def setup():
global DIRPATH
DIRPATH = tempfile.mkdtemp()
# Create DAT file.
raw_data = create_trace(nsamples, nchannels)
for start, end in excerpts(nsamples, nexcerpts=10, excerpt_size=10):
raw_data[start:end] += np.random.randint(low=-10000, high=10000,
size=(10, nchannels))
raw_data.tofile(op.join(DIRPATH, dat_filename))
# Create PRM file.
prm = get_params(**{
'raw_data_files': dat_filename,
'experiment_name': name,
'nchannels': nchannels,
'sample_rate': sample_rate,
'detect_spikes': 'positive',
'prb_file': prb_filename,
})
prm_contents = pydict_to_python(prm)
with open(op.join(DIRPATH, prm_filename), 'w') as f:
f.write(prm_contents)
# Create PRB file.
prb_contents = """
nchannels = %NCHANNELS%
channel_groups = {0:
{
'channels': list(range(nchannels)),
'graph': [(i, i + 1) for i in range(nchannels - 1)],
}
}""".replace('%NCHANNELS%', str(nchannels)).replace(' ', '')
with open(op.join(DIRPATH, prb_filename), 'w') as f:
f.write(prb_contents)
def test_pydict_to_python():
pydict = dict(MYVAR1='myvalue1', MYVAR2=.123, MYVAR3=['myvalue3', .456])
python = pydict_to_python(pydict)
assert python == """
MYVAR1 = 'myvalue1'
MYVAR2 = 0.123
MYVAR3 = ['myvalue3', 0.456]
""".replace(' ', '').strip()
def test_params_to_python():
params = dict(MYVAR1='myvalue1',
MYVAR2=.123,
MYVAR3=['myvalue3', .456],
SAMPLE_RATE=1)
python = pydict_to_python(params)
assert python == """
MYVAR1 = 'myvalue1'
MYVAR2 = 0.123
MYVAR3 = ['myvalue3', 0.456]
SAMPLE_RATE = 1
""".replace(' ', '').strip()
def test_pydict_to_python():
pydict = dict(
MYVAR1 = 'myvalue1',
MYVAR2 = .123,
MYVAR3 = ['myvalue3', .456])
python = pydict_to_python(pydict)
assert python == """
MYVAR1 = 'myvalue1'
MYVAR2 = 0.123
MYVAR3 = ['myvalue3', 0.456]
""".replace(' ', '').strip()
def test_params_to_python():
params = dict(
MYVAR1 = 'myvalue1',
MYVAR2 = .123,
MYVAR3 = ['myvalue3', .456],
SAMPLE_RATE = 1)
python = pydict_to_python(params)
assert python == """
MYVAR1 = 'myvalue1'
MYVAR2 = 0.123
MYVAR3 = ['myvalue3', 0.456]
SAMPLE_RATE = 1
""".replace(' ', '').strip()
def setup():
global DIRPATH
DIRPATH = tempfile.mkdtemp()
# Create DAT file.
raw_data = create_trace(nsamples, nchannels)
for start, end in excerpts(nsamples, nexcerpts=10, excerpt_size=10):
raw_data[start:end] += np.random.randint(low=-10000,
high=10000,
size=(10, nchannels))
raw_data.tofile(op.join(DIRPATH, dat_filename))
# Create PRM file.
prm = get_params(
**{
'raw_data_files': dat_filename,
'experiment_name': name,
'nchannels': nchannels,
'sample_rate': sample_rate,
'detect_spikes': 'positive',
'prb_file': prb_filename,
})
prm_contents = pydict_to_python(prm)
with open(op.join(DIRPATH, prm_filename), 'w') as f:
f.write(prm_contents)
# Create PRB file.
prb_contents = """
nchannels = %NCHANNELS%
channel_groups = {0:
{
'channels': list(range(nchannels)),
'graph': [(i, i + 1) for i in range(nchannels - 1)],
}
}""".replace('%NCHANNELS%', str(nchannels)).replace(' ', '')
with open(op.join(DIRPATH, prb_filename), 'w') as f:
f.write(prb_contents)
