Skip to content

Navigation Menu

Sign in
Appearance settings

Search code, repositories, users, issues, pull requests...

Provide feedback

We read every piece of feedback, and take your input very seriously.

Saved searches

Use saved searches to filter your results more quickly
Appearance settings

Catch specgram warnings during tests #7985

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 6 commits into from
Feb 6, 2017
Merged

Catch specgram warnings during tests #7985

Changes from all commits
Commits
Show all changes
6 commits
Select commit Hold shift + click to select a range
62ad55b
Increase data length of specgram() test to remove UserWarnings (fixes…
DietBru Jan 29, 2017
7893b7b
Added test to check if specgram() warning is raised if len(x)<=NFFT.
DietBru Jan 29, 2017
804ade1
Typo + code beautification
DietBru Jan 30, 2017
17c40aa
Test the case len(x) < NFFT for psd() to restore code coverage.
DietBru Jan 31, 2017
379d128
Make sure that warning is always triggered.
DietBru Feb 1, 2017
850bb2e
Restore code coverage (second attempt).
DietBru Feb 3, 2017
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
109 changes: 72 additions & 37 deletions 109 lib/matplotlib/tests/test_mlab.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -4,6 +4,7 @@
import six

import tempfile
import warnings

from numpy.testing import (assert_allclose, assert_almost_equal,
assert_array_equal)
Expand Down Expand Up @@ -359,46 +360,46 @@ def test_csv2rec_names_with_comments(self):
assert len(array.dtype) == 3

def test_csv2rec_usdate(self):
self.fd.write('01/11/14\n' +
'03/05/76 12:00:01 AM\n' +
'07/09/83 5:17:34 PM\n' +
'06/20/2054 2:31:45 PM\n' +
'10/31/00 11:50:23 AM\n')
self.fd.write('01/11/14\n'
'03/05/76 12:00:01 AM\n'
'07/09/83 5:17:34 PM\n'
'06/20/2054 2:31:45 PM\n'
'10/31/00 11:50:23 AM\n')
expected = [datetime.datetime(2014, 1, 11, 0, 0),
datetime.datetime(1976, 3, 5, 0, 0, 1),
datetime.datetime(1983, 7, 9, 17, 17, 34),
datetime.datetime(2054, 6, 20, 14, 31, 45),
datetime.datetime(2000, 10, 31, 11, 50, 23)]
datetime.datetime(1976, 3, 5, 0, 0, 1),
datetime.datetime(1983, 7, 9, 17, 17, 34),
datetime.datetime(2054, 6, 20, 14, 31, 45),
datetime.datetime(2000, 10, 31, 11, 50, 23)]
self.fd.seek(0)
array = mlab.csv2rec(self.fd, names='a')
assert_array_equal(array['a'].tolist(), expected)

def test_csv2rec_dayfirst(self):
self.fd.write('11/01/14\n' +
'05/03/76 12:00:01 AM\n' +
'09/07/83 5:17:34 PM\n' +
'20/06/2054 2:31:45 PM\n' +
'31/10/00 11:50:23 AM\n')
'05/03/76 12:00:01 AM\n'
'09/07/83 5:17:34 PM\n'
'20/06/2054 2:31:45 PM\n'
'31/10/00 11:50:23 AM\n')
expected = [datetime.datetime(2014, 1, 11, 0, 0),
datetime.datetime(1976, 3, 5, 0, 0, 1),
datetime.datetime(1983, 7, 9, 17, 17, 34),
datetime.datetime(2054, 6, 20, 14, 31, 45),
datetime.datetime(2000, 10, 31, 11, 50, 23)]
datetime.datetime(1976, 3, 5, 0, 0, 1),
datetime.datetime(1983, 7, 9, 17, 17, 34),
datetime.datetime(2054, 6, 20, 14, 31, 45),
datetime.datetime(2000, 10, 31, 11, 50, 23)]
self.fd.seek(0)
array = mlab.csv2rec(self.fd, names='a', dayfirst=True)
assert_array_equal(array['a'].tolist(), expected)

def test_csv2rec_yearfirst(self):
self.fd.write('14/01/11\n' +
'76/03/05 12:00:01 AM\n' +
'83/07/09 5:17:34 PM\n' +
'2054/06/20 2:31:45 PM\n' +
'00/10/31 11:50:23 AM\n')
self.fd.write('14/01/11\n'
'76/03/05 12:00:01 AM\n'
'83/07/09 5:17:34 PM\n'
'2054/06/20 2:31:45 PM\n'
'00/10/31 11:50:23 AM\n')
expected = [datetime.datetime(2014, 1, 11, 0, 0),
datetime.datetime(1976, 3, 5, 0, 0, 1),
datetime.datetime(1983, 7, 9, 17, 17, 34),
datetime.datetime(2054, 6, 20, 14, 31, 45),
datetime.datetime(2000, 10, 31, 11, 50, 23)]
datetime.datetime(1976, 3, 5, 0, 0, 1),
datetime.datetime(1983, 7, 9, 17, 17, 34),
datetime.datetime(2054, 6, 20, 14, 31, 45),
datetime.datetime(2000, 10, 31, 11, 50, 23)]
self.fd.seek(0)
array = mlab.csv2rec(self.fd, names='a', yearfirst=True)
assert_array_equal(array['a'].tolist(), expected)
Expand Down Expand Up @@ -1629,6 +1630,18 @@ def test_csd(self):
assert_allclose(fsp, freqs, atol=1e-06)
assert spec.shape == freqs.shape

def test_csd_padding(self):
"""Test zero padding of csd(). """
if self.NFFT_density is None: # for derived classes
return
sargs = dict(x=self.y, y=self.y+1, Fs=self.Fs, window=mlab.window_none,
sides=self.sides)

spec0, _ = mlab.csd(NFFT=self.NFFT_density, **sargs)
spec1, _ = mlab.csd(NFFT=self.NFFT_density*2, **sargs)
assert_almost_equal(np.sum(np.conjugate(spec0)*spec0).real,
np.sum(np.conjugate(spec1/2)*spec1/2).real)

def test_psd(self):
freqs = self.freqs_density
spec, fsp = mlab.psd(x=self.y,
Expand Down Expand Up @@ -2103,6 +2116,15 @@ def test_specgram_phase(self):
assert spec.shape[0] == freqs.shape[0]
assert spec.shape[1] == self.t_specgram.shape[0]

def test_specgram_warn_only1seg(self):
"""Warning should be raised if len(x) <= NFFT. """
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always", category=UserWarning)
mlab.specgram(x=self.y, NFFT=len(self.y), Fs=self.Fs)
assert len(w) == 1
assert issubclass(w[0].category, UserWarning)
assert str(w[0].message).startswith("Only one segment is calculated")

def test_psd_csd_equal(self):
freqs = self.freqs_density
Pxx, freqsxx = mlab.psd(x=self.y,
Expand Down Expand Up @@ -2543,7 +2565,7 @@ class Test_spectral_nosig_real_onesided_trim(
Test_spectral_nosig_real_onesided):
def setUp(self):
self.createStim(fstims=[],
len_x=256,
len_x=1024,
NFFT_density=512, pad_to_spectrum=128,
iscomplex=False, sides='onesided', nsides=1)

Expand All @@ -2552,7 +2574,7 @@ class Test_spectral_nosig_real_twosided_trim(
Test_spectral_nosig_real_onesided):
def setUp(self):
self.createStim(fstims=[],
len_x=256,
len_x=1024,
NFFT_density=512, pad_to_spectrum=128,
iscomplex=False, sides='twosided', nsides=2)

Expand All @@ -2561,7 +2583,7 @@ class Test_spectral_nosig_real_defaultsided_trim(
Test_spectral_nosig_real_onesided):
def setUp(self):
self.createStim(fstims=[],
len_x=256,
len_x=1024,
NFFT_density=512, pad_to_spectrum=128,
iscomplex=False, sides='default', nsides=1)

Expand All @@ -2570,7 +2592,7 @@ class Test_spectral_nosig_complex_onesided_trim(
Test_spectral_nosig_real_onesided):
def setUp(self):
self.createStim(fstims=[],
len_x=256,
len_x=1024,
NFFT_density=512, pad_to_spectrum=128,
iscomplex=True, sides='onesided', nsides=1)

Expand All @@ -2579,7 +2601,7 @@ class Test_spectral_nosig_complex_twosided_trim(
Test_spectral_nosig_real_onesided):
def setUp(self):
self.createStim(fstims=[],
len_x=256,
len_x=1024,
NFFT_density=512, pad_to_spectrum=128,
iscomplex=True, sides='twosided', nsides=2)

Expand Down Expand Up @@ -2705,7 +2727,7 @@ class Test_spectral_nosig_real_onesided_stretch(
Test_spectral_nosig_real_onesided):
def setUp(self):
self.createStim(fstims=[],
len_x=128,
len_x=256,
NFFT_density=128,
pad_to_density=256, pad_to_spectrum=256,
iscomplex=False, sides='onesided', nsides=1)
Expand All @@ -2715,7 +2737,7 @@ class Test_spectral_nosig_real_twosided_stretch(
Test_spectral_nosig_real_onesided):
def setUp(self):
self.createStim(fstims=[],
len_x=128,
len_x=256,
NFFT_density=128,
pad_to_density=256, pad_to_spectrum=256,
iscomplex=False, sides='twosided', nsides=2)
Expand All @@ -2725,7 +2747,7 @@ class Test_spectral_nosig_real_defaultsided_stretch(
Test_spectral_nosig_real_onesided):
def setUp(self):
self.createStim(fstims=[],
len_x=128,
len_x=256,
NFFT_density=128,
pad_to_density=256, pad_to_spectrum=256,
iscomplex=False, sides='default', nsides=1)
Expand All @@ -2735,7 +2757,7 @@ class Test_spectral_nosig_complex_onesided_stretch(
Test_spectral_nosig_real_onesided):
def setUp(self):
self.createStim(fstims=[],
len_x=128,
len_x=256,
NFFT_density=128,
pad_to_density=256, pad_to_spectrum=256,
iscomplex=True, sides='onesided', nsides=1)
Expand All @@ -2745,7 +2767,7 @@ class Test_spectral_nosig_complex_twosided_stretch(
Test_spectral_nosig_real_onesided):
def setUp(self):
self.createStim(fstims=[],
len_x=128,
len_x=256,
NFFT_density=128,
pad_to_density=256, pad_to_spectrum=256,
iscomplex=True, sides='twosided', nsides=2)
Expand All @@ -2755,7 +2777,7 @@ class Test_spectral_nosig_complex_defaultsided_stretch(
Test_spectral_nosig_real_onesided):
def setUp(self):
self.createStim(fstims=[],
len_x=128,
len_x=256,
NFFT_density=128,
pad_to_density=256, pad_to_spectrum=256,
iscomplex=True, sides='default', nsides=2)
Expand Down Expand Up @@ -3102,3 +3124,16 @@ def test_psd_onesided_norm():
sides='onesided')
Su_1side = np.append([Su[0]], Su[1:4] + Su[4:][::-1])
assert_allclose(P, Su_1side, atol=1e-06)


def test_psd_oversampling():
"""Test the case len(x) < NFFT for psd(). """
u = np.array([0, 1, 2, 3, 1, 2, 1])
dt = 1.0
Su = np.abs(np.fft.fft(u) * dt)**2 / float(dt * u.size)
P, f = mlab.psd(u, NFFT=u.size*2, Fs=1/dt, window=mlab.window_none,
detrend=mlab.detrend_none, noverlap=0, pad_to=None,
scale_by_freq=None,
sides='onesided')
Su_1side = np.append([Su[0]], Su[1:4] + Su[4:][::-1])
assert_almost_equal(np.sum(P), np.sum(Su_1side)) # same energy
Morty Proxy This is a proxified and sanitized view of the page, visit original site.