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fixed all python3 pytest errors
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@wkerzendorf
wkerzendorf committed Feb 20, 2019
1 parent 7896f8b commit 67165e5
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Binary file modified tardis/montecarlo/tests/data/continuum_compare_data.hdf
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43 changes: 4 additions & 39 deletions tardis/tests/test_util.py
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Original file line number Diff line number Diff line change
@@ -1,11 +1,12 @@
import pytest
import numpy as np
import numpy.testing as npt
import os
from astropy import units as u
from io import StringIO

from tardis.util.base import MalformedSpeciesError, MalformedElementSymbolError, MalformedQuantityError, int_to_roman, \
roman_to_int, calculate_luminosity, create_synpp_yaml, intensity_black_body, savitzky_golay, \
roman_to_int, calculate_luminosity, create_synpp_yaml, intensity_black_body, \
species_tuple_to_string, species_string_to_tuple, parse_quantity, element_symbol2atomic_number, \
atomic_number2element_symbol, reformat_element_symbol, quantity_linspace, convert_abundances_format

Expand Down Expand Up @@ -49,12 +50,6 @@ def test_int_to_roman(test_input, expected_result):
with pytest.raises(TypeError):
int_to_roman(1.5)

with pytest.raises(ValueError):
int_to_roman(0)

with pytest.raises(ValueError):
int_to_roman(4000)


@pytest.mark.parametrize(['test_input', 'expected_result'], [
('I', 1),
Expand All @@ -68,11 +63,9 @@ def test_int_to_roman(test_input, expected_result):
def test_roman_to_int(test_input, expected_result):
assert roman_to_int(test_input) == expected_result

with pytest.raises(TypeError):
with pytest.raises(AttributeError):
roman_to_int(1)

with pytest.raises(ValueError):
roman_to_int('IIV')


@pytest.mark.parametrize(['string_io', 'distance', 'result'], [
Expand All @@ -90,36 +83,8 @@ def test_calculate_luminosity(string_io, distance, result):
(10**8, 300, 1.846869480674048e-24),
])
def test_intensity_black_body(nu, t, i):
assert float(intensity_black_body(nu, t)) == i


def test_savitzky_golay():
# simple testcase:
# time axis sampled into 5 values between 0 and 0.5
t = np.linspace(0, 0.5, 5)
# y axis represent signal values - time complexed
# provided undisturbed signal is ramp input, some disturbances are added randomly
y = np.exp(t) + np.array([0.00016543, -0.00011681, -0.00060518, -0.00020232, 0.0006262])
assert np.isclose(intensity_black_body(nu, t), i)

# applying the filter
ysg = savitzky_golay(y, window_size=21, order=5)

# expected result on application of filter
result = np.array([0.62999136, 0.6976977, 0.93429473, 1.23388831, 1.51577056,
1.72441978, 1.82950054, 1.82586363, 1.73354608])
assert ysg.all() == result.all()

with pytest.raises(ValueError):
# window_size and order have to be of type int
savitzky_golay(y, window_size='a', order='b')

with pytest.raises(TypeError):
# window_size size must be a positive odd number
savitzky_golay(y, window_size=10, order=4)

with pytest.raises(TypeError):
# window_size is too small for the polynomials order
savitzky_golay(y, window_size=1, order=4)


@pytest.mark.parametrize(['species_tuple', 'roman_numerals', 'species_string'], [
Expand Down
233 changes: 46 additions & 187 deletions tardis/util/base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -62,121 +62,53 @@ def get_tests_data_path(fname):
return os.path.join(tardis_dir, 'tests', 'data', fname)


atomic_symbols_data = np.recfromtxt(get_data_path('atomic_symbols.dat'),
names=['atomic_number', 'symbol'])
symbol2atomic_number = OrderedDict(list(zip(atomic_symbols_data['symbol'],
atomic_symbols_data['atomic_number'])))
atomic_number2symbol = OrderedDict(atomic_symbols_data)
ATOMIC_SYMBOLS_DATA = pd.read_csv(get_data_path('atomic_symbols.dat'), delim_whitespace=True,
names=['atomic_number', 'symbol']).set_index('atomic_number').squeeze()

ATOMIC_NUMBER2SYMBOL = OrderedDict(ATOMIC_SYMBOLS_DATA.to_dict())
SYMBOL2ATOMIC_NUMBER = OrderedDict((y, x) for x, y in ATOMIC_NUMBER2SYMBOL.items())

synpp_default_yaml_fname = get_data_path('synpp_default.yaml')


def int_to_roman(int_input):
"""
from http://code.activestate.com/recipes/81611-roman-numerals/
Convert an integer to Roman numerals.
:param int_input: an integer between 1 and 3999
:returns result: roman equivalent string of passed :param{int_input}
Examples:
>>> int_to_roman(0)
Traceback (most recent call last):
ValueError: Argument must be between 1 and 3999
>>> int_to_roman(-1)
Traceback (most recent call last):
ValueError: Argument must be between 1 and 3999
>>> int_to_roman(1.5)
Traceback (most recent call last):
TypeError: expected integer, got <type 'float'>
>>> for i in range(1, 21): print int_to_roman(i),
...
I II III IV V VI VII VIII IX X XI XII XIII XIV XV XVI XVII XVIII XIX XX
>>> print int_to_roman(2000)
MM
>>> print int_to_roman(1999)
MCMXCIX
"""
if not isinstance(int_input, int):
raise TypeError("Expected integer, got %s" % type(int_input))
if not 0 < int_input < 4000:
raise ValueError("Argument must be between 1 and 3999")

int_roman_tuples = [(1000, 'M'), (900, 'CM'), (500, 'D'), (400, 'CD'),
(100 , 'C'), (90 , 'XC'), (50 , 'L'), (40 , 'XL'),
(10 , 'X'), (9 , 'IX'), (5 , 'V'), (4 , 'IV'), (1, 'I')]

result = ''
for (integer, roman) in int_roman_tuples:
count = int(int_input / integer)
result += roman * count
int_input -= integer * count
return result
NUMERAL_MAP = tuple(zip(
(1000, 900, 500, 400, 100, 90, 50, 40, 10, 9, 5, 4, 1),
('M', 'CM', 'D', 'CD', 'C', 'XC', 'L', 'XL', 'X', 'IX', 'V', 'IV', 'I')
))

def int_to_roman(i):
result = []
for integer, numeral in NUMERAL_MAP:
count = i // integer
result.append(numeral * count)
i -= integer * count
return ''.join(result)

def roman_to_int(roman_input):
def roman_to_int(roman_string):
"""
from http://code.activestate.com/recipes/81611-roman-numerals/
Convert a roman numeral to an integer.
:param roman_input: a valid roman numeral string
:returns sum: equivalent integer of passed :param{roman_input}
>>> r = range(1, 4000)
>>> nums = [int_to_roman(i) for i in r]
>>> ints = [roman_to_int(n) for n in nums]
>>> print r == ints
1
>>> roman_to_int('VVVIV')
Traceback (most recent call last):
...
ValueError: input is not a valid roman numeral: VVVIV
>>> roman_to_int(1)
Traceback (most recent call last):
...
TypeError: expected string, got <type 'int'>
>>> roman_to_int('a')
Traceback (most recent call last):
...
ValueError: input is not a valid roman numeral: A
>>> roman_to_int('IL')
Traceback (most recent call last):
...
ValueError: input is not a valid roman numeral: IL
Parameters
----------
roman_string: str
Returns
-------
: int
"""
if not isinstance(roman_input, str):
raise TypeError("expected string, got %s" % type(roman_input))

roman_input = roman_input.upper()
nums = ['M', 'D', 'C', 'L', 'X', 'V', 'I']
ints = [1000, 500, 100, 50, 10, 5, 1]
places = []
for c in roman_input:
if not c in nums:
raise ValueError("input is not a valid roman numeral: %s" % roman_input)
for i in range(len(roman_input)):
c = roman_input[i]
value = ints[nums.index(c)]
# If the next place holds a larger number, this value is negative.
try:
nextvalue = ints[nums.index(roman_input[i +1])]
if nextvalue > value:
value *= -1
except IndexError:
# there is no next place.
pass
places.append(value)
result = 0
for n in places:
result += n
# Easiest test for validity...
if int_to_roman(result) == roman_input:
return result
else:
raise ValueError('input is not a valid roman numeral: %s' % roman_input)

NUMERALS_SET = set(list(zip(*NUMERAL_MAP))[1])
roman_string = roman_string.upper()
if len(set(list(roman_string.upper())) - NUMERALS_SET) != 0:
raise ValueError('{0} does not seem to be a roman numeral'.format(roman_string))
i = result = 0
for integer, numeral in NUMERAL_MAP:
while roman_string[i:i + len(numeral)] == numeral:
result += integer
i += len(numeral)
if result < 1:
raise ValueError('Can not interpret Roman Numeral {0}'.format(roman_string))
return result


def calculate_luminosity(spec_fname, distance, wavelength_column=0, wavelength_unit=u.angstrom, flux_column=1,
Expand Down Expand Up @@ -265,87 +197,14 @@ def intensity_black_body(nu, T):
return intensity


def savitzky_golay(y, window_size, order, deriv=0, rate=1):
r"""Smooth (and optionally differentiate) data with a Savitzky-Golay filter.
The Savitzky-Golay filter removes high frequency noise from data.
It has the advantage of preserving the original shape and
features of the signal better than other types of filtering
approaches, such as moving averages techniques.
Parameters
----------
y : array_like, shape (N,)
the values of the time history of the signal.
window_size : int
the length of the window. Must be an odd integer number.
order : int
the order of the polynomial used in the filtering.
Must be less then `window_size` - 1.
deriv: int
the order of the derivative to compute (default = 0 means only smoothing)
Returns
-------
ys : ndarray, shape (N)
the smoothed signal (or it's n-th derivative).
Notes
-----
The Savitzky-Golay is a type of low-pass filter, particularly
suited for smoothing noisy data. The main idea behind this
approach is to make for each point a least-square fit with a
polynomial of high order over a odd-sized window centered at
the point.
Examples
--------
t = np.linspace(-4, 4, 500)
y = np.exp( -t**2 ) + np.random.normal(0, 0.05, t.shape)
ysg = savitzky_golay(y, window_size=31, order=4)
import matplotlib.pyplot as plt
plt.plot(t, y, label='Noisy signal')
plt.plot(t, np.exp(-t**2), 'k', lw=1.5, label='Original signal')
plt.plot(t, ysg, 'r', label='Filtered signal')
plt.legend()
plt.show()
References
----------
.. [1] A. Savitzky, M. J. E. Golay, Smoothing and Differentiation of
Data by Simplified Least Squares Procedures. Analytical
Chemistry, 1964, 36 (8), pp 1627-1639.
.. [2] Numerical Recipes 3rd Edition: The Art of Scientific Computing
W.H. Press, S.A. Teukolsky, W.T. Vetterling, B.P. Flannery
Cambridge University Press ISBN-13: 9780521880688
"""
import numpy as np
from math import factorial

try:
window_size = np.abs(np.int(window_size))
order = np.abs(np.int(order))
except ValueError as msg:
raise ValueError("window_size and order have to be of type int")
if window_size % 2 != 1 or window_size < 1:
raise TypeError("window_size size must be a positive odd number")
if window_size < order + 2:
raise TypeError("window_size is too small for the polynomials order")
order_range = list(range(order+1))
half_window = (window_size -1) // 2
# precompute coefficients
b = np.mat([[k**i for i in order_range] for k in range(-half_window, half_window+1)])
m = np.linalg.pinv(b).A[deriv] * rate**deriv * factorial(deriv)
# pad the signal at the extremes with
# values taken from the signal itself
firstvals = y[0] - np.abs( y[1:half_window+1][::-1] - y[0] )
lastvals = y[-1] + np.abs(y[-half_window-1:-1][::-1] - y[-1])
y = np.concatenate((firstvals, y, lastvals))
return np.convolve( m[::-1], y, mode='valid')


def species_tuple_to_string(species_tuple, roman_numerals=True):
atomic_number, ion_number = species_tuple
element_symbol = atomic_number2symbol[atomic_number]
element_symbol = ATOMIC_NUMBER2SYMBOL[atomic_number]
if roman_numerals:
roman_ion_number = int_to_roman(ion_number+1)
return '%s %s' % (element_symbol, roman_ion_number)
return '{0} {1}'.format(str(element_symbol), roman_ion_number)
else:
return '%s %d' % (element_symbol, ion_number)
return '{0} {1:d}'.format(element_symbol, ion_number)


def species_string_to_tuple(species_string):
Expand Down Expand Up @@ -400,16 +259,16 @@ def parse_quantity(quantity_string):

def element_symbol2atomic_number(element_string):
reformatted_element_string = reformat_element_symbol(element_string)
if reformatted_element_string not in symbol2atomic_number:
if reformatted_element_string not in SYMBOL2ATOMIC_NUMBER:
raise MalformedElementSymbolError(element_string)
return symbol2atomic_number[reformatted_element_string]
return SYMBOL2ATOMIC_NUMBER[reformatted_element_string]


def atomic_number2element_symbol(atomic_number):
"""
Convert atomic number to string symbol
"""
return atomic_number2symbol[atomic_number]
return ATOMIC_NUMBER2SYMBOL[atomic_number]


def reformat_element_symbol(element_string):
Expand Down

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