def test_pad(self):
shape_0, shape_1 = zip(
*[cell_obj.data.shape for cell_obj in self.cells])
shape_0_max, shape_1_max = np.max(shape_0), np.max(shape_1)
cell_list = CellList([
pad_cell(cell_obj, (shape_0_max, shape_1_max))
for cell_obj in self.cells
])
for cell in cell_list:
self.assertEqual((shape_0_max, shape_1_max), cell.data.shape)
self.assertEqual((shape_0_max, shape_1_max), cell.coords.shape)
# pad by zero and check if the results are the same
x, y = self.cells.r_dist(20, 1, method='box')
cell_list = CellList([
pad_cell(cell_obj, cell_obj.data.shape) for cell_obj in self.cells
])
xn, yn = cell_list.r_dist(20, 1, method='box')
self.assertArrayEqual(y, yn)
#pad by known amount and check of storm coords more accordingly
cell = self.cells[0]
shape_0, shape_1 = cell.data.shape
padded_cell = pad_cell(cell, (shape_0 + 10, shape_1 + 10))
self.assertArrayEqual(cell.data.data_dict['storm']['x'] + 5,
padded_cell.data.data_dict['storm']['x'])
def _test_cell_list(self):
#todo check order
print(hashlib.md5(self.data).hexdigest())
cell_list = data_to_cells(self.data,
initial_crop=2,
cell_frac=0.5,
rotate='binary')
print(hashlib.md5(self.data).hexdigest())
cell_list = data_to_cells(self.data,
initial_crop=2,
cell_frac=0.5,
rotate='binary')
print(hashlib.md5(self.data).hexdigest())
d = self.data.copy()
print(d == self.data)
cl = CellList(cell_list)
self.assertEqual(len(cl), 48)
c5 = cl[5]
self.assertIsInstance(c5, Cell)
del cl[5]
self.assertEqual(len(cl), 47)
self.assertTrue(cl[3] in cl)
cl.append(c5)
self.assertTrue(c5 in cl)
vol = cl.volume
self.assertEqual(len(vol), 48)
def test_crop(self):
shape_0, shape_1 = 20, 30
cell_list = CellList([
crop_cell(cell_obj, (shape_0, shape_1)) for cell_obj in self.cells
])
for cell in cell_list:
self.assertEqual((shape_0, shape_1), cell.data.shape)
self.assertEqual((shape_0, shape_1), cell.coords.shape)
def __init__(self, cell_list, pad=True):
if pad:
shape_0, shape_1 = zip(
*[cell_obj.data.shape for cell_obj in cell_list])
self.cell_list = CellList([
pad_cell(cell_obj, (np.max(shape_0), np.max(shape_1)))
for cell_obj in cell_list
])
else:
self.cell_list = cell_list
def setUp(self):
self.data = load_testdata('ds1')
f_path = os.path.dirname(os.path.realpath(__file__))
self.storm_cells_1 = load(
os.path.join(f_path, 'test_data/test_single_spot_storm.hdf5'))
self.storm_cells_2 = load(
os.path.join(f_path, 'test_data/test_double_spot_storm.hdf5'))
cells_no_flu = []
for c in self.storm_cells_2:
d = Data()
d.add_data(c.data.binary_img, 'binary')
d.add_data(c.data.data_dict['storm_1'], 'storm', 'storm_1')
d.add_data(c.data.data_dict['storm_2'], 'storm', 'storm_2')
cell = Cell(d)
cells_no_flu.append(cell)
self.storm_cells_2_no_flu = CellList(cells_no_flu)
def load(file_path):
"""
Load ``Cell`` or ``CellList`` from disk.
Parameters
----------
file_path : :obj:`str`
Source file path.
Returns
-------
cell : :class:`~colicoords.cell.Cell` or :class:`~colicoords.cell.CellList`
Loaded ``Cell`` or ``CellList``
"""
with h5py.File(file_path, 'r') as f:
cell_list = [_load_cell(f[key]) for key in f.keys()]
if len(cell_list) == 1:
return cell_list[0]
else:
return CellList(cell_list)