def from_file(source_file="connectivity_76.zip", instance=None):
if instance is None:
result = Connectivity()
else:
result = instance
source_full_path = try_get_absolute_path("tvb_data.connectivity", source_file)
if source_file.endswith(".h5"):
reader = H5Reader(source_full_path)
result.weights = reader.read_field("weights")
result.centres = reader.read_field("centres")
result.region_labels = reader.read_field("region_labels")
result.orientations = reader.read_optional_field("orientations")
result.cortical = reader.read_optional_field("cortical")
result.hemispheres = reader.read_field("hemispheres")
result.areas = reader.read_optional_field("areas")
result.tract_lengths = reader.read_field("tract_lengths")
else:
reader = ZipReader(source_full_path)
result.weights = reader.read_array_from_file("weights")
result.centres = reader.read_array_from_file("centres", use_cols=(1, 2, 3))
result.region_labels = reader.read_array_from_file("centres", dtype=numpy.str, use_cols=(0,))
result.orientations = reader.read_optional_array_from_file("average_orientations")
result.cortical = reader.read_optional_array_from_file("cortical", dtype=numpy.bool)
result.hemispheres = reader.read_optional_array_from_file("hemispheres", dtype=numpy.bool)
result.areas = reader.read_optional_array_from_file("areas")
result.tract_lengths = reader.read_array_from_file("tract_lengths")
return result
def from_file(source_file="nonexistent.zip", instance=None):
'''
Borrowed from connectivity.Connectivity - copied here and modified to match filesnames of Berlin connectivity .txts in connectivity.zip (ie orientation.txt rather than average_orientations.txt)
:param source_file:
:param instance:
:return: Connectivity object from source_file.
'''
if instance is None:
result = connectivity.Connectivity()
else:
result = instance
source_full_path = try_get_absolute_path("tvb_data.connectivity", source_file)
reader = ZipReader(source_full_path)
result.areas = reader.read_array_from_file("area")
result.region_labels = reader.read_array_from_file("centres", dtype=numpy.str, use_cols=(0,))
result.centres = reader.read_array_from_file("centres", use_cols=(1, 2, 3))
result.cortical = reader.read_array_from_file("cortical", dtype=numpy.bool)
result.hemispheres = reader.read_array_from_file("hemisphere", dtype=numpy.bool)
result.orientations = reader.read_array_from_file("orientation")
result.tract_lengths = reader.read_array_from_file("tract")
result.weights = reader.read_array_from_file("weights")
return result
def from_file(cls, source_file="cortex_16384.zip"):
"""Construct a Surface from source_file."""
result = cls()
source_full_path = try_get_absolute_path("tvb_data.surfaceData", source_file)
reader = ZipReader(source_full_path)
result.vertices = reader.read_array_from_file("vertices.txt")
result.vertex_normals = reader.read_array_from_file("normals.txt")
result.triangles = reader.read_array_from_file("triangles.txt", dtype=numpy.int32)
return result
def from_file(cls, source_file=os.path.join("cortex_reg13", "surface_cortex_reg13.zip"), instance=None):
"""
Construct a Surface from source_file.
"""
if instance is None:
result = cls()
else:
result = instance
source_full_path = try_get_absolute_path("tvb_data.surfaceData", source_file)
reader = ZipReader(source_full_path)
result.vertices = reader.read_array_from_file("vertices.txt")
result.vertex_normals = reader.read_array_from_file("normals.txt")
result.triangles = reader.read_array_from_file("triangles.txt", dtype=numpy.int32)
return result
def from_file(source_file="connectivity_76.zip", instance=None):
source_full_path = try_get_absolute_path("tvb_data.connectivity",
source_file)
if source_file.endswith(".h5"):
reader = H5Reader(source_full_path)
weights = reader.read_field("weights")
centres = reader.read_field("centres")
region_labels = reader.read_field("region_labels")
orientations = reader.read_optional_field("orientations")
cortical = reader.read_optional_field("cortical")
hemispheres = reader.read_field("hemispheres")
areas = reader.read_optional_field("areas")
tract_lengths = reader.read_field("tract_lengths")
else:
reader = ZipReader(source_full_path)
weights = reader.read_array_from_file("weights")
if reader.has_file_like("centres"):
centres = reader.read_array_from_file("centres",
use_cols=(1, 2, 3))
region_labels = reader.read_array_from_file("centres",
dtype=numpy.str,
use_cols=(0, ))
else:
centres = reader.read_array_from_file("centers",
use_cols=(1, 2, 3))
region_labels = reader.read_array_from_file("centers",
dtype=numpy.str,
use_cols=(0, ))
orientations = reader.read_optional_array_from_file(
"average_orientations")
cortical = reader.read_optional_array_from_file("cortical",
dtype=numpy.bool)
hemispheres = reader.read_optional_array_from_file(
"hemispheres", dtype=numpy.bool)
areas = reader.read_optional_array_from_file("areas")
tract_lengths = reader.read_array_from_file("tract_lengths")
return weights, centres, region_labels, orientations, cortical, hemispheres, areas, tract_lengths