def _get_voxel_time_series_region(self, ts_h5, x, y, z, var=0, mode=0):
region_mapping_volume_gid = ts_h5.region_mapping_volume.load()
if region_mapping_volume_gid is None:
raise Exception("Invalid method called for TS without Volume Mapping!")
volume_rm_h5_class, volume_rm_h5_path = self._load_h5_of_gid(region_mapping_volume_gid.hex)
volume_rm_h5 = volume_rm_h5_class(volume_rm_h5_path)
volume_rm_shape = volume_rm_h5.array_data.shape
x, y, z = preprocess_space_parameters(x, y, z, volume_rm_shape[0], volume_rm_shape[1], volume_rm_shape[2])
idx_slices = slice(x, x + 1), slice(y, y + 1), slice(z, z + 1)
idx = int(volume_rm_h5.array_data[idx_slices])
time_length = ts_h5.data.shape[0]
var, mode = int(var), int(mode)
voxel_slices = prepare_time_slice(time_length), slice(var, var + 1), slice(idx, idx + 1), slice(mode, mode + 1)
connectivity_gid = volume_rm_h5.connectivity.load()
connectivity_h5_class, connectivity_h5_path = self._load_h5_of_gid(connectivity_gid.hex)
connectivity_h5 = connectivity_h5_class(connectivity_h5_path)
label = connectivity_h5.region_labels.load()[idx]
background, back_min, back_max = None, None, None
if idx < 0:
back_min, back_max = ts_h5.get_min_max_values()
background = numpy.ones((time_length, 1)) * ts_h5.out_of_range(back_min)
label = 'background'
volume_rm_h5.close()
connectivity_h5.close()
result = postprocess_voxel_ts(ts_h5, voxel_slices, background, back_min, back_max, label)
return result
def get_view_region(self,
ts_h5,
volume_rm_h5,
from_idx,
to_idx,
x,
y,
z,
var=0,
mode=0):
idx_slices = slice(x, x + 1), slice(y, y + 1), slice(z, z + 1)
idx = int(volume_rm_h5.array_data[idx_slices])
time_length = ts_h5.data.shape[0]
var, mode = int(var), int(mode)
voxel_slices = prepare_time_slice(time_length), slice(
var, var + 1), slice(idx, idx + 1), slice(mode, mode + 1)
connectivity_gid = volume_rm_h5.connectivity.load()
with h5.h5_file_for_gid(connectivity_gid) as connectivity_h5:
label = connectivity_h5.region_labels.load()[idx]
background, back_min, back_max = None, None, None
if idx < 0:
back_min, back_max = ts_h5.get_min_max_values()
background = numpy.ones(
(time_length, 1)) * ts_h5.out_of_range(back_min)
label = 'background'
result = postprocess_voxel_ts(ts_h5, voxel_slices, background,
back_min, back_max, label)
return result
def get_voxel_time_series(self, x, y, z, **kwargs):
"""
Retrieve for a given voxel (x,y,z) the entire timeline.
:param x: int coordinate
:param y: int coordinate
:param z: int coordinate
:return: A complex dictionary with information about current voxel.
The main part will be a vector with all the values over time from the x,y,z coordinates.
"""
overall_shape = self.data.shape
x, y, z = preprocess_space_parameters(x, y, z, overall_shape[1], overall_shape[2], overall_shape[3])
slices = prepare_time_slice(overall_shape[0]), slice(x, x + 1), slice(y, y + 1), slice(z, z + 1)
result = postprocess_voxel_ts(self, slices)
return result