def capture_objects(self):
"""!
@return (list) Indexes of captured objects by each neuron.
"""
if (self.__ccore_som_pointer is not None):
self._capture_objects = wrapper.som_get_capture_objects(self.__ccore_som_pointer);
return self._capture_objects;
def capture_objects(self):
"""!
@return (list) Indexes of captured objects by each neuron.
"""
if (self.__ccore_som_pointer is not None):
self._capture_objects = wrapper.som_get_capture_objects(self.__ccore_som_pointer);
return self._capture_objects;
def capture_objects(self):
"""!
@brief Returns indexes of captured objects by each neuron.
@details For example, network with size 2x2 has been trained on 5 sample, we neuron #1 has won one object with
index '1', neuron #2 - objects with indexes '0', '3', '4', neuron #3 - nothing, neuron #4 - object
with index '2'. Thus, output is [ [1], [0, 3, 4], [], [2] ].
@return (list) Indexes of captured objects by each neuron.
"""
if self.__ccore_som_pointer is not None:
self._capture_objects = wrapper.som_get_capture_objects(self.__ccore_som_pointer)
return self._capture_objects
def capture_objects(self):
"""!
@brief Returns indexes of captured objects by each neuron.
@details For example, network with size 2x2 has been trained on 5 sample, we neuron #1 has won one object with
index '1', neuron #2 - objects with indexes '0', '3', '4', neuron #3 - nothing, neuron #4 - object
with index '2'. Thus, output is [ [1], [0, 3, 4], [], [2] ].
@return (list) Indexes of captured objects by each neuron.
"""
if (self.__ccore_som_pointer is not None):
self._capture_objects = wrapper.som_get_capture_objects(self.__ccore_som_pointer);
return self._capture_objects;
def capture_objects(self):
"""!
@brief Returns indexes of captured objects by each neuron.
@details For example, a network with size 2x2 has been trained on a sample with five objects. Suppose neuron #1
won an object with index `1`, neuron #2 won objects `0`, `3`, `4`, neuron #3 did not won anything and
finally neuron #4 won an object with index `2`. Thus, for this example we will have the following
output `[[1], [0, 3, 4], [], [2]]`.
@return (list) Indexes of captured objects by each neuron.
"""
if self.__ccore_som_pointer is not None:
self._capture_objects = wrapper.som_get_capture_objects(self.__ccore_som_pointer)
return self._capture_objects
def __download_dump_from_ccore(self):
self._location = self.__initialize_locations(self._rows, self._cols)
self._weights = wrapper.som_get_weights(self.__ccore_som_pointer)
self._award = wrapper.som_get_awards(self.__ccore_som_pointer)
self._capture_objects = wrapper.som_get_capture_objects(self.__ccore_som_pointer)
def __download_dump_from_ccore(self):
self._location = self.__initialize_locations(self._rows, self._cols)
self._weights = wrapper.som_get_weights(self.__ccore_som_pointer)
self._award = wrapper.som_get_awards(self.__ccore_som_pointer)
self._capture_objects = wrapper.som_get_capture_objects(self.__ccore_som_pointer)
