File | Description |
---|---|
cauchy_neighborhood_function_utilities.f90 | This module defines the Cauchy neighborhood function |
constants_utilities.f90 | This module defines several numerical constants used in the ATALIB library. These constants can be imported in any module of the library. This module is in constant evolution and new constants are being added to the library. |
correlation_distance_utilities.f90 | This module defines a class to calculate the correlation distance between kohonen prototypes |
dataframe_utilities.f90 | This module defines a data structure called dataframe |
direction_cosine_distance_utilities.f90 | This module defines a class to calculate the direction cosine distance between kohonen prototypes |
distance_base_utilities.f90 | This module defines an abstract class called |
euclidean_distance_utilities.f90 | This module defines a class to calculate the Euclidean distance between kohonen prototypes |
exponential_learning_rate_function_utilities.f90 | This module defines a class to define learning rate functions |
factory_distance_utilities.f90 | This module defines a factory to create distance objects |
factory_learning_rate_function_utilities.f90 | This module defines a factory to create learning rate functions |
gaussian_learning_rate_function_utilities.f90 | This module defines a class that represents the gaussian learning rate function |
gaussian_neighborhood_function_utilities.f90 | This module defines the Gaussian neighborhood function |
general_utilities.f90 | This module includes general purpose functions used in several parts of the library |
kohonen_layer_base_utilities.f90 | This module defines an abstract class that represents a layer in a self-organizing map |
kohonen_layer_parameters_utilities.f90 | |
kohonen_layer_utilities.f90 | This module defines a class that represents a layer in a self-organizing map |
kohonen_map_base_utilities.f90 | This module defines an abstract class for kohonen maps |
kohonen_pattern_utilities.f90 | This module defines a class called |
kohonen_prototype_utilities.f90 | This module defines a class for kohonen prototype (units inside kohonen layers) |
learning_rate_function_base_utilities.f90 | This module defines an abstract class to define learning rate functions |
linear_learning_rate_function_utilities.f90 | This module defines a class to define learning rate functions |
logger_utilities.f90 | This module includes the definition of a class called logger that is used to log messages on the screen during the development or running of a given application |
manhattan_distance_utilities.f90 | This module defines a class to calculate the Manhattan distance between kohonen prototypes |
max_distance_utilities.f90 | This module defines a class to calculate the Max distance between kohonen prototypes |
mt19937_64.f90 | This is a Fortran translation of the 64-bit version of the Mersenne Twister pseudorandom number generator |
multilayer_self_organizing_map_utilities.f90 | This module defines a class that represents a multilayer self_organized_map defined using several kohonen layers |
neighborhood_function_base_utilities.f90 | This module defines an abstract class to define neighborhood functions |
precision_utilities.f90 | This module defines the precision constants used in all modules of the library. |
quicksort_utilities.f90 | This module includes the definition of a class called quicksort that is used to encapsulate the quicksorting algorithm. This algorithm is highly efficient. |
random_generator_base_utilities.f90 | Define an abstract class random_generator_base to be used to derive different types of random number generators to be use with ATALIB03 |
random_number_generator_utilities.f90 | This module defines the random_number_generator class that is used to generate random numbers in several procedures across ATALIB. |
rkiss05_generator_utilities.f90 | This module includes the definition of a class called rkiss05_generator that is used to generate random numbers with an uniform disitribution using the rkiss approach |
self_organizing_map_utilities.f90 | This module defines a class for simple self_organizing_map (one kohonen layer) |
som_predict_variables.f90 | |
som_train_variables.f90 | This module defines the variables for the program som_train |
sort_base_utilities.f90 | Define an abstract class to represent a generic sort procedure. |
two_level_self_organizing_map_utilities.f90 | This module defines a class that represents a two layer self_organizing_map for clustering |
two_level_som_estimate_variables.f90 | |
two_level_som_train_variables.f90 |