A2 = sqrtR1 * wixi(-nps.sqrt(tau*R2)) - sqrtR2 * wixi(-nps.sqrt(tau*R1))
@@ -151,10 +152,10 @@ def CF_gz_AC(parms, tau, wixi=wixi):
Rt = D * (Conc_3D / (Beta * Conc_2D))**2
Rr = k_a * Conc_3D + k_d
# Define even more constants:
- sqrtR1 = -Rr/(2*nps.sqrt(Rt)) + nps.sqrt( Rr**2/(4*Rt) - Rr )
- sqrtR2 = -Rr/(2*nps.sqrt(Rt)) - nps.sqrt( Rr**2/(4*Rt) - Rr )
- R1 = sqrtR1 **2
- R2 = sqrtR2 **2
+ sqrtR1 = -Rr/(2*nps.sqrt(Rt)) + nps.sqrt(Rr**2/(4*Rt) - Rr)
+ sqrtR2 = -Rr/(2*nps.sqrt(Rt)) - nps.sqrt(Rr**2/(4*Rt) - Rr)
+ R1 = sqrtR1 ** 2
+ R2 = sqrtR2 ** 2
# And even more more:
sqrtR3 = sqrtR1 + nps.sqrt(Re)
sqrtR4 = sqrtR2 + nps.sqrt(Re)
@@ -163,9 +164,9 @@ def CF_gz_AC(parms, tau, wixi=wixi):
# Calculate return function
A1 = eta_2D * Conc_2D * k_d / (eta_3D * Conc_3D)
A2 = sqrtR4*wixi(-nps.sqrt(tau*R1)) - sqrtR3*wixi(-nps.sqrt(tau*R2))
- A3 = ( sqrtR1 - sqrtR2 ) * wixi( nps.sqrt(tau*Re) )
- A4 = ( sqrtR1 - sqrtR2 ) * sqrtR3 * sqrtR4
- Solution = A1 * ( A2 + A3 ) / A4
+ A3 = (sqrtR1 - sqrtR2) * wixi(nps.sqrt(tau*Re))
+ A4 = (sqrtR1 - sqrtR2) * sqrtR3 * sqrtR4
+ Solution = A1 * (A2 + A3) / A4
# There are some below numerical errors-imaginary numbers.
# We do not want them.
return np.real_if_close(Solution)
@@ -211,30 +212,30 @@ def CF_gz_AA(parms, tau, wixi=wixi):
Rt = D * (Conc_3D / (Beta * Conc_2D))**2
Rr = k_a * Conc_3D + k_d
# Define even more constants:
- sqrtR1 = -Rr/(2*nps.sqrt(Rt)) + nps.sqrt( Rr**2/(4*Rt) - Rr )
- sqrtR2 = -Rr/(2*nps.sqrt(Rt)) - nps.sqrt( Rr**2/(4*Rt) - Rr )
- R1 = sqrtR1 **2
- R2 = sqrtR2 **2
+ sqrtR1 = -Rr/(2*nps.sqrt(Rt)) + nps.sqrt(Rr**2/(4*Rt) - Rr)
+ sqrtR2 = -Rr/(2*nps.sqrt(Rt)) - nps.sqrt(Rr**2/(4*Rt) - Rr)
+ R1 = sqrtR1 ** 2
+ R2 = sqrtR2 ** 2
# And even more more:
sqrtR3 = sqrtR1 + nps.sqrt(Re)
sqrtR4 = sqrtR2 + nps.sqrt(Re)
- R3 = sqrtR3 **2
- R4 = sqrtR4 **2
+ R3 = sqrtR3 ** 2
+ R4 = sqrtR4 ** 2
# Calculate return function
- Sum1 = d * nps.sqrt( Re*tau/np.pi )
- Sum2 = -d/2*(2*tau*Re -1) * wixi(np.sqrt(tau*Re))
- Sum3Mult1 = - eta_2D * Conc_2D * k_d / ( eta_3D * Conc_3D *
- (sqrtR1 - sqrtR2) )
+ Sum1 = d * nps.sqrt(Re*tau/np.pi)
+ Sum2 = -d/2*(2*tau*Re - 1) * wixi(np.sqrt(tau*Re))
+ Sum3Mult1 = - eta_2D * Conc_2D * k_d / (eta_3D * Conc_3D *
+ (sqrtR1 - sqrtR2))
S3M2S1M1 = sqrtR1/R3
S3M2S1M2S1 = wixi(-nps.sqrt(tau*R1)) + -2*nps.sqrt(tau*R3/np.pi)
- S3M2S1M2S2 = ( 2*tau*sqrtR1*nps.sqrt(Re) + 2*tau*Re -1 ) * \
- wixi(nps.sqrt(tau*Re))
+ S3M2S1M2S2 = (2*tau*sqrtR1*nps.sqrt(Re) + 2*tau*Re - 1) * \
+ wixi(nps.sqrt(tau*Re))
S3M2S2M1 = -sqrtR2/R4
S3M2S2M2S1 = wixi(-nps.sqrt(tau*R2)) + -2*nps.sqrt(tau*R4/np.pi)
- S3M2S2M2S2 = ( 2*tau*sqrtR2*nps.sqrt(Re) + 2*tau*Re -1 ) * \
- wixi(nps.sqrt(tau*Re))
- Sum3 = Sum3Mult1 * ( S3M2S1M1 * (S3M2S1M2S1 + S3M2S1M2S2) +
- S3M2S2M1 * (S3M2S2M2S1 + S3M2S2M2S2) )
+ S3M2S2M2S2 = (2*tau*sqrtR2*nps.sqrt(Re) + 2*tau*Re - 1) * \
+ wixi(nps.sqrt(tau*Re))
+ Sum3 = Sum3Mult1 * (S3M2S1M1 * (S3M2S1M2S1 + S3M2S1M2S2) +
+ S3M2S2M1 * (S3M2S2M2S1 + S3M2S2M2S2))
Sum = Sum1 + Sum2 + Sum3
# There are some below numerical errors-imaginary numbers.
# We do not want them.
@@ -242,9 +243,9 @@ def CF_gz_AA(parms, tau, wixi=wixi):
# 3D-2D binding/unbinding TIRF
-def CF_Gxyz_TIR_square_ubibi(parms, tau,
- gAAz=CF_gz_AA, gACz=CF_gz_AC, gCCz=CF_gz_CC,
- gxy=CF_gxy_square):
+def CF_Gxyz_TIR_square_ubibi(parms, tau,
+ gAAz=CF_gz_AA, gACz=CF_gz_AC, gCCz=CF_gz_CC,
+ gxy=CF_gxy_square):
u""" Two-component two- and three-dimensional diffusion
with a square-shaped lateral detection area taking into account
the size of the point spread function; and an exponential
@@ -287,7 +288,7 @@ def CF_Gxyz_TIR_square_ubibi(parms, tau,
eta_2D = parms[8]
#k_a = parms[9]
#k_d = parms[10]
- ## We now need to copmute a real beast:
+ # We now need to copmute a real beast:
# Inter species non-normalized correlation functions
# gAA = gAAz * gxy(D_3D)
# gAC = gACz * np.sqrt ( gxy(D_3D) * gxy(D_2D) )
@@ -310,11 +311,11 @@ def CF_Gxyz_TIR_square_ubibi(parms, tau,
parms_xy_3D = [D_3D, sigma, a]
# Here we go.
gAA = gAAz(parms, tau) * gxy(parms_xy_3D, tau)
- gAC = gACz(parms, tau) * nps.sqrt( gxy(parms_xy_3D, tau) *
- gxy(parms_xy_2D, tau) )
+ gAC = gACz(parms, tau) * nps.sqrt(gxy(parms_xy_3D, tau) *
+ gxy(parms_xy_2D, tau))
gCC = gCCz(parms, tau) * gxy(parms_xy_2D, tau)
# Nonnormalized correlation function
- g = eta_3D * Conc_3D * ( gAA + 2*gAC + gCC )
+ g = eta_3D * Conc_3D * (gAA + 2*gAC + gCC)
# Expectation value of fluorescence signal
F = eta_3D * Conc_3D / kappa + eta_2D * Conc_2D
# Normalized correlation function
@@ -324,10 +325,7 @@ def CF_Gxyz_TIR_square_ubibi(parms, tau,
return G.real
#FNEW = eta_3D * Conc_3D / kappa
#GNEW = eta_3D * Conc_3D * gCCz(parms, tau) / FNEW**2
- #return GNEW.real
-
-
-
+ # return GNEW.real
# 3D-2D binding Model TIR
@@ -337,61 +335,61 @@ def CF_Gxyz_TIR_square_ubibi(parms, tau,
labels_6021 = [u"D_3D [10 ĀµmĀ²/s]",
u"D_2D [10 ĀµmĀ²/s]",
u"Ļ [100 nm]",
- u"a [100 nm]",
- u"d_eva [100 nm]",
- u"C_3D [1000 /ĀµmĀ³]",
- u"C_2D[100 /ĀµmĀ²]",
- u"Ī·_3D",
- u"Ī·_2D",
- u"k_a [ĀµmĀ³/s]",
+ u"a [100 nm]",
+ u"d_eva [100 nm]",
+ u"C_3D [1000 /ĀµmĀ³]",
+ u"C_2D[100 /ĀµmĀ²]",
+ u"Ī·_3D",
+ u"Ī·_2D",
+ u"k_a [ĀµmĀ³/s]",
u"k_d [10Ā³ /s]"
- ]
+ ]
values_6021 = [
- 9.0, # D_3D [10 ĀµmĀ²/s]
- 0.0, # D_2D [10 ĀµmĀ²/s]
- 2.3, # Ļ [100 nm]
- 7.50, # a [100 nm]
- 1.0, # d_eva [100 nm]
- 0.01, # conc.3D [1000 /ĀµmĀ³]
- 0.03, # conc.2D [100 /ĀµmĀ²]
- 1, # Ī·_3D
- 1, # Ī·_2D
- 0.00001, # k_a [ĀµmĀ³/s]
- 0.000064 # k_d [10Ā³ /s]
- ]
+ 9.0, # D_3D [10 ĀµmĀ²/s]
+ 0.0, # D_2D [10 ĀµmĀ²/s]
+ 2.3, # Ļ [100 nm]
+ 7.50, # a [100 nm]
+ 1.0, # d_eva [100 nm]
+ 0.01, # conc.3D [1000 /ĀµmĀ³]
+ 0.03, # conc.2D [100 /ĀµmĀ²]
+ 1, # Ī·_3D
+ 1, # Ī·_2D
+ 0.00001, # k_a [ĀµmĀ³/s]
+ 0.000064 # k_d [10Ā³ /s]
+]
valuestofit_6021 = [False, True, False, False, False, False, True, False,
False, False, False]
# For user comfort we add values that are human readable.
# Theese will be used for output that only humans can read.
labels_human_readable_6021 = [
- u"D_3D [ĀµmĀ²/s]",
- u"D_2D [ĀµmĀ²/s]",
- u"Ļ [nm]",
- u"a [nm]",
- u"d_eva [nm]",
- u"C_3D [1/ĀµmĀ³]",
- u"C_2D [1/ĀµmĀ²]",
- u"Ī·_3D",
- u"Ī·_2D",
- u"k_a [ĀµmĀ³/s]",
- u"k_d [1/s]"
- ]
-values_factor_human_readable_6021 = [10, # "D_3D [ĀµmĀ²/s]",
- 10, # D_2D [10 ĀµmĀ²/s]
- 100, # Ļ [100 nm]
- 100, # a [100 nm]
- 100, # d_eva [100 nm]
- 1000, # conc.3D [1000 /ĀµmĀ³]
- 100, # conc.2D [100 /ĀµmĀ²]
- 1, # Ī·_3D
- 1, # Ī·_2D
- 1, # k_a [ĀµmĀ³/s]
- 1000 # k_d [10Ā³ /s]
- ]
+ u"D_3D [ĀµmĀ²/s]",
+ u"D_2D [ĀµmĀ²/s]",
+ u"Ļ [nm]",
+ u"a [nm]",
+ u"d_eva [nm]",
+ u"C_3D [1/ĀµmĀ³]",
+ u"C_2D [1/ĀµmĀ²]",
+ u"Ī·_3D",
+ u"Ī·_2D",
+ u"k_a [ĀµmĀ³/s]",
+ u"k_d [1/s]"
+]
+values_factor_human_readable_6021 = [10, # "D_3D [ĀµmĀ²/s]",
+ 10, # D_2D [10 ĀµmĀ²/s]
+ 100, # Ļ [100 nm]
+ 100, # a [100 nm]
+ 100, # d_eva [100 nm]
+ 1000, # conc.3D [1000 /ĀµmĀ³]
+ 100, # conc.2D [100 /ĀµmĀ²]
+ 1, # Ī·_3D
+ 1, # Ī·_2D
+ 1, # k_a [ĀµmĀ³/s]
+ 1000 # k_d [10Ā³ /s]
+ ]
parms_6021 = [labels_6021, values_6021, valuestofit_6021,
labels_human_readable_6021, values_factor_human_readable_6021]
-boundaries = [ [0, np.inf] ] * len(values_6021)
+boundaries = [[0, np.inf]] * len(values_6021)
model1 = dict()
model1["Parameters"] = parms_6021
diff --git a/pycorrfit/models/MODEL_TIRF_3D3D.py b/pycorrfit/models/MODEL_TIRF_3D3D.py
index b01334bb..10131cd4 100755
--- a/pycorrfit/models/MODEL_TIRF_3D3D.py
+++ b/pycorrfit/models/MODEL_TIRF_3D3D.py
@@ -14,7 +14,7 @@ def wixi(x):
wixi = sps.wofz(z)
# We should have a real solution. Make sure nobody complains about
# some zero-value imaginary numbers.
-
+
return np.real_if_close(wixi)
@@ -49,37 +49,37 @@ def CF_Gxyz_TIR_square_3d3d(parms, tau, wixi=wixi):
Conc_3D2 = parms[6]
alpha = parms[7]
- ## First, the 3D diffusion of species 1
- # Axial correlation
+ # First, the 3D diffusion of species 1
+ # Axial correlation
x1 = np.sqrt(D_3D1*tau)*kappa
w_ix1 = wixi(x1)
gz1 = np.sqrt(D_3D1*tau/np.pi) - (2*D_3D1*tau*kappa**2 - 1)/(2*kappa) * \
- w_ix1
+ w_ix1
# Lateral correlation
gx1_1 = 2/(a**2*np.sqrt(np.pi)) * np.sqrt(sigma**2+D_3D1*tau) * \
- ( np.exp(-a**2/(4*(sigma**2+D_3D1*tau))) -1 )
- gx2_1 = 1/a * sps.erf( a / (2*np.sqrt(sigma**2 + D_3D1*tau)))
- gx1 = gx1_1 + gx2_1
+ (np.exp(-a**2/(4*(sigma**2+D_3D1*tau))) - 1)
+ gx2_1 = 1/a * sps.erf(a / (2*np.sqrt(sigma**2 + D_3D1*tau)))
+ gx1 = gx1_1 + gx2_1
gxy1 = gx1**2
# Non normalized correlation function
g3D1 = Conc_3D1 * gxy1 * gz1
- ## Second, the 3D diffusion of species 2
- # Axial correlation
+ # Second, the 3D diffusion of species 2
+ # Axial correlation
x2 = np.sqrt(D_3D2*tau)*kappa
w_ix2 = wixi(x2)
gz2 = np.sqrt(D_3D2*tau/np.pi) - (2*D_3D2*tau*kappa**2 - 1)/(2*kappa) * \
- w_ix2
+ w_ix2
# Lateral correlation
gx1_2 = 2/(a**2*np.sqrt(np.pi)) * np.sqrt(sigma**2+D_3D2*tau) * \
- ( np.exp(-a**2/(4*(sigma**2+D_3D2*tau))) -1 )
- gx2_2 = 1/a * sps.erf( a / (2*np.sqrt(sigma**2 + D_3D2*tau)))
- gx2 = gx1_2 + gx2_2
+ (np.exp(-a**2/(4*(sigma**2+D_3D2*tau))) - 1)
+ gx2_2 = 1/a * sps.erf(a / (2*np.sqrt(sigma**2 + D_3D2*tau)))
+ gx2 = gx1_2 + gx2_2
gxy2 = gx2**2
# Non normalized correlation function
g3D2 = alpha**2 * Conc_3D2 * gxy2 * gz2
- ## Finally the Prefactor
+ # Finally the Prefactor
F = (Conc_3D1 + alpha * Conc_3D2) / kappa
G = (g3D1 + g3D2) / F**2
return G
@@ -92,45 +92,45 @@ def CF_Gxyz_TIR_square_3d3d(parms, tau, wixi=wixi):
labels_6023 = [u"D"+u"\u2081"+u" [10 ĀµmĀ²/s]",
u"D"+u"\u2082"+u" [10 ĀµmĀ²/s]",
u"Ļ [100 nm]",
- u"a [100 nm]",
- u"d_eva [100 nm]",
- u"C"+u"\u2081"+u" [1000 /ĀµmĀ³]",
- u"C"+u"\u2082"+u" [1000 /ĀµmĀ³]",
+ u"a [100 nm]",
+ u"d_eva [100 nm]",
+ u"C"+u"\u2081"+u" [1000 /ĀµmĀ³]",
+ u"C"+u"\u2082"+u" [1000 /ĀµmĀ³]",
u"\u03b1"+" (q"+u"\u2082"+"/q"+u"\u2081"+")"
- ]
+ ]
values_6023 = [
- 0.9, # D_3Dā [10 ĀµmĀ²/s]
- 9.0, # D_3Dā [10 ĀµmĀ²/s]
- 2.3, # Ļ [100 nm]
- 7.50, # a [100 nm]
- 1.0, # d_eva [100 nm]
- 0.01, # conc.3Dā [1000 /ĀµmĀ³]
- 0.03, # conc.3Dā [1000 /ĀµmĀ³]
- 1 # alpha
- ]
+ 0.9, # D_3Dā [10 ĀµmĀ²/s]
+ 9.0, # D_3Dā [10 ĀµmĀ²/s]
+ 2.3, # Ļ [100 nm]
+ 7.50, # a [100 nm]
+ 1.0, # d_eva [100 nm]
+ 0.01, # conc.3Dā [1000 /ĀµmĀ³]
+ 0.03, # conc.3Dā [1000 /ĀµmĀ³]
+ 1 # alpha
+]
# For user comfort we add values that are human readable.
# Theese will be used for output that only humans can read.
labels_human_readable_6023 = [
- u"D"+u"\u2081"+u" [ĀµmĀ²/s]",
- u"D"+u"\u2082"+u" [ĀµmĀ²/s]",
- u"Ļ [nm]",
- u"a [nm]",
- u"d_eva [nm]",
- u"C"+u"\u2081"+u" [1/ĀµmĀ³]",
- u"C"+u"\u2082"+u" [1/ĀµmĀ³]",
- u"\u03b1"+" (q"+u"\u2082"+"/q"+u"\u2081"+")"
- ]
-values_factor_human_readable_6023 = [10, # "D_3Dā [ĀµmĀ²/s]",
- 10, # D_3Dā [10 ĀµmĀ²/s]
- 100, # Ļ [100 nm]
- 100, # a [100 nm]
- 100, # d_eva [100 nm]
- 1000, # conc.3Dā [1000 /ĀµmĀ³]
- 1000, # conc.3Dā [1000 /ĀµmĀ³]
- 1 # alpha
- ]
+ u"D"+u"\u2081"+u" [ĀµmĀ²/s]",
+ u"D"+u"\u2082"+u" [ĀµmĀ²/s]",
+ u"Ļ [nm]",
+ u"a [nm]",
+ u"d_eva [nm]",
+ u"C"+u"\u2081"+u" [1/ĀµmĀ³]",
+ u"C"+u"\u2082"+u" [1/ĀµmĀ³]",
+ u"\u03b1"+" (q"+u"\u2082"+"/q"+u"\u2081"+")"
+]
+values_factor_human_readable_6023 = [10, # "D_3Dā [ĀµmĀ²/s]",
+ 10, # D_3Dā [10 ĀµmĀ²/s]
+ 100, # Ļ [100 nm]
+ 100, # a [100 nm]
+ 100, # d_eva [100 nm]
+ 1000, # conc.3Dā [1000 /ĀµmĀ³]
+ 1000, # conc.3Dā [1000 /ĀµmĀ³]
+ 1 # alpha
+ ]
valuestofit_6023 = [False, True, False, False, False, False, True, False]
-parms_6023 = [labels_6023, values_6023, valuestofit_6023,
+parms_6023 = [labels_6023, values_6023, valuestofit_6023,
labels_human_readable_6023, values_factor_human_readable_6023]
diff --git a/pycorrfit/models/MODEL_TIRF_gaussian_1C.py b/pycorrfit/models/MODEL_TIRF_gaussian_1C.py
index 2be593e7..70fd33fc 100755
--- a/pycorrfit/models/MODEL_TIRF_gaussian_1C.py
+++ b/pycorrfit/models/MODEL_TIRF_gaussian_1C.py
@@ -1,6 +1,7 @@
import numpy as np
import scipy.special as sps
+
def wixi(x):
""" Complex Error Function (Faddeeva/Voigt).
w(i*x) = exp(x**2) * ( 1-erf(x) )
@@ -13,9 +14,10 @@ def wixi(x):
wixi = sps.wofz(z)
# We should have a real solution. Make sure nobody complains about
# some zero-value imaginary numbers.
-
+
return np.real_if_close(wixi)
+
def CF_Gxyz_TIR_gauss(parms, tau):
u""" Three-dimensional free diffusion with a Gaussian lateral
detection profile and an exponentially decaying profile
@@ -50,16 +52,17 @@ def CF_Gxyz_TIR_gauss(parms, tau):
taudiff = r0**2/(4*D)
# 2D gauss component
# G2D = 1/N2D * g2D = 1/(Aeff*Conc.2D) * g2D
- g2D = 1 / ( (1.+tau/taudiff) )
+ g2D = 1 / ((1.+tau/taudiff))
# 1d TIR component
- # Axial correlation
+ # Axial correlation
kappa = 1/deva
x = np.sqrt(D*tau)*kappa
w_ix = wixi(x)
# Gz = 1/N1D * gz = kappa / Conc.1D * gz
- gz = kappa * (np.sqrt(D*tau/np.pi) - (2*D*tau*kappa**2 - 1)/(2*kappa) * w_ix)
+ gz = kappa * (np.sqrt(D*tau/np.pi) -
+ (2*D*tau*kappa**2 - 1)/(2*kappa) * w_ix)
# gz * g2D * 1/( deva *A2D) * 1 / Conc3D
@@ -69,7 +72,6 @@ def CF_Gxyz_TIR_gauss(parms, tau):
# 1 / (Conc * deva * np.pi * r0) * gz * g2D
return 1 / (Neff) * g2D * gz
-
def CF_Gxyz_TIR_gauss_trip(parms, tau):
@@ -102,8 +104,8 @@ def CF_Gxyz_TIR_gauss_trip(parms, tau):
r0 = parms[1]
deva = parms[2]
Conc = parms[3]
- tautrip=parms[4]
- T=parms[5]
+ tautrip = parms[4]
+ T = parms[5]
# Calculate sigma: width of the gaussian approximation of the PSF
Veff = np.pi * r0**2 * deva
@@ -112,18 +114,19 @@ def CF_Gxyz_TIR_gauss_trip(parms, tau):
taudiff = r0**2/(4*D)
# 2D gauss component
# G2D = 1/N2D * g2D = 1/(Aeff*Conc.2D) * g2D
- g2D = 1 / ( (1.+tau/taudiff) )
+ g2D = 1 / ((1.+tau/taudiff))
# 1d TIR component
- # Axial correlation
+ # Axial correlation
kappa = 1/deva
x = np.sqrt(D*tau)*kappa
w_ix = wixi(x)
# Gz = 1/N1D * gz = kappa / Conc.1D * gz
- gz = kappa * (np.sqrt(D*tau/np.pi) - (2*D*tau*kappa**2 - 1)/(2*kappa) * w_ix)
+ gz = kappa * (np.sqrt(D*tau/np.pi) -
+ (2*D*tau*kappa**2 - 1)/(2*kappa) * w_ix)
- ### triplet
+ # triplet
if tautrip == 0 or T == 0:
triplet = 1
else:
@@ -137,7 +140,6 @@ def CF_Gxyz_TIR_gauss_trip(parms, tau):
return 1 / (Neff) * g2D * gz * triplet
-
def MoreInfo_6013(parms, countrate=None):
u"""Supplementary variables:
Beware that the effective volume is chosen arbitrarily.
@@ -152,7 +154,7 @@ def MoreInfo_6013(parms, countrate=None):
r0 = parms[1]
deva = parms[2]
Conc = parms[3]
- Info=list()
+ Info = list()
# Detection area:
Veff = np.pi * r0**2 * deva
Neff = Conc * Veff
@@ -182,7 +184,7 @@ def MoreInfo_6014(parms, countrate=None):
r0 = parms[1]
deva = parms[2]
Conc = parms[3]
- Info=list()
+ Info = list()
# Detection area:
Veff = np.pi * r0**2 * deva
Neff = Conc * Veff
@@ -204,6 +206,7 @@ def get_boundaries_6014(parms):
boundaries[5] = [0, 1]
return boundaries
+
def get_boundaries_6013(parms):
# strictly positive
boundaries = [[0, None]]*len(parms)
@@ -211,7 +214,7 @@ def get_boundaries_6013(parms):
# 3D Model TIR gaussian
-m_3dtirsq6013 = [6013, "3D","Simple 3D diffusion w/ TIR",
+m_3dtirsq6013 = [6013, "3D", "Simple 3D diffusion w/ TIR",
CF_Gxyz_TIR_gauss]
labels_6013 = [u"D [10 ĀµmĀ²/s]",
u"rā [100 nm]",
@@ -227,13 +230,13 @@ def get_boundaries_6013(parms):
u"rā [nm]",
u"d_eva [nm]",
u"C_3D [1/ĀµmĀ³]"]
-values_factor_human_readable_6013 = [10,
+values_factor_human_readable_6013 = [10,
100,
100,
1000]
valuestofit_6013 = [True, False, False, True]
parms_6013 = [labels_6013, values_6013, valuestofit_6013,
- labels_human_readable_6013, values_factor_human_readable_6013]
+ labels_human_readable_6013, values_factor_human_readable_6013]
# Pack the models
model1 = dict()
@@ -244,7 +247,7 @@ def get_boundaries_6013(parms):
# 3D Model TIR gaussian + triplet
-m_3dtirsq6014 = [6014, "T+3D","Simple 3D diffusion + triplet w/ TIR",
+m_3dtirsq6014 = [6014, "T+3D", "Simple 3D diffusion + triplet w/ TIR",
CF_Gxyz_TIR_gauss_trip]
labels_6014 = [u"D [10 ĀµmĀ²/s]",
u"rā [100 nm]",
@@ -272,7 +275,7 @@ def get_boundaries_6013(parms):
1]
valuestofit_6014 = [True, False, False, True, False, False]
parms_6014 = [labels_6014, values_6014, valuestofit_6014,
- labels_human_readable_6014, values_factor_human_readable_6014]
+ labels_human_readable_6014, values_factor_human_readable_6014]
# Pack the models
model2 = dict()
diff --git a/pycorrfit/models/MODEL_TIRF_gaussian_3D2D.py b/pycorrfit/models/MODEL_TIRF_gaussian_3D2D.py
index c1f762f2..c823f75a 100755
--- a/pycorrfit/models/MODEL_TIRF_gaussian_3D2D.py
+++ b/pycorrfit/models/MODEL_TIRF_gaussian_3D2D.py
@@ -14,11 +14,13 @@ def wixi(x):
wixi = sps.wofz(z)
# We should have a real solution. Make sure nobody complains about
# some zero-value imaginary numbers.
-
+
return np.real_if_close(wixi)
# 3D + 2D + T
# model 6033
+
+
def CF_Gxyz_3d2dT_gauss(parms, tau):
u""" Two-component, two- and three-dimensional diffusion
with a Gaussian lateral detection profile and
@@ -58,45 +60,45 @@ def CF_Gxyz_3d2dT_gauss(parms, tau):
[9] offset
*tau* - lag time
"""
- n=parms[0]
- D2D=parms[1]
- D3D=parms[2]
- F=parms[3]
- r0=parms[4]
- deva=parms[5]
- alpha=parms[6]
- tautrip=parms[7]
- T=parms[8]
- off=parms[9]
-
- ### 2D species
+ n = parms[0]
+ D2D = parms[1]
+ D3D = parms[2]
+ F = parms[3]
+ r0 = parms[4]
+ deva = parms[5]
+ alpha = parms[6]
+ tautrip = parms[7]
+ T = parms[8]
+ off = parms[9]
+
+ # 2D species
taud2D = r0**2/(4*D2D)
- particle2D = (1-F)/ (1+tau/taud2D)
+ particle2D = (1-F) / (1+tau/taud2D)
- ### 3D species
+ # 3D species
taud3D = r0**2/(4*D3D)
# 2D gauss component
- g2D3D = 1 / ( (1.+tau/taud3D) )
+ g2D3D = 1 / ((1.+tau/taud3D))
# 1d TIR component
- # Axial correlation
+ # Axial correlation
kappa = 1/deva
x = np.sqrt(D3D*tau)*kappa
w_ix = wixi(x)
# Gz = 1/N1D * gz = kappa / Conc.1D * gz
- gz = kappa * (np.sqrt(D3D*tau/np.pi) -
- (2*D3D*tau*kappa**2 - 1)/(2*kappa) * w_ix)
+ gz = kappa * (np.sqrt(D3D*tau/np.pi) -
+ (2*D3D*tau*kappa**2 - 1)/(2*kappa) * w_ix)
particle3D = alpha**2*F * g2D3D * gz
- ### triplet
+ # triplet
if tautrip == 0 or T == 0:
triplet = 1
else:
triplet = 1 + T/(1-T) * np.exp(-tau/tautrip)
- ### Norm
+ # Norm
norm = (1-F + alpha*F)**2
- ### Correlation function
+ # Correlation function
G = 1/n*(particle2D + particle3D)*triplet/norm
return G + off
@@ -128,15 +130,15 @@ def MoreInfo(parms, countrate=None):
[15] C_3D [nM] = n3D/V_eff
"""
# We can only give you the effective particle number
- n=parms[0]
- #D2D=parms[1]
- #D3D=parms[2]
- F=parms[3]
- r0=parms[4]
- deva=parms[5]
- #alpha=parms[6]
-
- Info=list()
+ n = parms[0]
+ # D2D=parms[1]
+ # D3D=parms[2]
+ F = parms[3]
+ r0 = parms[4]
+ deva = parms[5]
+ # alpha=parms[6]
+
+ Info = list()
# The enumeration of these parameters is very important for
# plotting the normalized curve. Countrate must come out last!
Info.append([u"n3D", n*F])
@@ -144,7 +146,7 @@ def MoreInfo(parms, countrate=None):
# Detection area:
Veff = np.pi * r0**2 * deva
C3D = n*F / Veff
- C2D = n*(1-F) / ( np.pi*r0**2 )
+ C2D = n*(1-F) / (np.pi*r0**2)
# Correlation function at tau = 0
G_0 = CF_Gxyz_3d2dT_gauss(parms, 0)
Info.append([u"G(0)", G_0])
@@ -161,57 +163,58 @@ def MoreInfo(parms, countrate=None):
# 3D + 3D + T model gauss
m_gauss_3d_2d_t = [6033, "T+3D+2D",
- "Separate 3D and 2D diffusion + triplet w/ TIR",
- CF_Gxyz_3d2dT_gauss]
-labels = [ u"n",
- u"D_2D [10 ĀµmĀ²/s]",
- u"D_3D [10 ĀµmĀ²/s]",
- u"F_3D",
- u"rā [100 nm]",
- u"d_eva [100 nm]",
- u"\u03b1"+" (q_3D/q_2D)",
- u"Ļ_trip [ms]",
+ "Separate 3D and 2D diffusion + triplet w/ TIR",
+ CF_Gxyz_3d2dT_gauss]
+labels = [u"n",
+ u"D_2D [10 ĀµmĀ²/s]",
+ u"D_3D [10 ĀµmĀ²/s]",
+ u"F_3D",
+ u"rā [100 nm]",
+ u"d_eva [100 nm]",
+ u"\u03b1"+" (q_3D/q_2D)",
+ u"Ļ_trip [ms]",
+ u"T",
+ u"offset"
+ ]
+values = [
+ 25, # n
+ 0.51, # D2D
+ 25.1, # D3D
+ 0.45, # F3D
+ 9.44, # r0
+ 1.0, # deva
+ 1.0, # alpha
+ 0.001, # tautrip
+ 0.01, # T
+ 0.0 # offset
+]
+# Human readable stuff
+labelshr = [u"n",
+ u"D_2D [ĀµmĀ²/s]",
+ u"D_3D [ĀµmĀ²/s]",
+ u"F_3D",
+ u"rā [nm]",
+ u"d_eva [nm]",
+ u"\u03b1"+u" (q_3D/q_2D)",
+ u"Ļ_trip [Āµs]",
u"T",
u"offset"
- ]
-values = [
- 25, # n
- 0.51, # D2D
- 25.1, # D3D
- 0.45, # F3D
- 9.44, # r0
- 1.0, # deva
- 1.0, # alpha
- 0.001, # tautrip
- 0.01, # T
- 0.0 # offset
- ]
-# Human readable stuff
-labelshr = [u"n",
- u"D_2D [ĀµmĀ²/s]",
- u"D_3D [ĀµmĀ²/s]",
- u"F_3D",
- u"rā [nm]",
- u"d_eva [nm]",
- u"\u03b1"+u" (q_3D/q_2D)",
- u"Ļ_trip [Āµs]",
- u"T",
- u"offset"
- ]
-valueshr = [
- 1., # n
- 10., # D2D
- 10., # D3D
- 1., # F3D
- 100., # r0
- 100., # deva
- 1., # alpha
- 1000., # tautrip
- 1., # T
- 1. # offset
- ]
-
-valuestofit = [True, True, True, True, False, False, False, False, False, False]
+ ]
+valueshr = [
+ 1., # n
+ 10., # D2D
+ 10., # D3D
+ 1., # F3D
+ 100., # r0
+ 100., # deva
+ 1., # alpha
+ 1000., # tautrip
+ 1., # T
+ 1. # offset
+]
+
+valuestofit = [True, True, True, True,
+ False, False, False, False, False, False]
parms = [labels, values, valuestofit, labelshr, valueshr]
diff --git a/pycorrfit/models/MODEL_TIRF_gaussian_3D3D.py b/pycorrfit/models/MODEL_TIRF_gaussian_3D3D.py
index 060c04f6..ba81ce22 100755
--- a/pycorrfit/models/MODEL_TIRF_gaussian_3D3D.py
+++ b/pycorrfit/models/MODEL_TIRF_gaussian_3D3D.py
@@ -14,11 +14,13 @@ def wixi(x):
wixi = sps.wofz(z)
# We should have a real solution. Make sure nobody complains about
# some zero-value imaginary numbers.
-
- return np.real_if_close(wixi)
+
+ return np.real_if_close(wixi)
# 3D + 3D + T
# model 6034
+
+
def CF_Gxyz_3D3DT_gauss(parms, tau):
u""" Two-component three-dimensional diffusion with a Gaussian
lateral detection profile and an exponentially decaying profile
@@ -64,26 +66,25 @@ def CF_Gxyz_3D3DT_gauss(parms, tau):
[9] offset
*tau* - lag time
"""
- n=parms[0]
- D1=parms[1]
- D2=parms[2]
- F=parms[3]
- r0=parms[4]
- deva=parms[5]
- alpha=parms[6]
- tautrip=parms[7]
- T=parms[8]
- off=parms[9]
+ n = parms[0]
+ D1 = parms[1]
+ D2 = parms[2]
+ F = parms[3]
+ r0 = parms[4]
+ deva = parms[5]
+ alpha = parms[6]
+ tautrip = parms[7]
+ T = parms[8]
+ off = parms[9]
kappa = 1/deva
-
- ### 1st species
+ # 1st species
tauD1 = r0**2/(4*D1)
# 2D gauss component
- g2D1 = 1 / ( (1.+tau/tauD1) )
+ g2D1 = 1 / ((1.+tau/tauD1))
# 1d TIR component
- # Axial correlation
+ # Axial correlation
x1 = np.sqrt(D1*tau)*kappa
w_ix1 = wixi(x1)
# Gz = 1/N1D * gz = kappa / Conc.1D * gz
@@ -91,12 +92,12 @@ def CF_Gxyz_3D3DT_gauss(parms, tau):
(2*D1*tau*kappa**2 - 1)/(2*kappa) * w_ix1)
particle1 = F * g2D1 * gz1
- ### 2nd species
+ # 2nd species
tauD2 = r0**2/(4*D2)
# 2D gauss component
- g2D2 = 1 / ( (1.+tau/tauD2) )
+ g2D2 = 1 / ((1.+tau/tauD2))
# 1d TIR component
- # Axial correlation
+ # Axial correlation
x2 = np.sqrt(D2*tau)*kappa
w_ix2 = wixi(x2)
# Gz = 1/N1D * gz = kappa / Conc.1D * gz
@@ -104,16 +105,16 @@ def CF_Gxyz_3D3DT_gauss(parms, tau):
(2*D2*tau*kappa**2 - 1)/(2*kappa) * w_ix2)
particle2 = alpha**2*(1-F) * g2D2 * gz2
- ### triplet
+ # triplet
if tautrip == 0 or T == 0:
triplet = 1
else:
triplet = 1 + T/(1-T) * np.exp(-tau/tautrip)
- ### Norm
+ # Norm
norm = (F + alpha*(1-F))**2
- ### Correlation function
+ # Correlation function
G = 1/n*(particle1 + particle2)*triplet/norm
return G + off
@@ -146,15 +147,15 @@ def MoreInfo(parms, countrate=None):
[15] Cā [nM] = nā/V_eff
"""
# We can only give you the effective particle number
- n=parms[0]
- #D1=parms[1]
- #D2=parms[2]
- F=parms[3]
- r0=parms[4]
- deva=parms[5]
- #alpha=parms[6]
-
- Info=list()
+ n = parms[0]
+ # D1=parms[1]
+ # D2=parms[2]
+ F = parms[3]
+ r0 = parms[4]
+ deva = parms[5]
+ # alpha=parms[6]
+
+ Info = list()
# The enumeration of these parameters is very important for
# plotting the normalized curve. Countrate must come out last!
Info.append([u"n\u2081", n*F])
@@ -179,57 +180,58 @@ def MoreInfo(parms, countrate=None):
# 3D + 3D + T model gauss
m_gauss_3d_3d_t = [6034, "T+3D+3D",
- "Combined 3D diffusion + triplet w/ TIR",
- CF_Gxyz_3D3DT_gauss]
-labels = [u"n",
- u"D"+u"\u2081"+u" [10 ĀµmĀ²/s]",
- u"D"+u"\u2082"+u" [10 ĀµmĀ²/s]",
- u"F"+u"\u2081",
- u"rā [100 nm]",
- u"d_eva [100 nm]",
- u"\u03b1"+" (q"+u"\u2082"+"/q"+u"\u2081"+")",
- u"Ļ_trip [ms]",
- u"T",
- u"offset"
- ]
-values = [
- 25, # n
- 0.9, # D1
- 25.0, # D2
- 0.5, # F1
- 9.44, # r0
- 1.0, # deva
- 1.0, # alpha
- 0.001, # tautrip
- 0.01, # T
- 0.0 # offset
- ]
+ "Combined 3D diffusion + triplet w/ TIR",
+ CF_Gxyz_3D3DT_gauss]
+labels = [u"n",
+ u"D"+u"\u2081"+u" [10 ĀµmĀ²/s]",
+ u"D"+u"\u2082"+u" [10 ĀµmĀ²/s]",
+ u"F"+u"\u2081",
+ u"rā [100 nm]",
+ u"d_eva [100 nm]",
+ u"\u03b1"+" (q"+u"\u2082"+"/q"+u"\u2081"+")",
+ u"Ļ_trip [ms]",
+ u"T",
+ u"offset"
+ ]
+values = [
+ 25, # n
+ 0.9, # D1
+ 25.0, # D2
+ 0.5, # F1
+ 9.44, # r0
+ 1.0, # deva
+ 1.0, # alpha
+ 0.001, # tautrip
+ 0.01, # T
+ 0.0 # offset
+]
# Human readable stuff
-labelshr = [ u"n",
- u"D"+u"\u2081"+u" [ĀµmĀ²/s]",
- u"D"+u"\u2082"+u" [ĀµmĀ²/s]",
- u"F"+u"\u2081",
- u"rā [nm]",
- u"d_eva [nm]",
- u"\u03b1"+" (q"+u"\u2082"+"/q"+u"\u2081"+")",
- u"Ļ_trip [Āµs]",
- u"T",
- u"offset"
- ]
-valueshr = [
- 1., # n
- 10., # D1
- 10., # D2
- 1., # F1
- 100., # r0
- 100., # deva
- 1., # alpha
- 1000., # tautrip
- 1., # T
- 1. # offset
- ]
-
-valuestofit = [True, True, True, True, False, False, False, False, False, False]
+labelshr = [u"n",
+ u"D"+u"\u2081"+u" [ĀµmĀ²/s]",
+ u"D"+u"\u2082"+u" [ĀµmĀ²/s]",
+ u"F"+u"\u2081",
+ u"rā [nm]",
+ u"d_eva [nm]",
+ u"\u03b1"+" (q"+u"\u2082"+"/q"+u"\u2081"+")",
+ u"Ļ_trip [Āµs]",
+ u"T",
+ u"offset"
+ ]
+valueshr = [
+ 1., # n
+ 10., # D1
+ 10., # D2
+ 1., # F1
+ 100., # r0
+ 100., # deva
+ 1., # alpha
+ 1000., # tautrip
+ 1., # T
+ 1. # offset
+]
+
+valuestofit = [True, True, True, True,
+ False, False, False, False, False, False]
parms = [labels, values, valuestofit, labelshr, valueshr]
diff --git a/pycorrfit/models/__init__.py b/pycorrfit/models/__init__.py
index dcdfe846..fde098e8 100644
--- a/pycorrfit/models/__init__.py
+++ b/pycorrfit/models/__init__.py
@@ -134,6 +134,7 @@ def GetModelType(modelid):
warnings.warn("No shorttype defined for `{}`.".format(key))
return key
+
def GetModelFunctionFromId(modelid):
return modeldict[modelid][3]
@@ -145,6 +146,7 @@ def GetModelParametersFromId(modelid):
def GetModelFitBoolFromId(modelid):
return valuedict[modelid][2]
+
def GetMoreInfo(modelid, Page):
""" This functino is called by someone who has already calculated
some stuff or wants to know more about the model he is looking at.
@@ -160,16 +162,16 @@ def GetMoreInfo(modelid, Page):
Info = list()
corr = Page.corr
if corr.is_ac:
- if len(corr.traces)==1:
+ if len(corr.traces) == 1:
countrate = corr.traces[0].countrate
else:
countrate = None
- ## First import the supplementary parameters of the model
- ## The order is important for plot normalization and session
- ## saving as of version 0.7.8
+ # First import the supplementary parameters of the model
+ # The order is important for plot normalization and session
+ # saving as of version 0.7.8
# Try to get the dictionary entry of a model
# Background information
- if len(corr.backgrounds)==1:
+ if len(corr.backgrounds) == 1:
bgaverage = corr.backgrounds[0].countrate
# Now set the correct countrate
# We already printed the countrate, so there's no harm done.
@@ -199,12 +201,12 @@ def GetMoreInfo(modelid, Page):
# Background might overwrite countrate.
Info.append(["avg. signal [kHz]", corr.traces[0].countrate])
else:
- ## Cross correlation curves usually have two traces. Since we
- ## do not know how to compute the cpp, we will pass the argument
- ## "None" as the countrate.
- ## First import the supplementary parameters of the model
- ## The order is important for plot normalization and session
- ## saving as of version 0.7.8
+ # Cross correlation curves usually have two traces. Since we
+ # do not know how to compute the cpp, we will pass the argument
+ # "None" as the countrate.
+ # First import the supplementary parameters of the model
+ # The order is important for plot normalization and session
+ # saving as of version 0.7.8
# Try to get the dictionary entry of a model
try:
# This function should return all important information
@@ -216,7 +218,7 @@ def GetMoreInfo(modelid, Page):
except KeyError:
# No information available
pass
- if len(corr.traces)==2:
+ if len(corr.traces) == 2:
# Measurement time
duration = corr.traces[0].duration/1000
Info.append(["duration [s]", duration])
diff --git a/pycorrfit/models/classes.py b/pycorrfit/models/classes.py
index 898f18ba..af840095 100644
--- a/pycorrfit/models/classes.py
+++ b/pycorrfit/models/classes.py
@@ -7,6 +7,7 @@
class Model(object):
"""General class for handling FCS fitting models"""
+
def __init__(self, datadict):
"""datadict is an item in Modelarray"""
self._parameters = datadict["Parameters"]
@@ -32,7 +33,7 @@ def __init__(self, datadict):
# in e.g. confocal t_3d_3d_3d model.
if (isinstance(cc[0], numbers.Integral) and
isinstance(cc[2], numbers.Integral) and
- cc[0] < cc[2]):
+ cc[0] < cc[2]):
if cc[1] == ">":
cc = [cc[2], "<", cc[0]]
elif cc[1] == "<":
@@ -51,8 +52,8 @@ def __getitem__(self, key):
def __repr__(self):
text = "Model {} - {}".format(
- self.id,
- self.description_short)
+ self.id,
+ self.description_short)
return text
def apply(self, parameters, tau):
@@ -106,7 +107,8 @@ def func_supplements(self):
@property
def func_verification(self):
- warnings.warn("`func_verification is deprecated: please do not use it!")
+ warnings.warn(
+ "`func_verification is deprecated: please do not use it!")
return lambda x: x
def get_supplementary_parameters(self, values, countrate=None):
@@ -135,7 +137,7 @@ def get_supplementary_values(self, values, countrate=None):
count rate in Hz
"""
out = list()
- for item in self.get_supplementary_parameters(values, countrate):
+ for item in self.get_supplementary_parameters(values, countrate):
out.append(item[1])
return out
diff --git a/pycorrfit/models/control.py b/pycorrfit/models/control.py
index c4c24fba..937171ee 100644
--- a/pycorrfit/models/control.py
+++ b/pycorrfit/models/control.py
@@ -1,4 +1,29 @@
# -*- coding: utf-8 -*-
+from . import MODEL_TIRF_3D2Dkin_Ries
+from . import MODEL_TIRF_3D3D
+from . import MODEL_TIRF_3D2D
+from . import MODEL_TIRF_2D2D
+from . import MODEL_TIRF_1C
+from . import MODEL_TIRF_gaussian_3D3D
+from . import MODEL_TIRF_gaussian_3D2D
+from . import MODEL_TIRF_gaussian_1C
+from . import model_confocal_tt_3d_2d
+from . import model_confocal_tt_2d_2d
+from . import model_confocal_tt_2d
+from . import model_confocal_tt_3d_3d
+from . import model_confocal_tt_3d
+from . import model_confocal_t_3d_3d_2d
+from . import model_confocal_t_3d_3d_3d
+from . import model_confocal_t_3d_2d
+from . import model_confocal_t_2d_2d
+from . import model_confocal_t_2d
+from . import model_confocal_t_3d_3d
+from . import model_confocal_t_3d
+from . import model_confocal_3d_2d
+from . import model_confocal_2d_2d
+from . import model_confocal_2d
+from . import model_confocal_3d_3d
+from . import model_confocal_3d
""" pycorrfit.models.control
Controls which fitting models are imported an in which order.
@@ -7,6 +32,7 @@
from .classes import Model
+
def append_model(modelarray):
""" Append a new model from a modelarray. *Modelarray* has to be a list
whose elements have two items:
@@ -118,7 +144,8 @@ def model_setup(modelid, name, comp, mtype, fctn, par_labels, par_values,
par_hr_factors,
]:
if p is not None:
- assert len(p) == len(par_values), "Number of parameters must match!"
+ assert len(p) == len(
+ par_values), "Number of parameters must match!"
if par_hr_factors is None or par_hr_labels is None:
assert par_hr_factors is None, "human readable requires two parameter"
@@ -134,7 +161,7 @@ def model_setup(modelid, name, comp, mtype, fctn, par_labels, par_values,
par_hr_labels = par_labels
par_hr_factors = np.ones_like(par_values)
- model={}
+ model = {}
model["Parameters"] = [par_labels, par_values, par_vary,
par_hr_labels, par_hr_factors]
@@ -181,25 +208,6 @@ def model_setup(modelid, name, comp, mtype, fctn, par_labels, par_values,
# The order of the import matters!
# These models perform the integration by themselves using the `model_setup` method.
-from . import model_confocal_3d
-from . import model_confocal_3d_3d
-from . import model_confocal_2d
-from . import model_confocal_2d_2d
-from . import model_confocal_3d_2d
-
-from . import model_confocal_t_3d
-from . import model_confocal_t_3d_3d
-from . import model_confocal_t_2d
-from . import model_confocal_t_2d_2d
-from . import model_confocal_t_3d_2d
-from . import model_confocal_t_3d_3d_3d
-from . import model_confocal_t_3d_3d_2d
-
-from . import model_confocal_tt_3d
-from . import model_confocal_tt_3d_3d
-from . import model_confocal_tt_2d
-from . import model_confocal_tt_2d_2d
-from . import model_confocal_tt_3d_2d
# These lines can be removed once all models are converted
@@ -208,15 +216,7 @@ def model_setup(modelid, name, comp, mtype, fctn, par_labels, par_values,
modeltypes[u"TIR (ā”xĻ/Exp.)"] = [6010, 6023, 6000, 6022, 6020, 6021]
-## Models
-from . import MODEL_TIRF_gaussian_1C
-from . import MODEL_TIRF_gaussian_3D2D
-from . import MODEL_TIRF_gaussian_3D3D
-from . import MODEL_TIRF_1C
-from . import MODEL_TIRF_2D2D
-from . import MODEL_TIRF_3D2D
-from . import MODEL_TIRF_3D3D
-from . import MODEL_TIRF_3D2Dkin_Ries
+# Models
# Load all models from the imported "MODEL_*" submodules
# These are the models that were not imported using the `model_setup` method.
diff --git a/pycorrfit/models/cp_confocal.py b/pycorrfit/models/cp_confocal.py
index 75892335..485605ff 100644
--- a/pycorrfit/models/cp_confocal.py
+++ b/pycorrfit/models/cp_confocal.py
@@ -7,4 +7,4 @@ def threed(tau, taudiff, SP):
def twod(tau, taudiff):
- return 1/((1 + tau/taudiff))
\ No newline at end of file
+ return 1/((1 + tau/taudiff))
diff --git a/pycorrfit/models/cp_mix.py b/pycorrfit/models/cp_mix.py
index 5ad89cb6..3753ccb4 100644
--- a/pycorrfit/models/cp_mix.py
+++ b/pycorrfit/models/cp_mix.py
@@ -84,4 +84,4 @@ def triple_pnum(n,
G = 1/n * (g1 + g2 + g3) / norm
- return G
\ No newline at end of file
+ return G
diff --git a/pycorrfit/models/model_confocal_2d.py b/pycorrfit/models/model_confocal_2d.py
index 739c9c9d..93163d75 100644
--- a/pycorrfit/models/model_confocal_2d.py
+++ b/pycorrfit/models/model_confocal_2d.py
@@ -4,6 +4,8 @@
from .cp_confocal import twod
# 2D simple gauss
+
+
def CF_Gxy_gauss(parms, tau):
u""" Two-dimensional diffusion with a Gaussian laser profile.
@@ -44,21 +46,21 @@ def supplements(parms, countrate=None):
parms = [4.0, 0.4, 0.0]
-## boundaries
+# boundaries
boundaries = [[0, np.inf]]*len(parms)
boundaries[-1] = [-np.inf, np.inf]
model_setup(
- modelid=6001,
- name="2D diffusion (confocal)",
- comp="2D",
- mtype="Confocal (Gaussian)",
- fctn=CF_Gxy_gauss,
- par_labels=[ u"n",
- u"Ļ_diff [ms]",
- u"offset"],
- par_values=parms,
- par_vary=[True, True, False],
- par_boundaries=boundaries,
- supplementary_method=supplements
- )
+ modelid=6001,
+ name="2D diffusion (confocal)",
+ comp="2D",
+ mtype="Confocal (Gaussian)",
+ fctn=CF_Gxy_gauss,
+ par_labels=[u"n",
+ u"Ļ_diff [ms]",
+ u"offset"],
+ par_values=parms,
+ par_vary=[True, True, False],
+ par_boundaries=boundaries,
+ supplementary_method=supplements
+)
diff --git a/pycorrfit/models/model_confocal_2d_2d.py b/pycorrfit/models/model_confocal_2d_2d.py
index c65c68ff..4f9ee609 100644
--- a/pycorrfit/models/model_confocal_2d_2d.py
+++ b/pycorrfit/models/model_confocal_2d_2d.py
@@ -6,7 +6,7 @@
# 2D + 2D GauĆ
- # Model 6037
+# Model 6037
def CF_Gxyz_gauss_2D2D(parms, tau):
u""" Two-component, two-dimensional diffusion with a Gaussian laser
profile, including a triplet component.
@@ -32,22 +32,22 @@ def CF_Gxyz_gauss_2D2D(parms, tau):
[5] offset
*tau* - lag time
"""
- n=parms[0]
- taud1=parms[1]
- taud2=parms[2]
- F=parms[3]
- alpha=parms[4]
- off=parms[5]
+ n = parms[0]
+ taud1 = parms[1]
+ taud2 = parms[2]
+ F = parms[3]
+ alpha = parms[4]
+ off = parms[5]
g = double_pnum(n=n,
F1=F,
alpha=alpha,
comp1=twod,
comp2=twod,
- kwargs1={"tau":tau,
- "taudiff":taud1},
- kwargs2={"tau":tau,
- "taudiff":taud2},
+ kwargs1={"tau": tau,
+ "taudiff": taud1},
+ kwargs2={"tau": tau,
+ "taudiff": taud2},
)
G = off + g
@@ -75,39 +75,39 @@ def supplements(parms, countrate=None):
parms = [
- 25, # n
- 5, # taud1
- 1000, # taud2
- 0.5, # F
- 1.0, # alpha
- 0.0 # offset
- ]
+ 25, # n
+ 5, # taud1
+ 1000, # taud2
+ 0.5, # F
+ 1.0, # alpha
+ 0.0 # offset
+]
-## Boundaries
+# Boundaries
# strictly positive
boundaries = [[0, np.inf]]*len(parms)
# F
-boundaries[3] = [0,.9999999999999]
+boundaries[3] = [0, .9999999999999]
boundaries[-1] = [-np.inf, np.inf]
model_setup(
- modelid=6037,
- name="Separate 2D diffusion (confocal)",
- comp="2D+2D",
- mtype="Confocal (Gaussian)",
- fctn=CF_Gxyz_gauss_2D2D,
- par_labels=[
- u"n",
- u"Ļ"+u"\u2081"+u" [ms]",
- u"Ļ"+u"\u2082"+u" [ms]",
- u"F"+u"\u2081",
- u"\u03b1"+u" (q"+u"\u2082"+"/q"+u"\u2081"+")",
- u"offset"
- ],
- par_values=parms,
- par_vary=[True, True, True, True, False, False],
- par_boundaries=boundaries,
- par_constraints=[[2, ">", 1]],
- supplementary_method=supplements
- )
+ modelid=6037,
+ name="Separate 2D diffusion (confocal)",
+ comp="2D+2D",
+ mtype="Confocal (Gaussian)",
+ fctn=CF_Gxyz_gauss_2D2D,
+ par_labels=[
+ u"n",
+ u"Ļ"+u"\u2081"+u" [ms]",
+ u"Ļ"+u"\u2082"+u" [ms]",
+ u"F"+u"\u2081",
+ u"\u03b1"+u" (q"+u"\u2082"+"/q"+u"\u2081"+")",
+ u"offset"
+ ],
+ par_values=parms,
+ par_vary=[True, True, True, True, False, False],
+ par_boundaries=boundaries,
+ par_constraints=[[2, ">", 1]],
+ supplementary_method=supplements
+)
diff --git a/pycorrfit/models/model_confocal_3d.py b/pycorrfit/models/model_confocal_3d.py
index 5d88ec7f..f0405780 100644
--- a/pycorrfit/models/model_confocal_3d.py
+++ b/pycorrfit/models/model_confocal_3d.py
@@ -4,6 +4,8 @@
from .cp_confocal import threed
# 3D simple gauss
+
+
def CF_Gxyz_gauss(parms, tau):
# Model 6012
u""" Three-dimanesional free diffusion with a Gaussian laser profile
@@ -36,7 +38,7 @@ def CF_Gxyz_gauss(parms, tau):
off = parms[3]
BB = threed(tau, taudiff, SP)
-
+
G = off + 1/n * BB
return G
@@ -57,18 +59,18 @@ def supplements(parms, countrate=None):
boundaries[-1] = [-np.inf, np.inf]
model_setup(
- modelid=6012,
- name="3D diffusion (confocal)",
- comp="3D",
- mtype="Confocal (Gaussian)",
- fctn=CF_Gxyz_gauss,
- par_labels=[
- u"n",
- u"Ļ_diff [ms]",
- u"SP",
- u"offset"],
- par_values=parms,
- par_vary=[True, True, False, False],
- par_boundaries=boundaries,
- supplementary_method=supplements
- )
+ modelid=6012,
+ name="3D diffusion (confocal)",
+ comp="3D",
+ mtype="Confocal (Gaussian)",
+ fctn=CF_Gxyz_gauss,
+ par_labels=[
+ u"n",
+ u"Ļ_diff [ms]",
+ u"SP",
+ u"offset"],
+ par_values=parms,
+ par_vary=[True, True, False, False],
+ par_boundaries=boundaries,
+ supplementary_method=supplements
+)
diff --git a/pycorrfit/models/model_confocal_3d_2d.py b/pycorrfit/models/model_confocal_3d_2d.py
index 9bc457d7..4b0ec3f3 100644
--- a/pycorrfit/models/model_confocal_3d_2d.py
+++ b/pycorrfit/models/model_confocal_3d_2d.py
@@ -9,7 +9,7 @@
def CF_Gxyz_3d2d_gauss(parms, tau):
u""" Two-component, two- and three-dimensional diffusion
with a Gaussian laser profile.
-
+
particle2D = (1-F)/ (1+Ļ/Ļ_2D)
particle3D = Ī±Ā²*F/( (1+Ļ/Ļ_3D) * sqrt(1+Ļ/(Ļ_3D*SPĀ²)))
norm = (1-F + Ī±*F)Ā²
@@ -30,29 +30,30 @@ def CF_Gxyz_3d2d_gauss(parms, tau):
[6] offset
*tau* - lag time
"""
- n=parms[0]
- taud2D=parms[1]
- taud3D=parms[2]
- F=parms[3]
- SP=parms[4]
- alpha=parms[5]
- off=parms[6]
+ n = parms[0]
+ taud2D = parms[1]
+ taud3D = parms[2]
+ F = parms[3]
+ SP = parms[4]
+ alpha = parms[5]
+ off = parms[6]
g = double_pnum(n=n,
F1=1-F,
alpha=alpha,
comp1=twod,
comp2=threed,
- kwargs1={"tau":tau,
- "taudiff":taud2D},
- kwargs2={"tau":tau,
- "taudiff":taud3D,
- "SP":SP},
+ kwargs1={"tau": tau,
+ "taudiff": taud2D},
+ kwargs2={"tau": tau,
+ "taudiff": taud3D,
+ "SP": SP},
)
G = off + g
return G
+
def supplements(parms, countrate=None):
u"""Supplementary parameters:
Effective number of freely diffusing particles in 3D solution:
@@ -75,42 +76,42 @@ def supplements(parms, countrate=None):
return Info
-parms = [
- 25, # n
- 240, # taud2D
- 0.1, # taud3D
- 0.5, # F3D
- 7, # SP
- 1.0, # alpha
- 0.0 # offset
- ]
+parms = [
+ 25, # n
+ 240, # taud2D
+ 0.1, # taud3D
+ 0.5, # F3D
+ 7, # SP
+ 1.0, # alpha
+ 0.0 # offset
+]
-## Boundaries
+# Boundaries
# strictly positive
boundaries = [[0, np.inf]]*len(parms)
# F
-boundaries[3] = [0,.9999999999999]
+boundaries[3] = [0, .9999999999999]
boundaries[-1] = [-np.inf, np.inf]
model_setup(
- modelid=6036,
- name="Separate 3D and 2D diffusion (confocal)",
- comp="3D+2D",
- mtype="Confocal (Gaussian)",
- fctn=CF_Gxyz_3d2d_gauss,
- par_labels=[
- u"n",
- u"Ļ_2D [ms]",
- u"Ļ_3D [ms]",
- u"F_3D",
- u"SP",
- u"\u03b1"+" (q_3D/q_2D)",
- u"offset"
- ],
- par_values=parms,
- par_vary=[True, True, True, True, False, False, False],
- par_boundaries=boundaries,
- par_constraints=[[2, "<", 1]],
- supplementary_method=supplements
- )
+ modelid=6036,
+ name="Separate 3D and 2D diffusion (confocal)",
+ comp="3D+2D",
+ mtype="Confocal (Gaussian)",
+ fctn=CF_Gxyz_3d2d_gauss,
+ par_labels=[
+ u"n",
+ u"Ļ_2D [ms]",
+ u"Ļ_3D [ms]",
+ u"F_3D",
+ u"SP",
+ u"\u03b1"+" (q_3D/q_2D)",
+ u"offset"
+ ],
+ par_values=parms,
+ par_vary=[True, True, True, True, False, False, False],
+ par_boundaries=boundaries,
+ par_constraints=[[2, "<", 1]],
+ supplementary_method=supplements
+)
diff --git a/pycorrfit/models/model_confocal_3d_3d.py b/pycorrfit/models/model_confocal_3d_3d.py
index 74a40c47..9339dda9 100644
--- a/pycorrfit/models/model_confocal_3d_3d.py
+++ b/pycorrfit/models/model_confocal_3d_3d.py
@@ -29,30 +29,31 @@ def CF_Gxyz_gauss_3D3D(parms, tau):
[6] offset
*tau* - lag time
"""
- n=parms[0]
- taud1=parms[1]
- taud2=parms[2]
- F=parms[3]
- SP=parms[4]
- alpha=parms[5]
- off=parms[6]
+ n = parms[0]
+ taud1 = parms[1]
+ taud2 = parms[2]
+ F = parms[3]
+ SP = parms[4]
+ alpha = parms[5]
+ off = parms[6]
g = double_pnum(n=n,
F1=F,
alpha=alpha,
comp1=threed,
comp2=threed,
- kwargs1={"tau":tau,
- "taudiff":taud1,
- "SP":SP},
- kwargs2={"tau":tau,
- "taudiff":taud2,
- "SP":SP},
+ kwargs1={"tau": tau,
+ "taudiff": taud1,
+ "SP": SP},
+ kwargs2={"tau": tau,
+ "taudiff": taud2,
+ "SP": SP},
)
G = off + g
return G
+
def supplements(parms, countrate=None):
u"""Supplementary parameters:
[7] nā = n*Fā Particle number of species 1
@@ -74,41 +75,41 @@ def supplements(parms, countrate=None):
return Info
-parms = [ 25, # n
- 5, # taud1
- 1000, # taud2
- 0.5, # F
- 5, # SP
- 1.0, # alpha
- 0.0 # offset
- ]
+parms = [25, # n
+ 5, # taud1
+ 1000, # taud2
+ 0.5, # F
+ 5, # SP
+ 1.0, # alpha
+ 0.0 # offset
+ ]
-## Boundaries
+# Boundaries
# strictly positive
boundaries = [[0, np.inf]]*len(parms)
# F
-boundaries[3] = [0,.9999999999999]
+boundaries[3] = [0, .9999999999999]
boundaries[-1] = [-np.inf, np.inf]
model_setup(
- modelid=6035,
- name="Separate 3D diffusion (confocal)",
- comp="3D+3D",
- mtype="Confocal (Gaussian)",
- fctn=CF_Gxyz_gauss_3D3D,
- par_labels=[
- u"n",
- u"Ļ"+u"\u2081"+" [ms]",
- u"Ļ"+u"\u2082"+" [ms]",
- u"F"+u"\u2081",
- u"SP",
- u"\u03b1"+" (q"+u"\u2082"+"/q"+u"\u2081"+")",
- u"offset"
- ],
- par_values=parms,
- par_vary=[True, True, True, True, False, False, False],
- par_boundaries=boundaries,
- par_constraints=[[2, ">", 1]],
- supplementary_method=supplements
- )
+ modelid=6035,
+ name="Separate 3D diffusion (confocal)",
+ comp="3D+3D",
+ mtype="Confocal (Gaussian)",
+ fctn=CF_Gxyz_gauss_3D3D,
+ par_labels=[
+ u"n",
+ u"Ļ"+u"\u2081"+" [ms]",
+ u"Ļ"+u"\u2082"+" [ms]",
+ u"F"+u"\u2081",
+ u"SP",
+ u"\u03b1"+" (q"+u"\u2082"+"/q"+u"\u2081"+")",
+ u"offset"
+ ],
+ par_values=parms,
+ par_vary=[True, True, True, True, False, False, False],
+ par_boundaries=boundaries,
+ par_constraints=[[2, ">", 1]],
+ supplementary_method=supplements
+)
diff --git a/pycorrfit/models/model_confocal_t_2d.py b/pycorrfit/models/model_confocal_t_2d.py
index bc4c390b..da120651 100644
--- a/pycorrfit/models/model_confocal_t_2d.py
+++ b/pycorrfit/models/model_confocal_t_2d.py
@@ -15,7 +15,7 @@ def CF_Gxy_T_gauss(parms, tau):
triplet = 1 + T/(1-T)*exp(-Ļ/Ļ_trip)
G(Ļ) = offset + 1/( n * (1+Ļ/Ļ_diff) )*triplet
-
+
Calculation of diffusion coefficient and concentration
from the effective radius of the detection profile (rā = 2*Ļ):
D = rāĀ²/(4*Ļ_diff)
@@ -40,7 +40,7 @@ def CF_Gxy_T_gauss(parms, tau):
triplet = trip(tau=tau, tautrip=tautrip, T=T)
BB = twod(tau=tau, taudiff=taudiff)
-
+
G = dc + 1/n * BB * triplet
return G
@@ -58,35 +58,35 @@ def supplements(parms, countrate=None):
parms = [4.0, 0.4, 0.001, 0.01, 0.0]
-## Boundaries
+# Boundaries
# strictly positive
boundaries = [[0, np.inf]]*len(parms)
# F
-boundaries[3] = [0,.9999999999999]
+boundaries[3] = [0, .9999999999999]
boundaries[-1] = [-np.inf, np.inf]
model_setup(
- modelid=6002,
- name="2D diffusion with triplet (confocal)",
- comp="T+2D",
- mtype="Confocal (Gaussian) and triplet",
- fctn=CF_Gxy_T_gauss,
- par_labels=[
- u"n",
- u"Ļ_diff [ms]",
- u"Ļ_trip [ms]",
- u"T",
- u"offset"],
- par_values=parms,
- par_vary=[True, True, True, True, False],
- par_boundaries=boundaries,
- par_constraints=[[2, "<", 1]],
- par_hr_labels=[
- u"n",
- u"Ļ_diff [ms]",
- u"Ļ_trip [Āµs]",
- u"T",
- u"offset"],
- par_hr_factors=[1., 1., 1000., 1., 1.],
- supplementary_method=supplements
- )
+ modelid=6002,
+ name="2D diffusion with triplet (confocal)",
+ comp="T+2D",
+ mtype="Confocal (Gaussian) and triplet",
+ fctn=CF_Gxy_T_gauss,
+ par_labels=[
+ u"n",
+ u"Ļ_diff [ms]",
+ u"Ļ_trip [ms]",
+ u"T",
+ u"offset"],
+ par_values=parms,
+ par_vary=[True, True, True, True, False],
+ par_boundaries=boundaries,
+ par_constraints=[[2, "<", 1]],
+ par_hr_labels=[
+ u"n",
+ u"Ļ_diff [ms]",
+ u"Ļ_trip [Āµs]",
+ u"T",
+ u"offset"],
+ par_hr_factors=[1., 1., 1000., 1., 1.],
+ supplementary_method=supplements
+)
diff --git a/pycorrfit/models/model_confocal_t_2d_2d.py b/pycorrfit/models/model_confocal_t_2d_2d.py
index 77532f31..fe24c928 100644
--- a/pycorrfit/models/model_confocal_t_2d_2d.py
+++ b/pycorrfit/models/model_confocal_t_2d_2d.py
@@ -7,7 +7,7 @@
# 2D + 2D + Triplet GauĆ
- # Model 6031
+# Model 6031
def CF_Gxyz_gauss_2D2DT(parms, tau):
u""" Two-component, two-dimensional diffusion with a Gaussian laser
profile, including a triplet component.
@@ -37,24 +37,24 @@ def CF_Gxyz_gauss_2D2DT(parms, tau):
[7] offset
*tau* - lag time
"""
- n=parms[0]
- taud1=parms[1]
- taud2=parms[2]
- F=parms[3]
- alpha=parms[4]
- tautrip=parms[5]
- T=parms[6]
- off=parms[7]
+ n = parms[0]
+ taud1 = parms[1]
+ taud2 = parms[2]
+ F = parms[3]
+ alpha = parms[4]
+ tautrip = parms[5]
+ T = parms[6]
+ off = parms[7]
g = double_pnum(n=n,
F1=F,
alpha=alpha,
comp1=twod,
comp2=twod,
- kwargs1={"tau":tau,
- "taudiff":taud1},
- kwargs2={"tau":tau,
- "taudiff":taud2},
+ kwargs1={"tau": tau,
+ "taudiff": taud1},
+ kwargs2={"tau": tau,
+ "taudiff": taud2},
)
tr = trip(tau=tau, T=T, tautrip=tautrip)
@@ -84,65 +84,65 @@ def supplements(parms, countrate=None):
parms = [
- 25, # n
- 5, # taud1
- 1000, # taud2
- 0.5, # F
- 1.0, # alpha
- 0.001, # tautrip
- 0.01, # T
- 0.0 # offset
- ]
+ 25, # n
+ 5, # taud1
+ 1000, # taud2
+ 0.5, # F
+ 1.0, # alpha
+ 0.001, # tautrip
+ 0.01, # T
+ 0.0 # offset
+]
-## Boundaries
+# Boundaries
# strictly positive
boundaries = [[0, np.inf]]*len(parms)
# F
-boundaries[3] = [0,.9999999999999]
+boundaries[3] = [0, .9999999999999]
# T
-boundaries[6] = [0,.9999999999999]
+boundaries[6] = [0, .9999999999999]
boundaries[-1] = [-np.inf, np.inf]
model_setup(
- modelid=6031,
- name="Separate 2D diffusion with triplet (confocal)",
- comp="T+2D+2D",
- mtype="Confocal (Gaussian) and triplet",
- fctn=CF_Gxyz_gauss_2D2DT,
- par_labels=[
- u"n",
- u"Ļ"+u"\u2081"+u" [ms]",
- u"Ļ"+u"\u2082"+u" [ms]",
- u"F"+u"\u2081",
- u"\u03b1"+u" (q"+u"\u2082"+"/q"+u"\u2081"+")",
- u"Ļ_trip [ms]",
- u"T",
- u"offset"
- ],
- par_values=parms,
- par_vary=[True, True, True, True, False, False, False, False],
- par_boundaries=boundaries,
- par_constraints=[[2, ">", 1], [5, "<", 1]],
- par_hr_labels=[
- u"n",
- u"Ļ"+u"\u2081"+u" [ms]",
- u"Ļ"+u"\u2082"+u" [ms]",
- u"F"+u"\u2081",
- u"\u03b1"+" (q"+u"\u2082"+"/q"+u"\u2081"+")",
- u"Ļ_trip [Āµs]",
- u"T",
- u"offset"
- ],
- par_hr_factors=[
- 1., # "n",
- 1., # "Ļ"+u"\u2081"+" [ms]",
- 1., # "Ļ"+u"\u2082"+" [ms]",
- 1., # "F"+u"\u2081",
- 1., # u"\u03b1"+" (q"+u"\u2082"+"/q"+u"\u2081"+")",
- 1000., # "Ļ_trip [Āµs]",
- 1., # "T",
- 1. # "offset"
- ],
- supplementary_method=supplements
- )
+ modelid=6031,
+ name="Separate 2D diffusion with triplet (confocal)",
+ comp="T+2D+2D",
+ mtype="Confocal (Gaussian) and triplet",
+ fctn=CF_Gxyz_gauss_2D2DT,
+ par_labels=[
+ u"n",
+ u"Ļ"+u"\u2081"+u" [ms]",
+ u"Ļ"+u"\u2082"+u" [ms]",
+ u"F"+u"\u2081",
+ u"\u03b1"+u" (q"+u"\u2082"+"/q"+u"\u2081"+")",
+ u"Ļ_trip [ms]",
+ u"T",
+ u"offset"
+ ],
+ par_values=parms,
+ par_vary=[True, True, True, True, False, False, False, False],
+ par_boundaries=boundaries,
+ par_constraints=[[2, ">", 1], [5, "<", 1]],
+ par_hr_labels=[
+ u"n",
+ u"Ļ"+u"\u2081"+u" [ms]",
+ u"Ļ"+u"\u2082"+u" [ms]",
+ u"F"+u"\u2081",
+ u"\u03b1"+" (q"+u"\u2082"+"/q"+u"\u2081"+")",
+ u"Ļ_trip [Āµs]",
+ u"T",
+ u"offset"
+ ],
+ par_hr_factors=[
+ 1., # "n",
+ 1., # "Ļ"+u"\u2081"+" [ms]",
+ 1., # "Ļ"+u"\u2082"+" [ms]",
+ 1., # "F"+u"\u2081",
+ 1., # u"\u03b1"+" (q"+u"\u2082"+"/q"+u"\u2081"+")",
+ 1000., # "Ļ_trip [Āµs]",
+ 1., # "T",
+ 1. # "offset"
+ ],
+ supplementary_method=supplements
+)
diff --git a/pycorrfit/models/model_confocal_t_3d.py b/pycorrfit/models/model_confocal_t_3d.py
index 1b57433c..fefc66a8 100644
--- a/pycorrfit/models/model_confocal_t_3d.py
+++ b/pycorrfit/models/model_confocal_t_3d.py
@@ -40,7 +40,7 @@ def CF_Gxyz_blink(parms, tau):
AA = trip(tau, tautrip, T)
BB = threed(tau, taudiff, SP)
-
+
G = off + 1/n * AA * BB
return G
@@ -58,37 +58,37 @@ def supplements(parms, countrate=None):
parms = [4.0, 0.2, 0.001, 0.4, 5.0, 0.0]
-## Boundaries
+# Boundaries
boundaries = [[0, np.inf]]*len(parms)
# T
-boundaries[1] = [0,.9999999999999]
+boundaries[1] = [0, .9999999999999]
boundaries[-1] = [-np.inf, np.inf]
model_setup(
- modelid=6011,
- name="3D diffusion with triplet (confocal)",
- comp="T+3D",
- mtype="Confocal (Gaussian) and triplet",
- fctn=CF_Gxyz_blink,
- par_labels=[
- u"n",
- u"T",
- u"Ļ_trip [ms]",
- u"Ļ_diff [ms]",
- u"SP",
- u"offset"],
- par_values=parms,
- par_vary=[True, True, True, True, False, False],
- par_boundaries=boundaries,
- par_constraints=[[3, ">", 2]],
- par_hr_labels=[
- u"n",
- u"T",
- u"Ļ_trip [Āµs]",
- u"Ļ_diff [ms]",
- u"SP",
- u"offset"],
- par_hr_factors=[1., 1., 1000., 1., 1., 1.],
- supplementary_method=supplements
- )
+ modelid=6011,
+ name="3D diffusion with triplet (confocal)",
+ comp="T+3D",
+ mtype="Confocal (Gaussian) and triplet",
+ fctn=CF_Gxyz_blink,
+ par_labels=[
+ u"n",
+ u"T",
+ u"Ļ_trip [ms]",
+ u"Ļ_diff [ms]",
+ u"SP",
+ u"offset"],
+ par_values=parms,
+ par_vary=[True, True, True, True, False, False],
+ par_boundaries=boundaries,
+ par_constraints=[[3, ">", 2]],
+ par_hr_labels=[
+ u"n",
+ u"T",
+ u"Ļ_trip [Āµs]",
+ u"Ļ_diff [ms]",
+ u"SP",
+ u"offset"],
+ par_hr_factors=[1., 1., 1000., 1., 1., 1.],
+ supplementary_method=supplements
+)
diff --git a/pycorrfit/models/model_confocal_t_3d_2d.py b/pycorrfit/models/model_confocal_t_3d_2d.py
index bf201d65..38487a93 100644
--- a/pycorrfit/models/model_confocal_t_3d_2d.py
+++ b/pycorrfit/models/model_confocal_t_3d_2d.py
@@ -38,26 +38,26 @@ def CF_Gxyz_3d2dT_gauss(parms, tau):
[8] offset
*tau* - lag time
"""
- n=parms[0]
- taud2D=parms[1]
- taud3D=parms[2]
- F=parms[3]
- SP=parms[4]
- alpha=parms[5]
- tautrip=parms[6]
- T=parms[7]
- off=parms[8]
+ n = parms[0]
+ taud2D = parms[1]
+ taud3D = parms[2]
+ F = parms[3]
+ SP = parms[4]
+ alpha = parms[5]
+ tautrip = parms[6]
+ T = parms[7]
+ off = parms[8]
g = double_pnum(n=n,
F1=1-F,
alpha=alpha,
comp1=twod,
comp2=threed,
- kwargs1={"tau":tau,
- "taudiff":taud2D},
- kwargs2={"tau":tau,
- "taudiff":taud3D,
- "SP":SP},
+ kwargs1={"tau": tau,
+ "taudiff": taud2D},
+ kwargs2={"tau": tau,
+ "taudiff": taud3D,
+ "SP": SP},
)
tr = trip(tau=tau, T=T, tautrip=tautrip)
@@ -65,6 +65,7 @@ def CF_Gxyz_3d2dT_gauss(parms, tau):
G = off + g*tr
return G
+
def supplements(parms, countrate=None):
u"""Supplementary parameters:
Effective number of freely diffusing particles in 3D solution:
@@ -87,70 +88,70 @@ def supplements(parms, countrate=None):
return Info
-parms = [
- 25, # n
- 240, # taud2D
- 0.1, # taud3D
- 0.5, # F3D
- 7, # SP
- 1.0, # alpha
- 0.001, # tautrip
- 0.01, # T
- 0.0 # offset
- ]
+parms = [
+ 25, # n
+ 240, # taud2D
+ 0.1, # taud3D
+ 0.5, # F3D
+ 7, # SP
+ 1.0, # alpha
+ 0.001, # tautrip
+ 0.01, # T
+ 0.0 # offset
+]
-## Boundaries
+# Boundaries
# strictly positive
boundaries = [[0, np.inf]]*len(parms)
# F
-boundaries[3] = [0,.9999999999999]
+boundaries[3] = [0, .9999999999999]
# T
-boundaries[7] = [0,.9999999999999]
+boundaries[7] = [0, .9999999999999]
boundaries[-1] = [-np.inf, np.inf]
model_setup(
- modelid=6032,
- name="Separate 3D and 2D diffusion with triplet (confocal)",
- comp="T+3D+2D",
- mtype="Confocal (Gaussian) and triplet",
- fctn=CF_Gxyz_3d2dT_gauss,
- par_labels=[
- u"n",
- u"Ļ_2D [ms]",
- u"Ļ_3D [ms]",
- u"F_3D",
- u"SP",
- u"\u03b1"+" (q_3D/q_2D)",
- u"Ļ_trip [ms]",
- u"T",
- u"offset"
- ],
- par_values=parms,
- par_vary=[True, True, True, True, False, False, False, False, False],
- par_boundaries=boundaries,
- par_constraints=[[2, "<", 1], [6, "<", 2]],
- par_hr_labels=[
- u"n",
- u"Ļ_2D [ms]",
- u"Ļ_3D [ms]",
- u"F_3D",
- u"SP",
- u"\u03b1"+" (q_3D/q_2D)",
- u"Ļ_trip [Āµs]",
- u"T",
- u"offset"
- ],
- par_hr_factors=[
- 1., # "n",
- 1., # "Ļ_2D [ms]",
- 1., # "Ļ_3D [ms]",
- 1., # "F_3D",
- 1., # "SP",
- 1., # u"\u03b1"+" (q_3D/q_2D)",
- 1000., # "Ļ_trip [Āµs]",
- 1., # "T",
- 1. # "offset"
- ],
- supplementary_method=supplements
- )
+ modelid=6032,
+ name="Separate 3D and 2D diffusion with triplet (confocal)",
+ comp="T+3D+2D",
+ mtype="Confocal (Gaussian) and triplet",
+ fctn=CF_Gxyz_3d2dT_gauss,
+ par_labels=[
+ u"n",
+ u"Ļ_2D [ms]",
+ u"Ļ_3D [ms]",
+ u"F_3D",
+ u"SP",
+ u"\u03b1"+" (q_3D/q_2D)",
+ u"Ļ_trip [ms]",
+ u"T",
+ u"offset"
+ ],
+ par_values=parms,
+ par_vary=[True, True, True, True, False, False, False, False, False],
+ par_boundaries=boundaries,
+ par_constraints=[[2, "<", 1], [6, "<", 2]],
+ par_hr_labels=[
+ u"n",
+ u"Ļ_2D [ms]",
+ u"Ļ_3D [ms]",
+ u"F_3D",
+ u"SP",
+ u"\u03b1"+" (q_3D/q_2D)",
+ u"Ļ_trip [Āµs]",
+ u"T",
+ u"offset"
+ ],
+ par_hr_factors=[
+ 1., # "n",
+ 1., # "Ļ_2D [ms]",
+ 1., # "Ļ_3D [ms]",
+ 1., # "F_3D",
+ 1., # "SP",
+ 1., # u"\u03b1"+" (q_3D/q_2D)",
+ 1000., # "Ļ_trip [Āµs]",
+ 1., # "T",
+ 1. # "offset"
+ ],
+ supplementary_method=supplements
+)
diff --git a/pycorrfit/models/model_confocal_t_3d_3d.py b/pycorrfit/models/model_confocal_t_3d_3d.py
index 81b5e9f3..9fc53830 100644
--- a/pycorrfit/models/model_confocal_t_3d_3d.py
+++ b/pycorrfit/models/model_confocal_t_3d_3d.py
@@ -36,27 +36,27 @@ def CF_Gxyz_gauss_3D3DT(parms, tau):
[8] offset
*tau* - lag time
"""
- n=parms[0]
- taud1=parms[1]
- taud2=parms[2]
- F=parms[3]
- SP=parms[4]
- alpha=parms[5]
- tautrip=parms[6]
- T=parms[7]
- off=parms[8]
+ n = parms[0]
+ taud1 = parms[1]
+ taud2 = parms[2]
+ F = parms[3]
+ SP = parms[4]
+ alpha = parms[5]
+ tautrip = parms[6]
+ T = parms[7]
+ off = parms[8]
g = double_pnum(n=n,
F1=F,
alpha=alpha,
comp1=threed,
comp2=threed,
- kwargs1={"tau":tau,
- "taudiff":taud1,
- "SP":SP},
- kwargs2={"tau":tau,
- "taudiff":taud2,
- "SP":SP},
+ kwargs1={"tau": tau,
+ "taudiff": taud1,
+ "SP": SP},
+ kwargs2={"tau": tau,
+ "taudiff": taud2,
+ "SP": SP},
)
tr = trip(tau=tau, T=T, tautrip=tautrip)
@@ -64,6 +64,7 @@ def CF_Gxyz_gauss_3D3DT(parms, tau):
G = off + g*tr
return G
+
def supplements(parms, countrate=None):
u"""Supplementary parameters:
[9] nā = n*Fā Particle number of species 1
@@ -84,69 +85,69 @@ def supplements(parms, countrate=None):
return Info
-parms = [ 25, # n
- 5, # taud1
- 1000, # taud2
- 0.5, # F
- 5, # SP
- 1.0, # alpha
- 0.001, # tautrip
- 0.01, # T
- 0.0 # offset
- ]
+parms = [25, # n
+ 5, # taud1
+ 1000, # taud2
+ 0.5, # F
+ 5, # SP
+ 1.0, # alpha
+ 0.001, # tautrip
+ 0.01, # T
+ 0.0 # offset
+ ]
-## Boundaries
+# Boundaries
# strictly positive
boundaries = [[0, np.inf]]*len(parms)
# F
-boundaries[3] = [0,.9999999999999]
+boundaries[3] = [0, .9999999999999]
# T
-boundaries[7] = [0,.9999999999999]
+boundaries[7] = [0, .9999999999999]
boundaries[-1] = [-np.inf, np.inf]
model_setup(
- modelid=6030,
- name="Separate 3D diffusion with triplet (confocal)",
- comp="T+3D+3D",
- mtype="Confocal (Gaussian) and triplet",
- fctn=CF_Gxyz_gauss_3D3DT,
- par_labels=[
- u"n",
- u"Ļ"+u"\u2081"+" [ms]",
- u"Ļ"+u"\u2082"+" [ms]",
- u"F"+u"\u2081",
- u"SP",
- u"\u03b1"+" (q"+u"\u2082"+"/q"+u"\u2081"+")",
- u"Ļ_trip [ms]",
- u"T",
- u"offset"
- ],
- par_values=parms,
- par_vary=[True, True, True, True, False, False, False, False, False],
- par_boundaries=boundaries,
- par_constraints=[[2, ">", 1], [6, "<", 1]],
- par_hr_labels=[
- u"n",
- u"Ļ"+u"\u2081"+" [ms]",
- u"Ļ"+u"\u2082"+" [ms]",
- u"F"+u"\u2081",
- u"SP",
- u"\u03b1"+" (q"+u"\u2082"+"/q"+u"\u2081"+")",
- u"Ļ_trip [Āµs]",
- u"T",
- u"offset"
- ],
- par_hr_factors=[
- 1., # n
- 1., # taud1
- 1., # taud2
- 1., # F
- 1., # SP
- 1., # alpha
- 1000., # tautrip [Āµs]
- 1., # T
- 1. # offset
- ],
- supplementary_method=supplements
- )
+ modelid=6030,
+ name="Separate 3D diffusion with triplet (confocal)",
+ comp="T+3D+3D",
+ mtype="Confocal (Gaussian) and triplet",
+ fctn=CF_Gxyz_gauss_3D3DT,
+ par_labels=[
+ u"n",
+ u"Ļ"+u"\u2081"+" [ms]",
+ u"Ļ"+u"\u2082"+" [ms]",
+ u"F"+u"\u2081",
+ u"SP",
+ u"\u03b1"+" (q"+u"\u2082"+"/q"+u"\u2081"+")",
+ u"Ļ_trip [ms]",
+ u"T",
+ u"offset"
+ ],
+ par_values=parms,
+ par_vary=[True, True, True, True, False, False, False, False, False],
+ par_boundaries=boundaries,
+ par_constraints=[[2, ">", 1], [6, "<", 1]],
+ par_hr_labels=[
+ u"n",
+ u"Ļ"+u"\u2081"+" [ms]",
+ u"Ļ"+u"\u2082"+" [ms]",
+ u"F"+u"\u2081",
+ u"SP",
+ u"\u03b1"+" (q"+u"\u2082"+"/q"+u"\u2081"+")",
+ u"Ļ_trip [Āµs]",
+ u"T",
+ u"offset"
+ ],
+ par_hr_factors=[
+ 1., # n
+ 1., # taud1
+ 1., # taud2
+ 1., # F
+ 1., # SP
+ 1., # alpha
+ 1000., # tautrip [Āµs]
+ 1., # T
+ 1. # offset
+ ],
+ supplementary_method=supplements
+)
diff --git a/pycorrfit/models/model_confocal_t_3d_3d_2d.py b/pycorrfit/models/model_confocal_t_3d_3d_2d.py
index 8d2ae1db..54a3b94c 100644
--- a/pycorrfit/models/model_confocal_t_3d_3d_2d.py
+++ b/pycorrfit/models/model_confocal_t_3d_3d_2d.py
@@ -43,18 +43,18 @@ def CF_Gxyz_gauss_3D3D2DT(parms, tau):
[11] offset
*tau* - lag time
"""
- n=parms[0]
- taud1=parms[1]
- taud2=parms[2]
- taud3=parms[3]
- F1=parms[4]
- F2=parms[5]
- SP=parms[6]
- alpha21=parms[7]
- alpha31=parms[8]
- tautrip=parms[9]
- T=parms[10]
- off=parms[11]
+ n = parms[0]
+ taud1 = parms[1]
+ taud2 = parms[2]
+ taud3 = parms[3]
+ F1 = parms[4]
+ F2 = parms[5]
+ SP = parms[6]
+ alpha21 = parms[7]
+ alpha31 = parms[8]
+ tautrip = parms[9]
+ T = parms[10]
+ off = parms[11]
g = triple_pnum(n=n,
F1=F1,
@@ -64,14 +64,14 @@ def CF_Gxyz_gauss_3D3D2DT(parms, tau):
comp1=threed,
comp2=threed,
comp3=twod,
- kwargs1={"tau":tau,
- "taudiff":taud1,
- "SP":SP},
- kwargs2={"tau":tau,
- "taudiff":taud2,
- "SP":SP},
- kwargs3={"tau":tau,
- "taudiff":taud3},
+ kwargs1={"tau": tau,
+ "taudiff": taud1,
+ "SP": SP},
+ kwargs2={"tau": tau,
+ "taudiff": taud2,
+ "SP": SP},
+ kwargs3={"tau": tau,
+ "taudiff": taud3},
)
tr = trip(tau=tau, T=T, tautrip=tautrip)
@@ -103,84 +103,84 @@ def supplements(parms, countrate=None):
return Info
-parms = [ 25, # n
- 5, # taud1
- 1000, # taud2
- 11000, # taud3
- 0.5, # F1
- 0.01, # F2
- 5, # SP
- 1.0, # alpha21
- 1.0, # alpha31
- 0.001, # tautrip
- 0.01, # T
- 0.0 # offset
- ]
+parms = [25, # n
+ 5, # taud1
+ 1000, # taud2
+ 11000, # taud3
+ 0.5, # F1
+ 0.01, # F2
+ 5, # SP
+ 1.0, # alpha21
+ 1.0, # alpha31
+ 0.001, # tautrip
+ 0.01, # T
+ 0.0 # offset
+ ]
-## Boundaries
+# Boundaries
# strictly positive
boundaries = [[0, np.inf]]*len(parms)
# F
-boundaries[4] = [0,.9999999999999]
-boundaries[5] = [0,.9999999999999]
+boundaries[4] = [0, .9999999999999]
+boundaries[5] = [0, .9999999999999]
# T
-boundaries[10] = [0,.9999999999999]
+boundaries[10] = [0, .9999999999999]
boundaries[-1] = [-np.inf, np.inf]
model_setup(
- modelid=6082,
- name="Twofold 3D and one 2D diffusion with triplet (confocal)",
- comp="T+3D+3D+2D",
- mtype="Confocal (Gaussian) and triplet",
- fctn=CF_Gxyz_gauss_3D3D2DT,
- par_labels=[
- u"n",
- u"Ļ"+u"\u2081"+" [ms]",
- u"Ļ"+u"\u2082"+" [ms]",
- u"Ļ"+u"\u2083"+" [ms]",
- u"F"+u"\u2081",
- u"F"+u"\u2082",
- u"SP",
- u"\u03b1\u2082\u2081",
- u"\u03b1\u2083\u2081",
- u"Ļ_trip [ms]",
- u"T",
- u"offset"
- ],
- par_values=parms,
- par_vary=[True, True, False, True,
- False, True, False, False,
- False, False, True, False],
- par_boundaries=boundaries,
- par_constraints=[[2, ">", 1], [3, ">", 2], [9, "<", 1], [5, 4, "<", "1"]],
- par_hr_labels=[
- u"n",
- u"Ļ"+u"\u2081"+" [ms]",
- u"Ļ"+u"\u2082"+" [ms]",
- u"Ļ"+u"\u2083"+" [ms]",
- u"F"+u"\u2081",
- u"F"+u"\u2082",
- u"SP",
- u"\u03b1\u2082\u2081",
- u"\u03b1\u2083\u2081",
- u"Ļ_trip [Āµs]",
- u"T",
- u"offset"
- ],
- par_hr_factors=[
- 1., # n
- 1., # taud1
- 1., # taud2
- 1., # taud3
- 1., # F1
- 1., # F2
- 1., # SP
- 1., # alpha21
- 1., # alpha31
- 1000., # tautrip [Āµs]
- 1., # T
- 1. # offset
- ],
- supplementary_method=supplements
- )
+ modelid=6082,
+ name="Twofold 3D and one 2D diffusion with triplet (confocal)",
+ comp="T+3D+3D+2D",
+ mtype="Confocal (Gaussian) and triplet",
+ fctn=CF_Gxyz_gauss_3D3D2DT,
+ par_labels=[
+ u"n",
+ u"Ļ"+u"\u2081"+" [ms]",
+ u"Ļ"+u"\u2082"+" [ms]",
+ u"Ļ"+u"\u2083"+" [ms]",
+ u"F"+u"\u2081",
+ u"F"+u"\u2082",
+ u"SP",
+ u"\u03b1\u2082\u2081",
+ u"\u03b1\u2083\u2081",
+ u"Ļ_trip [ms]",
+ u"T",
+ u"offset"
+ ],
+ par_values=parms,
+ par_vary=[True, True, False, True,
+ False, True, False, False,
+ False, False, True, False],
+ par_boundaries=boundaries,
+ par_constraints=[[2, ">", 1], [3, ">", 2], [9, "<", 1], [5, 4, "<", "1"]],
+ par_hr_labels=[
+ u"n",
+ u"Ļ"+u"\u2081"+" [ms]",
+ u"Ļ"+u"\u2082"+" [ms]",
+ u"Ļ"+u"\u2083"+" [ms]",
+ u"F"+u"\u2081",
+ u"F"+u"\u2082",
+ u"SP",
+ u"\u03b1\u2082\u2081",
+ u"\u03b1\u2083\u2081",
+ u"Ļ_trip [Āµs]",
+ u"T",
+ u"offset"
+ ],
+ par_hr_factors=[
+ 1., # n
+ 1., # taud1
+ 1., # taud2
+ 1., # taud3
+ 1., # F1
+ 1., # F2
+ 1., # SP
+ 1., # alpha21
+ 1., # alpha31
+ 1000., # tautrip [Āµs]
+ 1., # T
+ 1. # offset
+ ],
+ supplementary_method=supplements
+)
diff --git a/pycorrfit/models/model_confocal_t_3d_3d_3d.py b/pycorrfit/models/model_confocal_t_3d_3d_3d.py
index 2d4061ac..fa068640 100644
--- a/pycorrfit/models/model_confocal_t_3d_3d_3d.py
+++ b/pycorrfit/models/model_confocal_t_3d_3d_3d.py
@@ -43,18 +43,18 @@ def CF_Gxyz_gauss_3D3D3DT(parms, tau):
[11] offset
*tau* - lag time
"""
- n=parms[0]
- taud1=parms[1]
- taud2=parms[2]
- taud3=parms[3]
- F1=parms[4]
- F2=parms[5]
- SP=parms[6]
- alpha21=parms[7]
- alpha31=parms[8]
- tautrip=parms[9]
- T=parms[10]
- off=parms[11]
+ n = parms[0]
+ taud1 = parms[1]
+ taud2 = parms[2]
+ taud3 = parms[3]
+ F1 = parms[4]
+ F2 = parms[5]
+ SP = parms[6]
+ alpha21 = parms[7]
+ alpha31 = parms[8]
+ tautrip = parms[9]
+ T = parms[10]
+ off = parms[11]
g = triple_pnum(n=n,
F1=F1,
@@ -64,15 +64,15 @@ def CF_Gxyz_gauss_3D3D3DT(parms, tau):
comp1=threed,
comp2=threed,
comp3=threed,
- kwargs1={"tau":tau,
- "taudiff":taud1,
- "SP":SP},
- kwargs2={"tau":tau,
- "taudiff":taud2,
- "SP":SP},
- kwargs3={"tau":tau,
- "taudiff":taud3,
- "SP":SP},
+ kwargs1={"tau": tau,
+ "taudiff": taud1,
+ "SP": SP},
+ kwargs2={"tau": tau,
+ "taudiff": taud2,
+ "SP": SP},
+ kwargs3={"tau": tau,
+ "taudiff": taud3,
+ "SP": SP},
)
tr = trip(tau=tau, T=T, tautrip=tautrip)
@@ -104,84 +104,84 @@ def supplements(parms, countrate=None):
return Info
-parms = [ 25, # n
- 5, # taud1
- 1000, # taud2
- 11000, # taud3
- 0.5, # F1
- 0.01, # F2
- 5, # SP
- 1.0, # alpha21
- 1.0, # alpha31
- 0.001, # tautrip
- 0.01, # T
- 0.0 # offset
- ]
+parms = [25, # n
+ 5, # taud1
+ 1000, # taud2
+ 11000, # taud3
+ 0.5, # F1
+ 0.01, # F2
+ 5, # SP
+ 1.0, # alpha21
+ 1.0, # alpha31
+ 0.001, # tautrip
+ 0.01, # T
+ 0.0 # offset
+ ]
-## Boundaries
+# Boundaries
# strictly positive
boundaries = [[0, np.inf]]*len(parms)
# F
-boundaries[4] = [0,.9999999999999]
-boundaries[5] = [0,.9999999999999]
+boundaries[4] = [0, .9999999999999]
+boundaries[5] = [0, .9999999999999]
# T
-boundaries[10] = [0,.9999999999999]
+boundaries[10] = [0, .9999999999999]
boundaries[-1] = [-np.inf, np.inf]
model_setup(
- modelid=6081,
- name="Threefold 3D diffusion with triplet (confocal)",
- comp="T+3D+3D+3D",
- mtype="Confocal (Gaussian) and triplet",
- fctn=CF_Gxyz_gauss_3D3D3DT,
- par_labels=[
- u"n",
- u"Ļ"+u"\u2081"+" [ms]",
- u"Ļ"+u"\u2082"+" [ms]",
- u"Ļ"+u"\u2083"+" [ms]",
- u"F"+u"\u2081",
- u"F"+u"\u2082",
- u"SP",
- u"\u03b1\u2082\u2081",
- u"\u03b1\u2083\u2081",
- u"Ļ_trip [ms]",
- u"T",
- u"offset"
- ],
- par_values=parms,
- par_vary=[True, True, False, True,
- False, True, False, False,
- False, False, True, False],
- par_boundaries=boundaries,
- par_constraints=[[2, ">", 1], [3, ">", 2], [9, "<", 1], [5, 4, "<", "1"]],
- par_hr_labels=[
- u"n",
- u"Ļ"+u"\u2081"+" [ms]",
- u"Ļ"+u"\u2082"+" [ms]",
- u"Ļ"+u"\u2083"+" [ms]",
- u"F"+u"\u2081",
- u"F"+u"\u2082",
- u"SP",
- u"\u03b1\u2082\u2081",
- u"\u03b1\u2083\u2081",
- u"Ļ_trip [Āµs]",
- u"T",
- u"offset"
- ],
- par_hr_factors=[
- 1., # n
- 1., # taud1
- 1., # taud2
- 1., # taud3
- 1., # F1
- 1., # F2
- 1., # SP
- 1., # alpha21
- 1., # alpha31
- 1000., # tautrip [Āµs]
- 1., # T
- 1. # offset
- ],
- supplementary_method=supplements
- )
+ modelid=6081,
+ name="Threefold 3D diffusion with triplet (confocal)",
+ comp="T+3D+3D+3D",
+ mtype="Confocal (Gaussian) and triplet",
+ fctn=CF_Gxyz_gauss_3D3D3DT,
+ par_labels=[
+ u"n",
+ u"Ļ"+u"\u2081"+" [ms]",
+ u"Ļ"+u"\u2082"+" [ms]",
+ u"Ļ"+u"\u2083"+" [ms]",
+ u"F"+u"\u2081",
+ u"F"+u"\u2082",
+ u"SP",
+ u"\u03b1\u2082\u2081",
+ u"\u03b1\u2083\u2081",
+ u"Ļ_trip [ms]",
+ u"T",
+ u"offset"
+ ],
+ par_values=parms,
+ par_vary=[True, True, False, True,
+ False, True, False, False,
+ False, False, True, False],
+ par_boundaries=boundaries,
+ par_constraints=[[2, ">", 1], [3, ">", 2], [9, "<", 1], [5, 4, "<", "1"]],
+ par_hr_labels=[
+ u"n",
+ u"Ļ"+u"\u2081"+" [ms]",
+ u"Ļ"+u"\u2082"+" [ms]",
+ u"Ļ"+u"\u2083"+" [ms]",
+ u"F"+u"\u2081",
+ u"F"+u"\u2082",
+ u"SP",
+ u"\u03b1\u2082\u2081",
+ u"\u03b1\u2083\u2081",
+ u"Ļ_trip [Āµs]",
+ u"T",
+ u"offset"
+ ],
+ par_hr_factors=[
+ 1., # n
+ 1., # taud1
+ 1., # taud2
+ 1., # taud3
+ 1., # F1
+ 1., # F2
+ 1., # SP
+ 1., # alpha21
+ 1., # alpha31
+ 1000., # tautrip [Āµs]
+ 1., # T
+ 1. # offset
+ ],
+ supplementary_method=supplements
+)
diff --git a/pycorrfit/models/model_confocal_tt_2d.py b/pycorrfit/models/model_confocal_tt_2d.py
index 99ccfa0c..4580e0f5 100644
--- a/pycorrfit/models/model_confocal_tt_2d.py
+++ b/pycorrfit/models/model_confocal_tt_2d.py
@@ -31,13 +31,13 @@ def CF_Gxy_gauss_2DTT(parms, tau):
[6] offset
*tau* - lag time
"""
- n=parms[0]
- taud=parms[1]
- tautrip1=parms[2]
- T1=parms[3]
- tautrip2=parms[4]
- T2=parms[5]
- off=parms[6]
+ n = parms[0]
+ taud = parms[1]
+ tautrip1 = parms[2]
+ T1 = parms[3]
+ tautrip2 = parms[4]
+ T2 = parms[5]
+ off = parms[6]
g = twod(tau=tau, taudiff=taud)
@@ -61,61 +61,61 @@ def supplements(parms, countrate=None):
parms = [
- 4, # n
- .4, # taud
- 0.001, # tautrip1
- 0.01, # T1
- 0.002, # tautrip2
- 0.01, # T2
- 0.0 # offset
- ]
-
-## Boundaries
+ 4, # n
+ .4, # taud
+ 0.001, # tautrip1
+ 0.01, # T1
+ 0.002, # tautrip2
+ 0.01, # T2
+ 0.0 # offset
+]
+
+# Boundaries
# strictly positive
boundaries = [[0, np.inf]]*len(parms)
# T
-boundaries[3] = [0,.9999999999999]
-boundaries[5] = [0,.9999999999999]
+boundaries[3] = [0, .9999999999999]
+boundaries[5] = [0, .9999999999999]
# offset
boundaries[-1] = [-np.inf, np.inf]
model_setup(
- modelid=6003,
- name="2D diffusion with double triplet (confocal)",
- comp="T+T+2D",
- mtype="Confocal (Gaussian) with double triplet",
- fctn=CF_Gxy_gauss_2DTT,
- par_labels=[
- u"n",
- u"Ļ_diff [ms]",
- u"Ļ_tripā [ms]",
- u"Tā",
- u"Ļ_tripā [ms]",
- u"Tā",
- u"offset"
- ],
- par_values=parms,
- par_vary=[True, True, False, False, False, False, False],
- par_boundaries=boundaries,
- par_constraints=[[2, "<", 1], [4, ">", 2]],
- par_hr_labels=[
- u"n",
- u"Ļ_diff [ms]",
- u"Ļ_tripā [Āµs]",
- u"Tā",
- u"Ļ_tripā [Āµs]",
- u"Tā",
- u"offset"
- ],
- par_hr_factors=[
- 1., # n
- 1., # taudiff
- 1000., # tautrip1 [Āµs]
- 1., # T1
- 1000., # tautrip2 [Āµs]
- 1., # T2
- 1. # offset
- ],
- supplementary_method=supplements
- )
+ modelid=6003,
+ name="2D diffusion with double triplet (confocal)",
+ comp="T+T+2D",
+ mtype="Confocal (Gaussian) with double triplet",
+ fctn=CF_Gxy_gauss_2DTT,
+ par_labels=[
+ u"n",
+ u"Ļ_diff [ms]",
+ u"Ļ_tripā [ms]",
+ u"Tā",
+ u"Ļ_tripā [ms]",
+ u"Tā",
+ u"offset"
+ ],
+ par_values=parms,
+ par_vary=[True, True, False, False, False, False, False],
+ par_boundaries=boundaries,
+ par_constraints=[[2, "<", 1], [4, ">", 2]],
+ par_hr_labels=[
+ u"n",
+ u"Ļ_diff [ms]",
+ u"Ļ_tripā [Āµs]",
+ u"Tā",
+ u"Ļ_tripā [Āµs]",
+ u"Tā",
+ u"offset"
+ ],
+ par_hr_factors=[
+ 1., # n
+ 1., # taudiff
+ 1000., # tautrip1 [Āµs]
+ 1., # T1
+ 1000., # tautrip2 [Āµs]
+ 1., # T2
+ 1. # offset
+ ],
+ supplementary_method=supplements
+)
diff --git a/pycorrfit/models/model_confocal_tt_2d_2d.py b/pycorrfit/models/model_confocal_tt_2d_2d.py
index 4f68f204..b10e182a 100644
--- a/pycorrfit/models/model_confocal_tt_2d_2d.py
+++ b/pycorrfit/models/model_confocal_tt_2d_2d.py
@@ -40,26 +40,26 @@ def CF_Gxy_gauss_2D2DTT(parms, tau):
[9] offset
*tau* - lag time
"""
- n=parms[0]
- taud1=parms[1]
- taud2=parms[2]
- F=parms[3]
- alpha=parms[4]
- tautrip1=parms[5]
- T1=parms[6]
- tautrip2=parms[7]
- T2=parms[8]
- off=parms[9]
+ n = parms[0]
+ taud1 = parms[1]
+ taud2 = parms[2]
+ F = parms[3]
+ alpha = parms[4]
+ tautrip1 = parms[5]
+ T1 = parms[6]
+ tautrip2 = parms[7]
+ T2 = parms[8]
+ off = parms[9]
g = double_pnum(n=n,
F1=F,
alpha=alpha,
comp1=twod,
comp2=twod,
- kwargs1={"tau":tau,
- "taudiff":taud1},
- kwargs2={"tau":tau,
- "taudiff":taud2},
+ kwargs1={"tau": tau,
+ "taudiff": taud1},
+ kwargs2={"tau": tau,
+ "taudiff": taud2},
)
tr1 = trip(tau=tau, T=T1, tautrip=tautrip1)
@@ -91,74 +91,75 @@ def supplements(parms, countrate=None):
parms = [
- 25, # n
- 5, # taud1
- 1000, # taud2
- 0.5, # F
- 1.0, # alpha
- 0.001, # tautrip1
- 0.01, # T1
- 0.002, # tautrip2
- 0.01, # T2
- 0.0 # offset
- ]
-
-## Boundaries
+ 25, # n
+ 5, # taud1
+ 1000, # taud2
+ 0.5, # F
+ 1.0, # alpha
+ 0.001, # tautrip1
+ 0.01, # T1
+ 0.002, # tautrip2
+ 0.01, # T2
+ 0.0 # offset
+]
+
+# Boundaries
# strictly positive
boundaries = [[0, np.inf]]*len(parms)
# F
-boundaries[3] = [0,.9999999999999]
+boundaries[3] = [0, .9999999999999]
# T
-boundaries[6] = [0,.9999999999999]
-boundaries[8] = [0,.9999999999999]
+boundaries[6] = [0, .9999999999999]
+boundaries[8] = [0, .9999999999999]
boundaries[-1] = [-np.inf, np.inf]
model_setup(
- modelid=6044,
- name="Separate 2D diffusion with double triplet (confocal)",
- comp="T+T+2D+2D",
- mtype="Confocal (Gaussian) with double triplet",
- fctn=CF_Gxy_gauss_2D2DTT,
- par_labels=[
- u"n",
- u"Ļ"+u"\u2081"+" [ms]",
- u"Ļ"+u"\u2082"+" [ms]",
- u"F"+u"\u2081",
- u"\u03b1"+" (q"+u"\u2082"+"/q"+u"\u2081"+")",
- u"Ļ_tripā [ms]",
- u"Tā",
- u"Ļ_tripā [ms]",
- u"Tā",
- u"offset"
- ],
- par_values=parms,
- par_vary=[True, True, True, True, False, False, False, False, False, False],
- par_boundaries=boundaries,
- par_constraints=[[2, ">", 1], [5, "<", 1], [7, ">", 5]],
- par_hr_labels=[
- u"n",
- u"Ļā [ms]",
- u"Ļā [ms]",
- u"Fā",
- u"\u03b1"+u" (qā/qā)",
- u"Ļ_tripā [Āµs]",
- u"Tā",
- u"Ļ_tripā [Āµs]",
- u"Tā",
- u"offset"
- ],
- par_hr_factors=[
- 1., # n
- 1., # taud1
- 1., # taud2
- 1., # F
- 1., # alpha
- 1000., # tautrip1 [Āµs]
- 1., # T1
- 1000., # tautrip2 [Āµs]
- 1., # T2
- 1. # offset
- ],
- supplementary_method=supplements
- )
+ modelid=6044,
+ name="Separate 2D diffusion with double triplet (confocal)",
+ comp="T+T+2D+2D",
+ mtype="Confocal (Gaussian) with double triplet",
+ fctn=CF_Gxy_gauss_2D2DTT,
+ par_labels=[
+ u"n",
+ u"Ļ"+u"\u2081"+" [ms]",
+ u"Ļ"+u"\u2082"+" [ms]",
+ u"F"+u"\u2081",
+ u"\u03b1"+" (q"+u"\u2082"+"/q"+u"\u2081"+")",
+ u"Ļ_tripā [ms]",
+ u"Tā",
+ u"Ļ_tripā [ms]",
+ u"Tā",
+ u"offset"
+ ],
+ par_values=parms,
+ par_vary=[True, True, True, True, False,
+ False, False, False, False, False],
+ par_boundaries=boundaries,
+ par_constraints=[[2, ">", 1], [5, "<", 1], [7, ">", 5]],
+ par_hr_labels=[
+ u"n",
+ u"Ļā [ms]",
+ u"Ļā [ms]",
+ u"Fā",
+ u"\u03b1"+u" (qā/qā)",
+ u"Ļ_tripā [Āµs]",
+ u"Tā",
+ u"Ļ_tripā [Āµs]",
+ u"Tā",
+ u"offset"
+ ],
+ par_hr_factors=[
+ 1., # n
+ 1., # taud1
+ 1., # taud2
+ 1., # F
+ 1., # alpha
+ 1000., # tautrip1 [Āµs]
+ 1., # T1
+ 1000., # tautrip2 [Āµs]
+ 1., # T2
+ 1. # offset
+ ],
+ supplementary_method=supplements
+)
diff --git a/pycorrfit/models/model_confocal_tt_3d.py b/pycorrfit/models/model_confocal_tt_3d.py
index 3b837e58..81e79095 100644
--- a/pycorrfit/models/model_confocal_tt_3d.py
+++ b/pycorrfit/models/model_confocal_tt_3d.py
@@ -34,17 +34,17 @@ def CF_Gxyz_gauss_3DTT(parms, tau):
[7] offset
*tau* - lag time
"""
- n=parms[0]
- taudiff=parms[1]
- SP=parms[2]
- tautrip1=parms[3]
- T1=parms[4]
- tautrip2=parms[5]
- T2=parms[6]
- off=parms[7]
+ n = parms[0]
+ taudiff = parms[1]
+ SP = parms[2]
+ tautrip1 = parms[3]
+ T1 = parms[4]
+ tautrip2 = parms[5]
+ T2 = parms[6]
+ off = parms[7]
g = threed(tau=tau, taudiff=taudiff, SP=SP)
-
+
tr1 = trip(tau=tau, T=T1, tautrip=tautrip1)
tr2 = trip(tau=tau, T=T2, tautrip=tautrip2)
@@ -65,65 +65,65 @@ def supplements(parms, countrate=None):
parms = [
- 4, # n
- .4, # taud1
- 5, # SP
- 0.001, # tautrip1
- 0.01, # T1
- 0.002, # tautrip2
- 0.01, # T2
- 0.0 # offset
- ]
-
-## Boundaries
+ 4, # n
+ .4, # taud1
+ 5, # SP
+ 0.001, # tautrip1
+ 0.01, # T1
+ 0.002, # tautrip2
+ 0.01, # T2
+ 0.0 # offset
+]
+
+# Boundaries
# strictly positive
boundaries = [[0, np.inf]]*len(parms)
# T
-boundaries[4] = [0,.9999999999999]
-boundaries[6] = [0,.9999999999999]
+boundaries[4] = [0, .9999999999999]
+boundaries[6] = [0, .9999999999999]
# offset
boundaries[-1] = [-np.inf, np.inf]
model_setup(
- modelid=6009,
- name="3D diffusion with double triplet (confocal)",
- comp="T+T+3D",
- mtype="Confocal (Gaussian) with double triplet",
- fctn=CF_Gxyz_gauss_3DTT,
- par_labels=[
- u"n",
- u"Ļ_diff [ms]",
- u"SP",
- u"Ļ_tripā [ms]",
- u"Tā",
- u"Ļ_tripā [ms]",
- u"Tā",
- u"offset"
- ],
- par_values=parms,
- par_vary=[True, True, False, False, False, False, False, False],
- par_boundaries=boundaries,
- par_constraints=[[3, "<", 1], [5, ">", 3]],
- par_hr_labels=[
- u"n",
- u"Ļ_diff [ms]",
- u"SP",
- u"Ļ_tripā [Āµs]",
- u"Tā",
- u"Ļ_tripā [Āµs]",
- u"Tā",
- u"offset"
- ],
- par_hr_factors=[
- 1., # n
- 1., # taudiff
- 1., # SP
- 1000., # tautrip1 [Āµs]
- 1., # T1
- 1000., # tautrip2 [Āµs]
- 1., # T2
- 1. # offset
- ],
- supplementary_method=supplements
- )
+ modelid=6009,
+ name="3D diffusion with double triplet (confocal)",
+ comp="T+T+3D",
+ mtype="Confocal (Gaussian) with double triplet",
+ fctn=CF_Gxyz_gauss_3DTT,
+ par_labels=[
+ u"n",
+ u"Ļ_diff [ms]",
+ u"SP",
+ u"Ļ_tripā [ms]",
+ u"Tā",
+ u"Ļ_tripā [ms]",
+ u"Tā",
+ u"offset"
+ ],
+ par_values=parms,
+ par_vary=[True, True, False, False, False, False, False, False],
+ par_boundaries=boundaries,
+ par_constraints=[[3, "<", 1], [5, ">", 3]],
+ par_hr_labels=[
+ u"n",
+ u"Ļ_diff [ms]",
+ u"SP",
+ u"Ļ_tripā [Āµs]",
+ u"Tā",
+ u"Ļ_tripā [Āµs]",
+ u"Tā",
+ u"offset"
+ ],
+ par_hr_factors=[
+ 1., # n
+ 1., # taudiff
+ 1., # SP
+ 1000., # tautrip1 [Āµs]
+ 1., # T1
+ 1000., # tautrip2 [Āµs]
+ 1., # T2
+ 1. # offset
+ ],
+ supplementary_method=supplements
+)
diff --git a/pycorrfit/models/model_confocal_tt_3d_2d.py b/pycorrfit/models/model_confocal_tt_3d_2d.py
index 36835904..5120ef18 100644
--- a/pycorrfit/models/model_confocal_tt_3d_2d.py
+++ b/pycorrfit/models/model_confocal_tt_3d_2d.py
@@ -42,28 +42,28 @@ def CF_Gxyz_gauss_3D2DTT(parms, tau):
[10] offset
*tau* - lag time
"""
- n=parms[0]
- taud2D=parms[1]
- taud3D=parms[2]
- F=parms[3]
- SP=parms[4]
- alpha=parms[5]
- tautrip1=parms[6]
- T1=parms[7]
- tautrip2=parms[8]
- T2=parms[9]
- off=parms[10]
+ n = parms[0]
+ taud2D = parms[1]
+ taud3D = parms[2]
+ F = parms[3]
+ SP = parms[4]
+ alpha = parms[5]
+ tautrip1 = parms[6]
+ T1 = parms[7]
+ tautrip2 = parms[8]
+ T2 = parms[9]
+ off = parms[10]
g = double_pnum(n=n,
F1=1-F,
alpha=alpha,
comp1=twod,
comp2=threed,
- kwargs1={"tau":tau,
- "taudiff":taud2D},
- kwargs2={"tau":tau,
- "taudiff":taud3D,
- "SP":SP},
+ kwargs1={"tau": tau,
+ "taudiff": taud2D},
+ kwargs2={"tau": tau,
+ "taudiff": taud3D,
+ "SP": SP},
)
tr1 = trip(tau=tau, T=T1, tautrip=tautrip1)
@@ -93,82 +93,83 @@ def supplements(parms, countrate=None):
# CPP
cpp = countrate/n
Info.append([u"cpp [kHz]", cpp])
- return Info
-
+ return Info
+
parms = [
- 25, # n
- 240, # taud2D
- 0.1, # taud3D
- 0.5, # F3D
- 5, # SP
- 1.0, # alpha
- 0.001, # tautrip1
- 0.01, # T1
- 0.002, # tautrip2
- 0.01, # T2
- 0.0 # offset
- ]
-
-## Boundaries
+ 25, # n
+ 240, # taud2D
+ 0.1, # taud3D
+ 0.5, # F3D
+ 5, # SP
+ 1.0, # alpha
+ 0.001, # tautrip1
+ 0.01, # T1
+ 0.002, # tautrip2
+ 0.01, # T2
+ 0.0 # offset
+]
+
+# Boundaries
# strictly positive
boundaries = [[0, np.inf]]*len(parms)
# F
-boundaries[3] = [0,.9999999999999]
+boundaries[3] = [0, .9999999999999]
# T
-boundaries[7] = [0,.9999999999999]
-boundaries[9] = [0,.9999999999999]
+boundaries[7] = [0, .9999999999999]
+boundaries[9] = [0, .9999999999999]
boundaries[-1] = [-np.inf, np.inf]
model_setup(
- modelid=6045,
- name="Separate 3D and 2D diffusion with double triplet (confocal)",
- comp="T+T+3D+2D",
- mtype="Confocal (Gaussian) with double triplet",
- fctn=CF_Gxyz_gauss_3D2DTT,
- par_labels=[
- u"n",
- u"Ļ_2D [ms]",
- u"Ļ_3D [ms]",
- u"F_3D",
- u"SP",
- u"\u03b1"+" (q_3D/q_2D)",
- u"Ļ_tripā [ms]",
- u"Tā",
- u"Ļ_tripā [ms]",
- u"Tā",
- u"offset"
- ],
- par_values=parms,
- par_vary=[True, True, True, True, False, False, False, False, False, False, False],
- par_boundaries=boundaries,
- par_constraints=[[2, "<", 1], [6, "<", 2], [8, ">", 6]],
- par_hr_labels=[
- u"n",
- u"Ļ_2D [ms]",
- u"Ļ_3D [ms]",
- u"F_3D",
- u"SP",
- u"\u03b1"+" (q_3D/q_2D)",
- u"Ļ_tripā [Āµs]",
- u"Tā",
- u"Ļ_tripā [Āµs]",
- u"Tā",
- u"offset"
- ],
- par_hr_factors=[
- 1., # n
- 1., # "Ļ_2D [ms]",
- 1., # "Ļ_3D [ms]",
- 1., # "F_3D",
- 1., # "SP",
- 1., # u"\u03b1"+" (q_3D/q_2D)",
- 1000., # tautrip1 [Āµs]
- 1., # T1
- 1000., # tautrip2 [Āµs]
- 1., # T2
- 1. # offset
- ],
- supplementary_method=supplements
- )
+ modelid=6045,
+ name="Separate 3D and 2D diffusion with double triplet (confocal)",
+ comp="T+T+3D+2D",
+ mtype="Confocal (Gaussian) with double triplet",
+ fctn=CF_Gxyz_gauss_3D2DTT,
+ par_labels=[
+ u"n",
+ u"Ļ_2D [ms]",
+ u"Ļ_3D [ms]",
+ u"F_3D",
+ u"SP",
+ u"\u03b1"+" (q_3D/q_2D)",
+ u"Ļ_tripā [ms]",
+ u"Tā",
+ u"Ļ_tripā [ms]",
+ u"Tā",
+ u"offset"
+ ],
+ par_values=parms,
+ par_vary=[True, True, True, True, False,
+ False, False, False, False, False, False],
+ par_boundaries=boundaries,
+ par_constraints=[[2, "<", 1], [6, "<", 2], [8, ">", 6]],
+ par_hr_labels=[
+ u"n",
+ u"Ļ_2D [ms]",
+ u"Ļ_3D [ms]",
+ u"F_3D",
+ u"SP",
+ u"\u03b1"+" (q_3D/q_2D)",
+ u"Ļ_tripā [Āµs]",
+ u"Tā",
+ u"Ļ_tripā [Āµs]",
+ u"Tā",
+ u"offset"
+ ],
+ par_hr_factors=[
+ 1., # n
+ 1., # "Ļ_2D [ms]",
+ 1., # "Ļ_3D [ms]",
+ 1., # "F_3D",
+ 1., # "SP",
+ 1., # u"\u03b1"+" (q_3D/q_2D)",
+ 1000., # tautrip1 [Āµs]
+ 1., # T1
+ 1000., # tautrip2 [Āµs]
+ 1., # T2
+ 1. # offset
+ ],
+ supplementary_method=supplements
+)
diff --git a/pycorrfit/models/model_confocal_tt_3d_3d.py b/pycorrfit/models/model_confocal_tt_3d_3d.py
index 0b89b1d3..3a51c71f 100644
--- a/pycorrfit/models/model_confocal_tt_3d_3d.py
+++ b/pycorrfit/models/model_confocal_tt_3d_3d.py
@@ -42,29 +42,29 @@ def CF_Gxyz_gauss_3D3DTT(parms, tau):
[10] offset
*tau* - lag time
"""
- n=parms[0]
- taud1=parms[1]
- taud2=parms[2]
- F=parms[3]
- SP=parms[4]
- alpha=parms[5]
- tautrip1=parms[6]
- T1=parms[7]
- tautrip2=parms[8]
- T2=parms[9]
- off=parms[10]
+ n = parms[0]
+ taud1 = parms[1]
+ taud2 = parms[2]
+ F = parms[3]
+ SP = parms[4]
+ alpha = parms[5]
+ tautrip1 = parms[6]
+ T1 = parms[7]
+ tautrip2 = parms[8]
+ T2 = parms[9]
+ off = parms[10]
g = double_pnum(n=n,
F1=F,
alpha=alpha,
comp1=threed,
comp2=threed,
- kwargs1={"tau":tau,
- "taudiff":taud1,
- "SP":SP},
- kwargs2={"tau":tau,
- "taudiff":taud2,
- "SP":SP},
+ kwargs1={"tau": tau,
+ "taudiff": taud1,
+ "SP": SP},
+ kwargs2={"tau": tau,
+ "taudiff": taud2,
+ "SP": SP},
)
tr1 = trip(tau=tau, T=T1, tautrip=tautrip1)
@@ -96,78 +96,79 @@ def supplements(parms, countrate=None):
parms = [
- 25, # n
- 5, # taud1
- 1000, # taud2
- 0.5, # F
- 5, # SP
- 1.0, # alpha
- 0.001, # tautrip1
- 0.01, # T1
- 0.002, # tautrip2
- 0.01, # T2
- 0.0 # offset
- ]
-
-## Boundaries
+ 25, # n
+ 5, # taud1
+ 1000, # taud2
+ 0.5, # F
+ 5, # SP
+ 1.0, # alpha
+ 0.001, # tautrip1
+ 0.01, # T1
+ 0.002, # tautrip2
+ 0.01, # T2
+ 0.0 # offset
+]
+
+# Boundaries
# strictly positive
boundaries = [[0, np.inf]]*len(parms)
# F
-boundaries[3] = [0,.9999999999999]
+boundaries[3] = [0, .9999999999999]
# T
-boundaries[7] = [0,.9999999999999]
-boundaries[9] = [0,.9999999999999]
+boundaries[7] = [0, .9999999999999]
+boundaries[9] = [0, .9999999999999]
boundaries[-1] = [-np.inf, np.inf]
model_setup(
- modelid=6043,
- name="Separate 3D diffusion with double triplet (confocal)",
- comp="T+T+3D+3D",
- mtype="Confocal (Gaussian) with double triplet",
- fctn=CF_Gxyz_gauss_3D3DTT,
- par_labels=[
- u"n",
- u"Ļ"+u"\u2081"+" [ms]",
- u"Ļ"+u"\u2082"+" [ms]",
- u"F"+u"\u2081",
- u"SP",
- u"\u03b1"+" (q"+u"\u2082"+"/q"+u"\u2081"+")",
- u"Ļ_tripā [ms]",
- u"Tā",
- u"Ļ_tripā [ms]",
- u"Tā",
- u"offset"
- ],
- par_values=parms,
- par_vary=[True, True, True, True, False, False, False, False, False, False, False],
- par_boundaries=boundaries,
- par_constraints=[[2, ">", 1], [6, "<", 1], [8, ">", 6]],
- par_hr_labels=[
- u"n",
- u"Ļā [ms]",
- u"Ļā [ms]",
- u"Fā",
- u"SP",
- u"\u03b1"+u" (qā/qā)",
- u"Ļ_tripā [Āµs]",
- u"Tā",
- u"Ļ_tripā [Āµs]",
- u"Tā",
- u"offset"
- ],
- par_hr_factors=[
- 1., # n
- 1., # taud1
- 1., # taud2
- 1., # F
- 1., # SP
- 1., # alpha
- 1000., # tautrip1 [Āµs]
- 1., # T1
- 1000., # tautrip2 [Āµs]
- 1., # T2
- 1. # offset
- ],
- supplementary_method=supplements
- )
+ modelid=6043,
+ name="Separate 3D diffusion with double triplet (confocal)",
+ comp="T+T+3D+3D",
+ mtype="Confocal (Gaussian) with double triplet",
+ fctn=CF_Gxyz_gauss_3D3DTT,
+ par_labels=[
+ u"n",
+ u"Ļ"+u"\u2081"+" [ms]",
+ u"Ļ"+u"\u2082"+" [ms]",
+ u"F"+u"\u2081",
+ u"SP",
+ u"\u03b1"+" (q"+u"\u2082"+"/q"+u"\u2081"+")",
+ u"Ļ_tripā [ms]",
+ u"Tā",
+ u"Ļ_tripā [ms]",
+ u"Tā",
+ u"offset"
+ ],
+ par_values=parms,
+ par_vary=[True, True, True, True, False,
+ False, False, False, False, False, False],
+ par_boundaries=boundaries,
+ par_constraints=[[2, ">", 1], [6, "<", 1], [8, ">", 6]],
+ par_hr_labels=[
+ u"n",
+ u"Ļā [ms]",
+ u"Ļā [ms]",
+ u"Fā",
+ u"SP",
+ u"\u03b1"+u" (qā/qā)",
+ u"Ļ_tripā [Āµs]",
+ u"Tā",
+ u"Ļ_tripā [Āµs]",
+ u"Tā",
+ u"offset"
+ ],
+ par_hr_factors=[
+ 1., # n
+ 1., # taud1
+ 1., # taud2
+ 1., # F
+ 1., # SP
+ 1., # alpha
+ 1000., # tautrip1 [Āµs]
+ 1., # T1
+ 1000., # tautrip2 [Āµs]
+ 1., # T2
+ 1. # offset
+ ],
+ supplementary_method=supplements
+)
diff --git a/pycorrfit/openfile.py b/pycorrfit/openfile.py
index a7fea6d7..e351559a 100644
--- a/pycorrfit/openfile.py
+++ b/pycorrfit/openfile.py
@@ -80,7 +80,7 @@ def LoadSessionData(sessionfile, parameters_only=False):
# As of version 0.7.4 we save chi2 and shared pages -global fit
Infodict["Supplements"][idp[0]]["Chi sq"] = idp[2]
Infodict["Supplements"][idp[0]]["Global Share"] = idp[3]
- ## Preferences: Reserved for a future version of PyCorrFit :)
+ # Preferences: Reserved for a future version of PyCorrFit :)
prefname = "Preferences.yaml"
try:
Arc.getinfo(prefname)
@@ -102,19 +102,21 @@ def LoadSessionData(sessionfile, parameters_only=False):
# No more functions to import
key = 8000
else:
- funcfile = Arc.open(funcfilename)
+ funcfile = Arc.open(funcfilename)
Infodict["External Functions"][key] = funcfile.read()
funcfile.close()
- key=key+1
+ key = key+1
# Get the correlation arrays
Infodict["Correlations"] = dict()
for i in np.arange(len(Infodict["Parameters"])):
# The *number* is used to identify the correct file
- number = str(Infodict["Parameters"][i][0]).strip().strip(":").strip("#")
+ number = str(Infodict["Parameters"][i][0]
+ ).strip().strip(":").strip("#")
pageid = int(number)
expfilename = "data"+number+".csv"
expfile = Arc.open(expfilename, 'r')
- readdata = csv.reader(io.StringIO(expfile.read().decode()), delimiter=',')
+ readdata = csv.reader(io.StringIO(
+ expfile.read().decode()), delimiter=',')
dataexp = list()
tau = list()
if str(readdata.__next__()[0]) == "# tau only":
@@ -130,7 +132,7 @@ def LoadSessionData(sessionfile, parameters_only=False):
if (str(row[0])[0:1] != '#'):
dataexp.append((float(row[0]), float(row[1])))
dataexp = np.array(dataexp)
- tau = dataexp[:,0]
+ tau = dataexp[:, 0]
Infodict["Correlations"][pageid] = [tau, dataexp]
del readdata
expfile.close()
@@ -138,7 +140,8 @@ def LoadSessionData(sessionfile, parameters_only=False):
Infodict["Traces"] = dict()
for i in np.arange(len(Infodict["Parameters"])):
# The *number* is used to identify the correct file
- number = str(Infodict["Parameters"][i][0]).strip().strip(":").strip("#")
+ number = str(Infodict["Parameters"][i][0]
+ ).strip().strip(":").strip("#")
pageid = int(number)
# Find out, if we have a cross correlation data type
IsCross = False
@@ -152,7 +155,7 @@ def LoadSessionData(sessionfile, parameters_only=False):
else:
# Cross correlation uses two traces
tracefilenames = ["trace"+number+"A.csv",
- "trace"+number+"B.csv" ]
+ "trace"+number+"B.csv"]
thistrace = list()
for tracefilename in tracefilenames:
try:
@@ -161,7 +164,8 @@ def LoadSessionData(sessionfile, parameters_only=False):
pass
else:
tracefile = Arc.open(tracefilename, 'r')
- traceread = csv.reader(io.StringIO(tracefile.read().decode()), delimiter=',')
+ traceread = csv.reader(io.StringIO(
+ tracefile.read().decode()), delimiter=',')
singletrace = list()
for row in traceread:
# Exclude commentaries
@@ -188,7 +192,8 @@ def LoadSessionData(sessionfile, parameters_only=False):
commentfile = Arc.open(commentfilename, 'r')
Infodict["Comments"] = dict()
for i in np.arange(len(Infodict["Parameters"])):
- number = str(Infodict["Parameters"][i][0]).strip().strip(":").strip("#")
+ number = str(Infodict["Parameters"][i][0]
+ ).strip().strip(":").strip("#")
pageid = int(number)
# Strip line ending characters for all the Pages.
Infodict["Comments"][pageid] = commentfile.readline().strip()
@@ -209,19 +214,22 @@ def LoadSessionData(sessionfile, parameters_only=False):
# Open the file
Infodict["Backgrounds"] = list()
bgfile = Arc.open(bgfilename, 'r')
- bgread = csv.reader(io.StringIO(bgfile.read().decode()), delimiter='\t')
+ bgread = csv.reader(io.StringIO(
+ bgfile.read().decode()), delimiter='\t')
i = 0
for bgrow in bgread:
bgtracefilename = "bg_trace"+str(i)+".csv"
bgtracefile = Arc.open(bgtracefilename, 'r')
- bgtraceread = csv.reader(io.StringIO(bgtracefile.read().decode()), delimiter=',')
+ bgtraceread = csv.reader(io.StringIO(
+ bgtracefile.read().decode()), delimiter=',')
bgtrace = list()
for row in bgtraceread:
# Exclude commentaries
if (str(row[0])[0:1] != '#'):
bgtrace.append((np.float(row[0]), np.float(row[1])))
bgtrace = np.array(bgtrace)
- newbackground = Trace(trace=bgtrace, name=str(bgrow[1]), countrate=np.float(bgrow[0]))
+ newbackground = Trace(trace=bgtrace, name=str(
+ bgrow[1]), countrate=np.float(bgrow[0]))
Infodict["Backgrounds"].append(newbackground)
i = i + 1
bgfile.close()
@@ -255,7 +263,7 @@ def LoadSessionData(sessionfile, parameters_only=False):
Wdata.append(np.float(row[0]))
Weightsdict[pageid][Nkey] = np.array(Wdata)
Infodict["External Weights"] = Weightsdict
- ## Preferences
+ # Preferences
preferencesname = "preferences.cfg"
try:
# Raises KeyError, if file is not present:
@@ -274,7 +282,7 @@ def LoadSessionData(sessionfile, parameters_only=False):
key = key.strip()
value = value.strip()
if value.count(","):
- value = [ v.strip() for v in value.split(",")]
+ value = [v.strip() for v in value.split(",")]
prefdict[key] = value
Infodict["Preferences"] = prefdict
Arc.close()
@@ -318,7 +326,7 @@ def SaveSessionData(sessionfile, Infodict):
parmsfilename = "Parameters.yaml"
# Parameters have to be floats in lists
# in order for yaml.safe_load to work.
- Parms = Infodict["Parameters"]
+ Parms = Infodict["Parameters"]
ParmsKeys = list(Parms.keys())
ParmsKeys.sort()
Parmlist = list()
@@ -326,11 +334,11 @@ def SaveSessionData(sessionfile, Infodict):
# Make sure we do not accidently save arrays.
# This would not work correctly with yaml.
# Parameters
- Parms[idparm][2] = np.array(Parms[idparm][2],dtype="float").tolist()
+ Parms[idparm][2] = np.array(Parms[idparm][2], dtype="float").tolist()
# Parameter varied
- Parms[idparm][3] = np.array(Parms[idparm][3],dtype="bool").tolist()
+ Parms[idparm][3] = np.array(Parms[idparm][3], dtype="bool").tolist()
# Channel selection
- Parms[idparm][4] = np.array(Parms[idparm][4],dtype="int").tolist()
+ Parms[idparm][4] = np.array(Parms[idparm][4], dtype="int").tolist()
# Background selection
for ii in range(len(Parms[idparm][6])):
if Parms[idparm][6][ii] is not None:
@@ -339,7 +347,7 @@ def SaveSessionData(sessionfile, Infodict):
if Parms[idparm][8] is not None:
Parms[idparm][8] = int(Parms[idparm][8])
# Fit parameter range
- Parms[idparm][9] = np.array(Parms[idparm][9],dtype="float").tolist()
+ Parms[idparm][9] = np.array(Parms[idparm][9], dtype="float").tolist()
Parmlist.append(Parms[idparm])
try:
@@ -363,7 +371,7 @@ def SaveSessionData(sessionfile, Infodict):
os.remove(os.path.join(tempdir, parmsfilename))
# Supplementary data (errors of fit)
errsfilename = "Supplements.yaml"
- Sups = Infodict["Supplements"]
+ Sups = Infodict["Supplements"]
SupKeys = list(Sups.keys())
SupKeys.sort()
Suplist = list()
@@ -379,7 +387,7 @@ def SaveSessionData(sessionfile, Infodict):
# Save external functions
for key in Infodict["External Functions"].keys():
funcfilename = "model_"+str(key)+".txt"
- funcfile = codecs.open(funcfilename, 'w', encoding="utf-8")
+ funcfile = codecs.open(funcfilename, 'w', encoding="utf-8")
funcfile.write(Infodict["External Functions"][key])
funcfile.close()
Arc.write(funcfilename)
@@ -402,9 +410,9 @@ def SaveSessionData(sessionfile, Infodict):
# Otherwise, the experimental data will not be saved entirely,
# if it has been cropped. Because tau might be smaller, than
# exp[:,0] --> tau = exp[startcrop:endcrop,0]
- for j in np.arange(len(exp[:,0])):
- dataWriter.writerow(["%.20e" % exp[j,0],
- "%.20e" % exp[j,1]])
+ for j in np.arange(len(exp[:, 0])):
+ dataWriter.writerow(["%.20e" % exp[j, 0],
+ "%.20e" % exp[j, 1]])
else:
# Only write tau
dataWriter.writerow(['# tau'+' only'])
@@ -423,12 +431,12 @@ def SaveSessionData(sessionfile, Infodict):
if Infodict["Traces"][pageid] is not None and len(Infodict["Traces"][pageid]) != 0:
if Parms[pageid][7] is True:
# We have cross correlation: save two traces
- ## A
+ # A
tracefilenamea = "trace"+number+"A.csv"
tracefile = open(tracefilenamea, 'w')
traceWriter = csv.writer(tracefile, delimiter=',')
- time = Infodict["Traces"][pageid][0][:,0]
- rate = Infodict["Traces"][pageid][0][:,1]
+ time = Infodict["Traces"][pageid][0][:, 0]
+ rate = Infodict["Traces"][pageid][0][:, 1]
# Names of Columns
traceWriter.writerow(['# time', 'count rate'])
# Actual Data
@@ -439,7 +447,7 @@ def SaveSessionData(sessionfile, Infodict):
# Add to archive
Arc.write(tracefilenamea)
os.remove(os.path.join(tempdir, tracefilenamea))
- ## B (only if it exists...)
+ # B (only if it exists...)
try:
_ = Infodict["Traces"][pageid][1]
except IndexError:
@@ -448,8 +456,8 @@ def SaveSessionData(sessionfile, Infodict):
tracefilenameb = "trace"+number+"B.csv"
tracefile = open(tracefilenameb, 'w')
traceWriter = csv.writer(tracefile, delimiter=',')
- time = Infodict["Traces"][pageid][1][:,0]
- rate = Infodict["Traces"][pageid][1][:,1]
+ time = Infodict["Traces"][pageid][1][:, 0]
+ rate = Infodict["Traces"][pageid][1][:, 1]
# Names of Columns
traceWriter.writerow(['# time', 'count rate'])
# Actual Data
@@ -465,8 +473,8 @@ def SaveSessionData(sessionfile, Infodict):
tracefilename = "trace"+number+".csv"
tracefile = open(tracefilename, 'w')
traceWriter = csv.writer(tracefile, delimiter=',')
- time = Infodict["Traces"][pageid][0][:,0]
- rate = Infodict["Traces"][pageid][0][:,1]
+ time = Infodict["Traces"][pageid][0][:, 0]
+ rate = Infodict["Traces"][pageid][0][:, 1]
# Names of Columns
traceWriter.writerow(['# time', 'count rate'])
# Actual Data
@@ -494,7 +502,7 @@ def SaveSessionData(sessionfile, Infodict):
commentfile.close()
Arc.write(commentfilename)
os.remove(os.path.join(tempdir, commentfilename))
- ## Save Background information:
+ # Save Background information:
Background = Infodict["Backgrounds"]
if len(Background) > 0:
# We do not use a comma separated, but a tab separated file,
@@ -503,15 +511,16 @@ def SaveSessionData(sessionfile, Infodict):
bgfile = open(bgfilename, 'w')
bgwriter = csv.writer(bgfile, delimiter='\t')
for i in np.arange(len(Background)):
- bgwriter.writerow([str(Background[i].countrate), Background[i].name])
+ bgwriter.writerow(
+ [str(Background[i].countrate), Background[i].name])
# Traces
bgtracefilename = "bg_trace"+str(i)+".csv"
bgtracefile = open(bgtracefilename, 'w')
bgtraceWriter = csv.writer(bgtracefile, delimiter=',')
bgtraceWriter.writerow(['# time', 'count rate'])
# Actual Data
- time = Background[i][:,0]
- rate = Background[i][:,1]
+ time = Background[i][:, 0]
+ rate = Background[i][:, 1]
for j in np.arange(len(time)):
bgtraceWriter.writerow(["%.20e" % time[j],
"%.20e" % rate[j]])
@@ -522,7 +531,7 @@ def SaveSessionData(sessionfile, Infodict):
bgfile.close()
Arc.write(bgfilename)
os.remove(os.path.join(tempdir, bgfilename))
- ## Save External Weights information
+ # Save External Weights information
WeightedPageID = list(Infodict["External Weights"].keys())
WeightedPageID.sort()
WeightFilename = "externalweights.txt"
@@ -537,7 +546,7 @@ def SaveSessionData(sessionfile, Infodict):
for Nkey in NestWeights:
WeightWriter.writerow([number, str(Nkey).strip()])
# Add data to a File
- WeightDataFilename = "externalweights_data"+number+\
+ WeightDataFilename = "externalweights_data"+number +\
"_"+str(Nkey).strip()+".csv"
WeightDataFile = open(WeightDataFilename, 'w')
WeightDataWriter = csv.writer(WeightDataFile)
@@ -550,7 +559,7 @@ def SaveSessionData(sessionfile, Infodict):
WeightFile.close()
Arc.write(WeightFilename)
os.remove(os.path.join(tempdir, WeightFilename))
- ## Preferences
+ # Preferences
preferencesname = "preferences.cfg"
with codecs.open(preferencesname, 'w', encoding="utf-8") as fd:
for key in Infodict["Preferences"]:
@@ -562,7 +571,7 @@ def SaveSessionData(sessionfile, Infodict):
fd.write("{} = {}\n".format(key, value))
Arc.write(preferencesname)
os.remove(os.path.join(tempdir, preferencesname))
- ## Readme
+ # Readme
rmfilename = "Readme.txt"
rmfile = codecs.open(rmfilename, 'w', encoding="utf-8")
rmfile.write(ReadmeSession)
@@ -573,7 +582,7 @@ def SaveSessionData(sessionfile, Infodict):
Arc.close()
# Move archive to destination directory
shutil.move(os.path.join(tempdir, filename),
- os.path.join(dirname, filename) )
+ os.path.join(dirname, filename))
# Go to destination directory
os.chdir(returnWD)
os.rmdir(tempdir)
@@ -605,7 +614,7 @@ def ExportCorrelation(exportfile, correlation, page_info, savetrace=True):
the total particle number `n`.
"""
openedfile = codecs.open(exportfile, 'w', encoding='utf-8')
- ## First, some doc text
+ # First, some doc text
openedfile.write(ReadmeCSV.replace('\n', '\r\n'))
# The info
for line in page_info.splitlines():
@@ -614,13 +623,13 @@ def ExportCorrelation(exportfile, correlation, page_info, savetrace=True):
# Get all the data we need from the Page
# Modeled data
corr = correlation
- mod = corr.modeled_plot[:,1]
+ mod = corr.modeled_plot[:, 1]
if corr.correlation is not None:
# Experimental data
- tau = corr.correlation_plot[:,0]
- exp = corr.correlation_plot[:,1]
- res = corr.residuals_plot[:,0]
+ tau = corr.correlation_plot[:, 0]
+ exp = corr.correlation_plot[:, 1]
+ res = corr.residuals_plot[:, 0]
# Plotting! Because we only export plotted area.
if corr.is_weighted_fit:
@@ -634,9 +643,9 @@ def ExportCorrelation(exportfile, correlation, page_info, savetrace=True):
pass
elif len(weight) != len(exp):
- text = "Weights have not been calculated for the "+\
- "area you want to export. Pressing 'Fit' "+\
- "again should solve this issue. Weights will "+\
+ text = "Weights have not been calculated for the " +\
+ "area you want to export. Pressing 'Fit' " +\
+ "again should solve this issue. Weights will " +\
"not be saved."
warnings.warn(text)
weight = None
@@ -651,22 +660,22 @@ def ExportCorrelation(exportfile, correlation, page_info, savetrace=True):
# PyCorrFit thinks in [ms], but we will save as [s]
timefactor = 0.001
tau = [timefactor * t for t in tau]
- ## Now we want to write all that data into the file
+ # Now we want to write all that data into the file
# This is for csv writing:
- ## Correlation curve
+ # Correlation curve
dataWriter = csv.writer(openedfile, delimiter='\t')
if exp is not None:
- header = '# Lag time [s]'+"\t"+ \
- 'Experimental correlation'+"\t"+ \
- 'Fitted correlation'+ "\t"+ \
+ header = '# Lag time [s]'+"\t" + \
+ 'Experimental correlation'+"\t" + \
+ 'Fitted correlation' + "\t" + \
'Residuals'+"\r\n"
data = [tau, exp, mod, res]
if corr.is_weighted_fit and weight is not None:
header = "{} \t Weights [{}] \r\n".format(
- header.strip(), weightname)
+ header.strip(), weightname)
data.append(weight)
else:
- header = '# Lag time [s]'+"\t"+ \
+ header = '# Lag time [s]'+"\t" + \
'Correlation function'+"\r\n"
data = [tau, mod]
# Write header
@@ -679,7 +688,7 @@ def ExportCorrelation(exportfile, correlation, page_info, savetrace=True):
rowcoli = "{:.10e}".format(data[j][i])
datarow.append(rowcoli)
dataWriter.writerow(datarow)
- ## Trace
+ # Trace
# Only save the trace if user wants us to:
if savetrace:
# We will also save the trace in [s]
@@ -688,11 +697,11 @@ def ExportCorrelation(exportfile, correlation, page_info, savetrace=True):
# Mark beginning of Trace
openedfile.write('#\r\n#\r\n# BEGIN TRACE\r\n#\r\n')
# Columns
- time = corr.traces[0][:,0] * timefactor
- intensity = corr.traces[0][:,1]
+ time = corr.traces[0][:, 0] * timefactor
+ intensity = corr.traces[0][:, 1]
# Write
openedfile.write('# Time [s]'+"\t"
- 'Intensity trace [kHz]'+" \r\n")
+ 'Intensity trace [kHz]'+" \r\n")
for i in np.arange(len(time)):
dataWriter.writerow(["{:.10e}".format(time[i]),
"{:.10e}".format(intensity[i])])
@@ -701,12 +710,12 @@ def ExportCorrelation(exportfile, correlation, page_info, savetrace=True):
# Mark beginning of Trace B
openedfile.write('#\r\n#\r\n# BEGIN SECOND TRACE\r\n#\r\n')
# Columns
- time = corr.traces[1][:,0] * timefactor
- intensity = corr.traces[1][:,1]
+ time = corr.traces[1][:, 0] * timefactor
+ intensity = corr.traces[1][:, 1]
# Write
openedfile.write('# Time [s]'+"\t"
- 'Intensity trace [kHz]'+" \r\n")
+ 'Intensity trace [kHz]'+" \r\n")
for i in np.arange(len(time)):
dataWriter.writerow(["{:.10e}".format(time[i]),
"{:.10e}".format(intensity[i])])
diff --git a/pycorrfit/readfiles/__init__.py b/pycorrfit/readfiles/__init__.py
index 80cf4fb8..39112298 100644
--- a/pycorrfit/readfiles/__init__.py
+++ b/pycorrfit/readfiles/__init__.py
@@ -43,7 +43,7 @@ def get_supported_extensions():
for kf in list(filetypes_dict.keys()):
ext = kf.split("|")[-1]
ext = ext.split(";")
- ext = [ e.lower().strip("*. ") for e in ext]
+ ext = [e.lower().strip("*. ") for e in ext]
ext = list(np.unique(ext))
extlist += ext
extlist = list(np.unique(extlist))
@@ -119,13 +119,13 @@ def openZIP(path, filename=None):
path = path / filename
filename = path.name
- ## Open the archive:
+ # Open the archive:
Arc = zipfile.ZipFile(path, mode='r')
- Correlations = [] # Correlation information
+ Correlations = [] # Correlation information
Curvelist = [] # Type information
Filelist = [] # List of filenames corresponding to *Curvelist*
Trace = [] # Corresponding traces
- ## First test, if we are opening a session file
+ # First test, if we are opening a session file
sessionwc = [".fcsfit-session.zip", ".pcfs"]
if filename.endswith(sessionwc[0]) or filename.endswith(sessionwc[1]):
# Get the yaml parms dump:
@@ -142,7 +142,8 @@ def openZIP(path, filename=None):
number = str(Parms[i][0])
expfilename = "data"+number[1:len(number)-2]+".csv"
expfile = Arc.open(expfilename, 'r')
- readdata = csv.reader(io.StringIO(expfile.read().decode()), delimiter=',')
+ readdata = csv.reader(io.StringIO(
+ expfile.read().decode()), delimiter=',')
dataexp = list()
if str(readdata.__next__()[0]) == "# tau only":
# We do not have a curve here
@@ -178,7 +179,7 @@ def openZIP(path, filename=None):
else:
# Cross correlation uses two traces
tracefilenames = ["trace"+number[1:len(number)-2]+"A.csv",
- "trace"+number[1:len(number)-2]+"B.csv" ]
+ "trace"+number[1:len(number)-2]+"B.csv"]
Curvelist.append("CC")
thistrace = list()
for tracefilename in tracefilenames:
@@ -189,7 +190,8 @@ def openZIP(path, filename=None):
pass
else:
tracefile = Arc.open(tracefilename, 'r')
- traceread = csv.reader(io.StringIO(tracefile.read().decode()), delimiter=',')
+ traceread = csv.reader(io.StringIO(
+ tracefile.read().decode()), delimiter=',')
singletrace = list()
for row in traceread:
# Exclude commentaries
@@ -221,7 +223,7 @@ def openZIP(path, filename=None):
Trace += data["Trace"]
Curvelist += data["Type"]
fnames = data["Filename"]
- Filelist += [ filename+"/"+fs for fs in fnames ]
+ Filelist += [filename+"/"+fs for fs in fnames]
shutil.rmtree(path=tempdir, ignore_errors=True)
Arc.close()
dictionary = {}
@@ -232,32 +234,31 @@ def openZIP(path, filename=None):
return dictionary
-
# The string that is shown when opening all supported files
# We add an empty space so it is listed first in the dialogs.
ALL_SUP_STRING = " All supported files"
# Dictionary with filetypes that we can open
# The wildcards point to the appropriate functions.
-filetypes_dict = {"Correlator.com (*.SIN)|*.SIN;*.sin" : openSIN,
- "ALV (*.ASC)|*.ASC;*.asc" : openASC,
- "PyCorrFit (*.csv)|*.csv" : openCSV,
- "Matlab 'Ries (*.mat)|*.mat" : openMAT,
- "PicoQuant (*.pt3)|*.pt3" : openPT3,
- "Zeiss ConfoCor3 (*.fcs)|*.fcs" : openFCS,
- "Zip file (*.zip)|*.zip" : openZIP,
- "PyCorrFit session (*.pcfs)|*.pcfs" : openZIP
+filetypes_dict = {"Correlator.com (*.SIN)|*.SIN;*.sin": openSIN,
+ "ALV (*.ASC)|*.ASC;*.asc": openASC,
+ "PyCorrFit (*.csv)|*.csv": openCSV,
+ "Matlab 'Ries (*.mat)|*.mat": openMAT,
+ "PicoQuant (*.pt3)|*.pt3": openPT3,
+ "Zeiss ConfoCor3 (*.fcs)|*.fcs": openFCS,
+ "Zip file (*.zip)|*.zip": openZIP,
+ "PyCorrFit session (*.pcfs)|*.pcfs": openZIP
}
# For user comfort, add "All supported files" wildcard:
add_all_supported_filetype_entry(filetypes_dict)
# Dictionary with filetypes we can open that have intensity traces in them.
-filetypes_bg_dict = {"Correlator.com (*.SIN)|*.SIN;*.sin" : openSIN,
- "ALV (*.ASC)|*.ASC" : openASC,
- "PyCorrFit (*.csv)|*.csv" : openCSV,
- "PicoQuant (*.pt3)|*.pt3" : openPT3,
- "Zeiss ConfoCor3 (*.fcs)|*.fcs" : openFCS,
- "Zip file (*.zip)|*.zip" : openZIP,
- "PyCorrFit session (*.pcfs)|*.pcfs" : openZIP
+filetypes_bg_dict = {"Correlator.com (*.SIN)|*.SIN;*.sin": openSIN,
+ "ALV (*.ASC)|*.ASC": openASC,
+ "PyCorrFit (*.csv)|*.csv": openCSV,
+ "PicoQuant (*.pt3)|*.pt3": openPT3,
+ "Zeiss ConfoCor3 (*.fcs)|*.fcs": openFCS,
+ "Zip file (*.zip)|*.zip": openZIP,
+ "PyCorrFit session (*.pcfs)|*.pcfs": openZIP
}
add_all_supported_filetype_entry(filetypes_bg_dict)
diff --git a/pycorrfit/readfiles/read_ASC_ALV.py b/pycorrfit/readfiles/read_ASC_ALV.py
index aad10e81..462f6eb8 100644
--- a/pycorrfit/readfiles/read_ASC_ALV.py
+++ b/pycorrfit/readfiles/read_ASC_ALV.py
@@ -115,16 +115,16 @@ def openASC_old(path):
Alldata = openfile.readlines()
# End of trace
EndT = Alldata.__len__()
- ## Correlation function
+ # Correlation function
# Find out where the correlation function is
for i in np.arange(len(Alldata)):
if Alldata[i].startswith('Mode'):
mode = Alldata[i][5:].strip(' ":').strip().strip('"')
single_strings = ["a-ch0", "a-ch1", "auto ch0", "auto ch1",
"fast auto ch0", "fast auto ch1",
- ]
+ ]
if (mode.lower().count('single') or
- mode.lower().strip() in single_strings):
+ mode.lower().strip() in single_strings):
single = True
channel = mode.split(" ")[-1]
else:
@@ -139,7 +139,7 @@ def openASC_old(path):
# This tells us if there is only one curve or if there are
# multiple curves with an average.
if (Alldata[i].strip().lower() ==
- '"correlation (multi, averaged)"' ):
+ '"correlation (multi, averaged)"'):
multidata = True
else:
multidata = False
@@ -160,7 +160,7 @@ def openASC_old(path):
EndT = i-1
# Get the header
Namedata = Alldata[StartC-1: StartC]
- ## Define *curvelist*
+ # Define *curvelist*
curvelist = csv.reader(Namedata, delimiter='\t').__next__()
if len(curvelist) <= 2:
# Then we have just one single correlation curve
@@ -172,7 +172,7 @@ def openASC_old(path):
curvelist.remove(curvelist[0])
# Last column is empty
curvelist.remove(curvelist[-1])
- ## Correlation function
+ # Correlation function
Truedata = Alldata[StartC: EndC]
readdata = csv.reader(Truedata, delimiter='\t')
# Add lists to *data* according to the length of *curvelist*
@@ -181,14 +181,14 @@ def openASC_old(path):
for row in readdata:
for i in np.arange(len(curvelist)):
if len(row) > 0:
- data[i].append( (np.float(row[0]), np.float(row[i+1])) )
- ## Trace
+ data[i].append((np.float(row[0]), np.float(row[i+1])))
+ # Trace
# Trace is stored in two columns
# 1st column: time [s]
# 2nd column: trace [kHz]
# Get the trace
Tracedata = Alldata[StartT: EndT]
- timefactor = 1000 # because we want ms instead of s
+ timefactor = 1000 # because we want ms instead of s
readtrace = csv.reader(Tracedata, delimiter='\t')
trace = list()
trace2 = list()
@@ -273,7 +273,7 @@ def openASC_old(path):
channel = "CH1"
splittrace2 = mysplit(trace2[0], len(curvelist)/2-nav)
i = 0
- for t in range(int(len(curvelist)/2),int(len(curvelist))):
+ for t in range(int(len(curvelist)/2), int(len(curvelist))):
typ = curvelist[t]
if typ.lower()[:7] == "average":
typelist.append("{} average".format(channel))
@@ -300,7 +300,7 @@ def openASC_old(path):
typelist.append("{} average".format(channel))
corrlist.append(np.array(data[t]))
tracelist.append([np.array(trace[0]),
- np.array(trace2[0]) ])
+ np.array(trace2[0])])
else:
typelist.append("{} {}".format(accc, channel))
corrlist.append(np.array(data[t]))
@@ -309,14 +309,14 @@ def openASC_old(path):
# CHANNEL 1
channel = "CC10"
i = 0
- for t in range(int(len(curvelist)/2),int(len(curvelist))):
+ for t in range(int(len(curvelist)/2), int(len(curvelist))):
typ = curvelist[t]
if typ.lower()[:7] == "average":
typelist.append("{} average".format(channel))
corrlist.append(np.array(data[t]))
# order must be the same as above
tracelist.append([np.array(trace[0]),
- np.array(trace2[0]) ])
+ np.array(trace2[0])])
else:
typelist.append("{} {}".format(accc, channel))
corrlist.append(np.array(data[t]))
@@ -388,7 +388,7 @@ def openASC_ALV_7004(path):
# trace array: " "
allcorr = []
alltrac = []
- i=0
+ i = 0
intrace = False
mode = False
for item in Alldata:
@@ -401,41 +401,41 @@ def openASC_ALV_7004(path):
if item.count("\t") == 4:
if intrace:
it = item.split("\t")
- it = [ float(t.strip()) for t in it ]
+ it = [float(t.strip()) for t in it]
alltrac.append(it)
else:
ic = item.split("\t")
- ic = [ float(c.strip()) for c in ic ]
+ ic = [float(c.strip()) for c in ic]
allcorr.append(ic)
allcorr = np.array(allcorr)
alltrac = np.array(alltrac)
- tau = allcorr[:,0]
- time = alltrac[:,0] * 1000
+ tau = allcorr[:, 0]
+ time = alltrac[:, 0] * 1000
lenc = allcorr.shape[0]
lent = alltrac.shape[0]
# Traces
trace1 = np.zeros((lent, 2), dtype=np.float_)
- trace1[:,0] = time
- trace1[:,1] = alltrac[:,1]
+ trace1[:, 0] = time
+ trace1[:, 1] = alltrac[:, 1]
trace2 = trace1.copy()
- trace2[:,1] = alltrac[:,2]
+ trace2[:, 1] = alltrac[:, 2]
trace3 = trace1.copy()
- trace3[:,1] = alltrac[:,3]
+ trace3[:, 1] = alltrac[:, 3]
trace4 = trace1.copy()
- trace4[:,1] = alltrac[:,4]
+ trace4[:, 1] = alltrac[:, 4]
# Correlations
corr1 = np.zeros((lenc, 2), dtype=np.float_)
- corr1[:,0] = tau
- corr1[:,1] = allcorr[:,1]
+ corr1[:, 0] = tau
+ corr1[:, 1] = allcorr[:, 1]
corr2 = corr1.copy()
- corr2[:,1] = allcorr[:,2]
+ corr2[:, 1] = allcorr[:, 2]
corr3 = corr1.copy()
- corr3[:,1] = allcorr[:,3]
+ corr3[:, 1] = allcorr[:, 3]
corr4 = corr1.copy()
- corr4[:,1] = allcorr[:,4]
+ corr4[:, 1] = allcorr[:, 4]
typelist = []
corrlist = []
@@ -450,69 +450,69 @@ def openASC_ALV_7004(path):
if not (np.allclose(trace1, trace3, rtol=.01) and
np.allclose(trace2, trace4, rtol=.01)):
raise LoadALVError("Unexpected data format: {}".format(path))
- if not np.allclose(corr1[:,1], 0):
+ if not np.allclose(corr1[:, 1], 0):
corrlist.append(corr1)
filelist.append(filename)
tracelist.append(trace1)
typelist.append("AC1")
- if not np.allclose(corr2[:,1], 0):
+ if not np.allclose(corr2[:, 1], 0):
corrlist.append(corr2)
filelist.append(filename)
tracelist.append(trace2)
typelist.append("AC2")
- if not np.allclose(corr3[:,1], 0):
+ if not np.allclose(corr3[:, 1], 0):
corrlist.append(corr3)
filelist.append(filename)
tracelist.append([trace1, trace2])
typelist.append("CC12")
- if not np.allclose(corr4[:,1], 0):
+ if not np.allclose(corr4[:, 1], 0):
corrlist.append(corr4)
filelist.append(filename)
tracelist.append([trace1, trace2])
typelist.append("CC21")
elif mode in ["a-ch0", "a-ch0 a-"]:
- if not (np.allclose(trace2[:,1], 0) and
- np.allclose(trace3[:,1], 0) and
- np.allclose(trace4[:,1], 0) and
- np.allclose(corr2[:,1], 0) and
- np.allclose(corr3[:,1], 0) and
- np.allclose(corr4[:,1], 0)):
+ if not (np.allclose(trace2[:, 1], 0) and
+ np.allclose(trace3[:, 1], 0) and
+ np.allclose(trace4[:, 1], 0) and
+ np.allclose(corr2[:, 1], 0) and
+ np.allclose(corr3[:, 1], 0) and
+ np.allclose(corr4[:, 1], 0)):
raise LoadALVError("Unexpected data format: {}".format(path))
corrlist.append(corr1)
filelist.append(filename)
tracelist.append(trace1)
typelist.append("AC")
elif mode in ["a-ch1", "a-ch1 a-"]:
- if not (np.allclose(trace1[:,1], 0) and
- np.allclose(trace3[:,1], 0) and
- np.allclose(trace4[:,1], 0) and
- np.allclose(corr1[:,1], 0) and
- np.allclose(corr3[:,1], 0) and
- np.allclose(corr4[:,1], 0)):
+ if not (np.allclose(trace1[:, 1], 0) and
+ np.allclose(trace3[:, 1], 0) and
+ np.allclose(trace4[:, 1], 0) and
+ np.allclose(corr1[:, 1], 0) and
+ np.allclose(corr3[:, 1], 0) and
+ np.allclose(corr4[:, 1], 0)):
raise LoadALVError("Unexpected data format: {}".format(path))
corrlist.append(corr2)
filelist.append(filename)
tracelist.append(trace2)
typelist.append("AC")
elif mode in ["a-ch2", "a- a-ch2"]:
- if not (np.allclose(trace1[:,1], 0) and
- np.allclose(trace2[:,1], 0) and
- np.allclose(trace4[:,1], 0) and
- np.allclose(corr1[:,1], 0) and
- np.allclose(corr2[:,1], 0) and
- np.allclose(corr4[:,1], 0)):
+ if not (np.allclose(trace1[:, 1], 0) and
+ np.allclose(trace2[:, 1], 0) and
+ np.allclose(trace4[:, 1], 0) and
+ np.allclose(corr1[:, 1], 0) and
+ np.allclose(corr2[:, 1], 0) and
+ np.allclose(corr4[:, 1], 0)):
raise LoadALVError("Unexpected data format: {}".format(path))
corrlist.append(corr3)
filelist.append(filename)
tracelist.append(trace3)
typelist.append("AC")
elif mode in ["a-ch3", "a- a-ch3"]:
- if not (np.allclose(trace1[:,1], 0) and
- np.allclose(trace2[:,1], 0) and
- np.allclose(trace3[:,1], 0) and
- np.allclose(corr1[:,1], 0) and
- np.allclose(corr2[:,1], 0) and
- np.allclose(corr3[:,1], 0)):
+ if not (np.allclose(trace1[:, 1], 0) and
+ np.allclose(trace2[:, 1], 0) and
+ np.allclose(trace3[:, 1], 0) and
+ np.allclose(corr1[:, 1], 0) and
+ np.allclose(corr2[:, 1], 0) and
+ np.allclose(corr3[:, 1], 0)):
raise LoadALVError("Unexpected data format: {}".format(path))
corrlist.append(corr4)
filelist.append(filename)
@@ -543,24 +543,23 @@ def mysplit(a, n):
lensplit = np.int(np.ceil(N/n))
# xp is actually rounded -> recalculate
- xp = np.linspace(a[:,0][0], a[:,0][-1], N, endpoint=True)
+ xp = np.linspace(a[:, 0][0], a[:, 0][-1], N, endpoint=True)
# let xp start at zero
- xp -= a[:,0][0]
- yp = a[:,1]
+ xp -= a[:, 0][0]
+ yp = a[:, 1]
# time frame for each new curve
#dx = xp[-1]/n
# perform interpolation of new trace
x, newstep = np.linspace(0, xp[-1], lensplit*n,
- endpoint=True, retstep=True)
+ endpoint=True, retstep=True)
# interpolating reduces the variance and possibly changes the avg
- y = np.interp(x,xp,yp)
+ y = np.interp(x, xp, yp)
- data = np.zeros((lensplit*n,2))
- data[:,0] = x + newstep
+ data = np.zeros((lensplit*n, 2))
+ data[:, 0] = x + newstep
# make sure that the average stays the same:
- data[:,1] = y - np.average(y) + np.average(yp)
- return np.split(data,n)
-
+ data[:, 1] = y - np.average(y) + np.average(yp)
+ return np.split(data, n)
diff --git a/pycorrfit/readfiles/read_CSV_PyCorrFit.py b/pycorrfit/readfiles/read_CSV_PyCorrFit.py
index 5563cde1..4b486cbc 100644
--- a/pycorrfit/readfiles/read_CSV_PyCorrFit.py
+++ b/pycorrfit/readfiles/read_CSV_PyCorrFit.py
@@ -77,7 +77,7 @@ def openCSV(path, filename=None):
return None
# Define what will happen to the file
- timefactor = 1000 # because we want ms instead of s
+ timefactor = 1000 # because we want ms instead of s
csvfile = path.open('r', encoding='utf-8')
readdata = csv.reader(csvfile, delimiter=',')
data = list()
@@ -85,7 +85,7 @@ def openCSV(path, filename=None):
weightname = "external"
trace = None
traceA = None
- DataType="AC" # May be changed
+ DataType = "AC" # May be changed
numtraces = 0
prev_row = None
for row in readdata:
@@ -99,15 +99,15 @@ def openCSV(path, filename=None):
corrtype = str(row[0])[12:].strip().strip(":").strip()
if corrtype[:17].lower() == "cross-correlation":
# We will later try to import a second trace
- DataType="CC"
+ DataType = "CC"
DataType += corrtype[17:].strip()
elif corrtype[0:15].lower() == "autocorrelation":
- DataType="AC"
+ DataType = "AC"
DataType += corrtype[15:].strip()
elif str(row[0])[0:13].upper() == '# BEGIN TRACE':
# Correlation is over. We have a trace
corr = np.array(data)
- data=list()
+ data = list()
numtraces = 1
elif str(row[0])[0:20].upper() == '# BEGIN SECOND TRACE':
# First trace is over. We have a second trace
@@ -119,8 +119,8 @@ def openCSV(path, filename=None):
# Read the 1st section
# On Windows we had problems importing nan values that
# had some white-spaces around them. Therefore: strip()
- ## As of version 0.7.8 we are supporting white space
- ## separated values as well
+ # As of version 0.7.8 we are supporting white space
+ # separated values as well
if len(row) == 1:
row = row[0].split()
data.append((np.float(row[0].strip())*timefactor,
@@ -130,7 +130,9 @@ def openCSV(path, filename=None):
weights.append(np.float(row[4].strip()))
if weightname == "external":
try:
- weightname = "ext. "+prev_row[0].split("Weights")[1].split("[")[1].split("]")[0]
+ weightname = "ext. " + \
+ prev_row[0].split("Weights")[1].split(
+ "[")[1].split("]")[0]
except:
pass
prev_row = row
@@ -141,7 +143,7 @@ def openCSV(path, filename=None):
elif numtraces >= 1:
trace = rest
del data
- ## Remove any NaN numbers from thearray
+ # Remove any NaN numbers from thearray
# Explanation:
# np.isnan(data)
# finds the position of NaNs in the array (True positions); 2D array, bool
@@ -154,7 +156,7 @@ def openCSV(path, filename=None):
# Also check for infinities.
corr = corr[~np.isinf(corr).any(1)]
csvfile.close()
- Traces=list()
+ Traces = list()
# Set correct trace data for import
if numtraces == 1 and DataType[:2] == "AC":
Traces.append(trace)
@@ -171,6 +173,6 @@ def openCSV(path, filename=None):
dictionary["Type"] = [DataType]
dictionary["Filename"] = [filename]
if len(weights) != 0:
- dictionary["Weight"] = [ np.array(weights)]
+ dictionary["Weight"] = [np.array(weights)]
dictionary["Weight Name"] = [weightname]
return dictionary
diff --git a/pycorrfit/readfiles/read_FCS_Confocor3.py b/pycorrfit/readfiles/read_FCS_Confocor3.py
index bd8b41e2..c8b2c281 100644
--- a/pycorrfit/readfiles/read_FCS_Confocor3.py
+++ b/pycorrfit/readfiles/read_FCS_Confocor3.py
@@ -48,7 +48,7 @@ def openFCS_Multiple(path):
files created from the newer ZEN Software.
"""
filename = path.name
- ### TODO:
+ # TODO:
# match curves with their timestamp
# (actimelist and cctimelist)
#
@@ -96,14 +96,14 @@ def openFCS_Multiple(path):
aclist.append(FoundType)
else:
for ch2num in np.arange(4)+1:
- if FCStype == "Cross-correlation detector "+\
- str(chnum)+" versus detector "+\
+ if FCStype == "Cross-correlation detector " +\
+ str(chnum)+" versus detector " +\
str(ch2num):
FoundType = "CC"+str(chnum)+str(ch2num)
cclist.append(FoundType)
- elif FCStype == "Cross-correlation detector Meta"+\
- str(chnum)+" versus detector Meta"+\
- str(ch2num):
+ elif FCStype == "Cross-correlation detector Meta" +\
+ str(chnum)+" versus detector Meta" +\
+ str(ch2num):
FoundType = "CC"+str(chnum)+str(ch2num)
cclist.append(FoundType)
if FoundType is False:
@@ -121,9 +121,9 @@ def openFCS_Multiple(path):
# traces in those files are usually very large. We will bin
# the trace and import a lighter version of it.
tracelength = \
- int(Alldata[i].partition("=")[2].strip().partition(" ")[0])
+ int(Alldata[i].partition("=")[2].strip().partition(" ")[0])
if tracelength != 0:
- tracedata = Alldata[i+1 : i+tracelength+1]
+ tracedata = Alldata[i+1: i+tracelength+1]
# Jump foward in the index
i = i + tracelength
readtrace = csv.reader(tracedata, delimiter='\t')
@@ -132,8 +132,8 @@ def openFCS_Multiple(path):
for row in readtrace:
# tau in ms, trace in kHz
# So we need to put some factors here
- trace.append( (np.float(row[3])*1000,
- np.float(row[4])/1000) )
+ trace.append((np.float(row[3])*1000,
+ np.float(row[4])/1000))
trace = np.array(trace)
# If the trace is too big. Wee need to bin it.
newtrace = util.downsample_trace(trace)
@@ -141,27 +141,27 @@ def openFCS_Multiple(path):
traces.append(newtrace)
if FoundType[:2] != "AC":
# For every trace there is an entry in aclist
- print("Trace data saved in CC section."+ \
+ print("Trace data saved in CC section." +
"I cannot handle that.")
gottrace = True
if Alldata[i].partition("=")[0].strip() == "CorrelationArraySize":
# Get the correlation information
corrlength = int(Alldata[i].partition("=")[2].strip())
- if corrlength !=0:
+ if corrlength != 0:
# For cross correlation or something sometimes
# there is no trace information.
- if gottrace == False and FoundType[:2] =="AC":
+ if gottrace == False and FoundType[:2] == "AC":
# We think we know that there is no trace in CC curves
traces.append(None)
- corrdata = Alldata[i + 2 : i + corrlength + 2]
+ corrdata = Alldata[i + 2: i + corrlength + 2]
# Jump foward
i = i + corrlength
readcorr = csv.reader(corrdata, delimiter='\t')
corr = list()
for row in readcorr:
# tau in ms, corr-function
- corr.append( (np.float(row[3])*1000,
- np.float(row[4])-1) )
+ corr.append((np.float(row[3])*1000,
+ np.float(row[4])-1))
if FoundType[:2] == "AC":
ac_correlations.append(np.array(corr))
elif FoundType[:2] == "CC":
@@ -203,7 +203,7 @@ def openFCS_Multiple(path):
# These "None" type items should be at the end of these lists.
# If the user created .fcs files with averages between the curves,
# the *traces* contains *None* values at those positions.
- ## We now create:
+ # We now create:
# curvelist: All actually used data
# tracelist: Traces brought into right form (also for CCs)
# corrlist: Correlation curves
@@ -233,7 +233,8 @@ def openFCS_Multiple(path):
corrlist.append(ac_correlations[actids[0]])
else:
if traces[actids[0]] is not None:
- warnings.warn("File {} curve {} does not contain AC data.".format(filename, tid))
+ warnings.warn(
+ "File {} curve {} does not contain AC data.".format(filename, tid))
elif len(actids) == 2:
# Get AC data
if aclist[actids[0]] == "AC1":
@@ -247,16 +248,17 @@ def openFCS_Multiple(path):
acdat2 = ac_correlations[actids[0]]
trace2 = traces[actids[0]]
else:
- warnings.warn("File {} curve {}: unknown AC data.".format(filename, tid))
+ warnings.warn(
+ "File {} curve {}: unknown AC data.".format(filename, tid))
continue
if acdat1 is not None:
- #AC1
+ # AC1
curvelist.append("AC1")
tracelist.append(trace1)
corrlist.append(acdat1)
if acdat2 is not None:
- #AC2
+ # AC2
curvelist.append("AC2")
tracelist.append(trace2)
corrlist.append(acdat2)
@@ -270,17 +272,18 @@ def openFCS_Multiple(path):
ccdat12 = cc_correlations[cctids[1]]
ccdat21 = cc_correlations[cctids[0]]
else:
- warnings.warn("File {} curve {}: unknown CC data.".format(filename, tid))
+ warnings.warn(
+ "File {} curve {}: unknown CC data.".format(filename, tid))
continue
tracecc = [trace1, trace2]
if ccdat12 is not None:
- #CC12
+ # CC12
curvelist.append("CC12")
tracelist.append(tracecc)
corrlist.append(ccdat12)
if ccdat21 is not None:
- #CC21
+ # CC21
curvelist.append("CC21")
tracelist.append(tracecc)
corrlist.append(ccdat21)
@@ -318,7 +321,7 @@ def openFCS_Single(path):
if Alldata[i].partition("=")[0].strip() == "##DATA TYPE":
# Find out what type of correlation curve we have.
# Might be interesting to the user.
- Type = Alldata[i].partition("=")[2].strip()
+ Type = Alldata[i].partition("=")[2].strip()
if Type == "FCS Correlogram":
fcscurve = True
tracecurve = False
@@ -345,7 +348,7 @@ def openFCS_Single(path):
for row in readtrace:
# tau in ms, trace in kHz
# So we need to put some factors here
- trace.append( (np.float(row[0])*1000, np.float(row[1])) )
+ trace.append((np.float(row[0])*1000, np.float(row[1])))
trace = np.array(trace)
# If the trace is too big. Wee need to bin it.
newtrace = util.downsample_trace(trace)
@@ -355,7 +358,7 @@ def openFCS_Single(path):
# Get the correlation information
corrlength = int(Alldata[i].partition("=")[2].strip())
i = i + 2
- if corrlength !=0:
+ if corrlength != 0:
corrdata = Alldata.__getslice__(i, i+corrlength)
# Jump foward
i = i + corrlength
@@ -363,7 +366,7 @@ def openFCS_Single(path):
corr = list()
for row in readcorr:
# tau in ms, corr-function
- corr.append( (np.float(row[0]), np.float(row[1])-1) )
+ corr.append((np.float(row[0]), np.float(row[1])-1))
corr = np.array(corr)
fcscurve = False
diff --git a/pycorrfit/readfiles/read_SIN_correlator_com.py b/pycorrfit/readfiles/read_SIN_correlator_com.py
index 1bc0d45b..c91cdfa6 100644
--- a/pycorrfit/readfiles/read_SIN_correlator_com.py
+++ b/pycorrfit/readfiles/read_SIN_correlator_com.py
@@ -26,7 +26,7 @@ def openSIN(path, filename=None):
if line.lower().startswith("mode"):
mode = line.split("=")[1].strip().split()
# Find out what kind of mode it is
-
+
# The rationale is that when the mode
# consists of single characters separated
# by empty spaces, then we have integer mode.
@@ -38,17 +38,17 @@ def openSIN(path, filename=None):
def openSIN_integer_mode(path):
"""Integer mode file format of e.g. flex03lq-1 correlator (correlator.com)
-
+
This is a file format where the type (AC/CC) of the curve is
determined using integers in the "Mode=" line, e.g.
-
+
Mode= 2 3 3 2 0 1 1 0
-
+
which means the first correlation is CC23, the second CC32,
the third CC01, and the fourth CC10. Similarly,
-
+
Mode= 1 1 2 2 0 4 4 4
-
+
would translate to AC11, AC22, CC04, and AC44.
"""
with path.open() as fd:
@@ -59,16 +59,16 @@ def openSIN_integer_mode(path):
line = line.strip()
if line.lower().startswith("mode"):
mode = line.split("=")[1].strip().split()
- mode = [ int(m) for m in mode ]
+ mode = [int(m) for m in mode]
if len(mode) % 2 != 0:
msg = "mode must be multiples of two: {}".format(path)
raise OpenSINError(msg)
-
+
# build up the lists
corr_func = []
intensity = []
section = ""
-
+
# loop through lines
for line in data:
line = line.strip().lower()
@@ -89,49 +89,49 @@ def openSIN_integer_mode(path):
corr_func = np.array(corr_func, dtype=float)
intensity = np.array(intensity, dtype=float)
- timefactor = 1000 # because we want ms instead of s
- timedivfac = 1000 # because we want kHz instead of Hz
- intensity[:,0] *= timefactor
- corr_func[:,0] *= timefactor
- intensity[:,1:] /= timedivfac
-
+ timefactor = 1000 # because we want ms instead of s
+ timedivfac = 1000 # because we want kHz instead of Hz
+ intensity[:, 0] *= timefactor
+ corr_func[:, 0] *= timefactor
+ intensity[:, 1:] /= timedivfac
+
# correlator.com correlation is normalized to 1, not to 0
- corr_func[:,1:] -= 1
+ corr_func[:, 1:] -= 1
# Now sort the information for pycorrfit
correlations = []
traces = []
curvelist = []
-
+
for ii in range(len(mode)//2):
modea = mode[2*ii]
modeb = mode[2*ii+1]
-
+
if modea == modeb:
# curve type AC
curvelist.append("AC{}".format(modea))
# trace
- atrace = np.zeros((intensity.shape[0],2), dtype=float)
- atrace[:,0] = intensity[:, 0]
- atrace[:,1] = intensity[:, modea+1]
+ atrace = np.zeros((intensity.shape[0], 2), dtype=float)
+ atrace[:, 0] = intensity[:, 0]
+ atrace[:, 1] = intensity[:, modea+1]
traces.append(atrace)
else:
# curve type CC
- curvelist.append("CC{}{}".format(modea,modeb))
+ curvelist.append("CC{}{}".format(modea, modeb))
# trace
modmin = min(modea, modeb)
modmax = max(modea, modeb)
- tracea = np.zeros((intensity.shape[0],2), dtype=float)
- tracea[:,0] = intensity[:, 0]
- tracea[:,1] = intensity[:, modmin+1]
- traceb = np.zeros((intensity.shape[0],2), dtype=float)
- traceb[:,0] = intensity[:, 0]
- traceb[:,1] = intensity[:, modmax+1]
+ tracea = np.zeros((intensity.shape[0], 2), dtype=float)
+ tracea[:, 0] = intensity[:, 0]
+ tracea[:, 1] = intensity[:, modmin+1]
+ traceb = np.zeros((intensity.shape[0], 2), dtype=float)
+ traceb[:, 0] = intensity[:, 0]
+ traceb[:, 1] = intensity[:, modmax+1]
traces.append([tracea, traceb])
# correlation
- corr = np.zeros((corr_func.shape[0],2), dtype=float)
- corr[:,0] = corr_func[:, 0]
- corr[:,1] = corr_func[:, ii+1]
+ corr = np.zeros((corr_func.shape[0], 2), dtype=float)
+ corr[:, 0] = corr_func[:, 0]
+ corr[:, 1] = corr_func[:, ii+1]
correlations.append(corr)
dictionary = {}
@@ -147,7 +147,7 @@ def openSIN_integer_mode(path):
def openSIN_old(path):
"""Parses the simple sin file format (correlator.com)
-
+
Read data from a .SIN file, usually created by
the software using correlators from correlator.com.
@@ -240,7 +240,7 @@ def openSIN_old(path):
# Find out where the correlation function and trace are
for i in np.arange(len(Alldata)):
if Alldata[i][0:4] == "Mode":
-
+
Mode = Alldata[i].split("=")[1].strip()
if Alldata[i][0:21] == "[CorrelationFunction]":
StartC = i+1
@@ -248,7 +248,7 @@ def openSIN_old(path):
EndC = i-2
if Alldata[i][0:18] == "[IntensityHistory]":
# plus 2, because theres a line with the trace length
- StartT = i+2
+ StartT = i+2
if Alldata[i][0:11] == "[Histogram]":
EndT = i-2
curvelist = []
@@ -256,17 +256,17 @@ def openSIN_old(path):
traces = []
# Get the correlation function
Truedata = Alldata[StartC:EndC]
- timefactor = 1000 # because we want ms instead of s
+ timefactor = 1000 # because we want ms instead of s
readcorr = csv.reader(Truedata, delimiter='\t')
# Trace
# Trace is stored in three columns
# 1st column: time [s]
- # 2nd column: trace [Hz]
+ # 2nd column: trace [Hz]
# 3rd column: trace [Hz] - Single Auto: equivalent to 2nd
# Get the trace
Tracedata = Alldata[StartT:EndT]
# timefactor = 1000 # because we want ms instead of s
- timedivfac = 1000 # because we want kHz instead of Hz
+ timedivfac = 1000 # because we want kHz instead of Hz
readtrace = csv.reader(Tracedata, delimiter='\t')
# Process all Data:
if Mode == "Single Auto":
@@ -280,7 +280,7 @@ def openSIN_old(path):
for row in readtrace:
# tau in ms, corr-function minus "1"
trace.append((np.float(row[0])*timefactor,
- np.float(row[1])/timedivfac))
+ np.float(row[1])/timedivfac))
traces.append(np.array(trace))
elif Mode == "Single Cross":
curvelist.append("CC")
@@ -353,8 +353,10 @@ def openSIN_old(path):
# tau in ms, corr-function minus "1"
corrdata1.append((np.float(row[0])*timefactor, np.float(row[1])-1))
corrdata2.append((np.float(row[0])*timefactor, np.float(row[2])-1))
- corrdata12.append((np.float(row[0])*timefactor, np.float(row[3])-1))
- corrdata21.append((np.float(row[0])*timefactor, np.float(row[4])-1))
+ corrdata12.append(
+ (np.float(row[0])*timefactor, np.float(row[3])-1))
+ corrdata21.append(
+ (np.float(row[0])*timefactor, np.float(row[4])-1))
correlations.append(np.array(corrdata1))
correlations.append(np.array(corrdata2))
correlations.append(np.array(corrdata12))
@@ -373,9 +375,9 @@ def openSIN_old(path):
traces.append([np.array(trace1), np.array(trace2)])
else:
raise NotImplemented(
- "'Mode' type '{}' in {} not supported by this method!".
- Mode, format(path))
-
+ "'Mode' type '{}' in {} not supported by this method!".
+ Mode, format(path))
+
dictionary = {}
dictionary["Correlation"] = correlations
dictionary["Trace"] = traces
diff --git a/pycorrfit/readfiles/read_mat_ries.py b/pycorrfit/readfiles/read_mat_ries.py
index 6e258bd2..b69457e0 100644
--- a/pycorrfit/readfiles/read_mat_ries.py
+++ b/pycorrfit/readfiles/read_mat_ries.py
@@ -68,10 +68,10 @@ def openMAT(path, filename=None):
# Another workaround
# Sometimes, there's just one curve, which
# means that corr[0] has no length.
- if len( np.atleast_1d(corr[0]) ) == 1:
+ if len(np.atleast_1d(corr[0])) == 1:
final = np.zeros((len(corr), 2))
- final[:,0] = times
- final[:,1] = corr
+ final[:, 0] = times
+ final[:, 1] = corr
correlations.append(final)
curvelist.append("AC"+str(i+1))
try:
@@ -81,18 +81,17 @@ def openMAT(path, filename=None):
# No trace
traces.append(None)
else:
- trace = np.zeros((2,2))
- trace[1,0] = 1.0
- trace[:,1] = traceavg
+ trace = np.zeros((2, 2))
+ trace[1, 0] = 1.0
+ trace[:, 1] = traceavg
traces.append(trace)
-
elif len(corr) == len(times):
for j in np.arange(len(corr[0])):
final = np.zeros((len(corr), 2))
- final[:,0] = times
- final[:,1] = corr[:,j]
+ final[:, 0] = times
+ final[:, 1] = corr[:, j]
correlations.append(final)
curvelist.append("AC"+str(i+1))
try:
@@ -102,9 +101,9 @@ def openMAT(path, filename=None):
# No trace
traces.append(None)
else:
- trace = np.zeros((2,2))
- trace[1,0] = 1.0
- trace[:,1] = traceavg
+ trace = np.zeros((2, 2))
+ trace[1, 0] = 1.0
+ trace[:, 1] = traceavg
traces.append(trace)
# Get dc "dual color" functions
try:
@@ -123,8 +122,8 @@ def openMAT(path, filename=None):
for j in np.arange(len(corr[0])):
final = np.zeros((len(corr), 2))
- final[:,0] = times
- final[:,1] = corr[:,j]
+ final[:, 0] = times
+ final[:, 1] = corr[:, j]
correlations.append(final)
curvelist.append("CC dual color "+str(i+1))
traces.append(None)
@@ -145,8 +144,8 @@ def openMAT(path, filename=None):
for j in np.arange(len(corr[0])):
final = np.zeros((len(corr), 2))
- final[:,0] = times
- final[:,1] = corr[:,j]
+ final[:, 0] = times
+ final[:, 1] = corr[:, j]
correlations.append(final)
curvelist.append("CC two foci "+str(i+1))
traces.append(None)
@@ -167,8 +166,8 @@ def openMAT(path, filename=None):
for j in np.arange(len(corr[0])):
final = np.zeros((len(corr), 2))
- final[:,0] = times
- final[:,1] = corr[:,j]
+ final[:, 0] = times
+ final[:, 1] = corr[:, j]
correlations.append(final)
curvelist.append("CC dual color two foci "+str(i+1))
traces.append(None)
@@ -202,7 +201,8 @@ def _check_keys(adict):
for key in adict:
if isinstance(adict[key], mat_struct):
adict[key] = _todict(adict[key])
- return adict
+ return adict
+
def _todict(matobj):
'''
diff --git a/pycorrfit/readfiles/read_pt3_PicoQuant.py b/pycorrfit/readfiles/read_pt3_PicoQuant.py
index a3beb672..31d95f46 100644
--- a/pycorrfit/readfiles/read_pt3_PicoQuant.py
+++ b/pycorrfit/readfiles/read_pt3_PicoQuant.py
@@ -14,24 +14,26 @@
class ParameterClass():
"""Stores parameters for correlation """
+
def __init__(self):
- #Where the data is stored.
+ # Where the data is stored.
self.data = []
- self.objectRef =[]
- self.subObjectRef =[]
- self.colors = ['blue','green','red','cyan','magenta','yellow','black']
+ self.objectRef = []
+ self.subObjectRef = []
+ self.colors = ['blue', 'green', 'red',
+ 'cyan', 'magenta', 'yellow', 'black']
self.numOfLoaded = 0
self.NcascStart = 0
self.NcascEnd = 25
self.Nsub = 6
self.winInt = 10
self.photonCountBin = 25
-
+
def getTrace(picoObject, number):
"""
Extracts trace `number` from a `picoObject`.
-
+
Parameters
----------
picoObject: instance of picoObject
@@ -39,7 +41,7 @@ def getTrace(picoObject, number):
number:
The id of the trace, can be 1 or 2.
"""
-
+
attrint = "timeSeries{}".format(number)
attrtime = "timeSeriesScale{}".format(number)
@@ -49,21 +51,20 @@ def getTrace(picoObject, number):
time = np.array(getattr(picoObject, attrtime))
# time delta
deltat = np.abs(time[2]-time[1])
-
- trace = np.zeros((intensity.shape[0],2))
- trace[:,0] = time # ms
- trace[:,1] = intensity / deltat # kHz
-
+
+ trace = np.zeros((intensity.shape[0], 2))
+ trace[:, 0] = time # ms
+ trace[:, 1] = intensity / deltat # kHz
+
# If the trace is too big. Wee need to bin it.
newtrace = util.downsample_trace(trace)
-
+
return newtrace
-
def openPT3(path, filename=None):
""" Retreive correlation curves from PicoQuant data files
-
+
This function is a wrapper around the PicoQuant capability of
FCS_Viewer by Dominic Waithe.
"""
@@ -74,7 +75,7 @@ def openPT3(path, filename=None):
filename = path.name
par_obj = ParameterClass()
-
+
pt3file = picoObject(str(path), par_obj, None)
po = pt3file
@@ -87,43 +88,42 @@ def openPT3(path, filename=None):
typelist = list()
tracelist = list()
# Some data points are zero for some reason
- id1 = np.where(autotime!=0)
-
+ id1 = np.where(autotime != 0)
# AC0 - autocorrelation CH0
- corrac0 = auto[:,0,0]
+ corrac0 = auto[:, 0, 0]
if np.sum(np.abs(corrac0[id1])) != 0:
typelist.append("AC0")
# autotime,auto[:,0,0]
- corrlist.append(np.hstack( (autotime[id1].reshape(-1,1),
- corrac0[id1].reshape(-1,1)) ))
+ corrlist.append(np.hstack((autotime[id1].reshape(-1, 1),
+ corrac0[id1].reshape(-1, 1))))
tracelist.append([getTrace(po, 1)])
-
+
# AC1 - autocorrelation CH1
- corrac1 = auto[:,1,1]
+ corrac1 = auto[:, 1, 1]
if np.sum(np.abs(corrac1[id1])) != 0:
typelist.append("AC1")
# autotime,auto[:,1,1]
- corrlist.append(np.hstack( (autotime[id1].reshape(-1,1),
- corrac1[id1].reshape(-1,1)) ))
+ corrlist.append(np.hstack((autotime[id1].reshape(-1, 1),
+ corrac1[id1].reshape(-1, 1))))
tracelist.append([getTrace(po, 2)])
-
+
# CC01 - Cross-Correlation CH0-CH1
- corrcc01 = auto[:,0,1]
+ corrcc01 = auto[:, 0, 1]
if np.sum(np.abs(corrcc01[id1])) != 0:
typelist.append("CC01")
# autotime,auto[:,0,1]
- corrlist.append(np.hstack( (autotime[id1].reshape(-1,1),
- corrcc01[id1].reshape(-1,1)) ))
+ corrlist.append(np.hstack((autotime[id1].reshape(-1, 1),
+ corrcc01[id1].reshape(-1, 1))))
tracelist.append([getTrace(po, 1), getTrace(po, 2)])
-
+
# CC10 - Cross-Correlation CH1-CH0
- corrcc10 = auto[:,1,0]
+ corrcc10 = auto[:, 1, 0]
if np.sum(np.abs(corrcc10[id1])) != 0:
typelist.append("CC10")
# autotime,auto[:,1,0]
- corrlist.append(np.hstack( (autotime[id1].reshape(-1,1),
- corrcc10[id1].reshape(-1,1)) ))
+ corrlist.append(np.hstack((autotime[id1].reshape(-1, 1),
+ corrcc10[id1].reshape(-1, 1))))
tracelist.append([getTrace(po, 1), getTrace(po, 2)])
filelist = [filename] * len(typelist)
diff --git a/pycorrfit/readfiles/read_pt3_scripts/__init__.py b/pycorrfit/readfiles/read_pt3_scripts/__init__.py
index c1bb8a7d..9986b1dd 100644
--- a/pycorrfit/readfiles/read_pt3_scripts/__init__.py
+++ b/pycorrfit/readfiles/read_pt3_scripts/__init__.py
@@ -1 +1 @@
-from .__version__ import version
\ No newline at end of file
+from .__version__ import version
diff --git a/pycorrfit/readfiles/read_pt3_scripts/__version__.py b/pycorrfit/readfiles/read_pt3_scripts/__version__.py
index f3d21331..c529bd6e 100644
--- a/pycorrfit/readfiles/read_pt3_scripts/__version__.py
+++ b/pycorrfit/readfiles/read_pt3_scripts/__version__.py
@@ -1,2 +1,2 @@
# This file contains the GitHub hash of the file versions
-version = "8399ff7401"
\ No newline at end of file
+version = "8399ff7401"
diff --git a/pycorrfit/readfiles/read_pt3_scripts/correlation_methods.py b/pycorrfit/readfiles/read_pt3_scripts/correlation_methods.py
index 92f1967e..3e9754de 100644
--- a/pycorrfit/readfiles/read_pt3_scripts/correlation_methods.py
+++ b/pycorrfit/readfiles/read_pt3_scripts/correlation_methods.py
@@ -22,7 +22,7 @@
"""
-def tttr2xfcs (y,num,NcascStart,NcascEnd, Nsub):
+def tttr2xfcs(y, num, NcascStart, NcascEnd, Nsub):
"""autocorr, autotime = tttr2xfcs(y,num,10,20)
Translation into python of:
Fast calculation of fluorescence correlation data with asynchronous time-correlated single-photon counting.
@@ -30,116 +30,106 @@ def tttr2xfcs (y,num,NcascStart,NcascEnd, Nsub):
"""
dt = np.max(y)-np.min(y)
- y = np.round(y[:],0)
+ y = np.round(y[:], 0)
numshape = num.shape[0]
- autotime = np.zeros(((NcascEnd+1)*(Nsub+1),1));
- auto = np.zeros(((NcascEnd+1)*(Nsub+1), num.shape[1], num.shape[1])).astype(np.float64)
+ autotime = np.zeros(((NcascEnd+1)*(Nsub+1), 1))
+ auto = np.zeros(
+ ((NcascEnd+1)*(Nsub+1), num.shape[1], num.shape[1])).astype(np.float64)
shift = float(0)
delta = float(1)
+ for j in range(0, NcascEnd):
+ # Finds the unique photon times and their indices. The division of 'y' by '2' each cycle makes this more likely.
- for j in range(0,NcascEnd):
-
- #Finds the unique photon times and their indices. The division of 'y' by '2' each cycle makes this more likely.
-
- y,k1 = np.unique(y,1)
+ y, k1 = np.unique(y, 1)
k1shape = k1.shape[0]
- #Sums up the photon times in each bin.
- cs =np.cumsum(num,0).T
+ # Sums up the photon times in each bin.
+ cs = np.cumsum(num, 0).T
- #Prepares difference array so starts with zero.
- diffArr1 = np.zeros(( k1shape+1));
- diffArr2 = np.zeros(( k1shape+1));
+ # Prepares difference array so starts with zero.
+ diffArr1 = np.zeros((k1shape+1))
+ diffArr2 = np.zeros((k1shape+1))
- #Takes the cumulative sum of the unique photon arrivals
- diffArr1[1:] = cs[0,k1].reshape(-1)
- diffArr2[1:] = cs[1,k1].reshape(-1)
+ # Takes the cumulative sum of the unique photon arrivals
+ diffArr1[1:] = cs[0, k1].reshape(-1)
+ diffArr2[1:] = cs[1, k1].reshape(-1)
#del k1
#del cs
- num =np.zeros((k1shape,2))
-
+ num = np.zeros((k1shape, 2))
-
- #Finds the total photons in each bin. and represents as count.
- #This is achieved because we have the indices of each unique time photon and cumulative total at each point.
- num[:,0] = np.diff(diffArr1)
- num[:,1] = np.diff(diffArr2)
+ # Finds the total photons in each bin. and represents as count.
+ # This is achieved because we have the indices of each unique time photon and cumulative total at each point.
+ num[:, 0] = np.diff(diffArr1)
+ num[:, 1] = np.diff(diffArr2)
#diffArr1 = [];
#diffArr2 = [];
- for k in range(0,Nsub):
+ for k in range(0, Nsub):
shift = shift + delta
- lag = np.round(shift/delta,0)
-
+ lag = np.round(shift/delta, 0)
- #Allows the script to be sped up.
+ # Allows the script to be sped up.
if j >= NcascStart:
-
- #Old method
+ # Old method
#i1= np.in1d(y,y+lag,assume_unique=True)
#i2= np.in1d(y+lag,y,assume_unique=True)
- #New method, cython
- i1,i2 = dividAndConquer(y, y+lag,y.shape[0])
+ # New method, cython
+ i1, i2 = dividAndConquer(y, y+lag, y.shape[0])
- #If the weights (num) are one as in the first Ncasc round, then the correlation is equal to np.sum(i1)
+ # If the weights (num) are one as in the first Ncasc round, then the correlation is equal to np.sum(i1)
i1 = np.where(i1.astype(np.bool))[0]
i2 = np.where(i2.astype(np.bool))[0]
- #Now we want to weight each photon corectly.
- #Faster dot product method, faster than converting to matrix.
+ # Now we want to weight each photon corectly.
+ # Faster dot product method, faster than converting to matrix.
if i1.size and i2.size:
- auto[(k+(j)*Nsub),:,:] = np.dot((num[i1,:]).T,num[i2,:])/delta
+ auto[(k+(j)*Nsub), :, :] = np.dot((num[i1, :]).T,
+ num[i2, :])/delta
- autotime[k+(j)*Nsub] =shift;
+ autotime[k+(j)*Nsub] = shift
- #Equivalent to matlab round when numbers are %.5
+ # Equivalent to matlab round when numbers are %.5
y = np.ceil(np.array(0.5*y))
delta = 2*delta
for j in range(0, auto.shape[0]):
- auto[j,:,:] = auto[j,:,:]*dt/(dt-autotime[j])
+ auto[j, :, :] = auto[j, :, :]*dt/(dt-autotime[j])
autotime = autotime/1000000
-
- #Removes the trailing zeros.
+ # Removes the trailing zeros.
idauto = np.where(autotime != 0)[0]
autotime = autotime[idauto]
- auto = auto[idauto,:,:]
+ auto = auto[idauto, :, :]
return auto, autotime
def delayTime2bin(dTimeArr, chanArr, chanNum, winInt):
decayTime = np.array(dTimeArr)
- #This is the point and which each channel is identified.
- decayTimeCh =decayTime[chanArr == chanNum]
+ # This is the point and which each channel is identified.
+ decayTimeCh = decayTime[chanArr == chanNum]
- #Find the first and last entry
- firstDecayTime = 0;#np.min(decayTimeCh).astype(np.int32)
+ # Find the first and last entry
+ firstDecayTime = 0 # np.min(decayTimeCh).astype(np.int32)
tempLastDecayTime = np.max(decayTimeCh).astype(np.int32)
- #We floor this as the last bin is always incomplete and so we discard photons.
+ # We floor this as the last bin is always incomplete and so we discard photons.
numBins = np.floor((tempLastDecayTime-firstDecayTime)/winInt)
lastDecayTime = numBins*winInt
-
- bins = np.linspace(firstDecayTime,lastDecayTime, int(numBins)+1)
-
+ bins = np.linspace(firstDecayTime, lastDecayTime, int(numBins)+1)
photonsInBin, jnk = np.histogram(decayTimeCh, bins)
- #bins are valued as half their span.
+ # bins are valued as half their span.
decayScale = bins[:-1]+(winInt/2)
#decayScale = np.arange(0,decayTimeCh.shape[0])
-
-
-
return list(photonsInBin), list(decayScale)
diff --git a/pycorrfit/readfiles/read_pt3_scripts/correlation_objects.py b/pycorrfit/readfiles/read_pt3_scripts/correlation_objects.py
index f292aa6e..fc15c669 100644
--- a/pycorrfit/readfiles/read_pt3_scripts/correlation_objects.py
+++ b/pycorrfit/readfiles/read_pt3_scripts/correlation_objects.py
@@ -32,9 +32,9 @@
class picoObject():
# This is the class which holds the .pt3 data and parameters
- def __init__(self,filepath, par_obj, fit_obj):
+ def __init__(self, filepath, par_obj, fit_obj):
- #parameter object and fit object. If
+ # parameter object and fit object. If
self.par_obj = par_obj
self.fit_obj = fit_obj
self.type = 'mainObject'
@@ -45,21 +45,20 @@ def __init__(self,filepath, par_obj, fit_obj):
self.name = self.nameAndExt[0]
self.ext = self.nameAndExt[-1]
- self.par_obj.data.append(filepath);
+ self.par_obj.data.append(filepath)
self.par_obj.objectRef.append(self)
- #Imports pt3 file format to object.
+ # Imports pt3 file format to object.
self.unqID = self.par_obj.numOfLoaded
- #For fitting.
+ # For fitting.
self.objId1 = None
self.objId2 = None
self.objId3 = None
self.objId4 = None
- self.processData();
-
- self.plotOn = True;
+ self.processData()
+ self.plotOn = True
def processData(self):
@@ -69,136 +68,144 @@ def processData(self):
self.winInt = self.par_obj.winInt
self.photonCountBin = self.par_obj.photonCountBin
- #File import
+ # File import
if self.ext == 'pt3':
- self.subChanArr, self.trueTimeArr, self.dTimeArr,self.resolution = pt3import(self.filepath)
+ self.subChanArr, self.trueTimeArr, self.dTimeArr, self.resolution = pt3import(
+ self.filepath)
if self.ext == 'csv':
- self.subChanArr, self.trueTimeArr, self.dTimeArr,self.resolution = csvimport(self.filepath)
- #If the file is empty.
+ self.subChanArr, self.trueTimeArr, self.dTimeArr, self.resolution = csvimport(
+ self.filepath)
+ # If the file is empty.
if self.subChanArr == None:
- #Undoes any preparation of resource.
- self.par_obj.data.pop(-1);
+ # Undoes any preparation of resource.
+ self.par_obj.data.pop(-1)
self.par_obj.objectRef.pop(-1)
self.exit = True
- self.par_obj.image_status_text.showMessage("Your sample is not in the correct format.")
+ self.par_obj.image_status_text.showMessage(
+ "Your sample is not in the correct format.")
self.par_obj.fit_obj.app.processEvents()
return
-
-
- #Colour assigned to file.
+ # Colour assigned to file.
self.color = self.par_obj.colors[self.unqID % len(self.par_obj.colors)]
- #How many channels there are in the files.
- self.numOfCH = np.unique(np.array(self.subChanArr)).__len__()-1 #Minus 1 because not interested in channel 15.
+ # How many channels there are in the files.
+ # Minus 1 because not interested in channel 15.
+ self.numOfCH = np.unique(np.array(self.subChanArr)).__len__()-1
- #Finds the numbers which address the channels.
+ # Finds the numbers which address the channels.
self.ch_present = np.unique(np.array(self.subChanArr[0:100]))
- #Calculates decay function for both channels.
- self.photonDecayCh1,self.decayScale1 = delayTime2bin(np.array(self.dTimeArr),np.array(self.subChanArr),self.ch_present[0],self.winInt)
+ # Calculates decay function for both channels.
+ self.photonDecayCh1, self.decayScale1 = delayTime2bin(np.array(
+ self.dTimeArr), np.array(self.subChanArr), self.ch_present[0], self.winInt)
- if self.numOfCH == 2:
- self.photonDecayCh2,self.decayScale2 = delayTime2bin(np.array(self.dTimeArr),np.array(self.subChanArr),self.ch_present[1],self.winInt)
+ if self.numOfCH == 2:
+ self.photonDecayCh2, self.decayScale2 = delayTime2bin(np.array(
+ self.dTimeArr), np.array(self.subChanArr), self.ch_present[1], self.winInt)
- #Time series of photon counts. For visualisation.
- self.timeSeries1,self.timeSeriesScale1 = delayTime2bin(np.array(self.trueTimeArr)/1000000,np.array(self.subChanArr),self.ch_present[0],self.photonCountBin)
+ # Time series of photon counts. For visualisation.
+ self.timeSeries1, self.timeSeriesScale1 = delayTime2bin(np.array(
+ self.trueTimeArr)/1000000, np.array(self.subChanArr), self.ch_present[0], self.photonCountBin)
unit = self.timeSeriesScale1[-1]/self.timeSeriesScale1.__len__()
- #Converts to counts per
+ # Converts to counts per
self.kcount_CH1 = np.average(self.timeSeries1)
- raw_count = np.average(self.timeSeries1) #This is the unnormalised intensity count for int_time duration (the first moment)
+ # This is the unnormalised intensity count for int_time duration (the first moment)
+ raw_count = np.average(self.timeSeries1)
var_count = np.var(self.timeSeries1)
- self.brightnessNandBCH0=(((var_count -raw_count)/(raw_count))/(float(unit)))
+ self.brightnessNandBCH0 = (
+ ((var_count - raw_count)/(raw_count))/(float(unit)))
if (var_count-raw_count) == 0:
- self.numberNandBCH0 =0
+ self.numberNandBCH0 = 0
else:
self.numberNandBCH0 = (raw_count**2/(var_count-raw_count))
+ if self.numOfCH == 2:
-
- if self.numOfCH == 2:
-
- self.timeSeries2,self.timeSeriesScale2 = delayTime2bin(np.array(self.trueTimeArr)/1000000,np.array(self.subChanArr),self.ch_present[1],self.photonCountBin)
+ self.timeSeries2, self.timeSeriesScale2 = delayTime2bin(np.array(
+ self.trueTimeArr)/1000000, np.array(self.subChanArr), self.ch_present[1], self.photonCountBin)
unit = self.timeSeriesScale2[-1]/self.timeSeriesScale2.__len__()
self.kcount_CH2 = np.average(self.timeSeries2)
- raw_count = np.average(self.timeSeries2) #This is the unnormalised intensity count for int_time duration (the first moment)
+ # This is the unnormalised intensity count for int_time duration (the first moment)
+ raw_count = np.average(self.timeSeries2)
var_count = np.var(self.timeSeries2)
- self.brightnessNandBCH1= (((var_count -raw_count)/(raw_count))/(float(unit)))
+ self.brightnessNandBCH1 = (
+ ((var_count - raw_count)/(raw_count))/(float(unit)))
if (var_count-raw_count) == 0:
- self.numberNandBCH1 =0
+ self.numberNandBCH1 = 0
else:
self.numberNandBCH1 = (raw_count**2/(var_count-raw_count))
-
-
- #Calculates the Auto and Cross-correlation functions.
- self.crossAndAuto(np.array(self.trueTimeArr),np.array(self.subChanArr))
+ # Calculates the Auto and Cross-correlation functions.
+ self.crossAndAuto(np.array(self.trueTimeArr),
+ np.array(self.subChanArr))
if self.fit_obj != None:
- #If fit object provided then creates fit objects.
+ # If fit object provided then creates fit objects.
if self.objId1 == None:
- corrObj= corrObject(self.filepath,self.fit_obj);
+ corrObj = corrObject(self.filepath, self.fit_obj)
self.objId1 = corrObj.objId
self.fit_obj.objIdArr.append(corrObj.objId)
self.objId1.param = copy.deepcopy(self.fit_obj.def_param)
self.objId1.name = self.name+'_CH0_Auto_Corr'
- self.objId1.ch_type = 0 #channel 0 Auto
+ self.objId1.ch_type = 0 # channel 0 Auto
self.objId1.siblings = None
self.objId1.prepare_for_fit()
self.objId1.kcount = self.kcount_CH1
- self.objId1.autoNorm = np.array(self.autoNorm[:,0,0]).reshape(-1)
+ self.objId1.autoNorm = np.array(self.autoNorm[:, 0, 0]).reshape(-1)
self.objId1.autotime = np.array(self.autotime).reshape(-1)
self.objId1.param = copy.deepcopy(self.fit_obj.def_param)
-
- if self.numOfCH == 2:
+ if self.numOfCH == 2:
if self.objId3 == None:
- corrObj= corrObject(self.filepath,self.fit_obj);
+ corrObj = corrObject(self.filepath, self.fit_obj)
self.objId3 = corrObj.objId
self.objId3.param = copy.deepcopy(self.fit_obj.def_param)
self.fit_obj.objIdArr.append(corrObj.objId)
self.objId3.name = self.name+'_CH1_Auto_Corr'
- self.objId3.ch_type = 1 #channel 1 Auto
+ self.objId3.ch_type = 1 # channel 1 Auto
self.objId3.siblings = None
self.objId3.prepare_for_fit()
self.objId3.kcount = self.kcount_CH2
- self.objId3.autoNorm = np.array(self.autoNorm[:,1,1]).reshape(-1)
+ self.objId3.autoNorm = np.array(
+ self.autoNorm[:, 1, 1]).reshape(-1)
self.objId3.autotime = np.array(self.autotime).reshape(-1)
self.objId3.param = copy.deepcopy(self.fit_obj.def_param)
if self.objId2 == None:
- corrObj= corrObject(self.filepath,self.fit_obj);
+ corrObj = corrObject(self.filepath, self.fit_obj)
self.objId2 = corrObj.objId
self.objId2.param = copy.deepcopy(self.fit_obj.def_param)
self.fit_obj.objIdArr.append(corrObj.objId)
self.objId2.name = self.name+'_CH01_Cross_Corr'
- self.objId2.ch_type = 2 #01cross
+ self.objId2.ch_type = 2 # 01cross
self.objId2.siblings = None
self.objId2.prepare_for_fit()
- self.objId2.autoNorm = np.array(self.autoNorm[:,0,1]).reshape(-1)
+ self.objId2.autoNorm = np.array(
+ self.autoNorm[:, 0, 1]).reshape(-1)
self.objId2.autotime = np.array(self.autotime).reshape(-1)
self.objId2.param = copy.deepcopy(self.fit_obj.def_param)
-
if self.objId4 == None:
- corrObj= corrObject(self.filepath,self.fit_obj);
+ corrObj = corrObject(self.filepath, self.fit_obj)
self.objId4 = corrObj.objId
self.objId4.param = copy.deepcopy(self.fit_obj.def_param)
self.fit_obj.objIdArr.append(corrObj.objId)
self.objId4.name = self.name+'_CH10_Cross_Corr'
- self.objId4.ch_type = 3 #10cross
+ self.objId4.ch_type = 3 # 10cross
self.objId4.siblings = None
self.objId4.prepare_for_fit()
- self.objId4.autoNorm = np.array(self.autoNorm[:,1,0]).reshape(-1)
+ self.objId4.autoNorm = np.array(
+ self.autoNorm[:, 1, 0]).reshape(-1)
self.objId4.autotime = np.array(self.autotime).reshape(-1)
self.objId4.param = copy.deepcopy(self.fit_obj.def_param)
@@ -211,59 +218,63 @@ def processData(self):
del self.subChanArr
del self.trueTimeArr
del self.dTimeArr
- def crossAndAuto(self,trueTimeArr,subChanArr):
- #For each channel we loop through and find only those in the correct time gate.
- #We only want photons in channel 1 or two.
- y = trueTimeArr[subChanArr < 3]
- validPhotons = subChanArr[subChanArr < 3 ]
-
- #Creates boolean for photon events in either channel.
- num = np.zeros((validPhotons.shape[0],2))
- num[:,0] = (np.array([np.array(validPhotons) ==self.ch_present[0]])).astype(np.int32)
- if self.numOfCH ==2:
- num[:,1] = (np.array([np.array(validPhotons) ==self.ch_present[1]])).astype(np.int32)
+ def crossAndAuto(self, trueTimeArr, subChanArr):
+ # For each channel we loop through and find only those in the correct time gate.
+ # We only want photons in channel 1 or two.
+ y = trueTimeArr[subChanArr < 3]
+ validPhotons = subChanArr[subChanArr < 3]
+ # Creates boolean for photon events in either channel.
+ num = np.zeros((validPhotons.shape[0], 2))
+ num[:, 0] = (np.array([np.array(validPhotons) ==
+ self.ch_present[0]])).astype(np.int32)
+ if self.numOfCH == 2:
+ num[:, 1] = (np.array([np.array(validPhotons) ==
+ self.ch_present[1]])).astype(np.int32)
- self.count0 = np.sum(num[:,0])
- self.count1 = np.sum(num[:,1])
+ self.count0 = np.sum(num[:, 0])
+ self.count1 = np.sum(num[:, 1])
t1 = time.time()
- auto, self.autotime = tttr2xfcs(y,num,self.NcascStart,self.NcascEnd, self.Nsub)
+ auto, self.autotime = tttr2xfcs(
+ y, num, self.NcascStart, self.NcascEnd, self.Nsub)
t2 = time.time()
-
-
- #Normalisation of the TCSPC data:
+ # Normalisation of the TCSPC data:
maxY = np.ceil(max(self.trueTimeArr))
self.autoNorm = np.zeros((auto.shape))
- self.autoNorm[:,0,0] = ((auto[:,0,0]*maxY)/(self.count0*self.count0))-1
-
- if self.numOfCH == 2:
- self.autoNorm[:,1,1] = ((auto[:,1,1]*maxY)/(self.count1*self.count1))-1
- self.autoNorm[:,1,0] = ((auto[:,1,0]*maxY)/(self.count1*self.count0))-1
- self.autoNorm[:,0,1] = ((auto[:,0,1]*maxY)/(self.count0*self.count1))-1
-
-
- #Normalisaation of the decay functions.
- self.photonDecayCh1Min = self.photonDecayCh1-np.min(self.photonDecayCh1)
- self.photonDecayCh1Norm = self.photonDecayCh1Min/np.max(self.photonDecayCh1Min)
+ self.autoNorm[:, 0, 0] = (
+ (auto[:, 0, 0]*maxY)/(self.count0*self.count0))-1
+ if self.numOfCH == 2:
+ self.autoNorm[:, 1, 1] = (
+ (auto[:, 1, 1]*maxY)/(self.count1*self.count1))-1
+ self.autoNorm[:, 1, 0] = (
+ (auto[:, 1, 0]*maxY)/(self.count1*self.count0))-1
+ self.autoNorm[:, 0, 1] = (
+ (auto[:, 0, 1]*maxY)/(self.count0*self.count1))-1
+
+ # Normalisaation of the decay functions.
+ self.photonDecayCh1Min = self.photonDecayCh1 - \
+ np.min(self.photonDecayCh1)
+ self.photonDecayCh1Norm = self.photonDecayCh1Min / \
+ np.max(self.photonDecayCh1Min)
- if self.numOfCH == 2:
- self.photonDecayCh2Min = self.photonDecayCh2-np.min(self.photonDecayCh2)
- self.photonDecayCh2Norm = self.photonDecayCh2Min/np.max(self.photonDecayCh2Min)
+ if self.numOfCH == 2:
+ self.photonDecayCh2Min = self.photonDecayCh2 - \
+ np.min(self.photonDecayCh2)
+ self.photonDecayCh2Norm = self.photonDecayCh2Min / \
+ np.max(self.photonDecayCh2Min)
return
-
-
class subPicoObject():
- def __init__(self,parentId,xmin,xmax,TGid,par_obj):
- #Binning window for decay function
+ def __init__(self, parentId, xmin, xmax, TGid, par_obj):
+ # Binning window for decay function
self.TGid = TGid
- #Parameters for auto-correlation and cross-correlation.
+ # Parameters for auto-correlation and cross-correlation.
self.parentId = parentId
self.par_obj = par_obj
self.NcascStart = self.parentId.NcascStart
@@ -273,7 +284,7 @@ def __init__(self,parentId,xmin,xmax,TGid,par_obj):
self.ext = self.parentId.ext
self.type = 'subObject'
- #Appends the object to the subObject register.
+ # Appends the object to the subObject register.
self.par_obj.subObjectRef.append(self)
self.unqID = self.par_obj.subNum
self.parentUnqID = self.parentId.unqID
@@ -290,180 +301,183 @@ def __init__(self,parentId,xmin,xmax,TGid,par_obj):
self.xmax = xmax
self.nameAndExt = os.path.basename(self.filepath).split('.')
- self.name = 'TG-'+str(self.unqID)+'-xmin_'+str(round(xmin,0))+'-xmax_'+str(round(xmax,0))+'-'+self.nameAndExt[0]
+ self.name = 'TG-'+str(self.unqID)+'-xmin_'+str(round(xmin, 0)) + \
+ '-xmax_'+str(round(xmax, 0))+'-'+self.nameAndExt[0]
self.objId1 = None
self.objId2 = None
self.objId3 = None
self.objId4 = None
- self.processData();
+ self.processData()
self.plotOn = True
-
def processData(self):
- self.NcascStart= self.par_obj.NcascStart
- self.NcascEnd= self.par_obj.NcascEnd
+ self.NcascStart = self.par_obj.NcascStart
+ self.NcascEnd = self.par_obj.NcascEnd
self.Nsub = self.par_obj.Nsub
self.winInt = self.par_obj.winInt
-
#self.subChanArr, self.trueTimeArr, self.dTimeArr,self.resolution = pt3import(self.filepath)
if self.ext == 'pt3':
- self.subChanArr, self.trueTimeArr, self.dTimeArr,self.resolution = pt3import(self.filepath)
+ self.subChanArr, self.trueTimeArr, self.dTimeArr, self.resolution = pt3import(
+ self.filepath)
if self.ext == 'csv':
- self.subChanArr, self.trueTimeArr, self.dTimeArr,self.resolution = csvimport(self.filepath)
- #If the file is empty.
- #if self.subChanArr == None:
- #Undoes any preparation of resource.
+ self.subChanArr, self.trueTimeArr, self.dTimeArr, self.resolution = csvimport(
+ self.filepath)
+ # If the file is empty.
+ # if self.subChanArr == None:
+ # Undoes any preparation of resource.
# self.par_obj.subObjectRef.pop(-1)
- #self.exit = True
+ #self.exit = True
# return
-
- self.subArrayGeneration(self.xmin,self.xmax)
+ self.subArrayGeneration(self.xmin, self.xmax)
self.dTimeMin = self.parentId.dTimeMin
self.dTimeMax = self.parentId.dTimeMax
self.subDTimeMin = self.dTimeMin
self.subDTimeMax = self.dTimeMax
- #Time series of photon counts. For visualisation.
- self.timeSeries1,self.timeSeriesScale1 = delayTime2bin(np.array(self.trueTimeArr)/1000000,np.array(self.subChanArr),self.ch_present[0],self.photonCountBin)
+ # Time series of photon counts. For visualisation.
+ self.timeSeries1, self.timeSeriesScale1 = delayTime2bin(np.array(
+ self.trueTimeArr)/1000000, np.array(self.subChanArr), self.ch_present[0], self.photonCountBin)
unit = self.timeSeriesScale1[-1]/self.timeSeriesScale1.__len__()
self.kcount_CH1 = np.average(self.timeSeries1)
- if self.numOfCH == 2:
+ if self.numOfCH == 2:
- self.timeSeries2,self.timeSeriesScale2 = delayTime2bin(np.array(self.trueTimeArr)/1000000,np.array(self.subChanArr),self.ch_present[1],self.photonCountBin)
+ self.timeSeries2, self.timeSeriesScale2 = delayTime2bin(np.array(
+ self.trueTimeArr)/1000000, np.array(self.subChanArr), self.ch_present[1], self.photonCountBin)
unit = self.timeSeriesScale2[-1]/self.timeSeriesScale2.__len__()
self.kcount_CH2 = np.average(self.timeSeries2)
-
-
- #Adds names to the fit function for later fitting.
+ # Adds names to the fit function for later fitting.
if self.objId1 == None:
- corrObj= corrObject(self.filepath,self.fit_obj);
+ corrObj = corrObject(self.filepath, self.fit_obj)
self.objId1 = corrObj.objId
self.fit_obj.objIdArr.append(corrObj.objId)
self.objId1.param = copy.deepcopy(self.fit_obj.def_param)
self.objId1.name = self.name+'_CH0_Auto_Corr'
- self.objId1.ch_type = 0 #channel 0 Auto
+ self.objId1.ch_type = 0 # channel 0 Auto
self.objId1.siblings = None
self.objId1.prepare_for_fit()
self.objId1.kcount = self.kcount_CH1
- self.objId1.autoNorm = np.array(self.autoNorm[:,0,0]).reshape(-1)
+ self.objId1.autoNorm = np.array(self.autoNorm[:, 0, 0]).reshape(-1)
self.objId1.autotime = np.array(self.autotime).reshape(-1)
self.objId1.param = copy.deepcopy(self.fit_obj.def_param)
-
if self.numOfCH == 2:
if self.objId3 == None:
- corrObj= corrObject(self.filepath,self.fit_obj);
+ corrObj = corrObject(self.filepath, self.fit_obj)
self.objId3 = corrObj.objId
self.fit_obj.objIdArr.append(corrObj.objId)
self.objId3.param = copy.deepcopy(self.fit_obj.def_param)
self.objId3.name = self.name+'_CH1_Auto_Corr'
- self.objId3.ch_type = 1 #channel 1 Auto
+ self.objId3.ch_type = 1 # channel 1 Auto
self.objId3.siblings = None
self.objId3.prepare_for_fit()
self.objId3.kcount = self.kcount_CH2
- self.objId3.autoNorm = np.array(self.autoNorm[:,1,1]).reshape(-1)
+ self.objId3.autoNorm = np.array(self.autoNorm[:, 1, 1]).reshape(-1)
self.objId3.autotime = np.array(self.autotime).reshape(-1)
self.objId3.param = copy.deepcopy(self.fit_obj.def_param)
if self.objId2 == None:
- corrObj= corrObject(self.filepath,self.fit_obj);
+ corrObj = corrObject(self.filepath, self.fit_obj)
self.objId2 = corrObj.objId
self.objId2.param = copy.deepcopy(self.fit_obj.def_param)
self.fit_obj.objIdArr.append(corrObj.objId)
self.objId2.name = self.name+'_CH01_Cross_Corr'
- self.objId2.ch_type = 2 #channel 01 Cross
+ self.objId2.ch_type = 2 # channel 01 Cross
self.objId2.siblings = None
self.objId2.prepare_for_fit()
- self.objId2.autoNorm = np.array(self.autoNorm[:,0,1]).reshape(-1)
+ self.objId2.autoNorm = np.array(self.autoNorm[:, 0, 1]).reshape(-1)
self.objId2.autotime = np.array(self.autotime).reshape(-1)
self.objId2.param = copy.deepcopy(self.fit_obj.def_param)
if self.objId4 == None:
- corrObj= corrObject(self.filepath,self.fit_obj);
+ corrObj = corrObject(self.filepath, self.fit_obj)
self.objId4 = corrObj.objId
self.objId4.param = copy.deepcopy(self.fit_obj.def_param)
self.fit_obj.objIdArr.append(corrObj.objId)
self.objId4.name = self.name+'_CH10_Cross_Corr'
- self.objId4.ch_type = 3 #channel 10 Cross
+ self.objId4.ch_type = 3 # channel 10 Cross
self.objId4.siblings = None
self.objId4.prepare_for_fit()
- self.objId4.autoNorm = np.array(self.autoNorm[:,1,0]).reshape(-1)
+ self.objId4.autoNorm = np.array(self.autoNorm[:, 1, 0]).reshape(-1)
self.objId4.autotime = np.array(self.autotime).reshape(-1)
-
-
self.fit_obj.fill_series_list()
del self.subChanArr
del self.trueTimeArr
del self.dTimeArr
-
-
- def subArrayGeneration(self,xmin,xmax):
- if(xmax=xmin, self.dTimeArr<=xmax).astype(np.bool)
+ # Finds those photons which arrive above certain time or below certain time.
+ photonInd = np.logical_and(
+ self.dTimeArr >= xmin, self.dTimeArr <= xmax).astype(np.bool)
self.subChanArr[np.invert(photonInd).astype(np.bool)] = 16
self.crossAndAuto()
return
+
def crossAndAuto(self):
- #We only want photons in channel 1 or two.
+ # We only want photons in channel 1 or two.
validPhotons = self.subChanArr[self.subChanArr < 3]
y = self.trueTimeArr[self.subChanArr < 3]
- #Creates boolean for photon events in either channel.
- num = np.zeros((validPhotons.shape[0],2))
- num[:,0] = (np.array([np.array(validPhotons) ==self.ch_present[0]])).astype(np.int)
+ # Creates boolean for photon events in either channel.
+ num = np.zeros((validPhotons.shape[0], 2))
+ num[:, 0] = (np.array([np.array(validPhotons) ==
+ self.ch_present[0]])).astype(np.int)
if self.numOfCH == 2:
- num[:,1] = (np.array([np.array(validPhotons) ==self.ch_present[1]])).astype(np.int)
+ num[:, 1] = (np.array([np.array(validPhotons) ==
+ self.ch_present[1]])).astype(np.int)
- self.count0 = np.sum(num[:,0])
- self.count1 = np.sum(num[:,1])
- #Function which calculates auto-correlation and cross-correlation.
+ self.count0 = np.sum(num[:, 0])
+ self.count1 = np.sum(num[:, 1])
+ # Function which calculates auto-correlation and cross-correlation.
-
-
- auto, self.autotime = tttr2xfcs(y,num,self.NcascStart,self.NcascEnd, self.Nsub)
+ auto, self.autotime = tttr2xfcs(
+ y, num, self.NcascStart, self.NcascEnd, self.Nsub)
maxY = np.ceil(max(self.trueTimeArr))
self.autoNorm = np.zeros((auto.shape))
- self.autoNorm[:,0,0] = ((auto[:,0,0]*maxY)/(self.count0*self.count0))-1
- if self.numOfCH ==2:
- self.autoNorm[:,1,1] = ((auto[:,1,1]*maxY)/(self.count1*self.count1))-1
- self.autoNorm[:,1,0] = ((auto[:,1,0]*maxY)/(self.count1*self.count0))-1
- self.autoNorm[:,0,1] = ((auto[:,0,1]*maxY)/(self.count0*self.count1))-1
+ self.autoNorm[:, 0, 0] = (
+ (auto[:, 0, 0]*maxY)/(self.count0*self.count0))-1
+ if self.numOfCH == 2:
+ self.autoNorm[:, 1, 1] = (
+ (auto[:, 1, 1]*maxY)/(self.count1*self.count1))-1
+ self.autoNorm[:, 1, 0] = (
+ (auto[:, 1, 0]*maxY)/(self.count1*self.count0))-1
+ self.autoNorm[:, 0, 1] = (
+ (auto[:, 0, 1]*maxY)/(self.count0*self.count1))-1
return
+
class corrObject():
- def __init__(self,filepath,parentFn):
- #the container for the object.
+ def __init__(self, filepath, parentFn):
+ # the container for the object.
self.parentFn = parentFn
self.type = 'corrObject'
self.filepath = str(filepath)
self.nameAndExt = os.path.basename(self.filepath).split('.')
self.name = self.nameAndExt[0]
self.ext = self.nameAndExt[-1]
- self.autoNorm=[]
- self.autotime=[]
- self.model_autoNorm =[]
+ self.autoNorm = []
+ self.autotime = []
+ self.model_autoNorm = []
self.model_autotime = []
- self.datalen= []
- self.objId = self;
+ self.datalen = []
+ self.objId = self
self.param = []
self.goodFit = True
self.fitted = False
@@ -483,116 +497,109 @@ def prepare_for_fit(self):
self.toFit = True
if self.parentFn.ch_check_ch10.isChecked() == True and self.ch_type == 3:
self.toFit = True
- #self.parentFn.modelFitSel.clear()
- #for objId in self.parentFn.objIdArr:
+ # self.parentFn.modelFitSel.clear()
+ # for objId in self.parentFn.objIdArr:
# if objId.toFit == True:
# self.parentFn.modelFitSel.addItem(objId.name)
self.parentFn.updateFitList()
- def residual(self, param, x, data,options):
- A = equation_(param, x,options)
+ def residual(self, param, x, data, options):
+
+ A = equation_(param, x, options)
residuals = data-A
return residuals
- def fitToParameters(self):
- #self.parentFn.updateParamFirst()
- #self.parentFn.updateTableFirst()
- #self.parentFn.updateParamFirst()
+ def fitToParameters(self):
+ # self.parentFn.updateParamFirst()
+ # self.parentFn.updateTableFirst()
+ # self.parentFn.updateParamFirst()
- #Populate param for lmfit.
+ # Populate param for lmfit.
param = Parameters()
#self.def_param.add('A1', value=1.0, min=0,max=1.0, vary=False)
for art in self.param:
if self.param[art]['to_show'] == True:
- param.add(art, value=float(self.param[art]['value']), min=float(self.param[art]['minv']) ,max=float(self.param[art]['maxv']), vary=self.param[art]['vary']);
-
+ param.add(art, value=float(self.param[art]['value']), min=float(
+ self.param[art]['minv']), max=float(self.param[art]['maxv']), vary=self.param[art]['vary'])
- #Find the index of the nearest point in the scale.
+ # Find the index of the nearest point in the scale.
data = np.array(self.autoNorm).astype(np.float64).reshape(-1)
scale = np.array(self.autotime).astype(np.float64).reshape(-1)
- self.indx_L = int(np.argmin(np.abs(scale - self.parentFn.dr.xpos)))
- self.indx_R = int(np.argmin(np.abs(scale - self.parentFn.dr1.xpos)))
+ self.indx_L = int(np.argmin(np.abs(scale - self.parentFn.dr.xpos)))
+ self.indx_R = int(np.argmin(np.abs(scale - self.parentFn.dr1.xpos)))
- #Run the fitting.
- res = minimize(self.residual, param, args=(scale[self.indx_L:self.indx_R+1],data[self.indx_L:self.indx_R+1], self.parentFn.def_options))
+ # Run the fitting.
+ res = minimize(self.residual, param, args=(
+ scale[self.indx_L:self.indx_R+1], data[self.indx_L:self.indx_R+1], self.parentFn.def_options))
- #Repopulate the parameter object.
+ # Repopulate the parameter object.
for art in self.param:
if self.param[art]['to_show'] == True and self.param[art]['calc'] == False:
self.param[art]['value'] = param[art].value
self.param[art]['stderr'] = float(param[art].stderr)
- #Extra parameters, which are not fit or inherited.
+ # Extra parameters, which are not fit or inherited.
#self.param['N_FCS']['value'] = np.round(1/self.param['GN0']['value'],4)
-
self.residualVar = res.residual
output = fit_report(param)
- print('residual',res.chisqr)
- if(res.chisqr>0.05):
- print('CAUTION DATA DID NOT FIT WELL CHI^2 >0.05',res.chisqr)
+ print('residual', res.chisqr)
+ if(res.chisqr > 0.05):
+ print('CAUTION DATA DID NOT FIT WELL CHI^2 >0.05', res.chisqr)
self.goodFit = False
else:
self.goodFit = True
self.fitted = True
self.chisqr = res.chisqr
- self.localTime = time.asctime( time.localtime(time.time()) )
-
-
+ self.localTime = time.asctime(time.localtime(time.time()))
- #self.parentFn.updateTableFirst();
- self.model_autoNorm = equation_(param, scale[self.indx_L:self.indx_R+1],self.parentFn.def_options)
+ # self.parentFn.updateTableFirst();
+ self.model_autoNorm = equation_(
+ param, scale[self.indx_L:self.indx_R+1], self.parentFn.def_options)
self.model_autotime = scale[self.indx_L:self.indx_R+1]
- #self.parentFn.on_show()
+ # self.parentFn.on_show()
#self.parentFn.axes.plot(model_autotime,model_autoNorm, 'o-')
- #self.parentFn.canvas.draw();
-
- def load_from_file(self,channel):
- tscale = [];
- tdata = [];
- int_tscale =[];
- int_tdata=[];
+ # self.parentFn.canvas.draw();
+ def load_from_file(self, channel):
+ tscale = []
+ tdata = []
+ int_tscale = []
+ int_tdata = []
if self.ext == 'fcs':
-
-
corrObj = self
- text =[0]
- r_obj = csv.reader(open(corrObj.filepath, 'rb'),delimiter='\t')
+ text = [0]
+ r_obj = csv.reader(open(corrObj.filepath, 'rb'), delimiter='\t')
title = r_obj.next()
line = r_obj.next()
line = r_obj.next()
name = line[1].split(' = ')[1]
read = True
- while read == True:
+ while read == True:
- corrObj = corrObject(self.filepath,self.parentFn);
+ corrObj = corrObject(self.filepath, self.parentFn)
self.parentFn.objIdArr.append(corrObj)
corrObj.name = name
-
-
-
line = r_obj.next()
- text =[]
+ text = []
for part in line:
if part != '':
- text.append(part)
-
+ text.append(part)
- #Reads to first correlation array text.
- while text[0].split(' = ')[0] != 'CorrelationArray' or text[0].split(' = ')[1] == int(0):
+ # Reads to first correlation array text.
+ while text[0].split(' = ')[0] != 'CorrelationArray' or text[0].split(' = ')[1] == int(0):
line = r_obj.next()
- text =[]
+ text = []
for part in line:
if part != '':
text.append(part)
@@ -600,105 +607,89 @@ def load_from_file(self,channel):
tdata = []
tscale = []
-
- while text[0].split(' = ')[0] != 'PhotonCountHistogramArraySize':
+ while text[0].split(' = ')[0] != 'PhotonCountHistogramArraySize':
try:
line = r_obj.next()
except:
read = False
- break;
- text =[]
+ break
+ text = []
for part in line:
if part != '':
text.append(part)
- if text.__len__() >1:
+ if text.__len__() > 1:
tscale.append(float(text[0]))
tdata.append(float(text[1]))
if tdata.__len__() == 0:
corrObj = []
self.parentFn.objIdArr.pop(-1)
- break;
+ break
channel = 0
corrObj.siblings = None
- corrObj.autoNorm= np.array(tdata).astype(np.float64).reshape(-1)
- corrObj.autotime= np.array(tscale).astype(np.float64).reshape(-1)*1000
+ corrObj.autoNorm = np.array(
+ tdata).astype(np.float64).reshape(-1)
+ corrObj.autotime = np.array(tscale).astype(
+ np.float64).reshape(-1)*1000
corrObj.name = corrObj.name+'-CH'+str(channel)
- corrObj.ch_type = channel;
+ corrObj.ch_type = channel
corrObj.param = copy.deepcopy(self.parentFn.def_param)
self.parentFn.fill_series_list()
-
-
-
-
-
-
-
if self.ext == 'SIN':
self.parentFn.objIdArr.append(self.objId)
proceed = False
- for line in csv.reader(open(self.filepath, 'rb'),delimiter='\t'):
+ for line in csv.reader(open(self.filepath, 'rb'), delimiter='\t'):
- if proceed =='correlated':
- if line ==[]:
- proceed =False;
+ if proceed == 'correlated':
+ if line == []:
+ proceed = False
else:
tscale.append(float(line[0]))
tdata.append(float(line[channel+1]))
- if proceed =='intensity':
+ if proceed == 'intensity':
- if line ==[]:
- proceed=False;
- elif line.__len__()> 1:
+ if line == []:
+ proceed = False
+ elif line.__len__() > 1:
int_tscale.append(float(line[0]))
int_tdata.append(float(line[channel+1]))
- if (str(line) == "[\'[CorrelationFunction]\']"):
- proceed = 'correlated';
- elif (str(line) == "[\'[IntensityHistory]\']"):
- proceed = 'intensity';
-
-
-
+ if (str(line) == "[\'[CorrelationFunction]\']"):
+ proceed = 'correlated'
+ elif (str(line) == "[\'[IntensityHistory]\']"):
+ proceed = 'intensity'
self.siblings = None
- self.autoNorm= np.array(tdata).astype(np.float64).reshape(-1)
- self.autotime= np.array(tscale).astype(np.float64).reshape(-1)*1000
+ self.autoNorm = np.array(tdata).astype(np.float64).reshape(-1)
+ self.autotime = np.array(tscale).astype(
+ np.float64).reshape(-1)*1000
self.name = self.name+'-CH'+str(channel)
- self.ch_type = channel;
- #self.prepare_for_fit()
-
-
-
+ self.ch_type = channel
+ # self.prepare_for_fit()
-
-
- #Average counts per bin. For it to be seconds (Hz), must divide by duration.
+ # Average counts per bin. For it to be seconds (Hz), must divide by duration.
unit = int_tscale[-1]/(int_tscale.__len__()-1)
- #And to be in kHz we divide by 1000.
+ # And to be in kHz we divide by 1000.
self.kcount = np.average(np.array(int_tdata)/unit)/1000
self.param = copy.deepcopy(self.parentFn.def_param)
self.parentFn.fill_series_list()
+ # Where we add the names.
- #Where we add the names.
-
-
- if self.ext == 'csv' or self.ext =='CSV':
+ if self.ext == 'csv' or self.ext == 'CSV':
r_obj = csv.reader(open(self.filepath, 'rb'))
line_one = r_obj.next()
- if line_one.__len__()>1:
+ if line_one.__len__() > 1:
- if float(line_one[1]) == 2:
-
- version = 2
- else:
- print('version not known:',line_one[1])
+ if float(line_one[1]) == 2:
+ version = 2
+ else:
+ print('version not known:', line_one[1])
else:
version = 1
@@ -709,41 +700,40 @@ def load_from_file(self,channel):
c = 0
for line in csv.reader(open(self.filepath, 'rb')):
- if (c >0):
+ if (c > 0):
tscale.append(line[0])
tdata.append(line[1])
- c +=1;
+ c += 1
- self.autoNorm= np.array(tdata).astype(np.float64).reshape(-1)
- self.autotime= np.array(tscale).astype(np.float64).reshape(-1)
+ self.autoNorm = np.array(tdata).astype(np.float64).reshape(-1)
+ self.autotime = np.array(tscale).astype(np.float64).reshape(-1)
self.name = self.name+'-CH'+str(0)
self.ch_type = 0
- self.datalen= len(tdata)
+ self.datalen = len(tdata)
self.param = copy.deepcopy(self.parentFn.def_param)
self.parentFn.fill_series_list()
if version >= 2:
-
numOfCH = float(r_obj.next()[1])
if numOfCH == 1:
self.parentFn.objIdArr.append(self)
- self.type =str(r_obj.next()[1])
+ self.type = str(r_obj.next()[1])
self.ch_type = int(r_obj.next()[1])
self.name = self.name+'-CH'+str(self.ch_type)
line = r_obj.next()
- while line[0] != 'Time (ns)':
+ while line[0] != 'Time (ns)':
if line[0] == 'kcount':
self.kcount = float(line[1])
if line[0] == 'numberNandB':
self.numberNandB = float(line[1])
if line[0] == 'brightnessNandB':
- self.brightnessNandB = float(line[1])
+ self.brightnessNandB = float(line[1])
if line[0] == 'CV':
- self.CV = float(line[1])
+ self.CV = float(line[1])
if line[0] == 'carpet pos':
carpet = int(line[1])
if line[0] == 'pc':
@@ -755,30 +745,30 @@ def load_from_file(self,channel):
line = r_obj.next()
-
if pc_text != False:
- self.name = self.name +'_pc_m'+str(pc_text)
-
+ self.name = self.name + '_pc_m'+str(pc_text)
tscale = []
tdata = []
null = r_obj.next()
line = r_obj.next()
- while line[0] != 'end':
+ while line[0] != 'end':
tscale.append(line[0])
tdata.append(line[1])
line = r_obj.next()
- self.autoNorm= np.array(tdata).astype(np.float64).reshape(-1)
- self.autotime= np.array(tscale).astype(np.float64).reshape(-1)
+ self.autoNorm = np.array(tdata).astype(
+ np.float64).reshape(-1)
+ self.autotime = np.array(tscale).astype(
+ np.float64).reshape(-1)
self.siblings = None
self.param = copy.deepcopy(self.parentFn.def_param)
self.parentFn.fill_series_list()
if numOfCH == 2:
- corrObj2 = corrObject(self.filepath,self.parentFn);
- corrObj3 = corrObject(self.filepath,self.parentFn);
+ corrObj2 = corrObject(self.filepath, self.parentFn)
+ corrObj3 = corrObject(self.filepath, self.parentFn)
self.parentFn.objIdArr.append(self)
self.parentFn.objIdArr.append(corrObj2)
@@ -789,7 +779,6 @@ def load_from_file(self,channel):
corrObj2.type = str(line_type[1])
corrObj3.type = str(line_type[1])
-
line_ch = r_obj.next()
self.ch_type = int(line_ch[1])
corrObj2.ch_type = int(line_ch[2])
@@ -800,18 +789,18 @@ def load_from_file(self,channel):
corrObj3.name = corrObj3.name+'-CH'+str(corrObj3.ch_type)
line = r_obj.next()
- while line[0] != 'Time (ns)':
+ while line[0] != 'Time (ns)':
if line[0] == 'kcount':
self.kcount = float(line[1])
corrObj2.kcount = float(line[2])
if line[0] == 'numberNandB':
self.numberNandB = float(line[1])
- corrObj2.numberNandB = float(line[2])
+ corrObj2.numberNandB = float(line[2])
if line[0] == 'brightnessNandB':
- self.brightnessNandB = float(line[1])
- corrObj2.brightnessNandB = float(line[2])
+ self.brightnessNandB = float(line[1])
+ corrObj2.brightnessNandB = float(line[2])
if line[0] == 'CV':
- self.CV = float(line[1])
+ self.CV = float(line[1])
corrObj2.CV = float(line[2])
corrObj3.CV = float(line[3])
if line[0] == 'carpet pos':
@@ -827,12 +816,10 @@ def load_from_file(self,channel):
line = r_obj.next()
-
-
if pc_text != False:
- self.name = self.name +'_pc_m'+str(pc_text)
- corrObj2.name = corrObj2.name +'_pc_m'+str(pc_text)
- corrObj3.name = corrObj3.name +'_pc_m'+str(pc_text)
+ self.name = self.name + '_pc_m'+str(pc_text)
+ corrObj2.name = corrObj2.name + '_pc_m'+str(pc_text)
+ corrObj3.name = corrObj3.name + '_pc_m'+str(pc_text)
null = r_obj.next()
line = r_obj.next()
@@ -840,7 +827,7 @@ def load_from_file(self,channel):
tdata0 = []
tdata1 = []
tdata2 = []
- while line[0] != 'end':
+ while line[0] != 'end':
tscale.append(line[0])
tdata0.append(line[1])
@@ -848,18 +835,23 @@ def load_from_file(self,channel):
tdata2.append(line[3])
line = r_obj.next()
-
- self.autotime= np.array(tscale).astype(np.float64).reshape(-1)
- corrObj2.autotime= np.array(tscale).astype(np.float64).reshape(-1)
- corrObj3.autotime= np.array(tscale).astype(np.float64).reshape(-1)
-
- self.autoNorm= np.array(tdata0).astype(np.float64).reshape(-1)
- corrObj2.autoNorm= np.array(tdata1).astype(np.float64).reshape(-1)
- corrObj3.autoNorm= np.array(tdata2).astype(np.float64).reshape(-1)
-
- self.siblings = [corrObj2,corrObj3]
- corrObj2.siblings = [self,corrObj3]
- corrObj3.siblings = [self,corrObj2]
+ self.autotime = np.array(tscale).astype(
+ np.float64).reshape(-1)
+ corrObj2.autotime = np.array(
+ tscale).astype(np.float64).reshape(-1)
+ corrObj3.autotime = np.array(
+ tscale).astype(np.float64).reshape(-1)
+
+ self.autoNorm = np.array(tdata0).astype(
+ np.float64).reshape(-1)
+ corrObj2.autoNorm = np.array(
+ tdata1).astype(np.float64).reshape(-1)
+ corrObj3.autoNorm = np.array(
+ tdata2).astype(np.float64).reshape(-1)
+
+ self.siblings = [corrObj2, corrObj3]
+ corrObj2.siblings = [self, corrObj3]
+ corrObj3.siblings = [self, corrObj2]
self.param = copy.deepcopy(self.parentFn.def_param)
corrObj2.param = copy.deepcopy(self.parentFn.def_param)
diff --git a/pycorrfit/readfiles/read_pt3_scripts/fitting_methods.py b/pycorrfit/readfiles/read_pt3_scripts/fitting_methods.py
index a65359d8..deae60f0 100644
--- a/pycorrfit/readfiles/read_pt3_scripts/fitting_methods.py
+++ b/pycorrfit/readfiles/read_pt3_scripts/fitting_methods.py
@@ -18,332 +18,443 @@
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
"""
+
+
def initialise_fcs(int_obj):
- #default options for the fitting.
- int_obj.def_options ={}
-
- int_obj.def_options['Diff_eq'] = 1
- int_obj.def_options['Diff_species'] = 1
- int_obj.def_options['Triplet_eq'] = 1
- int_obj.def_options['Triplet_species'] = 1
-
- int_obj.def_options['Dimen'] =1
-
-
-
- A1 = {'alias':'A1','value':1.0,'minv':0.0,'maxv':1.0,'vary':False,'to_show':True,'stdev':False,'calc':False}
- A2 = {'alias':'A2','value':1.0,'minv':0.0,'maxv':1.0,'vary':False,'to_show':True,'calc':False}
- A3 = {'alias':'A3','value':1.0,'minv':0.0,'maxv':1.0,'vary':False,'to_show':True,'calc':False}
- #The offset
- offset = { 'alias':'offset','value':0.01,'minv':-1.0,'maxv':1.0,'vary':True,'to_show':True,'calc':False}
- #int_obj.defin.add('offset', value=0.0, min=-1.0,max=5.0,vary=False)
- #The amplitude
- GN0 = {'alias':'GN0','minv':0.001,'value':1,'maxv':1.0,'vary':True,'to_show':True,'calc':False}
- #int_obj.def_param.add('GN0', value=1.0, vary=True)
- #The alpha value
- #int_obj.def_param.add('alpha', value=1.0, min=0,max=1.0, vary=True)
- #lateral diffusion coefficent
- txy1 = {'alias':'txy1','value':0.01,'minv':0.001,'maxv':2000.0,'vary':True,'to_show':True,'calc':False}
- txy2 = {'alias':'txy2','value':0.01,'minv':0.001,'maxv':2000.0,'vary':True,'to_show':True,'calc':False}
- txy3 = {'alias':'txy3','value':0.01,'minv':0.001,'maxv':2000.0,'vary':True,'to_show':True,'calc':False}
-
-
-
- alpha1 = {'alias':'alpha1','value':1.0,'minv':0.0,'maxv':2.0,'vary':True,'to_show':True,'calc':False}
- alpha2 = {'alias':'alpha2','value':1.0,'minv':0.0,'maxv':2.0,'vary':True,'to_show':True,'calc':False}
- alpha3 = {'alias':'alpha3','value':1.0,'minv':0.0,'maxv':2.0,'vary':True,'to_show':True,'calc':False}
-
- tz1 = {'alias':'tz1','value':1.0,'minv':0.0,'maxv':1.0,'vary':True,'to_show':True,'calc':False}
- tz2 = {'alias':'tz2','value':1.0,'minv':0.0,'maxv':1.0,'vary':True,'to_show':True,'calc':False}
- tz3 = {'alias':'tz3','value':1.0,'minv':0.0,'maxv':1.0,'vary':True,'to_show':True,'calc':False}
-
- #Axial ratio coefficient
-
- AR1 = {'alias':'AR1','value':1.0,'minv':0.001,'maxv':1000.0,'vary':True,'to_show':True,'calc':False}
- AR2 = {'alias':'AR2','value':1.0,'minv':0.001,'maxv':1000.0,'vary':True,'to_show':True,'calc':False}
- AR3 = {'alias':'AR3','value':1.0,'minv':0.001,'maxv':1000.0,'vary':True,'to_show':True,'calc':False}
-
- B1 = {'alias':'B1','value':1.0,'minv':0.001,'maxv':1000.0,'vary':True,'to_show':True,'calc':False}
- B2 = {'alias':'B2','value':1.0,'minv':0.001,'maxv':1000.0,'vary':True,'to_show':True,'calc':False}
- B3 = {'alias':'B3','value':1.0,'minv':0.001,'maxv':1000.0,'vary':True,'to_show':True,'calc':False}
-
- T1 = {'alias':'T1','value':1.0,'minv':0.0,'maxv':1000.0,'vary':True,'to_show':True,'calc':False}
- T2 = {'alias':'T2','value':1.0,'minv':0.0,'maxv':1000.0,'vary':True,'to_show':True,'calc':False}
- T3 = {'alias':'T3','value':1.0,'minv':0.0,'maxv':1000.0,'vary':True,'to_show':True,'calc':False}
-
- tauT1 = {'alias':'tauT1','value':0.055,'minv':0.001,'maxv':1000.0,'vary':True,'to_show':True,'calc':False}
- tauT2 = {'alias':'tauT2','value':0.055,'minv':0.001,'maxv':1000.0,'vary':True,'to_show':True,'calc':False}
- tauT3 = {'alias':'tauT3','value':0.005,'minv':0.001,'maxv':1000.0,'vary':True,'to_show':True,'calc':False}
-
- N_FCS = {'alias':'N (FCS)','value':0.0,'minv':0.001,'maxv':1000.0,'vary':True,'to_show':True,'calc':True}
- cpm = {'alias':'cpm (kHz)','value':0.0,'minv':0.001,'maxv':1000.0,'vary':True,'to_show':True,'calc':True}
- N_mom = {'alias':'N (mom)','value':0.0,'minv':0.001,'maxv':1000.0,'vary':True,'to_show':True,'calc':True}
- bri = {'alias':'bri (kHz)','value':0.0,'minv':0.001,'maxv':1000.0,'vary':True,'to_show':True,'calc':True}
- CV = {'alias':'Coincidence','value':0.0,'minv':0.001,'maxv':1000.0,'vary':True,'to_show':True,'calc':True}
- f0 = {'alias':'PBC f0','value':0.0,'minv':0.001,'maxv':1000.0,'vary':True,'to_show':True,'calc':True}
- overtb = {'alias':'PBC tb','value':0.0,'minv':0.001,'maxv':1000.0,'vary':True,'to_show':True,'calc':True}
-
-
- ACAC = {'alias':'ACAC','value':0.0,'minv':0.001,'maxv':1000.0,'vary':True,'to_show':True,'calc':True}
- ACCC = {'alias':'ACCC','value':0.0,'minv':0.001,'maxv':1000.0,'vary':True,'to_show':True,'calc':True}
-
-
- int_obj.def_param ={'A1':A1,'A2':A2,'A3':A3,'txy1':txy1,'txy2':txy2,'txy3':txy3,'offset':offset,'GN0':GN0,'alpha1':alpha1,'alpha2':alpha2,'alpha3':alpha3,'tz1':tz1,'tz2':tz2,'tz3':tz3,'AR1':AR1,'AR2':AR2,'AR3':AR3,'B1':B1,'B2':B2,'B3':B3,'T1':T1,'T2':T2,'T3':T3,'tauT1':tauT1,'tauT2':tauT2,'tauT3':tauT3}
- int_obj.def_param['N_FCS'] = N_FCS
- int_obj.def_param['cpm'] = cpm
- int_obj.def_param['N_mom'] = N_mom
- int_obj.def_param['bri'] = bri
- int_obj.def_param['CV'] = CV
- int_obj.def_param['f0'] = f0
- int_obj.def_param['overtb'] = overtb
-
- int_obj.def_param['ACAC'] = ACAC
- int_obj.def_param['ACCC'] = ACCC
-
-
- int_obj.order_list = ['offset','GN0','N_FCS','cpm','A1','A2','A3','txy1','txy2','txy3','tz1','tz2','tz3','alpha1','alpha2','alpha3','AR1','AR2','AR3','B1','B2','B3','T1','T2','T3','tauT1','tauT2','tauT3','N_mom','bri','CV','f0','overtb','ACAC','ACCC']
+ # default options for the fitting.
+ int_obj.def_options = {}
+
+ int_obj.def_options['Diff_eq'] = 1
+ int_obj.def_options['Diff_species'] = 1
+ int_obj.def_options['Triplet_eq'] = 1
+ int_obj.def_options['Triplet_species'] = 1
+
+ int_obj.def_options['Dimen'] = 1
+
+ A1 = {'alias': 'A1', 'value': 1.0, 'minv': 0.0, 'maxv': 1.0,
+ 'vary': False, 'to_show': True, 'stdev': False, 'calc': False}
+ A2 = {'alias': 'A2', 'value': 1.0, 'minv': 0.0, 'maxv': 1.0,
+ 'vary': False, 'to_show': True, 'calc': False}
+ A3 = {'alias': 'A3', 'value': 1.0, 'minv': 0.0, 'maxv': 1.0,
+ 'vary': False, 'to_show': True, 'calc': False}
+ # The offset
+ offset = {'alias': 'offset', 'value': 0.01, 'minv': -1.0,
+ 'maxv': 1.0, 'vary': True, 'to_show': True, 'calc': False}
+ #int_obj.defin.add('offset', value=0.0, min=-1.0,max=5.0,vary=False)
+ # The amplitude
+ GN0 = {'alias': 'GN0', 'minv': 0.001, 'value': 1,
+ 'maxv': 1.0, 'vary': True, 'to_show': True, 'calc': False}
+ #int_obj.def_param.add('GN0', value=1.0, vary=True)
+ # The alpha value
+ #int_obj.def_param.add('alpha', value=1.0, min=0,max=1.0, vary=True)
+ # lateral diffusion coefficent
+ txy1 = {'alias': 'txy1', 'value': 0.01, 'minv': 0.001,
+ 'maxv': 2000.0, 'vary': True, 'to_show': True, 'calc': False}
+ txy2 = {'alias': 'txy2', 'value': 0.01, 'minv': 0.001,
+ 'maxv': 2000.0, 'vary': True, 'to_show': True, 'calc': False}
+ txy3 = {'alias': 'txy3', 'value': 0.01, 'minv': 0.001,
+ 'maxv': 2000.0, 'vary': True, 'to_show': True, 'calc': False}
+
+ alpha1 = {'alias': 'alpha1', 'value': 1.0, 'minv': 0.0,
+ 'maxv': 2.0, 'vary': True, 'to_show': True, 'calc': False}
+ alpha2 = {'alias': 'alpha2', 'value': 1.0, 'minv': 0.0,
+ 'maxv': 2.0, 'vary': True, 'to_show': True, 'calc': False}
+ alpha3 = {'alias': 'alpha3', 'value': 1.0, 'minv': 0.0,
+ 'maxv': 2.0, 'vary': True, 'to_show': True, 'calc': False}
+
+ tz1 = {'alias': 'tz1', 'value': 1.0, 'minv': 0.0,
+ 'maxv': 1.0, 'vary': True, 'to_show': True, 'calc': False}
+ tz2 = {'alias': 'tz2', 'value': 1.0, 'minv': 0.0,
+ 'maxv': 1.0, 'vary': True, 'to_show': True, 'calc': False}
+ tz3 = {'alias': 'tz3', 'value': 1.0, 'minv': 0.0,
+ 'maxv': 1.0, 'vary': True, 'to_show': True, 'calc': False}
+
+ # Axial ratio coefficient
+
+ AR1 = {'alias': 'AR1', 'value': 1.0, 'minv': 0.001,
+ 'maxv': 1000.0, 'vary': True, 'to_show': True, 'calc': False}
+ AR2 = {'alias': 'AR2', 'value': 1.0, 'minv': 0.001,
+ 'maxv': 1000.0, 'vary': True, 'to_show': True, 'calc': False}
+ AR3 = {'alias': 'AR3', 'value': 1.0, 'minv': 0.001,
+ 'maxv': 1000.0, 'vary': True, 'to_show': True, 'calc': False}
+
+ B1 = {'alias': 'B1', 'value': 1.0, 'minv': 0.001,
+ 'maxv': 1000.0, 'vary': True, 'to_show': True, 'calc': False}
+ B2 = {'alias': 'B2', 'value': 1.0, 'minv': 0.001,
+ 'maxv': 1000.0, 'vary': True, 'to_show': True, 'calc': False}
+ B3 = {'alias': 'B3', 'value': 1.0, 'minv': 0.001,
+ 'maxv': 1000.0, 'vary': True, 'to_show': True, 'calc': False}
+
+ T1 = {'alias': 'T1', 'value': 1.0, 'minv': 0.0, 'maxv': 1000.0,
+ 'vary': True, 'to_show': True, 'calc': False}
+ T2 = {'alias': 'T2', 'value': 1.0, 'minv': 0.0, 'maxv': 1000.0,
+ 'vary': True, 'to_show': True, 'calc': False}
+ T3 = {'alias': 'T3', 'value': 1.0, 'minv': 0.0, 'maxv': 1000.0,
+ 'vary': True, 'to_show': True, 'calc': False}
+
+ tauT1 = {'alias': 'tauT1', 'value': 0.055, 'minv': 0.001,
+ 'maxv': 1000.0, 'vary': True, 'to_show': True, 'calc': False}
+ tauT2 = {'alias': 'tauT2', 'value': 0.055, 'minv': 0.001,
+ 'maxv': 1000.0, 'vary': True, 'to_show': True, 'calc': False}
+ tauT3 = {'alias': 'tauT3', 'value': 0.005, 'minv': 0.001,
+ 'maxv': 1000.0, 'vary': True, 'to_show': True, 'calc': False}
+
+ N_FCS = {'alias': 'N (FCS)', 'value': 0.0, 'minv': 0.001,
+ 'maxv': 1000.0, 'vary': True, 'to_show': True, 'calc': True}
+ cpm = {'alias': 'cpm (kHz)', 'value': 0.0, 'minv': 0.001,
+ 'maxv': 1000.0, 'vary': True, 'to_show': True, 'calc': True}
+ N_mom = {'alias': 'N (mom)', 'value': 0.0, 'minv': 0.001,
+ 'maxv': 1000.0, 'vary': True, 'to_show': True, 'calc': True}
+ bri = {'alias': 'bri (kHz)', 'value': 0.0, 'minv': 0.001,
+ 'maxv': 1000.0, 'vary': True, 'to_show': True, 'calc': True}
+ CV = {'alias': 'Coincidence', 'value': 0.0, 'minv': 0.001,
+ 'maxv': 1000.0, 'vary': True, 'to_show': True, 'calc': True}
+ f0 = {'alias': 'PBC f0', 'value': 0.0, 'minv': 0.001,
+ 'maxv': 1000.0, 'vary': True, 'to_show': True, 'calc': True}
+ overtb = {'alias': 'PBC tb', 'value': 0.0, 'minv': 0.001,
+ 'maxv': 1000.0, 'vary': True, 'to_show': True, 'calc': True}
+
+ ACAC = {'alias': 'ACAC', 'value': 0.0, 'minv': 0.001,
+ 'maxv': 1000.0, 'vary': True, 'to_show': True, 'calc': True}
+ ACCC = {'alias': 'ACCC', 'value': 0.0, 'minv': 0.001,
+ 'maxv': 1000.0, 'vary': True, 'to_show': True, 'calc': True}
+
+ int_obj.def_param = {'A1': A1, 'A2': A2, 'A3': A3, 'txy1': txy1, 'txy2': txy2, 'txy3': txy3, 'offset': offset, 'GN0': GN0, 'alpha1': alpha1, 'alpha2': alpha2, 'alpha3': alpha3,
+ 'tz1': tz1, 'tz2': tz2, 'tz3': tz3, 'AR1': AR1, 'AR2': AR2, 'AR3': AR3, 'B1': B1, 'B2': B2, 'B3': B3, 'T1': T1, 'T2': T2, 'T3': T3, 'tauT1': tauT1, 'tauT2': tauT2, 'tauT3': tauT3}
+ int_obj.def_param['N_FCS'] = N_FCS
+ int_obj.def_param['cpm'] = cpm
+ int_obj.def_param['N_mom'] = N_mom
+ int_obj.def_param['bri'] = bri
+ int_obj.def_param['CV'] = CV
+ int_obj.def_param['f0'] = f0
+ int_obj.def_param['overtb'] = overtb
+
+ int_obj.def_param['ACAC'] = ACAC
+ int_obj.def_param['ACCC'] = ACCC
+
+ int_obj.order_list = ['offset', 'GN0', 'N_FCS', 'cpm', 'A1', 'A2', 'A3', 'txy1', 'txy2', 'txy3', 'tz1', 'tz2', 'tz3', 'alpha1', 'alpha2', 'alpha3',
+ 'AR1', 'AR2', 'AR3', 'B1', 'B2', 'B3', 'T1', 'T2', 'T3', 'tauT1', 'tauT2', 'tauT3', 'N_mom', 'bri', 'CV', 'f0', 'overtb', 'ACAC', 'ACCC']
def decide_which_to_show(int_obj):
-
- for art in int_obj.objId_sel.param:
- if int_obj.objId_sel.param[art]['to_show'] == True:
- int_obj.objId_sel.param[art]['to_show'] = False
-
- int_obj.objId_sel.param[ 'offset']['to_show'] = True
- int_obj.objId_sel.param[ 'GN0']['to_show'] = True
-
- int_obj.def_options['Diff_species'] = int_obj.diffNumSpecSpin.value()
- int_obj.def_options['Triplet_species'] =int_obj.tripNumSpecSpin.value()
-
- #Optional parameters
- for i in range(1,int_obj.def_options['Diff_species']+1):
- int_obj.objId_sel.param['A'+str(i)]['to_show'] = True
- int_obj.objId_sel.param['txy'+str(i)]['to_show'] = True
- int_obj.objId_sel.param['alpha'+str(i)]['to_show'] = True
- #2 in this case corresponds to 3D:
- if int_obj.def_options['Dimen'] == 2:
- if int_obj.def_options['Diff_eq'] == 1:
- int_obj.objId_sel.param['tz'+str(i)]['to_show'] = True
-
- if int_obj.def_options['Diff_eq'] == 2:
- int_obj.objId_sel.param[ 'AR'+str(i)]['to_show'] = True
-
- if int_obj.def_options['Triplet_eq'] == 2:
- #Triplet State equation1
- for i in range(1,int_obj.tripNumSpecSpin.value()+1):
- int_obj.objId_sel.param['B'+str(i)]['to_show'] = True
- int_obj.objId_sel.param['tauT'+str(i)]['to_show'] = True
-
- if int_obj.def_options['Triplet_eq'] == 3:
- #Triplet State equation2
- for i in range(1,int_obj.tripNumSpecSpin.value()+1):
- int_obj.objId_sel.param['T'+str(i)]['to_show'] = True
- int_obj.objId_sel.param['tauT'+str(i)]['to_show'] = True
- calc_param_fcs(int_obj,objId=int_obj.objId_sel)
-
-def update_each(int_obj,text):
- """Will try and populate paramaters with what is present in the inteface, but if new option will goto the default"""
- try:
- exec("valueV = int_obj."+text+"_value.value()"); exec("minV = int_obj."+text+"_min.value()"); exec("maxV = int_obj."+text+"_max.value()"); exec("varyV = int_obj."+text+"_vary.isChecked()");
-
- int_obj.objId_sel.param[text]['value'] = valueV
- int_obj.objId_sel.param[text]['minv'] = minV
- int_obj.objId_sel.param[text]['maxv'] = maxV
- int_obj.objId_sel.param[text]['vary'] = varyV
- except:
-
- int_obj.objId_sel.param[text] = copy.deepcopy(int_obj.def_param[text])
+
+ for art in int_obj.objId_sel.param:
+ if int_obj.objId_sel.param[art]['to_show'] == True:
+ int_obj.objId_sel.param[art]['to_show'] = False
+
+ int_obj.objId_sel.param['offset']['to_show'] = True
+ int_obj.objId_sel.param['GN0']['to_show'] = True
+
+ int_obj.def_options['Diff_species'] = int_obj.diffNumSpecSpin.value()
+ int_obj.def_options['Triplet_species'] = int_obj.tripNumSpecSpin.value()
+
+ # Optional parameters
+ for i in range(1, int_obj.def_options['Diff_species']+1):
+ int_obj.objId_sel.param['A'+str(i)]['to_show'] = True
+ int_obj.objId_sel.param['txy'+str(i)]['to_show'] = True
+ int_obj.objId_sel.param['alpha'+str(i)]['to_show'] = True
+ # 2 in this case corresponds to 3D:
+ if int_obj.def_options['Dimen'] == 2:
+ if int_obj.def_options['Diff_eq'] == 1:
+ int_obj.objId_sel.param['tz'+str(i)]['to_show'] = True
+
+ if int_obj.def_options['Diff_eq'] == 2:
+ int_obj.objId_sel.param['AR'+str(i)]['to_show'] = True
+
+ if int_obj.def_options['Triplet_eq'] == 2:
+ # Triplet State equation1
+ for i in range(1, int_obj.tripNumSpecSpin.value()+1):
+ int_obj.objId_sel.param['B'+str(i)]['to_show'] = True
+ int_obj.objId_sel.param['tauT'+str(i)]['to_show'] = True
+
+ if int_obj.def_options['Triplet_eq'] == 3:
+ # Triplet State equation2
+ for i in range(1, int_obj.tripNumSpecSpin.value()+1):
+ int_obj.objId_sel.param['T'+str(i)]['to_show'] = True
+ int_obj.objId_sel.param['tauT'+str(i)]['to_show'] = True
+ calc_param_fcs(int_obj, objId=int_obj.objId_sel)
+
+
+def update_each(int_obj, text):
+ """Will try and populate paramaters with what is present in the inteface, but if new option will goto the default"""
+ try:
+ exec("valueV = int_obj."+text+"_value.value()")
+ exec("minV = int_obj."+text+"_min.value()")
+ exec("maxV = int_obj."+text+"_max.value()")
+ exec("varyV = int_obj."+text+"_vary.isChecked()")
+
+ int_obj.objId_sel.param[text]['value'] = valueV
+ int_obj.objId_sel.param[text]['minv'] = minV
+ int_obj.objId_sel.param[text]['maxv'] = maxV
+ int_obj.objId_sel.param[text]['vary'] = varyV
+ except:
+
+ int_obj.objId_sel.param[text] = copy.deepcopy(int_obj.def_param[text])
+
+
def update_param_fcs(int_obj):
- """Depending on the menu options this function will update the params of the current data set. """
- if int_obj.objId_sel ==None:
- return
- decide_which_to_show(int_obj)
- #Set all the parameters to not show.
-
- for art in int_obj.objId_sel.param:
- if int_obj.objId_sel.param[art]['to_show'] == True:
- update_each(int_obj, art)
-
- calc_param_fcs(int_obj,objId=int_obj.objId_sel)
-def calc_param_fcs(int_obj,objId):
- #Calculated parameters.
- try:
- objId.param['N_FCS']['value'] = 1/objId.param['GN0']['value']
- objId.param['N_FCS']['to_show'] = True
- except:
- objId.param['N_FCS']['value'] = 1
- objId.param['N_FCS']['to_show'] = False
-
-
- try:
- objId.param['cpm']['value'] = float(objId.kcount)/(1/objId.param['GN0']['value'])
- objId.param['cpm']['to_show'] = True
- except:
- objId.param['cpm']['value'] = 1
- objId.param['cpm']['to_show'] = False
- try:
- objId.param['N_mom']['value'] = float(objId.numberNandB)
- objId.param['N_mom']['to_show'] = True
- except:
- objId.param['N_mom']['value'] = 1
- objId.param['N_mom']['to_show'] = False
- try:
- objId.param['bri']['value'] = float(objId.brightnessNandB)
- objId.param['bri']['to_show'] = True
- except:
- objId.param['bri']['value'] = 1
- objId.param['bri']['to_show'] = False
- try:
- objId.param['CV']['value'] = float(objId.CV)
- objId.param['CV']['to_show'] = True
- except:
- pass
- try:
- objId.param['f0']['value'] = float(objId.pbc_f0)
- objId.param['f0']['to_show'] = True
- objId.param['overtb']['value'] = float(objId.pbc_tb)
- objId.param['overtb']['to_show'] = True
- except:
- pass
-
- if int_obj.objIdArr != [] and objId.siblings !=None and objId.ch_type != 2:
-
- if objId.siblings[0].fitted == True:
-
- objId.param['ACAC']['value'] = float(objId.param['GN0']['value'])/float(objId.siblings[0].param['GN0']['value'])
- objId.param['ACAC']['to_show'] = True
- objId.param['ACCC']['value'] = float(objId.param['GN0']['value'])/float(objId.siblings[1].param['GN0']['value'])
- objId.param['ACCC']['to_show'] = True
-
-
-def equation_(param, tc,options):
- """This is equation for fitting"""
-
- #A1 is relative component of fluorescent species
- #tc is tau.
- #txy1 is xy difusion for fluorescent species one.
- #alpha1 is
- #tz1 is z diffusion for fluorescent species one.
- offset =param['offset'].value;
- GN0 =param['GN0'].value;
-
-
- if(options['Dimen'] == 2):
- if(options['Diff_eq']==1):
- #Equation 1A with 3D term.
- if (options['Diff_species'] == 1):
- A1 = param['A1'].value; txy1 = param['txy1'].value; alpha1 = param['alpha1'].value;tz1 = param['tz1'].value;
- #For one diffusing species
- GDiff = (A1*(((1+((tc/txy1)**alpha1))**-1)*((1+(tc/tz1))**-0.5)))
- elif (options['Diff_species'] == 2):
- A1 = param['A1'].value; txy1 = param['txy1'].value; alpha1 = param['alpha1'].value;tz1 = param['tz1'].value;
- A2 = param['A2'].value; txy2 = param['txy2'].value; alpha2 = param['alpha2'].value;tz2 = param['tz2'].value;
- param['A2'].value = 1.0-A1
- A2 = param['A2'].value
- #For two diffusing species
- GDiff = (A1*(((1+((tc/txy1)**alpha1))**-1)*((1+(tc/tz1))**-0.5)))+ (A2*(((1+((tc/txy2)**alpha2))**-1)*((1+(tc/tz2))**-0.5)))
- elif (options['Diff_species'] == 3):
- A1 = param['A1'].value; txy1 = param['txy1'].value; alpha1 = param['alpha1'].value;tz1 = param['tz1'].value;
- A2 = param['A2'].value; txy2 = param['txy2'].value; alpha2 = param['alpha2'].value;tz2 = param['tz2'].value;
- A3 = param['A3'].value; txy3 = param['txy3'].value; alpha3 = param['alpha3'].value;tz3 = param['tz3'].value;
- param['A2'].value = 1.0-A1-A3
- A2 = param['A2'].value
- param['A3'].value = 1.0-A2-A1
- A3 = param['A3'].value
- #For three diffusing species
- GDiff = (A1*(((1+((tc/txy1)**alpha1))**-1)*((1+(tc/tz1))**-0.5)))+ (A2*(((1+((tc/txy2)**alpha2))**-1)*((1+(tc/tz2))**-0.5)))+ (A3*(((1+((tc/txy3)**alpha3))**-1)*((1+(tc/tz3))**-0.5)))
- elif(options['Diff_eq']==2):
- if (options['Diff_species'] == 1):
- A1 = param['A1'].value; txy1 = param['txy1'].value; alpha1 = param['alpha1'].value;AR1 = param['AR1'].value;
- #For one diffusing species
- GDiff = (A1*(((1+((tc/txy1)**alpha1))**-1)*(((1+(tc/((AR1**2)*txy1)))**-0.5))))
- elif (options['Diff_species'] == 2):
- A1 = param['A1'].value; txy1 = param['txy1'].value; alpha1 = param['alpha1'].value;AR1 = param['AR1'].value;
- A2 = param['A2'].value; txy2 = param['txy2'].value; alpha2 = param['alpha2'].value;AR2 = param['AR2'].value;
- param['A2'].value = 1.0-A1
- A2 = param['A2'].value
- #For two diffusing species
- GDiff = (A1*(((1+((tc/txy1)**alpha1))**-1)*(((1+(tc/((AR1**2)*txy1)))**-0.5))))+(A2*(((1+((tc/txy2)**alpha2))**-1)*(((1+(tc/((AR2**2)*txy2)))**-0.5))))
- elif (options['Diff_species'] == 3):
- A1 = param['A1'].value; txy1 = param['txy1'].value; alpha1 = param['alpha1'].value;AR1 = param['AR1'].value;
- A2 = param['A2'].value; txy2 = param['txy2'].value; alpha2 = param['alpha2'].value;AR2 = param['AR2'].value;
- A3 = param['A3'].value; txy3 = param['txy3'].value; alpha3 = param['alpha3'].value;AR3 = param['AR3'].value;
- #For two diffusing species
- param['A2'].value = 1.0-A1-A3
- A2 = param['A2'].value
- param['A3'].value = 1.0-A2-A1
- A3 = param['A3'].value
- #For three diffusing species
- GDiff = (A1*(((1+((tc/txy1)**alpha1))**-1)*(((1+(tc/((AR1**2)*txy1)))**-0.5))))+(A2*(((1+((tc/txy2)**alpha2))**-1)*(((1+(tc/((AR2**2)*txy2)))**-0.5))))+(A3*(((1+((tc/txy3)**alpha3))**-1)*(((1+(tc/((AR3**2)*txy3)))**-0.5))))
-
- if(options['Dimen'] == 1):
- #Equation 1A with 2D term.
- if (options['Diff_species'] == 1):
- A1 = param['A1'].value; txy1 = param['txy1'].value; alpha1 = param['alpha1'].value;
- #For one diffusing species
- GDiff = (A1*(((1+((tc/txy1)**alpha1))**-1)))
- elif (options['Diff_species'] == 2):
- A1 = param['A1'].value; txy1 = param['txy1'].value; alpha1 = param['alpha1'].value;
- A2 = param['A2'].value; txy2 = param['txy2'].value; alpha2 = param['alpha2'].value;
- #For two diffusing species
-
- param['A2'].value = 1.0-A1
- A2 = param['A2'].value
-
- GDiff = (A1*(((1+(tc/txy1)**alpha1)**-1)))+(A2*(((1+(tc/txy2)**alpha2)**-1)))
-
- #if A1 +A2 != 1.0:
- # GDiff = 99999999999
- elif (options['Diff_species'] == 3):
- A1 = param['A1'].value; txy1 = param['txy1'].value; alpha1 = param['alpha1'].value;
- A2 = param['A2'].value; txy2 = param['txy2'].value; alpha2 = param['alpha2'].value;
- A3 = param['A3'].value; txy3 = param['txy3'].value; alpha3 = param['alpha3'].value;
- #For two diffusing species
- param['A2'].value = 1.0-A1-A3
- A2 = param['A2'].value
- param['A3'].value = 1.0-A2-A1
- A3 = param['A3'].value
- #For three diffusing species
- GDiff = (A1*(((1+(tc/txy1)**alpha1)**-1)))+(A2*(((1+(tc/txy2)**alpha2)**-1)))+(A3*(((1+(tc/txy3)**alpha3)**-1)))
-
- if(options['Triplet_eq'] ==1):
- #For no triplets.
- GT = 1
- elif(options['Triplet_eq'] ==2):
- #Equation (2) 1st equation.
- if (options['Triplet_species'] == 1):
- B1 = param['B1'].value;tauT1 = param['tauT1'].value;
- #For one dark state.
- GT = 1 + (B1*np.exp(-tc/tauT1))
- elif (options['Triplet_species'] == 2):
- B1 = param['B1'].value;tauT1 = param['tauT1'].value;
- B2 = param['B2'].value;tauT2 = param['tauT2'].value;
- #For two dark state
- GT = 1 + (B1*np.exp(-tc/tauT1))+(B2*np.exp(-tc/tauT2))
- elif (options['Triplet_species'] == 3):
- B1 = param['B1'].value;tauT1 = param['tauT1'].value;
- B2 = param['B2'].value;tauT2 = param['tauT2'].value;
- B3 = param['B3'].value;tauT3 = param['tauT3'].value;
- #For three dark state
- GT = 1 + (B1*np.exp(-tc/tauT1))+(B2*np.exp(-tc/tauT2))+(B3*np.exp(-tc/tauT3))
-
- elif(options['Triplet_eq'] ==3):
- #Equation (2) 2nd equation.
- if (options['Triplet_species'] == 1):
- T1 = param['T1'].value;tauT1 = param['tauT1'].value;
- #For one dark state.
- GT = 1- T1 + (T1*np.exp(-tc/tauT1))
- elif (options['Triplet_species'] == 2):
- T1 = param['T1'].value;tauT1 = param['tauT1'].value;
- T1 = param['T2'].value;tauT1 = param['tauT2'].value;
- #For two dark state.
- GT = 1- (T1+T2 )+ ((T1*np.exp(-tc/tauT1))+(T2*np.exp(-tc/tauT2)))
- elif (options['Triplet_species'] == 3):
- T1 = param['T1'].value;tauT1 = param['tauT1'].value;
- T2 = param['T2'].value;tauT1 = param['tauT2'].value;
- T3 = param['T3'].value;tauT1 = param['tauT3'].value;
- #For three dark state.
- GT = 1- (T1+T2+T3)+ ((T1*np.exp(-tc/tauT1))+(T2*np.exp(-tc/tauT2))+(T3*np.exp(-tc/tauT3)))
-
- return offset + (GN0*GDiff*GT)
\ No newline at end of file
+ """Depending on the menu options this function will update the params of the current data set. """
+ if int_obj.objId_sel == None:
+ return
+ decide_which_to_show(int_obj)
+ # Set all the parameters to not show.
+
+ for art in int_obj.objId_sel.param:
+ if int_obj.objId_sel.param[art]['to_show'] == True:
+ update_each(int_obj, art)
+
+ calc_param_fcs(int_obj, objId=int_obj.objId_sel)
+
+
+def calc_param_fcs(int_obj, objId):
+ # Calculated parameters.
+ try:
+ objId.param['N_FCS']['value'] = 1/objId.param['GN0']['value']
+ objId.param['N_FCS']['to_show'] = True
+ except:
+ objId.param['N_FCS']['value'] = 1
+ objId.param['N_FCS']['to_show'] = False
+
+ try:
+ objId.param['cpm']['value'] = float(
+ objId.kcount)/(1/objId.param['GN0']['value'])
+ objId.param['cpm']['to_show'] = True
+ except:
+ objId.param['cpm']['value'] = 1
+ objId.param['cpm']['to_show'] = False
+ try:
+ objId.param['N_mom']['value'] = float(objId.numberNandB)
+ objId.param['N_mom']['to_show'] = True
+ except:
+ objId.param['N_mom']['value'] = 1
+ objId.param['N_mom']['to_show'] = False
+ try:
+ objId.param['bri']['value'] = float(objId.brightnessNandB)
+ objId.param['bri']['to_show'] = True
+ except:
+ objId.param['bri']['value'] = 1
+ objId.param['bri']['to_show'] = False
+ try:
+ objId.param['CV']['value'] = float(objId.CV)
+ objId.param['CV']['to_show'] = True
+ except:
+ pass
+ try:
+ objId.param['f0']['value'] = float(objId.pbc_f0)
+ objId.param['f0']['to_show'] = True
+ objId.param['overtb']['value'] = float(objId.pbc_tb)
+ objId.param['overtb']['to_show'] = True
+ except:
+ pass
+
+ if int_obj.objIdArr != [] and objId.siblings != None and objId.ch_type != 2:
+
+ if objId.siblings[0].fitted == True:
+
+ objId.param['ACAC']['value'] = float(
+ objId.param['GN0']['value'])/float(objId.siblings[0].param['GN0']['value'])
+ objId.param['ACAC']['to_show'] = True
+ objId.param['ACCC']['value'] = float(
+ objId.param['GN0']['value'])/float(objId.siblings[1].param['GN0']['value'])
+ objId.param['ACCC']['to_show'] = True
+
+
+def equation_(param, tc, options):
+ """This is equation for fitting"""
+
+ # A1 is relative component of fluorescent species
+ # tc is tau.
+ # txy1 is xy difusion for fluorescent species one.
+ # alpha1 is
+ # tz1 is z diffusion for fluorescent species one.
+ offset = param['offset'].value
+ GN0 = param['GN0'].value
+
+ if(options['Dimen'] == 2):
+ if(options['Diff_eq'] == 1):
+ # Equation 1A with 3D term.
+ if (options['Diff_species'] == 1):
+ A1 = param['A1'].value
+ txy1 = param['txy1'].value
+ alpha1 = param['alpha1'].value
+ tz1 = param['tz1'].value
+ # For one diffusing species
+ GDiff = (A1*(((1+((tc/txy1)**alpha1))**-1)*((1+(tc/tz1))**-0.5)))
+ elif (options['Diff_species'] == 2):
+ A1 = param['A1'].value
+ txy1 = param['txy1'].value
+ alpha1 = param['alpha1'].value
+ tz1 = param['tz1'].value
+ A2 = param['A2'].value
+ txy2 = param['txy2'].value
+ alpha2 = param['alpha2'].value
+ tz2 = param['tz2'].value
+ param['A2'].value = 1.0-A1
+ A2 = param['A2'].value
+ # For two diffusing species
+ GDiff = (A1*(((1+((tc/txy1)**alpha1))**-1)*((1+(tc/tz1))**-0.5))) + \
+ (A2*(((1+((tc/txy2)**alpha2))**-1)*((1+(tc/tz2))**-0.5)))
+ elif (options['Diff_species'] == 3):
+ A1 = param['A1'].value
+ txy1 = param['txy1'].value
+ alpha1 = param['alpha1'].value
+ tz1 = param['tz1'].value
+ A2 = param['A2'].value
+ txy2 = param['txy2'].value
+ alpha2 = param['alpha2'].value
+ tz2 = param['tz2'].value
+ A3 = param['A3'].value
+ txy3 = param['txy3'].value
+ alpha3 = param['alpha3'].value
+ tz3 = param['tz3'].value
+ param['A2'].value = 1.0-A1-A3
+ A2 = param['A2'].value
+ param['A3'].value = 1.0-A2-A1
+ A3 = param['A3'].value
+ # For three diffusing species
+ GDiff = (A1*(((1+((tc/txy1)**alpha1))**-1)*((1+(tc/tz1))**-0.5))) + (A2*(((1+((tc/txy2)**alpha2))
+ ** -1)*((1+(tc/tz2))**-0.5))) + (A3*(((1+((tc/txy3)**alpha3))**-1)*((1+(tc/tz3))**-0.5)))
+ elif(options['Diff_eq'] == 2):
+ if (options['Diff_species'] == 1):
+ A1 = param['A1'].value
+ txy1 = param['txy1'].value
+ alpha1 = param['alpha1'].value
+ AR1 = param['AR1'].value
+ # For one diffusing species
+ GDiff = (A1*(((1+((tc/txy1)**alpha1))**-1) *
+ (((1+(tc/((AR1**2)*txy1)))**-0.5))))
+ elif (options['Diff_species'] == 2):
+ A1 = param['A1'].value
+ txy1 = param['txy1'].value
+ alpha1 = param['alpha1'].value
+ AR1 = param['AR1'].value
+ A2 = param['A2'].value
+ txy2 = param['txy2'].value
+ alpha2 = param['alpha2'].value
+ AR2 = param['AR2'].value
+ param['A2'].value = 1.0-A1
+ A2 = param['A2'].value
+ # For two diffusing species
+ GDiff = (A1*(((1+((tc/txy1)**alpha1))**-1)*(((1+(tc/((AR1**2)*txy1)))**-0.5)))) + \
+ (A2*(((1+((tc/txy2)**alpha2))**-1) *
+ (((1+(tc/((AR2**2)*txy2)))**-0.5))))
+ elif (options['Diff_species'] == 3):
+ A1 = param['A1'].value
+ txy1 = param['txy1'].value
+ alpha1 = param['alpha1'].value
+ AR1 = param['AR1'].value
+ A2 = param['A2'].value
+ txy2 = param['txy2'].value
+ alpha2 = param['alpha2'].value
+ AR2 = param['AR2'].value
+ A3 = param['A3'].value
+ txy3 = param['txy3'].value
+ alpha3 = param['alpha3'].value
+ AR3 = param['AR3'].value
+ # For two diffusing species
+ param['A2'].value = 1.0-A1-A3
+ A2 = param['A2'].value
+ param['A3'].value = 1.0-A2-A1
+ A3 = param['A3'].value
+ # For three diffusing species
+ GDiff = (A1*(((1+((tc/txy1)**alpha1))**-1)*(((1+(tc/((AR1**2)*txy1)))**-0.5))))+(A2*(((1+((tc/txy2)**alpha2))**-1)
+ * (((1+(tc/((AR2**2)*txy2)))**-0.5))))+(A3*(((1+((tc/txy3)**alpha3))**-1)*(((1+(tc/((AR3**2)*txy3)))**-0.5))))
+
+ if(options['Dimen'] == 1):
+ # Equation 1A with 2D term.
+ if (options['Diff_species'] == 1):
+ A1 = param['A1'].value
+ txy1 = param['txy1'].value
+ alpha1 = param['alpha1'].value
+ # For one diffusing species
+ GDiff = (A1*(((1+((tc/txy1)**alpha1))**-1)))
+ elif (options['Diff_species'] == 2):
+ A1 = param['A1'].value
+ txy1 = param['txy1'].value
+ alpha1 = param['alpha1'].value
+ A2 = param['A2'].value
+ txy2 = param['txy2'].value
+ alpha2 = param['alpha2'].value
+ # For two diffusing species
+
+ param['A2'].value = 1.0-A1
+ A2 = param['A2'].value
+
+ GDiff = (A1*(((1+(tc/txy1)**alpha1)**-1))) + \
+ (A2*(((1+(tc/txy2)**alpha2)**-1)))
+
+ # if A1 +A2 != 1.0:
+ # GDiff = 99999999999
+ elif (options['Diff_species'] == 3):
+ A1 = param['A1'].value
+ txy1 = param['txy1'].value
+ alpha1 = param['alpha1'].value
+ A2 = param['A2'].value
+ txy2 = param['txy2'].value
+ alpha2 = param['alpha2'].value
+ A3 = param['A3'].value
+ txy3 = param['txy3'].value
+ alpha3 = param['alpha3'].value
+ # For two diffusing species
+ param['A2'].value = 1.0-A1-A3
+ A2 = param['A2'].value
+ param['A3'].value = 1.0-A2-A1
+ A3 = param['A3'].value
+ # For three diffusing species
+ GDiff = (A1*(((1+(tc/txy1)**alpha1)**-1)))+(A2 *
+ (((1+(tc/txy2)**alpha2)**-1)))+(A3*(((1+(tc/txy3)**alpha3)**-1)))
+
+ if(options['Triplet_eq'] == 1):
+ # For no triplets.
+ GT = 1
+ elif(options['Triplet_eq'] == 2):
+ # Equation (2) 1st equation.
+ if (options['Triplet_species'] == 1):
+ B1 = param['B1'].value
+ tauT1 = param['tauT1'].value
+ # For one dark state.
+ GT = 1 + (B1*np.exp(-tc/tauT1))
+ elif (options['Triplet_species'] == 2):
+ B1 = param['B1'].value
+ tauT1 = param['tauT1'].value
+ B2 = param['B2'].value
+ tauT2 = param['tauT2'].value
+ # For two dark state
+ GT = 1 + (B1*np.exp(-tc/tauT1))+(B2*np.exp(-tc/tauT2))
+ elif (options['Triplet_species'] == 3):
+ B1 = param['B1'].value
+ tauT1 = param['tauT1'].value
+ B2 = param['B2'].value
+ tauT2 = param['tauT2'].value
+ B3 = param['B3'].value
+ tauT3 = param['tauT3'].value
+ # For three dark state
+ GT = 1 + (B1*np.exp(-tc/tauT1)) + \
+ (B2*np.exp(-tc/tauT2))+(B3*np.exp(-tc/tauT3))
+
+ elif(options['Triplet_eq'] == 3):
+ # Equation (2) 2nd equation.
+ if (options['Triplet_species'] == 1):
+ T1 = param['T1'].value
+ tauT1 = param['tauT1'].value
+ # For one dark state.
+ GT = 1 - T1 + (T1*np.exp(-tc/tauT1))
+ elif (options['Triplet_species'] == 2):
+ T1 = param['T1'].value
+ tauT1 = param['tauT1'].value
+ T1 = param['T2'].value
+ tauT1 = param['tauT2'].value
+ # For two dark state.
+ GT = 1 - (T1+T2) + ((T1*np.exp(-tc/tauT1))+(T2*np.exp(-tc/tauT2)))
+ elif (options['Triplet_species'] == 3):
+ T1 = param['T1'].value
+ tauT1 = param['tauT1'].value
+ T2 = param['T2'].value
+ tauT1 = param['tauT2'].value
+ T3 = param['T3'].value
+ tauT1 = param['tauT3'].value
+ # For three dark state.
+ GT = 1 - (T1+T2+T3) + ((T1*np.exp(-tc/tauT1)) +
+ (T2*np.exp(-tc/tauT2))+(T3*np.exp(-tc/tauT3)))
+
+ return offset + (GN0*GDiff*GT)
diff --git a/pycorrfit/readfiles/read_pt3_scripts/import_methods.py b/pycorrfit/readfiles/read_pt3_scripts/import_methods.py
index 5b99fa15..a6ecc2d5 100644
--- a/pycorrfit/readfiles/read_pt3_scripts/import_methods.py
+++ b/pycorrfit/readfiles/read_pt3_scripts/import_methods.py
@@ -21,25 +21,27 @@
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
"""
+
+
def csvimport(filepath):
r_obj = csv.reader(open(filepath, 'rb'))
line_one = r_obj.next()
- if line_one.__len__()>1:
+ if line_one.__len__() > 1:
if float(line_one[1]) == 2:
version = 2
else:
- print('version not known:',line_one[1])
+ print('version not known:', line_one[1])
if version == 2:
- type =str(r_obj.next()[1])
+ type = str(r_obj.next()[1])
if type == "pt uncorrelated":
Resolution = float(r_obj.next()[1])
chanArr = []
trueTimeArr = []
dTimeArr = []
line = r_obj.next()
- while line[0] != 'end':
+ while line[0] != 'end':
chanArr.append(int(line[0]))
trueTimeArr.append(float(line[1]))
@@ -48,8 +50,7 @@ def csvimport(filepath):
return np.array(chanArr), np.array(trueTimeArr), np.array(dTimeArr), Resolution
else:
print('type not recognised')
- return None, None,None,None
-
+ return None, None, None, None
def pt3import(filepath):
@@ -80,18 +81,18 @@ def pt3import(filepath):
DispTimeTo = struct.unpack('i', f.read(4))[0]
DispCountFrom = struct.unpack('i', f.read(4))[0]
DispCountTo = struct.unpack('i', f.read(4))[0]
- DispCurveMapTo = [];
- DispCurveShow =[];
- for i in range(0,8):
- DispCurveMapTo.append(struct.unpack('i', f.read(4))[0]);
- DispCurveShow.append(struct.unpack('i', f.read(4))[0]);
- ParamStart =[];
- ParamStep =[];
- ParamEnd =[];
- for i in range(0,3):
- ParamStart.append(struct.unpack('i', f.read(4))[0]);
- ParamStep.append(struct.unpack('i', f.read(4))[0]);
- ParamEnd.append(struct.unpack('i', f.read(4))[0]);
+ DispCurveMapTo = []
+ DispCurveShow = []
+ for i in range(0, 8):
+ DispCurveMapTo.append(struct.unpack('i', f.read(4))[0])
+ DispCurveShow.append(struct.unpack('i', f.read(4))[0])
+ ParamStart = []
+ ParamStep = []
+ ParamEnd = []
+ for i in range(0, 3):
+ ParamStart.append(struct.unpack('i', f.read(4))[0])
+ ParamStep.append(struct.unpack('i', f.read(4))[0])
+ ParamEnd.append(struct.unpack('i', f.read(4))[0])
RepeatMode = struct.unpack('i', f.read(4))[0]
RepeatsPerCurve = struct.unpack('i', f.read(4))[0]
@@ -99,7 +100,7 @@ def pt3import(filepath):
RepeatWait = struct.unpack('i', f.read(4))[0]
ScriptName = f.read(20)
- #The next is a board specific header
+ # The next is a board specific header
HardwareIdent = f.read(16)
HardwareVersion = f.read(8)
@@ -113,41 +114,41 @@ def pt3import(filepath):
Resolution = struct.unpack('f', f.read(4))[0]
- #below is new in format version 2.0
+ # below is new in format version 2.0
- RouterModelCode = struct.unpack('i', f.read(4))[0]
- RouterEnabled = struct.unpack('i', f.read(4))[0]
+ RouterModelCode = struct.unpack('i', f.read(4))[0]
+ RouterEnabled = struct.unpack('i', f.read(4))[0]
- #Router Ch1
- RtChan1_InputType = struct.unpack('i', f.read(4))[0]
- RtChan1_InputLevel = struct.unpack('i', f.read(4))[0]
- RtChan1_InputEdge = struct.unpack('i', f.read(4))[0]
- RtChan1_CFDPresent = struct.unpack('i', f.read(4))[0]
- RtChan1_CFDLevel = struct.unpack('i', f.read(4))[0]
+ # Router Ch1
+ RtChan1_InputType = struct.unpack('i', f.read(4))[0]
+ RtChan1_InputLevel = struct.unpack('i', f.read(4))[0]
+ RtChan1_InputEdge = struct.unpack('i', f.read(4))[0]
+ RtChan1_CFDPresent = struct.unpack('i', f.read(4))[0]
+ RtChan1_CFDLevel = struct.unpack('i', f.read(4))[0]
RtChan1_CFDZeroCross = struct.unpack('i', f.read(4))[0]
- #Router Ch2
- RtChan2_InputType = struct.unpack('i', f.read(4))[0]
- RtChan2_InputLevel = struct.unpack('i', f.read(4))[0]
- RtChan2_InputEdge = struct.unpack('i', f.read(4))[0]
- RtChan2_CFDPresent = struct.unpack('i', f.read(4))[0]
- RtChan2_CFDLevel = struct.unpack('i', f.read(4))[0]
+ # Router Ch2
+ RtChan2_InputType = struct.unpack('i', f.read(4))[0]
+ RtChan2_InputLevel = struct.unpack('i', f.read(4))[0]
+ RtChan2_InputEdge = struct.unpack('i', f.read(4))[0]
+ RtChan2_CFDPresent = struct.unpack('i', f.read(4))[0]
+ RtChan2_CFDLevel = struct.unpack('i', f.read(4))[0]
RtChan2_CFDZeroCross = struct.unpack('i', f.read(4))[0]
- #Router Ch3
- RtChan3_InputType = struct.unpack('i', f.read(4))[0]
- RtChan3_InputLevel = struct.unpack('i', f.read(4))[0]
- RtChan3_InputEdge = struct.unpack('i', f.read(4))[0]
- RtChan3_CFDPresent = struct.unpack('i', f.read(4))[0]
- RtChan3_CFDLevel = struct.unpack('i', f.read(4))[0]
+ # Router Ch3
+ RtChan3_InputType = struct.unpack('i', f.read(4))[0]
+ RtChan3_InputLevel = struct.unpack('i', f.read(4))[0]
+ RtChan3_InputEdge = struct.unpack('i', f.read(4))[0]
+ RtChan3_CFDPresent = struct.unpack('i', f.read(4))[0]
+ RtChan3_CFDLevel = struct.unpack('i', f.read(4))[0]
RtChan3_CFDZeroCross = struct.unpack('i', f.read(4))[0]
- #Router Ch4
- RtChan4_InputType = struct.unpack('i', f.read(4))[0]
- RtChan4_InputLevel = struct.unpack('i', f.read(4))[0]
- RtChan4_InputEdge = struct.unpack('i', f.read(4))[0]
- RtChan4_CFDPresent = struct.unpack('i', f.read(4))[0]
- RtChan4_CFDLevel = struct.unpack('i', f.read(4))[0]
+ # Router Ch4
+ RtChan4_InputType = struct.unpack('i', f.read(4))[0]
+ RtChan4_InputLevel = struct.unpack('i', f.read(4))[0]
+ RtChan4_InputEdge = struct.unpack('i', f.read(4))[0]
+ RtChan4_CFDPresent = struct.unpack('i', f.read(4))[0]
+ RtChan4_CFDLevel = struct.unpack('i', f.read(4))[0]
RtChan4_CFDZeroCross = struct.unpack('i', f.read(4))[0]
- #The next is a T3 mode specific header.
+ # The next is a T3 mode specific header.
ExtDevices = struct.unpack('i', f.read(4))[0]
Reserved1 = struct.unpack('i', f.read(4))[0]
@@ -158,65 +159,73 @@ def pt3import(filepath):
StopAfter = struct.unpack('i', f.read(4))[0]
StopReason = struct.unpack('i', f.read(4))[0]
Records = struct.unpack('i', f.read(4))[0]
- ImgHdrSize =struct.unpack('i', f.read(4))[0]
+ ImgHdrSize = struct.unpack('i', f.read(4))[0]
- #Special Header for imaging.
+ # Special Header for imaging.
if ImgHdrSize > 0:
ImgHdr = struct.unpack('i', f.read(ImgHdrSize))[0]
- ofltime = 0;
-
- cnt_1=0; cnt_2=0; cnt_3=0; cnt_4=0; cnt_Ofl=0; cnt_M=0; cnt_Err=0; # just counters
- WRAPAROUND=65536;
-
- #Put file Save info here.
-
- syncperiod = 1e9/CntRate0;
- #outfile stuff here.
- #fpout.
+ ofltime = 0
+
+ cnt_1 = 0
+ cnt_2 = 0
+ cnt_3 = 0
+ cnt_4 = 0
+ cnt_Ofl = 0
+ cnt_M = 0
+ cnt_Err = 0 # just counters
+ WRAPAROUND = 65536
+
+ # Put file Save info here.
+
+ syncperiod = 1e9/CntRate0
+ # outfile stuff here.
+ # fpout.
#T3RecordArr = [];
chanArr = [0]*Records
- trueTimeArr =[0]*Records
- dTimeArr=[0]*Records
+ trueTimeArr = [0]*Records
+ dTimeArr = [0]*Records
#f1=open('./testfile', 'w+')
- for b in range(0,Records):
- T3Record = struct.unpack('I', f.read(4))[0];
+ for b in range(0, Records):
+ T3Record = struct.unpack('I', f.read(4))[0]
- #T3RecordArr.append(T3Record)
+ # T3RecordArr.append(T3Record)
nsync = T3Record & 65535
- chan = ((T3Record >> 28) & 15);
- chanArr[b]=chan
+ chan = ((T3Record >> 28) & 15)
+ chanArr[b] = chan
#f1.write(str(i)+" "+str(T3Record)+" "+str(nsync)+" "+str(chan)+" ")
- dtime = 0;
+ dtime = 0
if chan == 1:
- cnt_1 = cnt_1+1;dtime = ((T3Record >> 16) & 4095);#f1.write(str(dtime)+" ")
+ cnt_1 = cnt_1+1
+ dtime = ((T3Record >> 16) & 4095) # f1.write(str(dtime)+" ")
elif chan == 2:
- cnt_2 = cnt_2+1;dtime = ((T3Record >> 16) & 4095);#f1.write(str(dtime)+" ")
+ cnt_2 = cnt_2+1
+ dtime = ((T3Record >> 16) & 4095) # f1.write(str(dtime)+" ")
elif chan == 3:
- cnt_3 = cnt_3+1;dtime = ((T3Record >> 16) & 4095);#f1.write(str(dtime)+" ")
+ cnt_3 = cnt_3+1
+ dtime = ((T3Record >> 16) & 4095) # f1.write(str(dtime)+" ")
elif chan == 4:
- cnt_4 = cnt_4+1;dtime = ((T3Record >> 16) & 4095);#f1.write(str(dtime)+" ")
+ cnt_4 = cnt_4+1
+ dtime = ((T3Record >> 16) & 4095) # f1.write(str(dtime)+" ")
elif chan == 15:
- markers = ((T3Record >> 16) & 15);
+ markers = ((T3Record >> 16) & 15)
- if markers ==0:
- ofltime = ofltime +WRAPAROUND;
+ if markers == 0:
+ ofltime = ofltime + WRAPAROUND
cnt_Ofl = cnt_Ofl+1
#f1.write("Ofl "+" ")
else:
- cnt_M=cnt_M+1
+ cnt_M = cnt_M+1
#f1.write("MA:%1u "+markers+" ")
- truensync = ofltime + nsync;
- truetime = (truensync * syncperiod) + (dtime*Resolution);
+ truensync = ofltime + nsync
+ truetime = (truensync * syncperiod) + (dtime*Resolution)
trueTimeArr[b] = truetime
dTimeArr[b] = dtime
#f1.write(str(truensync)+" "+str(truetime)+"\n")
- f.close();
- #f1.close();
-
-
+ f.close()
+ # f1.close();
- return np.array(chanArr), np.array(trueTimeArr), np.array(dTimeArr), Resolution
\ No newline at end of file
+ return np.array(chanArr), np.array(trueTimeArr), np.array(dTimeArr), Resolution
diff --git a/pycorrfit/readfiles/util.py b/pycorrfit/readfiles/util.py
index 633b598d..bae751e2 100644
--- a/pycorrfit/readfiles/util.py
+++ b/pycorrfit/readfiles/util.py
@@ -6,7 +6,7 @@ def downsample_trace(trace, bestlength=500):
"""
Reduces the length of a trace so that there is no undersampling on a
regular computer screen and the data size is not too large.
-
+
Downsampling is performed by averaging neighboring intensity values
for two time bins and omitting the first time bin.
"""
@@ -20,13 +20,13 @@ def downsample_trace(trace, bestlength=500):
# Simultaneously sum over all intervals
for j in np.arange(teiler):
newsignal = \
- newsignal+trace[j:newlength*teiler:teiler][:,1]
- newsignal = 1.* newsignal / teiler
- newtimes = trace[teiler-1:newlength*teiler:teiler][:,0]
- if len(trace)%teiler != 0:
+ newsignal+trace[j:newlength*teiler:teiler][:, 1]
+ newsignal = 1. * newsignal / teiler
+ newtimes = trace[teiler-1:newlength*teiler:teiler][:, 0]
+ if len(trace) % teiler != 0:
# We have a rest signal
# We average it and add it to the trace
- rest = trace[newlength*teiler:][:,1]
+ rest = trace[newlength*teiler:][:, 1]
lrest = len(rest)
rest = np.array([sum(rest)/lrest])
newsignal = np.concatenate((newsignal, rest),
@@ -34,11 +34,11 @@ def downsample_trace(trace, bestlength=500):
timerest = np.array([trace[-1][0]])
newtimes = np.concatenate((newtimes, timerest),
axis=0)
- newtrace=np.zeros((len(newtimes),2))
- newtrace[:,0] = newtimes
- newtrace[:,1] = newsignal
+ newtrace = np.zeros((len(newtimes), 2))
+ newtrace[:, 0] = newtimes
+ newtrace[:, 1] = newsignal
else:
# Declare newtrace -
# otherwise we have a problem down three lines ;)
newtrace = trace
- return newtrace
\ No newline at end of file
+ return newtrace
diff --git a/pycorrfit/trace.py b/pycorrfit/trace.py
index a78f4113..7a45136a 100644
--- a/pycorrfit/trace.py
+++ b/pycorrfit/trace.py
@@ -8,10 +8,11 @@
class Trace(object):
""" unifies trace handling
"""
+
def __init__(self, trace=None, countrate=None, duration=None,
name=None):
""" Load trace data
-
+
Parameters
----------
trace : ndarray of shape (N, 2)
@@ -29,34 +30,35 @@ def __init__(self, trace=None, countrate=None, duration=None,
self._duration = None
self._trace = None
self._uid = None
-
+
if trace is None:
self.countrate = countrate
self.duration = duration
else:
self.trace = trace
-
+
if name is None:
name = "{:.2f}kHz, {:.0f}s".format(self.countrate,
self.duration/1000)
self.name = name
-
+
def __getitem__(self, idx):
return self.trace[idx]
-
+
def __repr__(self):
text = "Trace of length {:.3f}s and countrate {:.3f}kHz".format(
- self.duration/1000, self.countrate)
+ self.duration/1000, self.countrate)
return text
-
+
@property
def countrate(self):
if self._countrate is None:
#self._countrate = np.average(self._trace[:,1])
# Take into account traces that have arbitrary sampling
- self._countrate = spintg.simps(self._trace[:,1], self._trace[:,0]) / self.duration
+ self._countrate = spintg.simps(
+ self._trace[:, 1], self._trace[:, 0]) / self.duration
return self._countrate
-
+
@countrate.setter
def countrate(self, value):
if value is None:
@@ -68,9 +70,9 @@ def countrate(self, value):
@property
def duration(self):
if not hasattr(self, "_duration") or self._duration is None:
- self._duration = self._trace[-1,0] - self._trace[0,0]
+ self._duration = self._trace[-1, 0] - self._trace[0, 0]
return self._duration
-
+
@duration.setter
def duration(self, value):
if value is None:
@@ -78,7 +80,7 @@ def duration(self, value):
if self._trace is not None:
raise ValueError("Cannot set duration; `self.trace` is set.")
self._duration = value
-
+
@property
def uid(self):
if self._uid is None:
@@ -88,15 +90,15 @@ def uid(self):
hasher.update(self.name)
self._uid = hasher.hexdigest()
return self._uid
-
+
@property
def trace(self):
if self._trace is None:
- self._trace = np.array([ [0, self.countrate],
- [self.duration, self.countrate]
+ self._trace = np.array([[0, self.countrate],
+ [self.duration, self.countrate]
])
return self._trace
-
+
@trace.setter
def trace(self, value):
if value is None: