def test_beam_io_runs():
cr = MEG_coreg("asdf", "fdsa", np.eye(4), np.eye(3))
b = Beam(np.array([5.0] * 3), np.random.randn(1000, 3), 200.0, np.arange(100), np.random.randn(1000), cr)
f = tempfile.mktemp(suffix=".npy")
try:
b.save(f)
b2 = Beam.load(f)
os.unlink(f)
assert True
except:
os.unlink(f)
assert False, "simple Beam I/O failed"
def __init__(self, voxelsize, voxels, srate, timepts,
sig, coreg, bands, timewindow,
coordmap=None, fixed_comparison=None, uses='F dB'):
"""
Parameters
----------
voxelsize : len-3 iterable
the voxel edge lengths
voxels : ndarray shaped (nvox, 3)
the voxel coordinates, in this Beam's target coordinate space
srate : float
the sampling rate of the MEG time series
timepts : ndarray
the sample times
sig : ndarray
the MEG signal data -- see NOTE
coreg : MEG_coreg object
the MEG-to-MRI coregistration info
coordmap : NIPY AffineTransform object
the MEG voxel index coordinate to voxel location coordinate mapping
Notes
-----
The signal argument can take on the following forms:
* a record/structured ndarray with 'active', 'control', ['noise']
components
* a list/tuple of ndarrays (taken to mean 'active', 'control',
['noise'] components)
* a normal ndarray with no separate components (literally, a
fixed comparison). In this case, the `fixed_comparison` keyword
argument is REQUIRED so that the TFBeam understands what the
data means
* adapted from MATLAB s_beam*.mat files, for `internal` use --
This format has dtype('object'), and may be a simple list of
components
"""
sig, voxels = self._init_signal(sig, voxels, fixed_comparison)
Beam.__init__(self, voxelsize, voxels, srate, timepts, sig, coreg,
coordmap=coordmap)
self.bands = np.atleast_2d(bands)
self.timewindow = np.atleast_2d(timewindow)
if not fixed_comparison:
# still mark it down for posterity (ie, array "pickling")
self.fixed_comparison = fixed_comparison
self.uses = uses
else:
self.fix_comparison(fixed_comparison)
