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)