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fix: Make plot autoscaling more robust (#47)
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Make the automatic disabling of automatic SI prefixes handle arrayparameters
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WilliamHPNielsen authored and jenshnielsen committed Jun 26, 2017
1 parent 74cd49f commit d7060d8
Showing 1 changed file with 84 additions and 31 deletions.
115 changes: 84 additions & 31 deletions qcodes/utils/wrappers.py
Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,9 @@
from copy import deepcopy
from collections import namedtuple
import matplotlib.pyplot as plt
import numpy as np

from time import sleep

from qcodes.plots.pyqtgraph import QtPlot
from qcodes.plots.qcmatplotlib import MatPlot
Expand All @@ -19,7 +22,7 @@
CURRENT_EXPERIMENT["logging_enabled"] = False


def init(mainfolder:str, sample_name: str, station, plot_x_position=0.66,
def init(mainfolder: str, sample_name: str, station, plot_x_position=0.66,
annotate_image=True):
"""
Expand All @@ -41,7 +44,7 @@ def init(mainfolder:str, sample_name: str, station, plot_x_position=0.66,

CURRENT_EXPERIMENT["mainfolder"] = mainfolder
CURRENT_EXPERIMENT["sample_name"] = sample_name
CURRENT_EXPERIMENT['init'] = True
CURRENT_EXPERIMENT['init'] = True

CURRENT_EXPERIMENT['plot_x_position'] = plot_x_position

Expand All @@ -66,7 +69,8 @@ def init(mainfolder:str, sample_name: str, station, plot_x_position=0.66,
# turn on logging only if in ipython
# else crash and burn
if ipython is None:
raise RuntimeWarning("History can't be saved refusing to proceed (use IPython/jupyter)")
raise RuntimeWarning("History can't be saved. "
"-Refusing to proceed (use IPython/jupyter)")
else:
logfile = "{}{}".format(path_to_experiment_folder, "commands.log")
CURRENT_EXPERIMENT['logfile'] = logfile
Expand Down Expand Up @@ -142,27 +146,65 @@ def _create_plot(plot, i, name, data, counter_two, j, k):
standardunits = ['V', 's', 'J', 'W', 'm', 'eV', 'A', 'K', 'g',
'Hz', 'rad', 'T', 'H', 'F', 'Pa', 'C', 'Ω', 'Ohm',
'S']
for arr in data.arrays.values():
if arr.unit not in standardunits:
subplot = plot.subplots[j + k]
if arr.is_setpoint: # setpoints on bottom axis
subplot.getAxis('bottom').enableAutoSIPrefix(False)
else: # measured values to the left
subplot.getAxis('left').enableAutoSIPrefix(False)

# Avoid misleading default xrange
if startranges is not None:
subplot = plot.subplots[j + k]
rangefuns = ['setXRange', 'setYRange']
for (prange, rangefun) in zip(startranges, rangefuns):
getattr(subplot.getViewBox(), rangefun)(prange[0],
prange[1])
# make a dict mapping axis labels to axis positions
# TODO: will the labels for two axes ever be identical?
whatwhere = {}
for pos in ('bottom', 'left', 'right'):
whatwhere.update({plot.subplots[j+k].getAxis(pos).labelText:
pos})
tdict = {'bottom': 'setXRange', 'left': 'setYRange'}
# now find the data (not setpoint)
thedata = [d for d in data.arrays.values() if not d.is_setpoint][0]

# Disable autoscale for the measured data
if thedata.unit not in standardunits:
subplot = plot.subplots[j+k]
try:
# 1D measurement
ax = subplot.getAxis(whatwhere[thedata.label])
ax.enableAutoSIPrefix(False)
except KeyError:
# 2D measurement
# Then we should fetch the colorbar
ax = plot.traces[0]['plot_object']['hist'].axis
ax.enableAutoSIPrefix(False)
ax.setLabel(text=thedata.label, unit=thedata.unit,
unitPrefix='')

# Set up axis scaling
for setarr in thedata.set_arrays:
subplot = plot.subplots[j+k]
ax = subplot.getAxis(whatwhere[setarr.label])
# check for autoscaling
if setarr.unit not in standardunits:
ax.enableAutoSIPrefix(False)
# At this point, it has already been decided that
# the scale is milli whatever
# (the default empty plot is from -0.5 to 0.5)
# so we must undo that
ax.setScale(1e-3)
ax.setLabel(text=setarr.label, unit=setarr.unit,
unitPrefix='')
# set the axis ranges
if not(np.all(np.isnan(setarr))):
# In this case the setpoints are "baked" into the parameter
rangesetter = getattr(subplot.getViewBox(),
tdict[whatwhere[setarr.label]])
rangesetter(setarr.min(), setarr.max())
else:
# in this case someone must tell _create_plot what the
# range should be. We get it from startranges
rangesetter = getattr(subplot.getViewBox(),
tdict[whatwhere[setarr.label]])
(rmin, rmax) = startranges[setarr.label]
rangesetter(rmin, rmax)

else:
if 'z' in inst_meta_data:
xlen, ylen = inst_meta_data['z'].shape
rasterized = xlen*ylen > 5000
plot.add(inst_meas_data, subplot=j + k + 1, rasterized=rasterized)
plot.add(inst_meas_data, subplot=j + k + 1,
rasterized=rasterized)
else:
rasterized = False
plot.add(inst_meas_data, subplot=j + k + 1, color=color)
Expand Down Expand Up @@ -289,8 +331,9 @@ def do1d(inst_set, start, stop, num_points, delay, *inst_meas, do_plots=True):
delay: Delay at every step
*inst_meas: any number of instrument to measure and/or tasks to
perform at each step of the sweep
do_plots: Default True: If False no plots are produced. Data is still saved
and can be displayed with show_num.
do_plots: Default True: If False no plots are produced.
Data is still saved
and can be displayed with show_num.
Returns:
plot, data : returns the plot and the dataset
Expand All @@ -300,13 +343,15 @@ def do1d(inst_set, start, stop, num_points, delay, *inst_meas, do_plots=True):
# try to flush VISA buffers at the beginning of a measurement
_flush_buffers(inst_set, *inst_meas)

# make a variable for aute pre-scaling the plot
startranges = ((start, stop),)
# make a variable for auto pre-scaling the plot
startranges = {inst_set.label: (start, stop)}

interrupted = False
loop = qc.Loop(inst_set.sweep(start,
stop, num=num_points), delay).each(*inst_meas)
stop,
num=num_points), delay).each(*inst_meas)
data = loop.get_data_set()

plottables = _select_plottables(inst_meas)
if do_plots:
plot, _ = _plot_setup(data, plottables, startranges=startranges)
Expand Down Expand Up @@ -370,7 +415,7 @@ def do1dDiagonal(inst_set, inst2_set, start, stop, num_points, delay, start2, sl
"""

# make a variable for aute pre-scaling the plot
startranges = ((start, stop),)
startranges = {inst_set.label: (start, stop)}

# try to flush VISA buffers at the beginning of a measurement
_flush_buffers(inst_set, inst2_set, *inst_meas)
Expand Down Expand Up @@ -444,7 +489,8 @@ def do2d(inst_set, start, stop, num_points, delay, inst_set2, start2, stop2, num
"""

# make a variable for aute pre-scaling the plot
startranges = ((start2, stop2), (start, stop))
startranges = {inst_set2.label: (start2, stop2),
inst_set.label: (start, stop)}

# try to flush VISA buffers at the beginning of a measurement
_flush_buffers(inst_set, inst_set2, *inst_meas)
Expand All @@ -454,19 +500,26 @@ def do2d(inst_set, start, stop, num_points, delay, inst_set2, start2, stop2, num
if getattr(inst, "setpoints", False):
raise ValueError("3d plotting is not supported")

loop = qc.Loop(inst_set.sweep(start, stop, num=num_points), delay).loop(inst_set2.sweep(start2,stop2,num=num_points2), delay2).each(
*inst_meas)
data = loop.get_data_set()
innerloop = qc.Loop(inst_set2.sweep(start2,
stop2,
num=num_points2),
delay2).each(*inst_meas)
outerloop = qc.Loop(inst_set.sweep(start,
stop,
num=num_points),
delay).each(innerloop)

data = outerloop.get_data_set()
plottables = _select_plottables(inst_meas)
if do_plots:
plot, _ = _plot_setup(data, plottables, startranges=startranges)
else:
plot = None
try:
if do_plots:
_ = loop.with_bg_task(plot.update).run()
_ = outerloop.with_bg_task(plot.update).run()
else:
_ = loop.run()
_ = outerloop.run()
except KeyboardInterrupt:
interrupted = True
print("Measurement Interrupted")
Expand Down

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