general_utilities Module

This module includes general purpose functions used in several parts of the library


Uses

  • module~~general_utilities~~UsesGraph module~general_utilities general_utilities module~precision_utilities precision_utilities module~general_utilities->module~precision_utilities iso_fortran_env iso_fortran_env module~precision_utilities->iso_fortran_env

Used by

  • module~~general_utilities~~UsedByGraph module~general_utilities general_utilities module~correlation_distance_utilities correlation_distance_utilities module~correlation_distance_utilities->module~general_utilities module~factory_distance_utilities factory_distance_utilities module~factory_distance_utilities->module~correlation_distance_utilities module~kohonen_layer_utilities kohonen_layer_utilities module~kohonen_layer_utilities->module~factory_distance_utilities module~multilayer_self_organizing_map_utilities multilayer_self_organizing_map_utilities module~multilayer_self_organizing_map_utilities->module~factory_distance_utilities module~self_organizing_map_utilities self_organizing_map_utilities module~self_organizing_map_utilities->module~factory_distance_utilities module~two_level_self_organizing_map_utilities two_level_self_organizing_map_utilities module~two_level_self_organizing_map_utilities->module~factory_distance_utilities module~som_predict_variables som_predict_variables module~som_predict_variables->module~self_organizing_map_utilities module~som_train_variables som_train_variables module~som_train_variables->module~self_organizing_map_utilities module~two_level_som_estimate_variables two_level_som_estimate_variables module~two_level_som_estimate_variables->module~two_level_self_organizing_map_utilities module~two_level_som_train_variables two_level_som_train_variables module~two_level_som_train_variables->module~two_level_self_organizing_map_utilities

Interfaces

public interface maximum

  • private subroutine maximum_only(a, mx)

    Subroutine to calculate the maximum of a real array

    Arguments

    Type IntentOptional Attributes Name
    real(kind=wp), dimension(:) :: a
    real(kind=wp) :: mx

  • private subroutine maximum_position(a, mx, p)

    Subroutine to find the position of the maximum value of a real array

    Arguments

    Type IntentOptional Attributes Name
    real(kind=wp), dimension(:) :: a

    A real array
    real(kind=wp) :: mx

    A real value with the maximum
    integer :: p

    An integer value with the position of the maximum

Functions

public function minimum(a) result(mn)

Function to calculate the minimum of an array

Arguments

Type IntentOptional Attributes Name
real(kind=wp), dimension(:) :: a

Real array

Return Value real(kind=wp)

Real value with the minimum

public function mean(a) result(mn)

Function to calculate the mean of a real array

Arguments

Type IntentOptional Attributes Name
real(kind=wp), intent(inout), dimension(:) :: a

A real array

Return Value real(kind=wp)

A real value with the calculated mean

public function variance(a) result(v)

Function to calculate the variance of a real array

Arguments

Type IntentOptional Attributes Name
real(kind=wp), intent(inout), dimension(:) :: a

A real array

Return Value real(kind=wp)

A real variable with the calculated variance

public function std(a) result(s)

Function to calculate the standard deviation of a real array

Arguments

Type IntentOptional Attributes Name
real(kind=wp), intent(inout), dimension(:) :: a

A real array

Return Value real(kind=wp)

A real variable with the calculated standard deviation

public function coefficient_of_variation(a) result(cov)

Function to calculate the coefficient of variation of a real array

Arguments

Type IntentOptional Attributes Name
real(kind=wp), intent(inout), dimension(:) :: a

A real array

Return Value real(kind=wp)

A real variable with the calculated coefficient of variation

public function correlation_coefficient(x, y) result(cor)

Function to calculate the correlation coefficient between two real vectors

Arguments

Type IntentOptional Attributes Name
real(kind=wp), intent(inout), dimension(:) :: x

Real arrays
real(kind=wp), intent(inout), dimension(:) :: y

Real arrays

Return Value real(kind=wp)

Real value with the correlation coefficient