partition stringclasses 3
values | func_name stringlengths 1 134 | docstring stringlengths 1 46.9k | path stringlengths 4 223 | original_string stringlengths 75 104k | code stringlengths 75 104k | docstring_tokens listlengths 1 1.97k | repo stringlengths 7 55 | language stringclasses 1
value | url stringlengths 87 315 | code_tokens listlengths 19 28.4k | sha stringlengths 40 40 |
|---|---|---|---|---|---|---|---|---|---|---|---|
valid | read_graph | !
@brief Read graph from file in GRPR format.
@param[in] filename (string): Path to file with graph in GRPR format.
@return (graph) Graph that is read from file. | pyclustering/utils/graph.py | def read_graph(filename):
"""!
@brief Read graph from file in GRPR format.
@param[in] filename (string): Path to file with graph in GRPR format.
@return (graph) Graph that is read from file.
"""
file = open(filename, 'r');
comments = "";
space_descr ... | def read_graph(filename):
"""!
@brief Read graph from file in GRPR format.
@param[in] filename (string): Path to file with graph in GRPR format.
@return (graph) Graph that is read from file.
"""
file = open(filename, 'r');
comments = "";
space_descr ... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/utils/graph.py#L138-L228 | [
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valid | draw_graph | !
@brief Draw graph.
@param[in] graph_instance (graph): Graph that should be drawn.
@param[in] map_coloring (list): List of color indexes for each vertex. Size of this list should be equal to size of graph (number of vertices).
If it's not specified (None) than grap... | pyclustering/utils/graph.py | def draw_graph(graph_instance, map_coloring = None):
"""!
@brief Draw graph.
@param[in] graph_instance (graph): Graph that should be drawn.
@param[in] map_coloring (list): List of color indexes for each vertex. Size of this list should be equal to size of graph (number of vertices).
... | def draw_graph(graph_instance, map_coloring = None):
"""!
@brief Draw graph.
@param[in] graph_instance (graph): Graph that should be drawn.
@param[in] map_coloring (list): List of color indexes for each vertex. Size of this list should be equal to size of graph (number of vertices).
... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/utils/graph.py#L232-L297 | [
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"... | 98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0 |
valid | fcm.process | !
@brief Performs cluster analysis in line with Fuzzy C-Means algorithm.
@see get_clusters()
@see get_centers()
@see get_membership() | pyclustering/cluster/fcm.py | def process(self):
"""!
@brief Performs cluster analysis in line with Fuzzy C-Means algorithm.
@see get_clusters()
@see get_centers()
@see get_membership()
"""
if self.__ccore is True:
self.__process_by_ccore()
else:
s... | def process(self):
"""!
@brief Performs cluster analysis in line with Fuzzy C-Means algorithm.
@see get_clusters()
@see get_centers()
@see get_membership()
"""
if self.__ccore is True:
self.__process_by_ccore()
else:
s... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/fcm.py#L141-L155 | [
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valid | fcm.__process_by_ccore | !
@brief Performs cluster analysis using C/C++ implementation. | pyclustering/cluster/fcm.py | def __process_by_ccore(self):
"""!
@brief Performs cluster analysis using C/C++ implementation.
"""
result = wrapper.fcm_algorithm(self.__data, self.__centers, self.__m, self.__tolerance, self.__itermax)
self.__clusters = result[wrapper.fcm_package_indexer.INDEX_CLUSTERS... | def __process_by_ccore(self):
"""!
@brief Performs cluster analysis using C/C++ implementation.
"""
result = wrapper.fcm_algorithm(self.__data, self.__centers, self.__m, self.__tolerance, self.__itermax)
self.__clusters = result[wrapper.fcm_package_indexer.INDEX_CLUSTERS... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/fcm.py#L204-L213 | [
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valid | fcm.__process_by_python | !
@brief Performs cluster analysis using Python implementation. | pyclustering/cluster/fcm.py | def __process_by_python(self):
"""!
@brief Performs cluster analysis using Python implementation.
"""
self.__data = numpy.array(self.__data)
self.__centers = numpy.array(self.__centers)
self.__membership = numpy.zeros((len(self.__data), len(self.__centers)))
... | def __process_by_python(self):
"""!
@brief Performs cluster analysis using Python implementation.
"""
self.__data = numpy.array(self.__data)
self.__centers = numpy.array(self.__centers)
self.__membership = numpy.zeros((len(self.__data), len(self.__centers)))
... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/fcm.py#L216-L237 | [
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valid | fcm.__calculate_centers | !
@brief Calculate center using membership of each cluster.
@return (list) Updated clusters as list of clusters. Each cluster contains indexes of objects from data.
@return (numpy.array) Updated centers. | pyclustering/cluster/fcm.py | def __calculate_centers(self):
"""!
@brief Calculate center using membership of each cluster.
@return (list) Updated clusters as list of clusters. Each cluster contains indexes of objects from data.
@return (numpy.array) Updated centers.
"""
dimension = self._... | def __calculate_centers(self):
"""!
@brief Calculate center using membership of each cluster.
@return (list) Updated clusters as list of clusters. Each cluster contains indexes of objects from data.
@return (numpy.array) Updated centers.
"""
dimension = self._... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/fcm.py#L240-L256 | [
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valid | fcm.__update_membership | !
@brief Update membership for each point in line with current cluster centers. | pyclustering/cluster/fcm.py | def __update_membership(self):
"""!
@brief Update membership for each point in line with current cluster centers.
"""
data_difference = numpy.zeros((len(self.__centers), len(self.__data)))
for i in range(len(self.__centers)):
data_difference[i] = numpy.sum(n... | def __update_membership(self):
"""!
@brief Update membership for each point in line with current cluster centers.
"""
data_difference = numpy.zeros((len(self.__centers), len(self.__data)))
for i in range(len(self.__centers)):
data_difference[i] = numpy.sum(n... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/fcm.py#L259-L276 | [
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valid | fcm.__calculate_changes | !
@brief Calculate changes between centers.
@return (float) Maximum change between centers. | pyclustering/cluster/fcm.py | def __calculate_changes(self, updated_centers):
"""!
@brief Calculate changes between centers.
@return (float) Maximum change between centers.
"""
changes = numpy.sum(numpy.square(self.__centers - updated_centers), axis=1).T
return numpy.max(changes) | def __calculate_changes(self, updated_centers):
"""!
@brief Calculate changes between centers.
@return (float) Maximum change between centers.
"""
changes = numpy.sum(numpy.square(self.__centers - updated_centers), axis=1).T
return numpy.max(changes) | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/fcm.py#L279-L287 | [
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valid | ga_observer.collect_global_best | !
@brief Stores the best chromosome and its fitness function's value.
@param[in] best_chromosome (list): The best chromosome that were observed.
@param[in] best_fitness_function (float): Fitness function value of the best chromosome. | pyclustering/cluster/ga.py | def collect_global_best(self, best_chromosome, best_fitness_function):
"""!
@brief Stores the best chromosome and its fitness function's value.
@param[in] best_chromosome (list): The best chromosome that were observed.
@param[in] best_fitness_function (float): Fitness function v... | def collect_global_best(self, best_chromosome, best_fitness_function):
"""!
@brief Stores the best chromosome and its fitness function's value.
@param[in] best_chromosome (list): The best chromosome that were observed.
@param[in] best_fitness_function (float): Fitness function v... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/ga.py#L87-L100 | [
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valid | ga_observer.collect_population_best | !
@brief Stores the best chromosome for current specific iteration and its fitness function's value.
@param[in] best_chromosome (list): The best chromosome on specific iteration.
@param[in] best_fitness_function (float): Fitness function value of the chromosome. | pyclustering/cluster/ga.py | def collect_population_best(self, best_chromosome, best_fitness_function):
"""!
@brief Stores the best chromosome for current specific iteration and its fitness function's value.
@param[in] best_chromosome (list): The best chromosome on specific iteration.
@param[in] best_fitnes... | def collect_population_best(self, best_chromosome, best_fitness_function):
"""!
@brief Stores the best chromosome for current specific iteration and its fitness function's value.
@param[in] best_chromosome (list): The best chromosome on specific iteration.
@param[in] best_fitnes... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/ga.py#L103-L116 | [
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valid | ga_observer.collect_mean | !
@brief Stores average value of fitness function among chromosomes on specific iteration.
@param[in] fitness_functions (float): Average value of fitness functions among chromosomes. | pyclustering/cluster/ga.py | def collect_mean(self, fitness_functions):
"""!
@brief Stores average value of fitness function among chromosomes on specific iteration.
@param[in] fitness_functions (float): Average value of fitness functions among chromosomes.
"""
if not self._need_mean_ff:
... | def collect_mean(self, fitness_functions):
"""!
@brief Stores average value of fitness function among chromosomes on specific iteration.
@param[in] fitness_functions (float): Average value of fitness functions among chromosomes.
"""
if not self._need_mean_ff:
... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/ga.py#L119-L130 | [
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] | 98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0 |
valid | ga_visualizer.show_evolution | !
@brief Displays evolution of fitness function for the best chromosome, for the current best chromosome and
average value among all chromosomes.
@param[in] observer (ga_observer): Genetic algorithm observer that was used for collecting evolution in the algorithm and
... | pyclustering/cluster/ga.py | def show_evolution(observer, start_iteration = 0, stop_iteration=None, ax=None, display=True):
"""!
@brief Displays evolution of fitness function for the best chromosome, for the current best chromosome and
average value among all chromosomes.
@param[in] observer (ga_obs... | def show_evolution(observer, start_iteration = 0, stop_iteration=None, ax=None, display=True):
"""!
@brief Displays evolution of fitness function for the best chromosome, for the current best chromosome and
average value among all chromosomes.
@param[in] observer (ga_obs... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/ga.py#L205-L244 | [
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valid | ga_visualizer.show_clusters | !
@brief Shows allocated clusters by the genetic algorithm.
@param[in] data (list): Input data that was used for clustering process by the algorithm.
@param[in] observer (ga_observer): Observer that was used for collection information about clustering process.
@param[in] marker ... | pyclustering/cluster/ga.py | def show_clusters(data, observer, marker='.', markersize=None):
"""!
@brief Shows allocated clusters by the genetic algorithm.
@param[in] data (list): Input data that was used for clustering process by the algorithm.
@param[in] observer (ga_observer): Observer that was used for ... | def show_clusters(data, observer, marker='.', markersize=None):
"""!
@brief Shows allocated clusters by the genetic algorithm.
@param[in] data (list): Input data that was used for clustering process by the algorithm.
@param[in] observer (ga_observer): Observer that was used for ... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/ga.py#L248-L272 | [
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valid | ga_visualizer.animate_cluster_allocation | !
@brief Animate clustering process of genetic clustering algorithm.
@details This method can be also used for rendering movie of clustering process and 'ffmpeg' is required for that purpuse.
@param[in] data (list): Input data that was used for clustering process by the algorithm.
... | pyclustering/cluster/ga.py | def animate_cluster_allocation(data, observer, animation_velocity=75, movie_fps=5, save_movie=None):
"""!
@brief Animate clustering process of genetic clustering algorithm.
@details This method can be also used for rendering movie of clustering process and 'ffmpeg' is required for that purpuse.
... | def animate_cluster_allocation(data, observer, animation_velocity=75, movie_fps=5, save_movie=None):
"""!
@brief Animate clustering process of genetic clustering algorithm.
@details This method can be also used for rendering movie of clustering process and 'ffmpeg' is required for that purpuse.
... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/ga.py#L276-L322 | [
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valid | genetic_algorithm.process | !
@brief Perform clustering procedure in line with rule of genetic clustering algorithm.
@see get_clusters() | pyclustering/cluster/ga.py | def process(self):
"""!
@brief Perform clustering procedure in line with rule of genetic clustering algorithm.
@see get_clusters()
"""
# Initialize population
chromosomes = self._init_population(self._count_clusters, len(self._data), self._chromosome_co... | def process(self):
"""!
@brief Perform clustering procedure in line with rule of genetic clustering algorithm.
@see get_clusters()
"""
# Initialize population
chromosomes = self._init_population(self._count_clusters, len(self._data), self._chromosome_co... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/ga.py#L430-L482 | [
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valid | genetic_algorithm._select | !
@brief Performs selection procedure where new chromosomes are calculated.
@param[in] chromosomes (numpy.array): Chromosomes | pyclustering/cluster/ga.py | def _select(chromosomes, data, count_clusters, select_coeff):
"""!
@brief Performs selection procedure where new chromosomes are calculated.
@param[in] chromosomes (numpy.array): Chromosomes
"""
# Calc centers
centres = ga_math.get_centres(chromosomes,... | def _select(chromosomes, data, count_clusters, select_coeff):
"""!
@brief Performs selection procedure where new chromosomes are calculated.
@param[in] chromosomes (numpy.array): Chromosomes
"""
# Calc centers
centres = ga_math.get_centres(chromosomes,... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/ga.py#L507-L534 | [
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valid | genetic_algorithm._crossover | !
@brief Crossover procedure. | pyclustering/cluster/ga.py | def _crossover(chromosomes):
"""!
@brief Crossover procedure.
"""
# Get pairs to Crossover
pairs_to_crossover = np.array(range(len(chromosomes)))
# Set random pairs
np.random.shuffle(pairs_to_crossover)
# Index offset ( pairs_to_crossover split... | def _crossover(chromosomes):
"""!
@brief Crossover procedure.
"""
# Get pairs to Crossover
pairs_to_crossover = np.array(range(len(chromosomes)))
# Set random pairs
np.random.shuffle(pairs_to_crossover)
# Index offset ( pairs_to_crossover split... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/ga.py#L538-L562 | [
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valid | genetic_algorithm._mutation | !
@brief Mutation procedure. | pyclustering/cluster/ga.py | def _mutation(chromosomes, count_clusters, count_gen_for_mutation, coeff_mutation_count):
"""!
@brief Mutation procedure.
"""
# Count gens in Chromosome
count_gens = len(chromosomes[0])
# Get random chromosomes for mutation
random_idx_chromosomes = np.a... | def _mutation(chromosomes, count_clusters, count_gen_for_mutation, coeff_mutation_count):
"""!
@brief Mutation procedure.
"""
# Count gens in Chromosome
count_gens = len(chromosomes[0])
# Get random chromosomes for mutation
random_idx_chromosomes = np.a... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/ga.py#L566-L589 | [
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... | 98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0 |
valid | genetic_algorithm._crossover_a_pair | !
@brief Crossovers a pair of chromosomes.
@param[in] chromosome_1 (numpy.array): The first chromosome for crossover.
@param[in] chromosome_2 (numpy.array): The second chromosome for crossover.
@param[in] mask (numpy.array): Crossover mask that defines which genes should be swap... | pyclustering/cluster/ga.py | def _crossover_a_pair(chromosome_1, chromosome_2, mask):
"""!
@brief Crossovers a pair of chromosomes.
@param[in] chromosome_1 (numpy.array): The first chromosome for crossover.
@param[in] chromosome_2 (numpy.array): The second chromosome for crossover.
@param[in] mask (... | def _crossover_a_pair(chromosome_1, chromosome_2, mask):
"""!
@brief Crossovers a pair of chromosomes.
@param[in] chromosome_1 (numpy.array): The first chromosome for crossover.
@param[in] chromosome_2 (numpy.array): The second chromosome for crossover.
@param[in] mask (... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/ga.py#L593-L607 | [
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valid | genetic_algorithm._get_crossover_mask | !
@brief Crossover mask to crossover a pair of chromosomes.
@param[in] mask_length (uint): Length of the mask. | pyclustering/cluster/ga.py | def _get_crossover_mask(mask_length):
"""!
@brief Crossover mask to crossover a pair of chromosomes.
@param[in] mask_length (uint): Length of the mask.
"""
# Initialize mask
mask = np.zeros(mask_length)
# Set a half of array to 1
mask[:... | def _get_crossover_mask(mask_length):
"""!
@brief Crossover mask to crossover a pair of chromosomes.
@param[in] mask_length (uint): Length of the mask.
"""
# Initialize mask
mask = np.zeros(mask_length)
# Set a half of array to 1
mask[:... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/ga.py#L611-L628 | [
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valid | genetic_algorithm._init_population | !
@brief Returns first population as a uniform random choice.
@param[in] count_clusters (uint): Amount of clusters that should be allocated.
@param[in] count_data (uint): Data size that is used for clustering process.
@param[in] chromosome_count (uint):Amount of chromosome that ... | pyclustering/cluster/ga.py | def _init_population(count_clusters, count_data, chromosome_count):
"""!
@brief Returns first population as a uniform random choice.
@param[in] count_clusters (uint): Amount of clusters that should be allocated.
@param[in] count_data (uint): Data size that is used for clustering... | def _init_population(count_clusters, count_data, chromosome_count):
"""!
@brief Returns first population as a uniform random choice.
@param[in] count_clusters (uint): Amount of clusters that should be allocated.
@param[in] count_data (uint): Data size that is used for clustering... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/ga.py#L632-L644 | [
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valid | genetic_algorithm._get_best_chromosome | !
@brief Returns the current best chromosome.
@param[in] chromosomes (list): Chromosomes that are used for searching.
@param[in] data (list): Input data that is used for clustering process.
@param[in] count_clusters (uint): Amount of clusters that should be allocated.
... | pyclustering/cluster/ga.py | def _get_best_chromosome(chromosomes, data, count_clusters):
"""!
@brief Returns the current best chromosome.
@param[in] chromosomes (list): Chromosomes that are used for searching.
@param[in] data (list): Input data that is used for clustering process.
@param[in] count_... | def _get_best_chromosome(chromosomes, data, count_clusters):
"""!
@brief Returns the current best chromosome.
@param[in] chromosomes (list): Chromosomes that are used for searching.
@param[in] data (list): Input data that is used for clustering process.
@param[in] count_... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/ga.py#L648-L671 | [
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"fitness_function... | 98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0 |
valid | genetic_algorithm._calc_fitness_function | !
@brief Calculate fitness function values for chromosomes.
@param[in] centres (list): Cluster centers.
@param[in] data (list): Input data that is used for clustering process.
@param[in] chromosomes (list): Chromosomes whose fitness function's values are calculated.
... | pyclustering/cluster/ga.py | def _calc_fitness_function(centres, data, chromosomes):
"""!
@brief Calculate fitness function values for chromosomes.
@param[in] centres (list): Cluster centers.
@param[in] data (list): Input data that is used for clustering process.
@param[in] chromosomes (list): Chrom... | def _calc_fitness_function(centres, data, chromosomes):
"""!
@brief Calculate fitness function values for chromosomes.
@param[in] centres (list): Cluster centers.
@param[in] data (list): Input data that is used for clustering process.
@param[in] chromosomes (list): Chrom... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/ga.py#L675-L706 | [
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valid | cfentry.get_distance | !
@brief Calculates distance between two clusters in line with measurement type.
@details In case of usage CENTROID_EUCLIDIAN_DISTANCE square euclidian distance will be returned.
Square root should be taken from the result for obtaining real euclidian distance between
... | pyclustering/container/cftree.py | def get_distance(self, entry, type_measurement):
"""!
@brief Calculates distance between two clusters in line with measurement type.
@details In case of usage CENTROID_EUCLIDIAN_DISTANCE square euclidian distance will be returned.
Square root should be taken from t... | def get_distance(self, entry, type_measurement):
"""!
@brief Calculates distance between two clusters in line with measurement type.
@details In case of usage CENTROID_EUCLIDIAN_DISTANCE square euclidian distance will be returned.
Square root should be taken from t... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L226-L257 | [
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valid | cfentry.get_centroid | !
@brief Calculates centroid of cluster that is represented by the entry.
@details It's calculated once when it's requested after the last changes.
@return (list) Centroid of cluster that is represented by the entry. | pyclustering/container/cftree.py | def get_centroid(self):
"""!
@brief Calculates centroid of cluster that is represented by the entry.
@details It's calculated once when it's requested after the last changes.
@return (list) Centroid of cluster that is represented by the entry.
"""
... | def get_centroid(self):
"""!
@brief Calculates centroid of cluster that is represented by the entry.
@details It's calculated once when it's requested after the last changes.
@return (list) Centroid of cluster that is represented by the entry.
"""
... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L260-L276 | [
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valid | cfentry.get_radius | !
@brief Calculates radius of cluster that is represented by the entry.
@details It's calculated once when it's requested after the last changes.
@return (double) Radius of cluster that is represented by the entry. | pyclustering/container/cftree.py | def get_radius(self):
"""!
@brief Calculates radius of cluster that is represented by the entry.
@details It's calculated once when it's requested after the last changes.
@return (double) Radius of cluster that is represented by the entry.
"""
... | def get_radius(self):
"""!
@brief Calculates radius of cluster that is represented by the entry.
@details It's calculated once when it's requested after the last changes.
@return (double) Radius of cluster that is represented by the entry.
"""
... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L279-L306 | [
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"... | 98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0 |
valid | cfentry.get_diameter | !
@brief Calculates diameter of cluster that is represented by the entry.
@details It's calculated once when it's requested after the last changes.
@return (double) Diameter of cluster that is represented by the entry. | pyclustering/container/cftree.py | def get_diameter(self):
"""!
@brief Calculates diameter of cluster that is represented by the entry.
@details It's calculated once when it's requested after the last changes.
@return (double) Diameter of cluster that is represented by the entry.
"""
... | def get_diameter(self):
"""!
@brief Calculates diameter of cluster that is represented by the entry.
@details It's calculated once when it's requested after the last changes.
@return (double) Diameter of cluster that is represented by the entry.
"""
... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L309-L328 | [
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... | 98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0 |
valid | cfentry.__get_average_inter_cluster_distance | !
@brief Calculates average inter cluster distance between current and specified clusters.
@param[in] entry (cfentry): Clustering feature to which distance should be obtained.
@return (double) Average inter cluster distance. | pyclustering/container/cftree.py | def __get_average_inter_cluster_distance(self, entry):
"""!
@brief Calculates average inter cluster distance between current and specified clusters.
@param[in] entry (cfentry): Clustering feature to which distance should be obtained.
@return (double) Average inter... | def __get_average_inter_cluster_distance(self, entry):
"""!
@brief Calculates average inter cluster distance between current and specified clusters.
@param[in] entry (cfentry): Clustering feature to which distance should be obtained.
@return (double) Average inter... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L331-L343 | [
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... | 98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0 |
valid | cfentry.__get_average_intra_cluster_distance | !
@brief Calculates average intra cluster distance between current and specified clusters.
@param[in] entry (cfentry): Clustering feature to which distance should be obtained.
@return (double) Average intra cluster distance. | pyclustering/container/cftree.py | def __get_average_intra_cluster_distance(self, entry):
"""!
@brief Calculates average intra cluster distance between current and specified clusters.
@param[in] entry (cfentry): Clustering feature to which distance should be obtained.
@return (double) Average intra... | def __get_average_intra_cluster_distance(self, entry):
"""!
@brief Calculates average intra cluster distance between current and specified clusters.
@param[in] entry (cfentry): Clustering feature to which distance should be obtained.
@return (double) Average intra... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L346-L363 | [
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valid | cfentry.__get_variance_increase_distance | !
@brief Calculates variance increase distance between current and specified clusters.
@param[in] entry (cfentry): Clustering feature to which distance should be obtained.
@return (double) Variance increase distance. | pyclustering/container/cftree.py | def __get_variance_increase_distance(self, entry):
"""!
@brief Calculates variance increase distance between current and specified clusters.
@param[in] entry (cfentry): Clustering feature to which distance should be obtained.
@return (double) Variance increase dis... | def __get_variance_increase_distance(self, entry):
"""!
@brief Calculates variance increase distance between current and specified clusters.
@param[in] entry (cfentry): Clustering feature to which distance should be obtained.
@return (double) Variance increase dis... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L366-L388 | [
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valid | cfnode.get_distance | !
@brief Calculates distance between nodes in line with specified type measurement.
@param[in] node (cfnode): CF-node that is used for calculation distance to the current node.
@param[in] type_measurement (measurement_type): Measurement type that is used for calculation distance.
... | pyclustering/container/cftree.py | def get_distance(self, node, type_measurement):
"""!
@brief Calculates distance between nodes in line with specified type measurement.
@param[in] node (cfnode): CF-node that is used for calculation distance to the current node.
@param[in] type_measurement (measurement_type)... | def get_distance(self, node, type_measurement):
"""!
@brief Calculates distance between nodes in line with specified type measurement.
@param[in] node (cfnode): CF-node that is used for calculation distance to the current node.
@param[in] type_measurement (measurement_type)... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L437-L448 | [
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] | 98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0 |
valid | non_leaf_node.insert_successor | !
@brief Insert successor to the node.
@param[in] successor (cfnode): Successor for adding. | pyclustering/container/cftree.py | def insert_successor(self, successor):
"""!
@brief Insert successor to the node.
@param[in] successor (cfnode): Successor for adding.
"""
self.feature += successor.feature;
self.successors.append(successor);
successor... | def insert_successor(self, successor):
"""!
@brief Insert successor to the node.
@param[in] successor (cfnode): Successor for adding.
"""
self.feature += successor.feature;
self.successors.append(successor);
successor... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L501-L512 | [
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valid | non_leaf_node.remove_successor | !
@brief Remove successor from the node.
@param[in] successor (cfnode): Successor for removing. | pyclustering/container/cftree.py | def remove_successor(self, successor):
"""!
@brief Remove successor from the node.
@param[in] successor (cfnode): Successor for removing.
"""
self.feature -= successor.feature;
self.successors.append(successor);
succe... | def remove_successor(self, successor):
"""!
@brief Remove successor from the node.
@param[in] successor (cfnode): Successor for removing.
"""
self.feature -= successor.feature;
self.successors.append(successor);
succe... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L515-L526 | [
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valid | non_leaf_node.merge | !
@brief Merge non-leaf node to the current.
@param[in] node (non_leaf_node): Non-leaf node that should be merged with current. | pyclustering/container/cftree.py | def merge(self, node):
"""!
@brief Merge non-leaf node to the current.
@param[in] node (non_leaf_node): Non-leaf node that should be merged with current.
"""
self.feature += node.feature;
for child in node.successors:
... | def merge(self, node):
"""!
@brief Merge non-leaf node to the current.
@param[in] node (non_leaf_node): Non-leaf node that should be merged with current.
"""
self.feature += node.feature;
for child in node.successors:
... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L529-L541 | [
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valid | non_leaf_node.get_farthest_successors | !
@brief Find pair of farthest successors of the node in line with measurement type.
@param[in] type_measurement (measurement_type): Measurement type that is used for obtaining farthest successors.
@return (list) Pair of farthest successors represented by list [cfnode1, cf... | pyclustering/container/cftree.py | def get_farthest_successors(self, type_measurement):
"""!
@brief Find pair of farthest successors of the node in line with measurement type.
@param[in] type_measurement (measurement_type): Measurement type that is used for obtaining farthest successors.
@return (l... | def get_farthest_successors(self, type_measurement):
"""!
@brief Find pair of farthest successors of the node in line with measurement type.
@param[in] type_measurement (measurement_type): Measurement type that is used for obtaining farthest successors.
@return (l... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L544-L570 | [
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valid | non_leaf_node.get_nearest_successors | !
@brief Find pair of nearest successors of the node in line with measurement type.
@param[in] type_measurement (measurement_type): Measurement type that is used for obtaining nearest successors.
@return (list) Pair of nearest successors represented by list. | pyclustering/container/cftree.py | def get_nearest_successors(self, type_measurement):
"""!
@brief Find pair of nearest successors of the node in line with measurement type.
@param[in] type_measurement (measurement_type): Measurement type that is used for obtaining nearest successors.
@return (list... | def get_nearest_successors(self, type_measurement):
"""!
@brief Find pair of nearest successors of the node in line with measurement type.
@param[in] type_measurement (measurement_type): Measurement type that is used for obtaining nearest successors.
@return (list... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L573-L599 | [
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valid | leaf_node.insert_entry | !
@brief Insert new clustering feature to the leaf node.
@param[in] entry (cfentry): Clustering feature. | pyclustering/container/cftree.py | def insert_entry(self, entry):
"""!
@brief Insert new clustering feature to the leaf node.
@param[in] entry (cfentry): Clustering feature.
"""
self.feature += entry;
self.entries.append(entry); | def insert_entry(self, entry):
"""!
@brief Insert new clustering feature to the leaf node.
@param[in] entry (cfentry): Clustering feature.
"""
self.feature += entry;
self.entries.append(entry); | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L656-L665 | [
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] | 98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0 |
valid | leaf_node.remove_entry | !
@brief Remove clustering feature from the leaf node.
@param[in] entry (cfentry): Clustering feature. | pyclustering/container/cftree.py | def remove_entry(self, entry):
"""!
@brief Remove clustering feature from the leaf node.
@param[in] entry (cfentry): Clustering feature.
"""
self.feature -= entry;
self.entries.remove(entry); | def remove_entry(self, entry):
"""!
@brief Remove clustering feature from the leaf node.
@param[in] entry (cfentry): Clustering feature.
"""
self.feature -= entry;
self.entries.remove(entry); | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L668-L677 | [
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valid | leaf_node.merge | !
@brief Merge leaf node to the current.
@param[in] node (leaf_node): Leaf node that should be merged with current. | pyclustering/container/cftree.py | def merge(self, node):
"""!
@brief Merge leaf node to the current.
@param[in] node (leaf_node): Leaf node that should be merged with current.
"""
self.feature += node.feature;
# Move entries from merged node
for entry... | def merge(self, node):
"""!
@brief Merge leaf node to the current.
@param[in] node (leaf_node): Leaf node that should be merged with current.
"""
self.feature += node.feature;
# Move entries from merged node
for entry... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L680-L692 | [
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valid | leaf_node.get_farthest_entries | !
@brief Find pair of farthest entries of the node.
@param[in] type_measurement (measurement_type): Measurement type that is used for obtaining farthest entries.
@return (list) Pair of farthest entries of the node that are represented by list. | pyclustering/container/cftree.py | def get_farthest_entries(self, type_measurement):
"""!
@brief Find pair of farthest entries of the node.
@param[in] type_measurement (measurement_type): Measurement type that is used for obtaining farthest entries.
@return (list) Pair of farthest entries of the no... | def get_farthest_entries(self, type_measurement):
"""!
@brief Find pair of farthest entries of the node.
@param[in] type_measurement (measurement_type): Measurement type that is used for obtaining farthest entries.
@return (list) Pair of farthest entries of the no... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L695-L721 | [
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valid | leaf_node.get_nearest_index_entry | !
@brief Find nearest index of nearest entry of node for the specified entry.
@param[in] entry (cfentry): Entry that is used for calculation distance.
@param[in] type_measurement (measurement_type): Measurement type that is used for obtaining nearest entry to the specified.
... | pyclustering/container/cftree.py | def get_nearest_index_entry(self, entry, type_measurement):
"""!
@brief Find nearest index of nearest entry of node for the specified entry.
@param[in] entry (cfentry): Entry that is used for calculation distance.
@param[in] type_measurement (measurement_type): Measurement ... | def get_nearest_index_entry(self, entry, type_measurement):
"""!
@brief Find nearest index of nearest entry of node for the specified entry.
@param[in] entry (cfentry): Entry that is used for calculation distance.
@param[in] type_measurement (measurement_type): Measurement ... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L724-L743 | [
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valid | leaf_node.get_nearest_entry | !
@brief Find nearest entry of node for the specified entry.
@param[in] entry (cfentry): Entry that is used for calculation distance.
@param[in] type_measurement (measurement_type): Measurement type that is used for obtaining nearest entry to the specified.
@retur... | pyclustering/container/cftree.py | def get_nearest_entry(self, entry, type_measurement):
"""!
@brief Find nearest entry of node for the specified entry.
@param[in] entry (cfentry): Entry that is used for calculation distance.
@param[in] type_measurement (measurement_type): Measurement type that is used for o... | def get_nearest_entry(self, entry, type_measurement):
"""!
@brief Find nearest entry of node for the specified entry.
@param[in] entry (cfentry): Entry that is used for calculation distance.
@param[in] type_measurement (measurement_type): Measurement type that is used for o... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L746-L758 | [
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valid | cftree.get_level_nodes | !
@brief Traverses CF-tree to obtain nodes at the specified level.
@param[in] level (uint): CF-tree level from that nodes should be returned.
@return (list) List of CF-nodes that are located on the specified level of the CF-tree. | pyclustering/container/cftree.py | def get_level_nodes(self, level):
"""!
@brief Traverses CF-tree to obtain nodes at the specified level.
@param[in] level (uint): CF-tree level from that nodes should be returned.
@return (list) List of CF-nodes that are located on the specified level of the CF-tre... | def get_level_nodes(self, level):
"""!
@brief Traverses CF-tree to obtain nodes at the specified level.
@param[in] level (uint): CF-tree level from that nodes should be returned.
@return (list) List of CF-nodes that are located on the specified level of the CF-tre... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L881-L895 | [
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valid | cftree.__recursive_get_level_nodes | !
@brief Traverses CF-tree to obtain nodes at the specified level recursively.
@param[in] level (uint): Current CF-tree level.
@param[in] node (cfnode): CF-node from that traversing is performed.
@return (list) List of CF-nodes that are located on the specified le... | pyclustering/container/cftree.py | def __recursive_get_level_nodes(self, level, node):
"""!
@brief Traverses CF-tree to obtain nodes at the specified level recursively.
@param[in] level (uint): Current CF-tree level.
@param[in] node (cfnode): CF-node from that traversing is performed.
@ret... | def __recursive_get_level_nodes(self, level, node):
"""!
@brief Traverses CF-tree to obtain nodes at the specified level recursively.
@param[in] level (uint): Current CF-tree level.
@param[in] node (cfnode): CF-node from that traversing is performed.
@ret... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L898-L917 | [
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valid | cftree.insert_cluster | !
@brief Insert cluster that is represented as list of points where each point is represented by list of coordinates.
@details Clustering feature is created for that cluster and inserted to the tree.
@param[in] cluster (list): Cluster that is represented by list of points that shoul... | pyclustering/container/cftree.py | def insert_cluster(self, cluster):
"""!
@brief Insert cluster that is represented as list of points where each point is represented by list of coordinates.
@details Clustering feature is created for that cluster and inserted to the tree.
@param[in] cluster (list): Cluster t... | def insert_cluster(self, cluster):
"""!
@brief Insert cluster that is represented as list of points where each point is represented by list of coordinates.
@details Clustering feature is created for that cluster and inserted to the tree.
@param[in] cluster (list): Cluster t... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L920-L930 | [
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valid | cftree.insert | !
@brief Insert clustering feature to the tree.
@param[in] entry (cfentry): Clustering feature that should be inserted. | pyclustering/container/cftree.py | def insert(self, entry):
"""!
@brief Insert clustering feature to the tree.
@param[in] entry (cfentry): Clustering feature that should be inserted.
"""
if (self.__root is None):
node = leaf_node(entry, None, [ entry ], None)... | def insert(self, entry):
"""!
@brief Insert clustering feature to the tree.
@param[in] entry (cfentry): Clustering feature that should be inserted.
"""
if (self.__root is None):
node = leaf_node(entry, None, [ entry ], None)... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L933-L956 | [
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valid | cftree.find_nearest_leaf | !
@brief Search nearest leaf to the specified clustering feature.
@param[in] entry (cfentry): Clustering feature.
@param[in] search_node (cfnode): Node from that searching should be started, if None then search process will be started for the root.
@return (leaf_n... | pyclustering/container/cftree.py | def find_nearest_leaf(self, entry, search_node = None):
"""!
@brief Search nearest leaf to the specified clustering feature.
@param[in] entry (cfentry): Clustering feature.
@param[in] search_node (cfnode): Node from that searching should be started, if None then search proc... | def find_nearest_leaf(self, entry, search_node = None):
"""!
@brief Search nearest leaf to the specified clustering feature.
@param[in] entry (cfentry): Clustering feature.
@param[in] search_node (cfnode): Node from that searching should be started, if None then search proc... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L959-L981 | [
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valid | cftree.__recursive_insert | !
@brief Recursive insert of the entry to the tree.
@details It performs all required procedures during insertion such as splitting, merging.
@param[in] entry (cfentry): Clustering feature.
@param[in] search_node (cfnode): Node from that insertion should be started.
... | pyclustering/container/cftree.py | def __recursive_insert(self, entry, search_node):
"""!
@brief Recursive insert of the entry to the tree.
@details It performs all required procedures during insertion such as splitting, merging.
@param[in] entry (cfentry): Clustering feature.
@param[in] search_node... | def __recursive_insert(self, entry, search_node):
"""!
@brief Recursive insert of the entry to the tree.
@details It performs all required procedures during insertion such as splitting, merging.
@param[in] entry (cfentry): Clustering feature.
@param[in] search_node... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L984-L1002 | [
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valid | cftree.__insert_for_leaf_node | !
@brief Recursive insert entry from leaf node to the tree.
@param[in] entry (cfentry): Clustering feature.
@param[in] search_node (cfnode): None-leaf node from that insertion should be started.
@return (bool) True if number of nodes at the below level is changed,... | pyclustering/container/cftree.py | def __insert_for_leaf_node(self, entry, search_node):
"""!
@brief Recursive insert entry from leaf node to the tree.
@param[in] entry (cfentry): Clustering feature.
@param[in] search_node (cfnode): None-leaf node from that insertion should be started.
@re... | def __insert_for_leaf_node(self, entry, search_node):
"""!
@brief Recursive insert entry from leaf node to the tree.
@param[in] entry (cfentry): Clustering feature.
@param[in] search_node (cfnode): None-leaf node from that insertion should be started.
@re... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L1005-L1039 | [
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valid | cftree.__insert_for_noneleaf_node | !
@brief Recursive insert entry from none-leaf node to the tree.
@param[in] entry (cfentry): Clustering feature.
@param[in] search_node (cfnode): None-leaf node from that insertion should be started.
@return (bool) True if number of nodes at the below level is cha... | pyclustering/container/cftree.py | def __insert_for_noneleaf_node(self, entry, search_node):
"""!
@brief Recursive insert entry from none-leaf node to the tree.
@param[in] entry (cfentry): Clustering feature.
@param[in] search_node (cfnode): None-leaf node from that insertion should be started.
... | def __insert_for_noneleaf_node(self, entry, search_node):
"""!
@brief Recursive insert entry from none-leaf node to the tree.
@param[in] entry (cfentry): Clustering feature.
@param[in] search_node (cfnode): None-leaf node from that insertion should be started.
... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L1042-L1092 | [
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valid | cftree.__merge_nearest_successors | !
@brief Find nearest sucessors and merge them.
@param[in] node (non_leaf_node): Node whose two nearest successors should be merged.
@return (bool): True if merging has been successfully performed, otherwise False. | pyclustering/container/cftree.py | def __merge_nearest_successors(self, node):
"""!
@brief Find nearest sucessors and merge them.
@param[in] node (non_leaf_node): Node whose two nearest successors should be merged.
@return (bool): True if merging has been successfully performed, otherwise False.
... | def __merge_nearest_successors(self, node):
"""!
@brief Find nearest sucessors and merge them.
@param[in] node (non_leaf_node): Node whose two nearest successors should be merged.
@return (bool): True if merging has been successfully performed, otherwise False.
... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L1095-L1119 | [
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valid | cftree.__split_procedure | !
@brief Starts node splitting procedure in the CF-tree from the specify node.
@param[in] split_node (cfnode): CF-tree node that should be splitted. | pyclustering/container/cftree.py | def __split_procedure(self, split_node):
"""!
@brief Starts node splitting procedure in the CF-tree from the specify node.
@param[in] split_node (cfnode): CF-tree node that should be splitted.
"""
if (split_node is self.__root):
self.__root =... | def __split_procedure(self, split_node):
"""!
@brief Starts node splitting procedure in the CF-tree from the specify node.
@param[in] split_node (cfnode): CF-tree node that should be splitted.
"""
if (split_node is self.__root):
self.__root =... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L1122-L1150 | [
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valid | cftree.__split_nonleaf_node | !
@brief Performs splitting of the specified non-leaf node.
@param[in] node (non_leaf_node): Non-leaf node that should be splitted.
@return (list) New pair of non-leaf nodes [non_leaf_node1, non_leaf_node2]. | pyclustering/container/cftree.py | def __split_nonleaf_node(self, node):
"""!
@brief Performs splitting of the specified non-leaf node.
@param[in] node (non_leaf_node): Non-leaf node that should be splitted.
@return (list) New pair of non-leaf nodes [non_leaf_node1, non_leaf_node2].
... | def __split_nonleaf_node(self, node):
"""!
@brief Performs splitting of the specified non-leaf node.
@param[in] node (non_leaf_node): Non-leaf node that should be splitted.
@return (list) New pair of non-leaf nodes [non_leaf_node1, non_leaf_node2].
... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L1153-L1183 | [
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valid | cftree.__split_leaf_node | !
@brief Performs splitting of the specified leaf node.
@param[in] node (leaf_node): Leaf node that should be splitted.
@return (list) New pair of leaf nodes [leaf_node1, leaf_node2].
@warning Splitted node is transformed to non_leaf. | pyclustering/container/cftree.py | def __split_leaf_node(self, node):
"""!
@brief Performs splitting of the specified leaf node.
@param[in] node (leaf_node): Leaf node that should be splitted.
@return (list) New pair of leaf nodes [leaf_node1, leaf_node2].
@warning Splitted node ... | def __split_leaf_node(self, node):
"""!
@brief Performs splitting of the specified leaf node.
@param[in] node (leaf_node): Leaf node that should be splitted.
@return (list) New pair of leaf nodes [leaf_node1, leaf_node2].
@warning Splitted node ... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L1186-L1216 | [
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... | 98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0 |
valid | cftree.show_feature_destibution | !
@brief Shows feature distribution.
@details Only features in 1D, 2D, 3D space can be visualized.
@param[in] data (list): List of points that will be used for visualization, if it not specified than feature will be displayed only. | pyclustering/container/cftree.py | def show_feature_destibution(self, data = None):
"""!
@brief Shows feature distribution.
@details Only features in 1D, 2D, 3D space can be visualized.
@param[in] data (list): List of points that will be used for visualization, if it not specified than feature will be displa... | def show_feature_destibution(self, data = None):
"""!
@brief Shows feature distribution.
@details Only features in 1D, 2D, 3D space can be visualized.
@param[in] data (list): List of points that will be used for visualization, if it not specified than feature will be displa... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/container/cftree.py#L1219-L1240 | [
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valid | agglomerative.process | !
@brief Performs cluster analysis in line with rules of agglomerative algorithm and similarity.
@see get_clusters() | pyclustering/cluster/agglomerative.py | def process(self):
"""!
@brief Performs cluster analysis in line with rules of agglomerative algorithm and similarity.
@see get_clusters()
"""
if (self.__ccore is True):
self.__clusters = wrapper.agglomerative_algorithm(self.__pointer_data, ... | def process(self):
"""!
@brief Performs cluster analysis in line with rules of agglomerative algorithm and similarity.
@see get_clusters()
"""
if (self.__ccore is True):
self.__clusters = wrapper.agglomerative_algorithm(self.__pointer_data, ... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/agglomerative.py#L145-L163 | [
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... | 98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0 |
valid | agglomerative.__merge_similar_clusters | !
@brief Merges the most similar clusters in line with link type. | pyclustering/cluster/agglomerative.py | def __merge_similar_clusters(self):
"""!
@brief Merges the most similar clusters in line with link type.
"""
if (self.__similarity == type_link.AVERAGE_LINK):
self.__merge_by_average_link();
elif (self.__similarity == type_link.CENTROID_LINK... | def __merge_similar_clusters(self):
"""!
@brief Merges the most similar clusters in line with link type.
"""
if (self.__similarity == type_link.AVERAGE_LINK):
self.__merge_by_average_link();
elif (self.__similarity == type_link.CENTROID_LINK... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/agglomerative.py#L194-L213 | [
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... | 98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0 |
valid | agglomerative.__merge_by_average_link | !
@brief Merges the most similar clusters in line with average link type. | pyclustering/cluster/agglomerative.py | def __merge_by_average_link(self):
"""!
@brief Merges the most similar clusters in line with average link type.
"""
minimum_average_distance = float('Inf');
for index_cluster1 in range(0, len(self.__clusters)):
for index_cluster2 in range(in... | def __merge_by_average_link(self):
"""!
@brief Merges the most similar clusters in line with average link type.
"""
minimum_average_distance = float('Inf');
for index_cluster1 in range(0, len(self.__clusters)):
for index_cluster2 in range(in... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/agglomerative.py#L216-L240 | [
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... | 98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0 |
valid | agglomerative.__merge_by_centroid_link | !
@brief Merges the most similar clusters in line with centroid link type. | pyclustering/cluster/agglomerative.py | def __merge_by_centroid_link(self):
"""!
@brief Merges the most similar clusters in line with centroid link type.
"""
minimum_centroid_distance = float('Inf');
indexes = None;
for index1 in range(0, len(self.__centers)):
for index2 i... | def __merge_by_centroid_link(self):
"""!
@brief Merges the most similar clusters in line with centroid link type.
"""
minimum_centroid_distance = float('Inf');
indexes = None;
for index1 in range(0, len(self.__centers)):
for index2 i... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/agglomerative.py#L243-L263 | [
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valid | agglomerative.__merge_by_complete_link | !
@brief Merges the most similar clusters in line with complete link type. | pyclustering/cluster/agglomerative.py | def __merge_by_complete_link(self):
"""!
@brief Merges the most similar clusters in line with complete link type.
"""
minimum_complete_distance = float('Inf');
indexes = None;
for index_cluster1 in range(0, len(self.__clusters)):
for... | def __merge_by_complete_link(self):
"""!
@brief Merges the most similar clusters in line with complete link type.
"""
minimum_complete_distance = float('Inf');
indexes = None;
for index_cluster1 in range(0, len(self.__clusters)):
for... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/agglomerative.py#L266-L284 | [
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valid | agglomerative.__calculate_farthest_distance | !
@brief Finds two farthest objects in two specified clusters in terms and returns distance between them.
@param[in] (uint) Index of the first cluster.
@param[in] (uint) Index of the second cluster.
@return The farthest euclidean distance between two clusters. | pyclustering/cluster/agglomerative.py | def __calculate_farthest_distance(self, index_cluster1, index_cluster2):
"""!
@brief Finds two farthest objects in two specified clusters in terms and returns distance between them.
@param[in] (uint) Index of the first cluster.
@param[in] (uint) Index of the second cluster.
... | def __calculate_farthest_distance(self, index_cluster1, index_cluster2):
"""!
@brief Finds two farthest objects in two specified clusters in terms and returns distance between them.
@param[in] (uint) Index of the first cluster.
@param[in] (uint) Index of the second cluster.
... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/agglomerative.py#L287-L305 | [
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valid | agglomerative.__merge_by_signle_link | !
@brief Merges the most similar clusters in line with single link type. | pyclustering/cluster/agglomerative.py | def __merge_by_signle_link(self):
"""!
@brief Merges the most similar clusters in line with single link type.
"""
minimum_single_distance = float('Inf');
indexes = None;
for index_cluster1 in range(0, len(self.__clusters)):
for index... | def __merge_by_signle_link(self):
"""!
@brief Merges the most similar clusters in line with single link type.
"""
minimum_single_distance = float('Inf');
indexes = None;
for index_cluster1 in range(0, len(self.__clusters)):
for index... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/agglomerative.py#L308-L326 | [
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... | 98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0 |
valid | agglomerative.__calculate_nearest_distance | !
@brief Finds two nearest objects in two specified clusters and returns distance between them.
@param[in] (uint) Index of the first cluster.
@param[in] (uint) Index of the second cluster.
@return The nearest euclidean distance between two clusters. | pyclustering/cluster/agglomerative.py | def __calculate_nearest_distance(self, index_cluster1, index_cluster2):
"""!
@brief Finds two nearest objects in two specified clusters and returns distance between them.
@param[in] (uint) Index of the first cluster.
@param[in] (uint) Index of the second cluster.
... | def __calculate_nearest_distance(self, index_cluster1, index_cluster2):
"""!
@brief Finds two nearest objects in two specified clusters and returns distance between them.
@param[in] (uint) Index of the first cluster.
@param[in] (uint) Index of the second cluster.
... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/agglomerative.py#L329-L347 | [
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valid | agglomerative.__calculate_center | !
@brief Calculates new center.
@return (list) New value of the center of the specified cluster. | pyclustering/cluster/agglomerative.py | def __calculate_center(self, cluster):
"""!
@brief Calculates new center.
@return (list) New value of the center of the specified cluster.
"""
dimension = len(self.__pointer_data[cluster[0]]);
center = [0] * dimension;
for index_point i... | def __calculate_center(self, cluster):
"""!
@brief Calculates new center.
@return (list) New value of the center of the specified cluster.
"""
dimension = len(self.__pointer_data[cluster[0]]);
center = [0] * dimension;
for index_point i... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/agglomerative.py#L350-L367 | [
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valid | som_create | !
@brief Create of self-organized map using CCORE pyclustering library.
@param[in] rows (uint): Number of neurons in the column (number of rows).
@param[in] cols (uint): Number of neurons in the row (number of columns).
@param[in] conn_type (type_conn): Type of connection between oscillators i... | pyclustering/core/som_wrapper.py | def som_create(rows, cols, conn_type, parameters):
"""!
@brief Create of self-organized map using CCORE pyclustering library.
@param[in] rows (uint): Number of neurons in the column (number of rows).
@param[in] cols (uint): Number of neurons in the row (number of columns).
@param[in] conn... | def som_create(rows, cols, conn_type, parameters):
"""!
@brief Create of self-organized map using CCORE pyclustering library.
@param[in] rows (uint): Number of neurons in the column (number of rows).
@param[in] cols (uint): Number of neurons in the row (number of columns).
@param[in] conn... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/core/som_wrapper.py#L45-L70 | [
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valid | som_load | !
@brief Load dump of the network to SOM.
@details Initialize SOM using existed weights, amount of captured objects by each neuron, captured
objects by each neuron. Initialization is not performed if weights are empty.
@param[in] som_pointer (POINTER): pointer to object of self-organized... | pyclustering/core/som_wrapper.py | def som_load(som_pointer, weights, award, capture_objects):
"""!
@brief Load dump of the network to SOM.
@details Initialize SOM using existed weights, amount of captured objects by each neuron, captured
objects by each neuron. Initialization is not performed if weights are empty.
@... | def som_load(som_pointer, weights, award, capture_objects):
"""!
@brief Load dump of the network to SOM.
@details Initialize SOM using existed weights, amount of captured objects by each neuron, captured
objects by each neuron. Initialization is not performed if weights are empty.
@... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/core/som_wrapper.py#L73-L95 | [
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valid | som_train | !
@brief Trains self-organized feature map (SOM) using CCORE pyclustering library.
@param[in] data (list): Input data - list of points where each point is represented by list of features, for example coordinates.
@param[in] epochs (uint): Number of epochs for training.
@param[in] autostop ... | pyclustering/core/som_wrapper.py | def som_train(som_pointer, data, epochs, autostop):
"""!
@brief Trains self-organized feature map (SOM) using CCORE pyclustering library.
@param[in] data (list): Input data - list of points where each point is represented by list of features, for example coordinates.
@param[in] epochs (uint): Numb... | def som_train(som_pointer, data, epochs, autostop):
"""!
@brief Trains self-organized feature map (SOM) using CCORE pyclustering library.
@param[in] data (list): Input data - list of points where each point is represented by list of features, for example coordinates.
@param[in] epochs (uint): Numb... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/core/som_wrapper.py#L110-L126 | [
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valid | som_simulate | !
@brief Processes input pattern (no learining) and returns index of neuron-winner.
@details Using index of neuron winner catched object can be obtained using property capture_objects.
@param[in] som_pointer (c_pointer): pointer to object of self-organized map.
@param[in] pattern (list): input... | pyclustering/core/som_wrapper.py | def som_simulate(som_pointer, pattern):
"""!
@brief Processes input pattern (no learining) and returns index of neuron-winner.
@details Using index of neuron winner catched object can be obtained using property capture_objects.
@param[in] som_pointer (c_pointer): pointer to object of self-orga... | def som_simulate(som_pointer, pattern):
"""!
@brief Processes input pattern (no learining) and returns index of neuron-winner.
@details Using index of neuron winner catched object can be obtained using property capture_objects.
@param[in] som_pointer (c_pointer): pointer to object of self-orga... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/core/som_wrapper.py#L129-L145 | [
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valid | som_get_winner_number | !
@brief Returns of number of winner at the last step of learning process.
@param[in] som_pointer (c_pointer): pointer to object of self-organized map. | pyclustering/core/som_wrapper.py | def som_get_winner_number(som_pointer):
"""!
@brief Returns of number of winner at the last step of learning process.
@param[in] som_pointer (c_pointer): pointer to object of self-organized map.
"""
ccore = ccore_library.get()
ccore.som_get_winner_number.restype = c_size_... | def som_get_winner_number(som_pointer):
"""!
@brief Returns of number of winner at the last step of learning process.
@param[in] som_pointer (c_pointer): pointer to object of self-organized map.
"""
ccore = ccore_library.get()
ccore.som_get_winner_number.restype = c_size_... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/core/som_wrapper.py#L148-L158 | [
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] | 98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0 |
valid | som_get_size | !
@brief Returns size of self-organized map (number of neurons).
@param[in] som_pointer (c_pointer): pointer to object of self-organized map. | pyclustering/core/som_wrapper.py | def som_get_size(som_pointer):
"""!
@brief Returns size of self-organized map (number of neurons).
@param[in] som_pointer (c_pointer): pointer to object of self-organized map.
"""
ccore = ccore_library.get()
ccore.som_get_size.restype = c_size_t
return ccore.som_get_... | def som_get_size(som_pointer):
"""!
@brief Returns size of self-organized map (number of neurons).
@param[in] som_pointer (c_pointer): pointer to object of self-organized map.
"""
ccore = ccore_library.get()
ccore.som_get_size.restype = c_size_t
return ccore.som_get_... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/core/som_wrapper.py#L161-L171 | [
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] | 98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0 |
valid | som_get_capture_objects | !
@brief Returns list of indexes of captured objects by each neuron.
@param[in] som_pointer (c_pointer): pointer to object of self-organized map. | pyclustering/core/som_wrapper.py | def som_get_capture_objects(som_pointer):
"""!
@brief Returns list of indexes of captured objects by each neuron.
@param[in] som_pointer (c_pointer): pointer to object of self-organized map.
"""
ccore = ccore_library.get()
ccore.som_get_capture_objects.restype = POI... | def som_get_capture_objects(som_pointer):
"""!
@brief Returns list of indexes of captured objects by each neuron.
@param[in] som_pointer (c_pointer): pointer to object of self-organized map.
"""
ccore = ccore_library.get()
ccore.som_get_capture_objects.restype = POI... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/core/som_wrapper.py#L174-L188 | [
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valid | hysteresis_dynamic.allocate_sync_ensembles | !
@brief Allocate clusters in line with ensembles of synchronous oscillators where each
synchronous ensemble corresponds to only one cluster.
@param[in] tolerance (double): Maximum error for allocation of synchronous ensemble oscillators.
@param[in] threshold_... | pyclustering/nnet/hysteresis.py | def allocate_sync_ensembles(self, tolerance = 0.1, threshold_steps = 1):
"""!
@brief Allocate clusters in line with ensembles of synchronous oscillators where each
synchronous ensemble corresponds to only one cluster.
@param[in] tolerance (double): Maximum err... | def allocate_sync_ensembles(self, tolerance = 0.1, threshold_steps = 1):
"""!
@brief Allocate clusters in line with ensembles of synchronous oscillators where each
synchronous ensemble corresponds to only one cluster.
@param[in] tolerance (double): Maximum err... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/nnet/hysteresis.py#L87-L131 | [
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valid | hysteresis_network.outputs | !
@brief Sets outputs of neurons. | pyclustering/nnet/hysteresis.py | def outputs(self, values):
"""!
@brief Sets outputs of neurons.
"""
self._outputs = [val for val in values];
self._outputs_buffer = [val for val in values]; | def outputs(self, values):
"""!
@brief Sets outputs of neurons.
"""
self._outputs = [val for val in values];
self._outputs_buffer = [val for val in values]; | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/nnet/hysteresis.py#L192-L199 | [
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] | 98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0 |
valid | hysteresis_network._neuron_states | !
@brief Returns new value of the neuron (oscillator).
@param[in] inputs (list): Initial values (current) of the neuron - excitatory.
@param[in] t (double): Current time of simulation.
@param[in] argv (tuple): Extra arguments that are not used for integration - index of the... | pyclustering/nnet/hysteresis.py | def _neuron_states(self, inputs, t, argv):
"""!
@brief Returns new value of the neuron (oscillator).
@param[in] inputs (list): Initial values (current) of the neuron - excitatory.
@param[in] t (double): Current time of simulation.
@param[in] argv (tuple): Extra arg... | def _neuron_states(self, inputs, t, argv):
"""!
@brief Returns new value of the neuron (oscillator).
@param[in] inputs (list): Initial values (current) of the neuron - excitatory.
@param[in] t (double): Current time of simulation.
@param[in] argv (tuple): Extra arg... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/nnet/hysteresis.py#L252-L279 | [
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valid | hysteresis_network.simulate_static | !
@brief Performs static simulation of hysteresis oscillatory network.
@param[in] steps (uint): Number steps of simulations during simulation.
@param[in] time (double): Time of simulation.
@param[in] solution (solve_type): Type of solution (solving).
@param[in] col... | pyclustering/nnet/hysteresis.py | def simulate_static(self, steps, time, solution = solve_type.RK4, collect_dynamic = False):
"""!
@brief Performs static simulation of hysteresis oscillatory network.
@param[in] steps (uint): Number steps of simulations during simulation.
@param[in] time (double): Time of si... | def simulate_static(self, steps, time, solution = solve_type.RK4, collect_dynamic = False):
"""!
@brief Performs static simulation of hysteresis oscillatory network.
@param[in] steps (uint): Number steps of simulations during simulation.
@param[in] time (double): Time of si... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/nnet/hysteresis.py#L298-L344 | [
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valid | hysteresis_network._calculate_states | !
@brief Calculates new states for neurons using differential calculus. Returns new states for neurons.
@param[in] solution (solve_type): Type solver of the differential equation.
@param[in] t (double): Current time of simulation.
@param[in] step (double): Step of solution ... | pyclustering/nnet/hysteresis.py | def _calculate_states(self, solution, t, step, int_step):
"""!
@brief Calculates new states for neurons using differential calculus. Returns new states for neurons.
@param[in] solution (solve_type): Type solver of the differential equation.
@param[in] t (double): Current ti... | def _calculate_states(self, solution, t, step, int_step):
"""!
@brief Calculates new states for neurons using differential calculus. Returns new states for neurons.
@param[in] solution (solve_type): Type solver of the differential equation.
@param[in] t (double): Current ti... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/nnet/hysteresis.py#L347-L367 | [
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valid | legion_dynamic.output | !
@brief Returns output dynamic of the network. | pyclustering/nnet/legion.py | def output(self):
"""!
@brief Returns output dynamic of the network.
"""
if (self.__ccore_legion_dynamic_pointer is not None):
return wrapper.legion_dynamic_get_output(self.__ccore_legion_dynamic_pointer);
return self.__output; | def output(self):
"""!
@brief Returns output dynamic of the network.
"""
if (self.__ccore_legion_dynamic_pointer is not None):
return wrapper.legion_dynamic_get_output(self.__ccore_legion_dynamic_pointer);
return self.__output; | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/nnet/legion.py#L119-L127 | [
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valid | legion_dynamic.inhibitor | !
@brief Returns output dynamic of the global inhibitor of the network. | pyclustering/nnet/legion.py | def inhibitor(self):
"""!
@brief Returns output dynamic of the global inhibitor of the network.
"""
if (self.__ccore_legion_dynamic_pointer is not None):
return wrapper.legion_dynamic_get_inhibitory_output(self.__ccore_legion_dynamic_pointer);
... | def inhibitor(self):
"""!
@brief Returns output dynamic of the global inhibitor of the network.
"""
if (self.__ccore_legion_dynamic_pointer is not None):
return wrapper.legion_dynamic_get_inhibitory_output(self.__ccore_legion_dynamic_pointer);
... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/nnet/legion.py#L131-L140 | [
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valid | legion_dynamic.time | !
@brief Returns simulation time. | pyclustering/nnet/legion.py | def time(self):
"""!
@brief Returns simulation time.
"""
if (self.__ccore_legion_dynamic_pointer is not None):
return wrapper.legion_dynamic_get_time(self.__ccore_legion_dynamic_pointer);
return list(range(len(self))); | def time(self):
"""!
@brief Returns simulation time.
"""
if (self.__ccore_legion_dynamic_pointer is not None):
return wrapper.legion_dynamic_get_time(self.__ccore_legion_dynamic_pointer);
return list(range(len(self))); | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/nnet/legion.py#L144-L152 | [
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valid | legion_dynamic.allocate_sync_ensembles | !
@brief Allocate clusters in line with ensembles of synchronous oscillators where each synchronous ensemble corresponds to only one cluster.
@param[in] tolerance (double): Maximum error for allocation of synchronous ensemble oscillators.
@return (list) Grours of indexes o... | pyclustering/nnet/legion.py | def allocate_sync_ensembles(self, tolerance = 0.1):
"""!
@brief Allocate clusters in line with ensembles of synchronous oscillators where each synchronous ensemble corresponds to only one cluster.
@param[in] tolerance (double): Maximum error for allocation of synchronous ensemble os... | def allocate_sync_ensembles(self, tolerance = 0.1):
"""!
@brief Allocate clusters in line with ensembles of synchronous oscillators where each synchronous ensemble corresponds to only one cluster.
@param[in] tolerance (double): Maximum error for allocation of synchronous ensemble os... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/nnet/legion.py#L193-L206 | [
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valid | legion_network.__create_stimulus | !
@brief Create stimulus for oscillators in line with stimulus map and parameters.
@param[in] stimulus (list): Stimulus for oscillators that is represented by list, number of stimulus should be equal number of oscillators. | pyclustering/nnet/legion.py | def __create_stimulus(self, stimulus):
"""!
@brief Create stimulus for oscillators in line with stimulus map and parameters.
@param[in] stimulus (list): Stimulus for oscillators that is represented by list, number of stimulus should be equal number of oscillators.
... | def __create_stimulus(self, stimulus):
"""!
@brief Create stimulus for oscillators in line with stimulus map and parameters.
@param[in] stimulus (list): Stimulus for oscillators that is represented by list, number of stimulus should be equal number of oscillators.
... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/nnet/legion.py#L305-L320 | [
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valid | legion_network.__create_dynamic_connections | !
@brief Create dynamic connection in line with input stimulus. | pyclustering/nnet/legion.py | def __create_dynamic_connections(self):
"""!
@brief Create dynamic connection in line with input stimulus.
"""
if (self._stimulus is None):
raise NameError("Stimulus should initialed before creation of the dynamic connections in the network.");
... | def __create_dynamic_connections(self):
"""!
@brief Create dynamic connection in line with input stimulus.
"""
if (self._stimulus is None):
raise NameError("Stimulus should initialed before creation of the dynamic connections in the network.");
... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/nnet/legion.py#L323-L347 | [
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valid | legion_network.simulate | !
@brief Performs static simulation of LEGION oscillatory network.
@param[in] steps (uint): Number steps of simulations during simulation.
@param[in] time (double): Time of simulation.
@param[in] stimulus (list): Stimulus for oscillators, number of stimulus should be equal ... | pyclustering/nnet/legion.py | def simulate(self, steps, time, stimulus, solution = solve_type.RK4, collect_dynamic = True):
"""!
@brief Performs static simulation of LEGION oscillatory network.
@param[in] steps (uint): Number steps of simulations during simulation.
@param[in] time (double): Time of simu... | def simulate(self, steps, time, stimulus, solution = solve_type.RK4, collect_dynamic = True):
"""!
@brief Performs static simulation of LEGION oscillatory network.
@param[in] steps (uint): Number steps of simulations during simulation.
@param[in] time (double): Time of simu... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/nnet/legion.py#L350-L410 | [
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valid | legion_network._calculate_states | !
@brief Calculates new state of each oscillator in the network.
@param[in] solution (solve_type): Type solver of the differential equation.
@param[in] t (double): Current time of simulation.
@param[in] step (double): Step of solution at the end of which states of oscillato... | pyclustering/nnet/legion.py | def _calculate_states(self, solution, t, step, int_step):
"""!
@brief Calculates new state of each oscillator in the network.
@param[in] solution (solve_type): Type solver of the differential equation.
@param[in] t (double): Current time of simulation.
@param[in] s... | def _calculate_states(self, solution, t, step, int_step):
"""!
@brief Calculates new state of each oscillator in the network.
@param[in] solution (solve_type): Type solver of the differential equation.
@param[in] t (double): Current time of simulation.
@param[in] s... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/nnet/legion.py#L413-L460 | [
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valid | legion_network._global_inhibitor_state | !
@brief Returns new value of global inhibitory
@param[in] z (dobule): Current value of inhibitory.
@param[in] t (double): Current time of simulation.
@param[in] argv (tuple): It's not used, can be ignored.
@return (double) New value if global inhibitory ... | pyclustering/nnet/legion.py | def _global_inhibitor_state(self, z, t, argv):
"""!
@brief Returns new value of global inhibitory
@param[in] z (dobule): Current value of inhibitory.
@param[in] t (double): Current time of simulation.
@param[in] argv (tuple): It's not used, can be ignored.
... | def _global_inhibitor_state(self, z, t, argv):
"""!
@brief Returns new value of global inhibitory
@param[in] z (dobule): Current value of inhibitory.
@param[in] t (double): Current time of simulation.
@param[in] argv (tuple): It's not used, can be ignored.
... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/nnet/legion.py#L464-L483 | [
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valid | legion_network._legion_state_simplify | !
@brief Returns new values of excitatory and inhibitory parts of oscillator of oscillator.
@details Simplify model doesn't consider oscillator potential.
@param[in] inputs (list): Initial values (current) of oscillator [excitatory, inhibitory].
@param[in] t (double): Curre... | pyclustering/nnet/legion.py | def _legion_state_simplify(self, inputs, t, argv):
"""!
@brief Returns new values of excitatory and inhibitory parts of oscillator of oscillator.
@details Simplify model doesn't consider oscillator potential.
@param[in] inputs (list): Initial values (current) of oscillator ... | def _legion_state_simplify(self, inputs, t, argv):
"""!
@brief Returns new values of excitatory and inhibitory parts of oscillator of oscillator.
@details Simplify model doesn't consider oscillator potential.
@param[in] inputs (list): Initial values (current) of oscillator ... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/nnet/legion.py#L486-L513 | [
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... | 98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0 |
valid | legion_network._legion_state | !
@brief Returns new values of excitatory and inhibitory parts of oscillator and potential of oscillator.
@param[in] inputs (list): Initial values (current) of oscillator [excitatory, inhibitory, potential].
@param[in] t (double): Current time of simulation.
@param[in] argv... | pyclustering/nnet/legion.py | def _legion_state(self, inputs, t, argv):
"""!
@brief Returns new values of excitatory and inhibitory parts of oscillator and potential of oscillator.
@param[in] inputs (list): Initial values (current) of oscillator [excitatory, inhibitory, potential].
@param[in] t (double)... | def _legion_state(self, inputs, t, argv):
"""!
@brief Returns new values of excitatory and inhibitory parts of oscillator and potential of oscillator.
@param[in] inputs (list): Initial values (current) of oscillator [excitatory, inhibitory, potential].
@param[in] t (double)... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/nnet/legion.py#L516-L547 | [
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... | 98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0 |
valid | syncgcolor_analyser.allocate_map_coloring | !
@brief Allocates coloring map for graph that has been processed.
@param[in] tolerance (double): Defines maximum deviation between phases.
@return (list) Colors for each node (index of node in graph), for example [color1, color2, color2, ...]. | pyclustering/gcolor/sync.py | def allocate_map_coloring(self, tolerance = 0.1):
"""!
@brief Allocates coloring map for graph that has been processed.
@param[in] tolerance (double): Defines maximum deviation between phases.
@return (list) Colors for each node (index of node in graph), for example [co... | def allocate_map_coloring(self, tolerance = 0.1):
"""!
@brief Allocates coloring map for graph that has been processed.
@param[in] tolerance (double): Defines maximum deviation between phases.
@return (list) Colors for each node (index of node in graph), for example [co... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/gcolor/sync.py#L64-L83 | [
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valid | syncgcolor._create_connections | !
@brief Creates connection in the network in line with graph.
@param[in] graph_matrix (list): Matrix representation of the graph. | pyclustering/gcolor/sync.py | def _create_connections(self, graph_matrix):
"""!
@brief Creates connection in the network in line with graph.
@param[in] graph_matrix (list): Matrix representation of the graph.
"""
for row in range(0, len(graph_matrix)):
for column in rang... | def _create_connections(self, graph_matrix):
"""!
@brief Creates connection in the network in line with graph.
@param[in] graph_matrix (list): Matrix representation of the graph.
"""
for row in range(0, len(graph_matrix)):
for column in rang... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/gcolor/sync.py#L116-L127 | [
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valid | syncgcolor._phase_kuramoto | !
@brief Returns result of phase calculation for oscillator in the network.
@param[in] teta (double): Value of phase of the oscillator with index argv in the network.
@param[in] t (double): Unused, can be ignored.
@param[in] argv (uint): Index of the oscillator in the network.
... | pyclustering/gcolor/sync.py | def _phase_kuramoto(self, teta, t, argv):
"""!
@brief Returns result of phase calculation for oscillator in the network.
@param[in] teta (double): Value of phase of the oscillator with index argv in the network.
@param[in] t (double): Unused, can be ignored.
@param[in] a... | def _phase_kuramoto(self, teta, t, argv):
"""!
@brief Returns result of phase calculation for oscillator in the network.
@param[in] teta (double): Value of phase of the oscillator with index argv in the network.
@param[in] t (double): Unused, can be ignored.
@param[in] a... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/gcolor/sync.py#L130-L151 | [
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"... | 98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0 |
valid | syncgcolor.process | !
@brief Performs simulation of the network (performs solving of graph coloring problem).
@param[in] order (double): Defines when process of synchronization in the network is over, range from 0 to 1.
@param[in] solution (solve_type): defines type (method) of solving diff. equation.
... | pyclustering/gcolor/sync.py | def process(self, order = 0.998, solution = solve_type.FAST, collect_dynamic = False):
"""!
@brief Performs simulation of the network (performs solving of graph coloring problem).
@param[in] order (double): Defines when process of synchronization in the network is over, range from 0 to ... | def process(self, order = 0.998, solution = solve_type.FAST, collect_dynamic = False):
"""!
@brief Performs simulation of the network (performs solving of graph coloring problem).
@param[in] order (double): Defines when process of synchronization in the network is over, range from 0 to ... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/gcolor/sync.py#L154-L167 | [
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valid | syncnet_analyser.allocate_clusters | !
@brief Returns list of clusters in line with state of ocillators (phases).
@param[in] eps (double): Tolerance level that define maximal difference between phases of oscillators in one cluster.
@param[in] indexes (list): List of real object indexes and it should be equal to amount ... | pyclustering/cluster/syncnet.py | def allocate_clusters(self, eps = 0.01, indexes = None, iteration = None):
"""!
@brief Returns list of clusters in line with state of ocillators (phases).
@param[in] eps (double): Tolerance level that define maximal difference between phases of oscillators in one cluster.
@... | def allocate_clusters(self, eps = 0.01, indexes = None, iteration = None):
"""!
@brief Returns list of clusters in line with state of ocillators (phases).
@param[in] eps (double): Tolerance level that define maximal difference between phases of oscillators in one cluster.
@... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/syncnet.py#L79-L91 | [
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] | 98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0 |
valid | syncnet_visualizer.animate_cluster_allocation | !
@brief Shows animation of output dynamic (output of each oscillator) during simulation on a circle from [0; 2pi].
@param[in] dataset (list): Input data that was used for processing by the network.
@param[in] analyser (syncnet_analyser): Output dynamic analyser of the Sync network.... | pyclustering/cluster/syncnet.py | def animate_cluster_allocation(dataset, analyser, animation_velocity = 75, tolerance = 0.1, save_movie = None, title = None):
"""!
@brief Shows animation of output dynamic (output of each oscillator) during simulation on a circle from [0; 2pi].
@param[in] dataset (list): Input data ... | def animate_cluster_allocation(dataset, analyser, animation_velocity = 75, tolerance = 0.1, save_movie = None, title = None):
"""!
@brief Shows animation of output dynamic (output of each oscillator) during simulation on a circle from [0; 2pi].
@param[in] dataset (list): Input data ... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/syncnet.py#L115-L161 | [
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... | 98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0 |
valid | syncnet._create_connections | !
@brief Create connections between oscillators in line with input radius of connectivity.
@param[in] radius (double): Connectivity radius between oscillators. | pyclustering/cluster/syncnet.py | def _create_connections(self, radius):
"""!
@brief Create connections between oscillators in line with input radius of connectivity.
@param[in] radius (double): Connectivity radius between oscillators.
"""
if (self._ena_conn_weight is True):
... | def _create_connections(self, radius):
"""!
@brief Create connections between oscillators in line with input radius of connectivity.
@param[in] radius (double): Connectivity radius between oscillators.
"""
if (self._ena_conn_weight is True):
... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/syncnet.py#L247-L289 | [
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valid | syncnet.process | !
@brief Peforms cluster analysis using simulation of the oscillatory network.
@param[in] order (double): Order of synchronization that is used as indication for stopping processing.
@param[in] solution (solve_type): Specified type of solving diff. equation.
@param[in] coll... | pyclustering/cluster/syncnet.py | def process(self, order = 0.998, solution = solve_type.FAST, collect_dynamic = True):
"""!
@brief Peforms cluster analysis using simulation of the oscillatory network.
@param[in] order (double): Order of synchronization that is used as indication for stopping processing.
@p... | def process(self, order = 0.998, solution = solve_type.FAST, collect_dynamic = True):
"""!
@brief Peforms cluster analysis using simulation of the oscillatory network.
@param[in] order (double): Order of synchronization that is used as indication for stopping processing.
@p... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/syncnet.py#L292-L309 | [
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valid | syncnet._phase_kuramoto | !
@brief Overrided method for calculation of oscillator phase.
@param[in] teta (double): Current value of phase.
@param[in] t (double): Time (can be ignored).
@param[in] argv (uint): Index of oscillator whose phase represented by argument teta.
@return (d... | pyclustering/cluster/syncnet.py | def _phase_kuramoto(self, teta, t, argv):
"""!
@brief Overrided method for calculation of oscillator phase.
@param[in] teta (double): Current value of phase.
@param[in] t (double): Time (can be ignored).
@param[in] argv (uint): Index of oscillator whose phase repre... | def _phase_kuramoto(self, teta, t, argv):
"""!
@brief Overrided method for calculation of oscillator phase.
@param[in] teta (double): Current value of phase.
@param[in] t (double): Time (can be ignored).
@param[in] argv (uint): Index of oscillator whose phase repre... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/syncnet.py#L312-L339 | [
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valid | syncnet.show_network | !
@brief Shows connections in the network. It supports only 2-d and 3-d representation. | pyclustering/cluster/syncnet.py | def show_network(self):
"""!
@brief Shows connections in the network. It supports only 2-d and 3-d representation.
"""
if ( (self._ccore_network_pointer is not None) and (self._osc_conn is None) ):
self._osc_conn = sync_connectivity_matrix(self._ccore... | def show_network(self):
"""!
@brief Shows connections in the network. It supports only 2-d and 3-d representation.
"""
if ( (self._ccore_network_pointer is not None) and (self._osc_conn is None) ):
self._osc_conn = sync_connectivity_matrix(self._ccore... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/syncnet.py#L342-L399 | [
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"... | 98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0 |
valid | hhn_network.simulate_static | !
@brief Performs static simulation of oscillatory network based on Hodgkin-Huxley neuron model.
@details Output dynamic is sensible to amount of steps of simulation and solver of differential equation.
Python implementation uses 'odeint' from 'scipy', CCORE uses classical RK4 and R... | pyclustering/nnet/hhn.py | def simulate_static(self, steps, time, solution = solve_type.RK4):
"""!
@brief Performs static simulation of oscillatory network based on Hodgkin-Huxley neuron model.
@details Output dynamic is sensible to amount of steps of simulation and solver of differential equation.
P... | def simulate_static(self, steps, time, solution = solve_type.RK4):
"""!
@brief Performs static simulation of oscillatory network based on Hodgkin-Huxley neuron model.
@details Output dynamic is sensible to amount of steps of simulation and solver of differential equation.
P... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/nnet/hhn.py#L286-L343 | [
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valid | hhn_network._calculate_states | !
@brief Caclculates new state of each oscillator in the network. Returns only excitatory state of oscillators.
@param[in] solution (solve_type): Type solver of the differential equations.
@param[in] t (double): Current time of simulation.
@param[in] step (uint): Step of so... | pyclustering/nnet/hhn.py | def _calculate_states(self, solution, t, step, int_step):
"""!
@brief Caclculates new state of each oscillator in the network. Returns only excitatory state of oscillators.
@param[in] solution (solve_type): Type solver of the differential equations.
@param[in] t (double): C... | def _calculate_states(self, solution, t, step, int_step):
"""!
@brief Caclculates new state of each oscillator in the network. Returns only excitatory state of oscillators.
@param[in] solution (solve_type): Type solver of the differential equations.
@param[in] t (double): C... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/nnet/hhn.py#L346-L397 | [
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"... | 98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0 |
valid | hhn_network.__update_peripheral_neurons | !
@brief Update peripheral neurons in line with new values of current in channels.
@param[in] t (doubles): Current time of simulation.
@param[in] step (uint): Step (time duration) during simulation when states of oscillators should be calculated.
@param[in] next_membrane (l... | pyclustering/nnet/hhn.py | def __update_peripheral_neurons(self, t, step, next_membrane, next_active_sodium, next_inactive_sodium, next_active_potassium):
"""!
@brief Update peripheral neurons in line with new values of current in channels.
@param[in] t (doubles): Current time of simulation.
@param[i... | def __update_peripheral_neurons(self, t, step, next_membrane, next_active_sodium, next_inactive_sodium, next_active_potassium):
"""!
@brief Update peripheral neurons in line with new values of current in channels.
@param[in] t (doubles): Current time of simulation.
@param[i... | [
"!"
] | annoviko/pyclustering | python | https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/nnet/hhn.py#L400-L436 | [
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... | 98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0 |
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