def from_file_projection_array(source_file="projection_eeg_62_surface_16k.mat",
matlab_data_name="ProjectionMatrix"):
source_full_path = try_get_absolute_path("tvb_data.projectionMatrix", source_file)
reader = FileReader(source_full_path)
return reader.read_array(matlab_data_name=matlab_data_name)
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(source_file="regionMapping_16k_76.txt"):
source_full_path = try_get_absolute_path("tvb_data.regionMapping",
source_file)
reader = FileReader(source_full_path)
result = RegionMapping()
result.array_data = reader.read_array(dtype=numpy.int32)
return result
def from_file(source_file="local_connectivity_16384.mat", instance=None):
source_full_path = try_get_absolute_path("tvb_data.local_connectivity",
source_file)
reader = FileReader(source_full_path)
matrix = reader.read_array(matlab_data_name="LocalCoupling")
return matrix
def from_file(source_file="regionMapping_16k_76.txt", instance=None):
source_full_path = try_get_absolute_path("tvb_data.regionMapping",
source_file)
reader = FileReader(source_full_path)
mapping = reader.read_array(dtype=numpy.int32)
return mapping
def from_file_region_mapping_array(source_file=os.path.join(
"cortex_reg13", "all_regions_cortex_reg13.txt")):
source_full_path = try_get_absolute_path("tvb_data.surfaceData",
source_file)
reader = FileReader(source_full_path)
return reader.read_array(dtype=numpy.int32)
def from_file(cls, source_file="meg_151.txt.bz2"):
result = super(SensorsMEG, cls).from_file(source_file)
source_full_path = try_get_absolute_path("tvb_data.sensors", source_file)
reader = FileReader(source_full_path)
result.orientations = reader.read_array(use_cols=(4, 5, 6))
return result
def populate_table(result, source_file):
source_full_path = try_get_absolute_path("tvb_data.tables",
source_file)
zip_data = numpy.load(source_full_path)
result.df = zip_data['df']
result.xmin, result.xmax = zip_data['min_max']
result.data = zip_data['f']
return result
def from_file(cls, source_file="meg_151.txt.bz2", instance=None):
#labels, locations = super(SensorsMEG, cls).from_file(source_file=source_file)
source_full_path = try_get_absolute_path("tvb_data.sensors",
source_file)
reader = FileReader(source_full_path)
orientations = reader.read_array(use_cols=(4, 5, 6))
return orientations
def from_file(source_file="local_connectivity_16384.mat"):
result = LocalConnectivity()
source_full_path = try_get_absolute_path("tvb_data.local_connectivity", source_file)
reader = FileReader(source_full_path)
result.matrix = reader.read_array(matlab_data_name="LocalCoupling")
return result
def from_file(cls, source_file=None, matlab_data_name=None, is_brainstorm=False, instance=None):
source_full_path = try_get_absolute_path("tvb_data.projectionMatrix", source_file)
reader = FileReader(source_full_path)
if is_brainstorm:
projection_data = reader.read_gain_from_brainstorm()
else:
projection_data = reader.read_array(matlab_data_name=matlab_data_name)
return projection_data
def from_file(cls, source_file="eeg_brainstorm_65.txt"):
result = cls()
source_full_path = try_get_absolute_path("tvb_data.sensors", source_file)
reader = FileReader(source_full_path)
result.labels = reader.read_array(dtype=numpy.str, use_cols=(0,))
result.locations = reader.read_array(use_cols=(1, 2, 3))
return result
def import_surface_rm(project_id, conn_gid):
# Import surface and region mapping from tvb_data berlin subjects (68 regions)
rm_file = try_get_absolute_path("tvb_data", "berlinSubjects/DH_20120806/DH_20120806_RegionMapping.txt")
surface_zip_file = try_get_absolute_path("tvb_data", "berlinSubjects/DH_20120806/DH_20120806_Surface_Cortex.zip")
surface_importer = ABCAdapter.build_adapter_from_class(ZIPSurfaceImporter)
surface_imp_model = ZIPSurfaceImporterModel()
surface_imp_model.uploaded = surface_zip_file
surface_imp_operation = fire_operation(project_id, surface_importer, surface_imp_model)
surface_imp_operation = wait_to_finish(surface_imp_operation)
surface_gid = dao.get_results_for_operation(surface_imp_operation.id)[0].gid
rm_importer = ABCAdapter.build_adapter_from_class(RegionMappingImporter)
rm_imp_model = RegionMappingImporterModel()
rm_imp_model.mapping_file = rm_file
rm_imp_model.surface = surface_gid
rm_imp_model.connectivity = conn_gid
rm_import_operation = fire_operation(project_id, rm_importer, rm_imp_model)
wait_to_finish(rm_import_operation)
def from_file(cls, source_file="eeg_brainstorm_65.txt", instance=None):
source_full_path = try_get_absolute_path("tvb_data.sensors",
source_file)
reader = FileReader(source_full_path)
labels = reader.read_array(dtype="string", use_cols=(0, ))
locations = reader.read_array(use_cols=(1, 2, 3))
return labels, locations
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(source_file=os.path.join("cortex_reg13", "region_mapping", "o52r00_irp2008_hemisphere_both_subcortical_false_regions_74.txt.bz2"), instance=None):
if instance is None:
result = RegionMapping()
else:
result = instance
source_full_path = try_get_absolute_path("tvb_data.surfaceData", source_file)
reader = FileReader(source_full_path)
result.array_data = reader.read_array(dtype=numpy.int32)
return result
def from_file(source_file="regionMapping_16k_76.txt", instance=None):
if instance is None:
result = RegionMapping()
else:
result = instance
source_full_path = try_get_absolute_path("tvb_data.regionMapping",
source_file)
reader = FileReader(source_full_path)
result.array_data = reader.read_array(dtype=numpy.int32)
return result
def from_file(source_file=os.path.join("cortex_reg13", "local_connectivity_surface_cortex_reg13.mat"),
instance=None):
if instance is None:
result = LocalConnectivity()
else:
result = instance
source_full_path = try_get_absolute_path("tvb_data.surfaceData", source_file)
reader = FileReader(source_full_path)
result.matrix = reader.read_array(matlab_data_name="LocalCoupling")
return result
def from_file(source_file=os.path.join("cortex_reg13",
"all_regions_cortex_reg13.txt"),
instance=None):
if instance is None:
result = RegionMapping()
else:
result = instance
source_full_path = try_get_absolute_path("tvb_data.surfaceData",
source_file)
reader = FileReader(source_full_path)
result.array_data = reader.read_array(dtype=numpy.int32)
return result
def from_file(cls, source_file="eeg_unitvector_62.txt.bz2", instance=None):
if instance is None:
result = cls()
else:
result = instance
source_full_path = try_get_absolute_path("tvb_data.sensors",
source_file)
reader = FileReader(source_full_path)
result.labels = reader.read_array(dtype="string", use_cols=(0, ))
result.locations = reader.read_array(use_cols=(1, 2, 3))
return result
def load_surface_projection_matrix(result, source_file):
source_full_path = try_get_absolute_path("tvb_data.projectionMatrix",
source_file)
if source_file.endswith(".mat"):
# consider we have a brainstorm format
mat = scipy.io.loadmat(source_full_path)
gain, loc, ori = (mat[field]
for field in 'Gain GridLoc GridOrient'.split())
result.projection_data = (gain.reshape(
(gain.shape[0], -1, 3)) * ori).sum(axis=-1)
elif source_file.endswith(".npy"):
# numpy array with the projection matrix already computed
result.projection_data = numpy.load(source_full_path)
else:
raise Exception(
"The projection matrix must be either a numpy array or a brainstorm mat file"
)
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
