def test_braindata():
vol = np.random.randn(*volshape)
tf = tempfile.TemporaryFile(suffix='.png')
mask = db.get_mask(subj, xfmname, "thick")
data = dataset.Volume(vol, subj, xfmname, cmap='RdBu_r', vmin=0, vmax=1)
# quickflat.make_png(tf, data)
mdata = data.masked['thick']
assert len(mdata.data) == mask.sum()
assert np.allclose(mdata.volume[:, mask], mdata.data)
def test_braindata(): vol = np.random.randn(31, 100, 100) tf = tempfile.TemporaryFile(suffix='.png') mask = db.get_mask(subj, xfmname, "thick") data = dataset.DataView((vol, subj, xfmname), cmap='RdBu_r', vmin=0, vmax=1) # quickflat.make_png(tf, data) mdata = data.copy(data.data.masked['thick']) assert len(mdata.data.data) == mask.sum() assert np.allclose(mdata.data.volume[mask], mdata.data.data)
def test_dataset():
vol = np.random.randn(*volshape)
stack = (np.ones(volshape[::-1])*np.linspace(0, 1, volshape[0])).T
mask = db.get_mask(subj, xfmname, "thick")
ds = dataset.Dataset(randvol=(vol, subj, xfmname), stack=(stack, subj, xfmname))
ds.append(thickstack=ds.stack.masked['thick'])
tf = tempfile.NamedTemporaryFile(suffix=".hdf")
ds.save(tf.name)
ds = dataset.Dataset.from_file(tf.name)
assert len(ds['thickstack'].data) == mask.sum()
assert np.allclose(ds['stack'].data[mask], ds['thickstack'].data)
return ds
def test_dataset():
vol = np.random.randn(*volshape)
stack = (np.ones(volshape[::-1])*np.linspace(0, 1, volshape[0])).T
mask = db.get_mask(subj, xfmname, "thick")
ds = dataset.Dataset(randvol=(vol, subj, xfmname), stack=(stack, subj, xfmname))
ds.append(thickstack=ds.stack.masked['thick'])
tf = tempfile.NamedTemporaryFile(suffix=".hdf")
ds.save(tf.name)
ds = dataset.Dataset.from_file(tf.name)
assert len(ds['thickstack'].data) == mask.sum()
assert np.allclose(ds['stack'].data[mask], ds['thickstack'].data)
return ds
def test_dataset(): vol = np.random.randn(31, 100, 100) stack = (np.ones((100, 100, 31))*np.linspace(0, 1, 31)).T raw = (np.random.rand(10, 31, 100, 100, 3)*256).astype(np.uint8) mask = db.get_mask(subj, xfmname, "thick") ds = dataset.Dataset(randvol=(vol, subj, xfmname), stack=(stack, subj, xfmname)) ds.append(thickstack=ds.stack.copy(ds.stack.data.masked['thick'])) ds.append(raw=dataset.VolumeData(raw, subj, xfmname).masked['thin']) tf = tempfile.NamedTemporaryFile(suffix=".hdf") ds.save(tf.name) ds = dataset.Dataset.from_file(tf.name) assert len(ds['thickstack'].data.data) == mask.sum() assert np.allclose(ds['stack'].data.data[mask], ds['thickstack'].data.data) assert ds['raw'].data.volume.shape == (10, 31, 100, 100, 4) return ds
def test_findmask():
vol = np.random.rand(10, *volshape)
mask = db.get_mask(subj, xfmname, "thin")
ds = dataset.Volume(vol[:, mask], subj, xfmname)
assert np.allclose(ds.volume[:, mask], vol[:, mask])
return ds
def test_findmask(): vol = (np.random.rand(10, 31, 100, 100, 3)*256).astype(np.uint8) mask = db.get_mask(subj, xfmname, "thin") ds = dataset.VolumeData(vol[:, mask], subj, xfmname) assert np.allclose(ds.volume[:, mask, :3], vol[:, mask]) return ds
def test_findmask():
vol = np.random.rand(10, *volshape)
mask = db.get_mask(subj, xfmname, "thin")
ds = dataset.Volume(vol[:, mask], subj, xfmname)
assert np.allclose(ds.volume[:, mask], vol[:, mask])
return ds
