pm_distLogUnif::getLogUnifRand Interface Reference

Generate and return a scalar (or array of arbitrary rank) of random value(s) from the LogUniform distribution with parameters \((x_\mathrm{min}, x_\mathrm{max})\).
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Detailed Description

Generate and return a scalar (or array of arbitrary rank) of random value(s) from the LogUniform distribution with parameters \((x_\mathrm{min}, x_\mathrm{max})\).

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

Parameters

[in]	minx	: The input scalar (or array of the same rank, shape, and size as other array like arguments), of type integer of kind any supported by the processor (e.g., IK, IK8, IK16, IK32, or IK64), type real of kind any supported by the processor (e.g., RK, RK32, RK64, or RK128), containing the first scale parameter of the distribution, representing the minimum of the support of the distribution.
[in]	maxx	: The input scalar (or array of the same rank, shape, and size as other array like arguments), of the same type and kind as minx, containing the second scale parameter of the distribution, representing the maximum of the support of the distribution.

Returns

rand : The output scalar (or array of the same rank, shape, and size as other array like arguments), of the same type and kind as minx, containing the random value(s) from the specified distribution.
By definition, the condition minx <= rand < maxx holds.

Possible calling interfaces ⛓

use pm_distLogUnif, only: getLogUnifRand
 
rand = getLogUnifRand(minx, maxx)

Warning

The conditions minx < maxx must hold for the corresponding input arguments.
This condition is verified only if the library is built with the preprocessor macro CHECK_ENABLED=1.

Remarks

The procedures under discussion are impure.

The procedures under discussion are elemental.

See also

setLogUnifLogRand

Example usage ⛓

program example
 
    use pm_kind, only: SK, IK, LK
    use pm_io, only: display_type
    use pm_distLogUnif, only: getLogUnifRand
 
    implicit none
 
    real :: rand(3)
 
    type(display_type) :: disp
    disp = display_type(file = "main.out.F90")
 
    call disp%skip()
    call disp%show("!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
    call disp%show("! Generate random value(s) from the LogUniform distribution.")
    call disp%show("!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
    call disp%skip()
 
    call disp%skip()
    call disp%show("rand(1) = getLogUnifRand(minx = 2., maxx = 5.)")
                    rand(1) = getLogUnifRand(minx = 2., maxx = 5.)
    call disp%show("rand(1)")
    call disp%show( rand(1) )
    call disp%skip()
 
    call disp%skip()
    call disp%show("rand(1:3) = getLogUnifRand(minx = [.3, .4, .25], maxx = 5.)")
                    rand(1:3) = getLogUnifRand(minx = [.3, .4, .25], maxx = 5.)
    call disp%show("rand(1:3)")
    call disp%show( rand(1:3) )
    call disp%skip()
 
    !%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    ! Output an example array for visualization.
    !%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
    block
        use pm_arraySpace, only: setLinSpace
        real :: MinX(2), MaxX(2), rand(2)
        integer(IK) :: fileUnit, i
        MinX = [3., 2.0]
        MaxX = [7., 10.]
        open(newunit = fileUnit, file = "getLogUnifRand.RK.txt")
        do i = 1, 2000
            rand = getLogUnifRand(MinX, MaxX)
            write(fileUnit, "(*(g0,:,', '))") rand
        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 ⛓

 
!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
! Generate random value(s) from the LogUniform distribution.
!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
 
rand(1) = getLogUnifRand(minx = 2., maxx = 5.)
rand(1)
+4.89251900
 
 
rand(1:3) = getLogUnifRand(minx = [.3, .4, .25], maxx = 5.)
rand(1:3)
+0.400148898, +2.12147903, +0.871802509
 
 

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" : "Random Value ( Real / Imaginary ))"
        , "IK" : "Random Value ( Integer )"
        , "RK" : "Random Value ( Real )"
        }
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":
            ax.hist ( df.values[:, 0]
                    , bins = 30
                    , histtype = "stepfilled"
                    , density = True
                    , alpha = 0.7
                    )
            ax.hist ( df.values[:, 1]
                    , bins = 30
                    , histtype = "stepfilled"
                    , density = True
                    , alpha = 0.7
                    )
        else:
            ax.hist ( df.values[:,:]
                    , bins = 50
                    , histtype = "stepfilled"
                    , density = True
                    , alpha = 0.7
                    )
            ax.legend   ( legends[::-1]
                        , fontsize = fontsize
                        )
 
        plt.xticks(fontsize = fontsize - 2)
        plt.yticks(fontsize = fontsize - 2)
        ax.set_xlabel(xlab[kind], fontsize = 17)
        ax.set_ylabel("Density", fontsize = 17)
        ax.set_title("Histogram of {} randomly generated values".format(len(df.values)), fontsize = fontsize)
        #ax.set_yscale("log")
        #ax.set_xscale("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")
        ax.set_axisbelow(True)
 
        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 1108 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