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="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(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(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 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(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(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="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 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", 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(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=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="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",
"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
K21=[0.15],
sigma=[0.3],
mu=[2.2],
variables_of_interest=["xi", "alpha"])
oscilator.configure()
# for alpha series uncomment the below code
# oscilator = models.ReducedSetHindmarshRose(r=[0.006], a=[1.0], b=[3.0], c=[1.0], d=[5.0], s=[4.0], xo=[-1.6], K11=[4.0], K12=[1.6], K21=[0.15], sigma=[0.4], mu=[2.2], variables_of_interest=["xi","alpha"])
# oscilator.configure()
# set up the structural connectivity
mypath = "" # insert the path to where all subjects connectivities are stored
subject = "" # specify which subject to load
# load connectivity weights
reader = FileReader(file_path=mypath + '/' + subject + '/weights.txt')
w = reader.read_array(dtype=numpy.float64,
skip_rows=0,
use_cols=None,
matlab_data_name=None)
# load region centers
reader = FileReader(file_path=mypath + '/' + subject + '/centres.txt')
rl = reader.read_array(dtype="string",
skip_rows=0,
use_cols=(0, ),
matlab_data_name=None)
c = reader.read_array(dtype=numpy.float64,
skip_rows=0,
use_cols=(1, 2, 3),
matlab_data_name=None)
