class MatlabAdapter(ABCGroupAdapter):
"""
Interface between Brain Connectivity Toolbox of Olaf Sporns and TVB Framework.
This adapter requires BCT and Matlab deployed locally.
"""
def __init__(self, xml_file_path):
ABCGroupAdapter.__init__(self, xml_file_path)
self.matlab_worker = MatlabWorker()
@staticmethod
def can_be_active():
return not not TvbProfile.current.MATLAB_EXECUTABLE
def get_required_memory_size(self, **kwargs):
"""
Return the required memory to run this algorithm.
"""
# Don't know how much memory is needed.
return -1
def get_required_disk_size(self, **kwargs):
"""
Returns the required disk size to be able to run the adapter (in kB).
"""
return 0
def get_matlab_file_root(self):
"""
Return the root folder in which the matlab files are stored.
"""
return self.xml_reader.get_additional_path()
def launch(self, **kwargs):
"""
Pick the correct algorithm to use, and launch the MATLAB call.
After computation, make sure the correct results are returned.
"""
# Read selected Algorithm identifier, from input arguments
bct_storage = self.xml_reader.get_additional_path()
if bct_storage is not None:
self.matlab_worker.add_to_path(bct_storage)
algorithm, kwargs = self.get_algorithm_and_attributes(**kwargs)
# Execute MATLAB code
mat_code = self.get_call_code(algorithm)
self.log.info("Starting execution of MATLAB code:" + mat_code)
runcode, matlablog, result = self.matlab_worker.matlab(mat_code, kwargs)
self.log.debug("Code run in MATLAB: " + str(runcode))
self.log.debug("MATLAB log: " + str(matlablog))
self.log.debug("Finished MATLAB execution:" + str(result))
# Now build PYTHON result objects
return self.build_result(algorithm, result, kwargs)
def __init__(self):
ABCAsynchronous.__init__(self)
self.matlab_worker = MatlabWorker()
class BaseBCT(ABCAsynchronous):
"""
Interface between Brain Connectivity Toolbox of Olaf Sporns and TVB Framework.
This adapter requires BCT deployed locally, and Matlab or Octave installed separately of TVB.
"""
def __init__(self):
ABCAsynchronous.__init__(self)
self.matlab_worker = MatlabWorker()
@staticmethod
def can_be_active():
return not not TvbProfile.current.MATLAB_EXECUTABLE
def get_form_class(self):
return BaseBCTForm
def get_output(self):
return [ConnectivityMeasureIndex, ValueWrapperIndex]
def get_required_memory_size(self, view_model):
# We do not know how much memory is needed.
return -1
def get_required_disk_size(self, view_model):
return 0
def get_connectivity(self, view_model):
conn_index = load_entity_by_gid(view_model.connectivity.hex)
return h5.load_from_index(conn_index)
def execute_matlab(self, matlab_code, data):
self.matlab_worker.add_to_path(BCT_PATH)
self.log.info("Starting execution of MATLAB code:" + matlab_code)
runcode, matlablog, result = self.matlab_worker.matlab(matlab_code,
data=data)
self.log.debug("Code run in MATLAB: " + str(runcode))
self.log.debug("MATLAB log: " + str(matlablog))
self.log.debug("Finished MATLAB execution:" + str(result))
return result
def build_connectivity_measure(self,
result,
key,
connectivity,
title="",
label_x="",
label_y=""):
measure = ConnectivityMeasure()
measure.array_data = result[key]
measure.connectivity = connectivity
measure.title = title
measure.label_x = label_x
measure.label_y = label_y
return h5.store_complete(measure, self.storage_path)
def build_float_value_wrapper(self, result, key, title=""):
value = ValueWrapperIndex()
value.data_value = float(result[key])
value.data_type = 'float'
value.data_name = title
return value
def build_int_value_wrapper(self, result, key, title=""):
value = ValueWrapperIndex()
value.data_value = int(result[key])
value.data_type = 'int'
value.data_name = title
return value
@abstractmethod
def launch(self, view_model):
pass
def __init__(self):
ABCAdapter.__init__(self)
self.matlab_worker = MatlabWorker()
def __init__(self):
ABCAsynchronous.__init__(self)
self.matlab_worker = MatlabWorker()
class BaseBCT(ABCAsynchronous):
"""
Interface between Brain Connectivity Toolbox of Olaf Sporns and TVB Framework.
This adapter requires BCT deployed locally, and Matlab or Octave installed separately of TVB.
"""
_ui_connectivity_label = "Connection matrix:"
def __init__(self):
ABCAsynchronous.__init__(self)
self.matlab_worker = MatlabWorker()
@staticmethod
def can_be_active():
return not not TvbProfile.current.MATLAB_EXECUTABLE
def get_input_tree(self):
return [dict(name="connectivity", label=self._ui_connectivity_label, type=Connectivity, required=True)]
def get_output(self):
return [ConnectivityMeasure, ValueWrapper]
def get_required_memory_size(self, **kwargs):
# We do not know how much memory is needed.
return -1
def get_required_disk_size(self, **kwargs):
return 0
def execute_matlab(self, matlab_code, **kwargs):
self.matlab_worker.add_to_path(BCT_PATH)
self.log.info("Starting execution of MATLAB code:" + matlab_code)
runcode, matlablog, result = self.matlab_worker.matlab(matlab_code, kwargs)
self.log.debug("Code run in MATLAB: " + str(runcode))
self.log.debug("MATLAB log: " + str(matlablog))
self.log.debug("Finished MATLAB execution:" + str(result))
return result
def build_connectivity_measure(self, result, key, connectivity, title="", label_x="", label_y=""):
measure = ConnectivityMeasure(storage_path=self.storage_path)
measure.array_data = result[key]
measure.connectivity = connectivity
measure.title = title
measure.label_x = label_x
measure.label_y = label_y
return measure
def build_float_value_wrapper(self, result, key, title=""):
value = ValueWrapper(storage_path=self.storage_path)
value.data_value = float(result[key])
value.data_type = 'float'
value.data_name = title
return value
def build_int_value_wrapper(self, result, key, title=""):
value = ValueWrapper(storage_path=self.storage_path)
value.data_value = int(result[key])
value.data_type = 'int'
value.data_name = title
return value
@abstractmethod
def launch(self, connectivity, **kwargs):
pass
class BaseBCT(ABCAsynchronous):
"""
Interface between Brain Connectivity Toolbox of Olaf Sporns and TVB Framework.
This adapter requires BCT deployed locally, and Matlab or Octave installed separately of TVB.
"""
_ui_connectivity_label = "Connection matrix:"
def __init__(self):
ABCAsynchronous.__init__(self)
self.matlab_worker = MatlabWorker()
@staticmethod
def can_be_active():
return not not TvbProfile.current.MATLAB_EXECUTABLE
def get_input_tree(self):
return [
dict(name="connectivity",
label=self._ui_connectivity_label,
type=Connectivity,
required=True)
]
def get_output(self):
return [ConnectivityMeasure, ValueWrapper]
def get_required_memory_size(self, **kwargs):
# We do not know how much memory is needed.
return -1
def get_required_disk_size(self, **kwargs):
return 0
def execute_matlab(self, matlab_code, **kwargs):
self.matlab_worker.add_to_path(BCT_PATH)
self.log.info("Starting execution of MATLAB code:" + matlab_code)
runcode, matlablog, result = self.matlab_worker.matlab(
matlab_code, kwargs)
self.log.debug("Code run in MATLAB: " + str(runcode))
self.log.debug("MATLAB log: " + str(matlablog))
self.log.debug("Finished MATLAB execution:" + str(result))
return result
def build_connectivity_measure(self,
result,
key,
connectivity,
title="",
label_x="",
label_y=""):
measure = ConnectivityMeasure(storage_path=self.storage_path)
measure.array_data = result[key]
measure.connectivity = connectivity
measure.title = title
measure.label_x = label_x
measure.label_y = label_y
return measure
def build_float_value_wrapper(self, result, key, title=""):
value = ValueWrapper(storage_path=self.storage_path)
value.data_value = float(result[key])
value.data_type = 'float'
value.data_name = title
return value
def build_int_value_wrapper(self, result, key, title=""):
value = ValueWrapper(storage_path=self.storage_path)
value.data_value = int(result[key])
value.data_type = 'int'
value.data_name = title
return value
@abstractmethod
def launch(self, connectivity, **kwargs):
pass
def __init__(self, xml_file_path):
ABCGroupAdapter.__init__(self, xml_file_path)
self.matlab_worker = MatlabWorker()
