pm_distLogUnif::getLogUnifCDF Interface Reference

Generate and return the Cumulative Distribution Function (CDF) of the LogUniform distribution for an input log(x) within the support of the distribution \(x \in [0 < x_\mathrm{min}, x_\mathrm{max} < +\infty]\).
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Detailed Description

Generate and return the Cumulative Distribution Function (CDF) of the LogUniform distribution for an input log(x) within the support of the distribution \(x \in [0 < x_\mathrm{min}, x_\mathrm{max} < +\infty]\).

See the documentation of pm_distLogUnif for more information on the LogUniform distribution.

Parameters

[in]	logx	: The input scalar or array of the same shape as other array like arguments, of type real of kind any supported by the processor (e.g., RK, RK32, RK64, or RK128), containing the natural logarithm of the value at which the CDF must be computed.
[in]	logMinX	: The input scalar or array of the same shape as other array-like arguments, of the same type and kind as logx, containing the natural logarithm of the first scale parameter of the distribution, representing the minimum of the support of the distribution.
[in]	logMaxX	: The input scalar or array of the same shape as other array-like arguments, of the same type and kind as logx, containing the natural logarithm of the second scale parameter of the distribution, representing the maximum of the support of the distribution.

Returns

cdf : The output scalar or array of the same shape as any input array-like argument, of the same type and kind the input argument logx, containing the CDF of the distribution.

Possible calling interfaces ⛓

use pm_distLogUnif, only: getLogUnifCDF
 
cdf = getLogUnifCDF(logx, logMinX, logMaxX)

Warning

The conditions logMinX <= logx must hold for the corresponding input arguments.
The conditions logx <= logMaxX must hold for the corresponding input arguments.
These conditions are verified only if the library is built with the preprocessor macro CHECK_ENABLED=1.

The pure procedure(s) documented herein become impure when the ParaMonte library is compiled with preprocessor macro CHECK_ENABLED=1.
By default, these procedures are pure in release build and impure in debug and testing builds.

Remarks

The procedures under discussion are elemental.

See also

setLogUnifCDF

Example usage ⛓

program example
 
    use pm_kind, only: SK, IK, LK
    use pm_io, only: display_type
    use pm_distLogUnif, only: getLogUnifCDF
 
    implicit none
 
    real :: CDF(3)
 
    type(display_type) :: disp
    disp = display_type(file = "main.out.F90")
 
    call disp%skip()
    call disp%show("!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
    call disp%show("! Compute the Cumulative Distribution Function (CDF) of the LogUniform distribution.")
    call disp%show("!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
    call disp%skip()
 
    call disp%skip()
    call disp%show("CDF(1) = getLogUnifCDF(logx = log(3.), logMinX = log(2.), logMaxX = log(5.))")
                    CDF(1) = getLogUnifCDF(logx = log(3.), logMinX = log(2.), logMaxX = log(5.))
    call disp%show("CDF(1)")
    call disp%show( CDF(1) )
    call disp%skip()
 
    call disp%skip()
    call disp%show("CDF(1:3) = getLogUnifCDF(logx = log([3., 4., 2.5]), logMinX = log(2.), logMaxX = log(5.))")
                    CDF(1:3) = getLogUnifCDF(logx = log([3., 4., 2.5]), logMinX = log(2.), logMaxX = log(5.))
    call disp%show("CDF(1:3)")
    call disp%show( CDF(1:3) )
    call disp%skip()
 
    !%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    ! Output an example array for visualization.
    !%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
    block
        use pm_arraySpace, only: setLinSpace
        real :: logMinX(2), logMaxX(2), CDF(2), logx(2000)
        integer(IK) :: fileUnit, i, j
        call setLinSpace(logx, x1 = log(1.), x2 = log(13.))
        logMinX = log([3., 2.0])
        logMaxX = log([7., 10.])
        open(newunit = fileUnit, file = "getLogUnifCDF.RK.txt")
        do i = 1, size(logx)
            do j = 1, size(CDF)
                if (logMaxX(j) <= logx(i)) then
                    CDF(j) = 1.
                elseif (logMinX(j) <= logx(i)) then
                    CDF(j) = getLogUnifCDF(logx(i), logMinX(j), logMaxX(j))
                else
                    CDF(j) = 0.
                end if
            end do
            write(fileUnit, "(*(g0,:,', '))") exp(logx(i)), CDF
        end do
        close(fileUnit)
    end block
 
end program example

Example Unix compile command via Intel ifort compiler ⛓

#!/usr/bin/env sh
rm main.exe
ifort -fpp -standard-semantics -O3 -Wl,-rpath,../../../lib -I../../../inc main.F90 ../../../lib/libparamonte* -o main.exe
./main.exe

Example Windows Batch compile command via Intel ifort compiler ⛓

del main.exe
set PATH=..\..\..\lib;%PATH%
ifort /fpp /standard-semantics /O3 /I:..\..\..\include main.F90 ..\..\..\lib\libparamonte*.lib /exe:main.exe
main.exe

Example Unix / MinGW compile command via GNU gfortran compiler ⛓

#!/usr/bin/env sh
rm main.exe
gfortran -cpp -ffree-line-length-none -O3 -Wl,-rpath,../../../lib -I../../../inc main.F90 ../../../lib/libparamonte* -o main.exe
./main.exe

Example output ⛓

 
!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
! Compute the Cumulative Distribution Function (CDF) of the LogUniform distribution.
!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
 
CDF(1) = getLogUnifCDF(logx = log(3.), logMinX = log(2.), logMaxX = log(5.))
CDF(1)
+0.442507058
 
 
CDF(1:3) = getLogUnifCDF(logx = log([3., 4., 2.5]), logMinX = log(2.), logMaxX = log(5.))
CDF(1:3)
+0.442507058, +0.756470799, +0.243529230
 
 

Postprocessing of the example output ⛓

#!/usr/bin/env python
 
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import glob
import sys
 
linewidth = 2
fontsize = 17
 
marker ={ "CK" : "-"
        , "IK" : "."
        , "RK" : "-"
        }
xlab =  { "CK" : "X ( real/imaginary components )"
        , "IK" : "X ( integer-valued )"
        , "RK" : "X ( real-valued )"
        }
legends =   [ r"$x_{min} = +3., x_{max} = +7.$"
            , r"$x_{min} = +2., x_{max} = +10.$"
            ]
 
for kind in ["IK", "CK", "RK"]:
 
    pattern = "*." + kind + ".txt"
    fileList = glob.glob(pattern)
    if len(fileList) == 1:
 
        df = pd.read_csv(fileList[0], delimiter = ", ")
 
        fig = plt.figure(figsize = 1.25 * np.array([6.4, 4.8]), dpi = 200)
        ax = plt.subplot()
 
        if kind == "CK":
            plt.plot( df.values[:, 0]
                    , df.values[:,1:5]
                    , marker[kind]
                    , linewidth = linewidth
                   #, color = "r"
                    )
            plt.plot( df.values[:, 1]
                    , df.values[:,1:5]
                    , marker[kind]
                    , linewidth = linewidth
                   #, color = "blue"
                    )
        else:
            plt.plot( df.values[:, 0]
                    , df.values[:,1:]
                    , marker[kind]
                    , linewidth = linewidth
                   #, color = "r"
                    )
            ax.legend   ( legends
                        , fontsize = fontsize - 5
                        )
 
        plt.xticks(fontsize = fontsize - 2)
        plt.yticks(fontsize = fontsize - 2)
        ax.set_xlabel(xlab[kind], fontsize = 17)
        ax.set_ylabel("Cumulative Distribution Function (CDF)", fontsize = 17)
        #ax.set_xscale("log")
        #ax.set_yscale("log")
 
        plt.grid(visible = True, which = "both", axis = "both", color = "0.85", linestyle = "-")
        ax.tick_params(axis = "y", which = "minor")
        ax.tick_params(axis = "x", which = "minor")
 
        plt.tight_layout()
        plt.savefig(fileList[0].replace(".txt",".png"))
 
    elif len(fileList) > 1:
 
        sys.exit("Ambiguous file list exists.")

Visualization of the example output ⛓

Test:

test_pm_distLogUnif

Todo:

Very Low Priority: This generic interface can be extended to complex arguments.

Final Remarks ⛓

---

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For details on the naming abbreviations, see this page.
For details on the naming conventions, see this page.
This software is distributed under the MIT license with additional terms outlined below.

1. If you use any parts or concepts from this library to any extent, please acknowledge the usage by citing the relevant publications of the ParaMonte library.
   
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Copyright

Computational Data Science Lab

Author:

Amir Shahmoradi, Oct 16, 2009, 11:14 AM, Michigan

Definition at line 602 of file pm_distLogUnif.F90.

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The documentation for this interface was generated from the following file:

• src/fortran/main/pm_distLogUnif.F90