Code Duplication - annoviko/pyclustering - Measure and Improve Code Quality continuously with Scrutinizer

Code Duplication Length = 18-19 lines in 2 locations

pyclustering/nnet/cnn.py 2 locations


        return len(self.output);


    def allocate_observation_matrix(self):
        """!
        @brief Allocates observation matrix in line with output dynamic of the network.
        @details Matrix where state of each neuron is denoted by zero/one in line with Heaviside function on each iteration.
        
        @return (list) Observation matrix of the network dynamic.
        
        """
        number_neurons = len(self.output[0]);
        observation_matrix = [];
        
        for iteration in range(len(self.output)):
            obervation_column = [];
            for index_neuron in range(number_neurons):
                obervation_column.append(heaviside(self.output[iteration][index_neuron]));
            
            observation_matrix.append(obervation_column);
        
        return observation_matrix;
    
    
    def __allocate_neuron_patterns(self, start_iteration, stop_iteration):

        return observation_matrix;
    
    
    def __allocate_neuron_patterns(self, start_iteration, stop_iteration):
        """!
        @brief Allocates observation transposed matrix of neurons that is limited by specified periods of simulation.
        @details Matrix where state of each neuron is denoted by zero/one in line with Heaviside function on each iteration.
        
        @return (list) Transposed observation matrix that is limited by specified periods of simulation.
        
        """
        
        pattern_matrix = [];
        for index_neuron in range(len(self.output[0])):
            pattern_neuron = [];
            for iteration in range(start_iteration, stop_iteration):
                pattern_neuron.append(heaviside(self.output[iteration][index_neuron]))
            
            pattern_matrix.append(pattern_neuron);
        
        return pattern_matrix;
    
    
    def allocate_sync_ensembles(self, steps):

		@@ 93-111 (lines=19) @@
90		return len(self.output);
91
92
93		def allocate_observation_matrix(self):
94		"""!
95		@brief Allocates observation matrix in line with output dynamic of the network.
96		@details Matrix where state of each neuron is denoted by zero/one in line with Heaviside function on each iteration.
97
98		@return (list) Observation matrix of the network dynamic.
99
100		"""
101		number_neurons = len(self.output[0]);
102		observation_matrix = [];
103
104		for iteration in range(len(self.output)):
105		obervation_column = [];
106		for index_neuron in range(number_neurons):
107		obervation_column.append(heaviside(self.output[iteration][index_neuron]));
108
109		observation_matrix.append(obervation_column);
110
111		return observation_matrix;
112
113
114		def __allocate_neuron_patterns(self, start_iteration, stop_iteration):
		@@ 114-131 (lines=18) @@
111		return observation_matrix;
112
113
114		def __allocate_neuron_patterns(self, start_iteration, stop_iteration):
115		"""!
116		@brief Allocates observation transposed matrix of neurons that is limited by specified periods of simulation.
117		@details Matrix where state of each neuron is denoted by zero/one in line with Heaviside function on each iteration.
118
119		@return (list) Transposed observation matrix that is limited by specified periods of simulation.
120
121		"""
122
123		pattern_matrix = [];
124		for index_neuron in range(len(self.output[0])):
125		pattern_neuron = [];
126		for iteration in range(start_iteration, stop_iteration):
127		pattern_neuron.append(heaviside(self.output[iteration][index_neuron]))
128
129		pattern_matrix.append(pattern_neuron);
130
131		return pattern_matrix;
132
133
134		def allocate_sync_ensembles(self, steps):

annoviko / pyclustering

Code Duplication Length = 18-19 lines in 2 locations

pyclustering/nnet/cnn.py 2 locations