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#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Test correlation-autocorrelation identity"""
from __future__ import division, print_function
import numpy as np
import multipletau
from test_autocorrelate import get_sample_arrays
def test_ac():
arrs = get_sample_arrays()
try:
multipletau.autocorrelate(a=arrs[0],
copy=2)
except ValueError as e:
assert "`copy` must be boolean!" in e.args
else:
assert False
try:
multipletau.autocorrelate(a=arrs[0],
ret_sum=2)
except ValueError as e:
assert "`ret_sum` must be boolean!" in e.args
else:
assert False
try:
multipletau.autocorrelate(a=arrs[0],
normalize=2)
except ValueError as e:
assert "`normalize` must be boolean!" in e.args
else:
assert False
try:
multipletau.autocorrelate(a=arrs[0],
compress="peter")
except ValueError as e:
assert "Invalid value for `compress`!" in e.args[0]
else:
assert False
try:
multipletau.autocorrelate(a=arrs[0],
normalize=True,
ret_sum=True)
except ValueError as e:
assert "'normalize' and 'ret_sum' must not both be True!" in e.args
else:
assert False
def test_ac_trace0():
arrs = get_sample_arrays()
try:
multipletau.autocorrelate(a=arrs[0] - np.mean(arrs[0]),
normalize=True)
except ValueError as e:
assert "Cannot normalize: Average of `a` is zero!" in e.args
else:
assert False
def test_ac_tracesize():
arrs = get_sample_arrays()
try:
multipletau.autocorrelate(a=arrs[0][:31],
m=16)
except ValueError as e:
assert '`len(a)` must be >= `2m`!' in e.args
else:
assert False
def test_cc():
arrs = get_sample_arrays()
try:
multipletau.correlate(a=arrs[0], v=arrs[0],
copy=2)
except ValueError as e:
assert "`copy` must be boolean!" in e.args
else:
assert False
try:
multipletau.correlate(a=arrs[0], v=arrs[0],
ret_sum=2)
except ValueError as e:
assert "`ret_sum` must be boolean!" in e.args
else:
assert False
try:
multipletau.correlate(a=arrs[0], v=arrs[0],
normalize=2)
except ValueError as e:
assert "`normalize` must be boolean!" in e.args
else:
assert False
try:
multipletau.correlate(a=arrs[0], v=arrs[0],
compress="peter")
except ValueError as e:
assert "Invalid value for `compress`!" in e.args[0]
else:
assert False
try:
multipletau.correlate(a=arrs[0], v=arrs[0],
normalize=True,
ret_sum=True)
except ValueError as e:
assert "'normalize' and 'ret_sum' must not both be True!" in e.args
else:
assert False
def test_cc_trace0():
arrs = get_sample_arrays()
try:
multipletau.correlate(a=arrs[0] - np.mean(arrs[0]),
v=arrs[0],
normalize=True)
except ValueError as e:
assert "Cannot normalize: Average of `a` is zero!" in e.args
else:
assert False
try:
multipletau.correlate(a=arrs[0],
v=arrs[0] - np.mean(arrs[0]),
normalize=True)
except ValueError as e:
assert "Cannot normalize: Average of `v` is zero!" in e.args
else:
assert False
def test_cc_tracesize():
arrs = get_sample_arrays()
try:
multipletau.correlate(a=arrs[0][:31],
v=arrs[0][:31],
m=16)
except ValueError as e:
assert '`len(a)` must be >= `2m`!' in e.args
else:
assert False
def test_cc_samesize():
arrs = get_sample_arrays()
try:
multipletau.correlate(a=arrs[0],
v=arrs[1],
normalize=True)
except ValueError as e:
assert "`a` and `v` must have same length!" in e.args
else:
assert False
def test_numpy_cc_trace0():
arrs = get_sample_arrays()
try:
multipletau.correlate_numpy(a=arrs[0] - np.mean(arrs[0]),
v=arrs[0],
normalize=True)
except ValueError as e:
assert "Cannot normalize: Average of `a` is zero!" in e.args
else:
assert False
try:
multipletau.correlate_numpy(a=arrs[0],
v=arrs[0] - np.mean(arrs[0]),
normalize=True)
except ValueError as e:
assert "Cannot normalize: Average of `v` is zero!" in e.args
else:
assert False
def test_numpy_cc_samesize():
arrs = get_sample_arrays()
try:
multipletau.correlate_numpy(a=arrs[0],
v=arrs[1],
normalize=True)
except ValueError as e:
assert "`a` and `v` must have same length!" in e.args
else:
assert False
if __name__ == "__main__":
# Run all tests
loc = locals()
for key in list(loc.keys()):
if key.startswith("test_") and hasattr(loc[key], "__call__"):
loc[key]()
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