def test_crm(tmpdir):
"""Test CRM Corpus functions."""
fs = 40000 # native rate, to avoid large resampling delay in testing
crm_info()
tempdir = str(tmpdir)
# corpus prep
talkers = [dict(sex='f', talker_num=0)]
crm_prepare_corpus(fs, path_out=tempdir, talker_list=talkers,
n_jobs=1)
crm_prepare_corpus(fs, path_out=tempdir, talker_list=talkers, n_jobs=1,
overwrite=True)
# no overwrite
pytest.raises(RuntimeError, crm_prepare_corpus, fs, path_out=tempdir)
# load sentence from hard drive
crm_sentence(fs, 'f', 0, 0, 0, 0, 0, ramp_dur=0, path=tempdir)
crm_sentence(fs, 1, '0', 'charlie', 'red', '5', stereo=True, path=tempdir)
# bad value requested
pytest.raises(ValueError, crm_sentence, fs, 1, 0, 0, 'periwinkle', 0,
path=tempdir)
# unprepared talker
pytest.raises(RuntimeError, crm_sentence, fs, 'm', 0, 0, 0, 0,
path=tempdir)
# unprepared sampling rate
pytest.raises(RuntimeError, crm_sentence, fs + 1, 0, 0, 0, 0, 0,
path=tempdir)
# CRMPreload class
crm = CRMPreload(fs, path=tempdir)
crm.sentence('f', 0, 0, 0, 0)
# unprepared sampling rate
pytest.raises(RuntimeError, CRMPreload, fs + 1)
# bad value requested
pytest.raises(ValueError, crm.sentence, 1, 0, 0, 'periwinkle', 0)
# unprepared talker
pytest.raises(RuntimeError, crm.sentence, 'm', 0, 0, 0, 0)
# try to specify parameters like fs, stereo, etc.
pytest.raises(TypeError, crm.sentence, fs, '1', '0', 'charlie', 'red', '5')
# add_pad
x1 = np.zeros(10)
x2 = np.ones((2, 5))
x = add_pad([x1, x2])
assert (np.sum(x[..., -1] == 0))
x = add_pad((x1, x2), 'center')
assert (np.sum(x[..., -1] == 0) and np.sum(x[..., 0] == 0))
x = add_pad((x1, x2), 'end')
assert (np.sum(x[..., 0] == 0))
def test_crm():
"""Test CRM Corpus functions."""
fs = 40000 # native rate, to avoid large resampling delay in testing
crm_info()
tempdir = _TempDir()
# corpus prep
talkers = [dict(sex='f', talker_num=0)]
crm_prepare_corpus(fs, path_out=tempdir, talker_list=talkers,
n_jobs=np.inf)
crm_prepare_corpus(fs, path_out=tempdir, talker_list=talkers,
overwrite=True)
# no overwrite
assert_raises(RuntimeError, crm_prepare_corpus, fs, path_out=tempdir)
# load sentence from hard drive
crm_sentence(fs, 'f', 0, 0, 0, 0, 0, ramp_dur=0, path=tempdir)
crm_sentence(fs, 1, '0', 'charlie', 'red', '5', stereo=True, path=tempdir)
# bad value requested
assert_raises(ValueError, crm_sentence, fs, 1, 0, 0, 'periwinkle', 0,
path=tempdir)
# unprepared talker
assert_raises(RuntimeError, crm_sentence, fs, 'm', 0, 0, 0, 0,
path=tempdir)
# unprepared sampling rate
assert_raises(RuntimeError, crm_sentence, fs + 1, 0, 0, 0, 0, 0,
path=tempdir)
# CRMPreload class
crm = CRMPreload(fs, path=tempdir)
crm.sentence('f', 0, 0, 0, 0)
# unprepared sampling rate
assert_raises(RuntimeError, CRMPreload, fs + 1)
# bad value requested
assert_raises(ValueError, crm.sentence, 1, 0, 0, 'periwinkle', 0)
# unprepared talker
assert_raises(RuntimeError, crm.sentence, 'm', 0, 0, 0, 0)
# try to specify parameters like fs, stereo, etc.
assert_raises(TypeError, crm.sentence, fs, '1', '0', 'charlie', 'red', '5')
# add_pad
x1 = np.zeros(10)
x2 = np.ones((2, 5))
x = add_pad([x1, x2])
assert_true(np.sum(x[..., -1] == 0))
x = add_pad((x1, x2), 'center')
assert_true(np.sum(x[..., -1] == 0) and np.sum(x[..., 0] == 0))
x = add_pad((x1, x2), 'end')
assert_true(np.sum(x[..., 0] == 0))
# sampling rate.
#
# .. note:: For your experiment, you only need to prepare the corpus once per
# sampling rate, you should probably use the default path, and you
# should just do all the talkers at once. For the example, we are
# using fs=40000 and only doing two talkers so that the stimulus
# preparation is very fast, and a temp directory so that we don't
# interfere with any other prepared corpuses. Your code will likely
# look like this line, and not appear in your actual experiment
# script::
#
# >>> crm_prepare_corpus(24414)
#
crm_prepare_corpus(fs, path_out=crm_path, overwrite=True,
talker_list=[dict(sex=0, talker_num=0),
dict(sex=1, talker_num=0)])
# print the valid callsigns
print('Valid callsigns are {0}'.format(crm_info()['callsign']))
# read a sentence in from the hard drive
x1 = 0.5 * crm_sentence(fs, 'm', '0', 'c', 'r', '5', path=crm_path)
# preload all the talkers and get a second sentence from memory
crm = CRMPreload(fs, path=crm_path)
x2 = crm.sentence('f', '0', 'ringo', 'green', '6')
x = add_pad([x1, x2], alignment='start')
###############################################################################
#
# .. note:: For your experiment, you only need to prepare the corpus once per
# sampling rate, you should probably use the default path, and you
# should just do all the talkers at once. For the example, we are
# using fs=40000 and only doing two talkers so that the stimulus
# preparation is very fast, and a temp directory so that we don't
# interfere with any other prepared corpuses. Your code will likely
# look like this line, and not appear in your actual experiment
# script::
#
# >>> crm_prepare_corpus(24414)
#
crm_prepare_corpus(
fs,
path_out=crm_path,
overwrite=True,
talker_list=[dict(sex=0, talker_num=0),
dict(sex=1, talker_num=0)])
# print the valid callsigns
print('Valid callsigns are {0}'.format(crm_info()['callsign']))
# read a sentence in from the hard drive
x1 = 0.5 * crm_sentence(fs, 'm', '0', 'c', 'r', '5', path=crm_path)
# preload all the talkers and get a second sentence from memory
crm = CRMPreload(fs, path=crm_path)
x2 = crm.sentence('f', '0', 'ringo', 'green', '6')
x = add_pad([x1, x2], alignment='start')