pm_distPoweto::getPowetoLogRand Interface Reference

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

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

See the documentation of pm_distPoweto for more information on the (Truncated) Poweto distribution.

Parameters

[in]	alpha	: 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 shape parameter of the distribution (i.e., the exponent of the power-law function).
[in]	logMinX	: The input scalar (or array of the same shape as other array-like arguments) of the same type and kind as alpha, containing the natural logarithm of the first scale parameter of the distribution, representing the minimum of the support of the distribution. (optional, default = \(-\infty\). It must be present if \(\alpha \leq 0\) holds.)
[in]	logMaxX	: The input scalar (or array of the same shape as other array-like arguments) of the same type and kind as alpha, containing the natural logarithm of the second scale parameter of the distribution, representing the maximum of the support of the distribution. (optional, default = \(+\infty\). It must be present if \(0 \leq \alpha\) holds.)

Returns

logRand : The output scalar (or array of the same rank, shape, and size as other array like arguments), of the same type and kind as alpha, containing the random value(s) from the specified distribution.

Possible calling interfaces ⛓

use pm_distPoweto, only: getPowetoLogRand
 
logRand = getPowetoLogRand(alpha, logMinX = logMinX, logMaxX = logMaxX)
!

Warning

The condition 0 < alpha .or. present(logMinX) must hold for the corresponding input arguments.
The condition alpha < 0 .or. present(logMaxX) must hold for the corresponding input arguments.
The conditions logMinX < 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.

Remarks

The procedures under discussion are impure.

The procedures under discussion are elemental.

See also

setPowetoLogRand

Example usage ⛓

program example
 
    use pm_kind, only: SK, IK, LK
    use pm_distPoweto, only: getPowetoLogCDFNF
    use pm_distPoweto, only: getPowetoLogRand
    use pm_io, only: display_type
 
    implicit none
 
    real                    :: logx(3)
 
    type(display_type)      :: disp
    disp = display_type(file = "main.out.F90")
 
    call disp%skip()
    call disp%show("!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
    call disp%show("! Compute random value(s) from the Poweto distribution.")
    call disp%show("!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
    call disp%skip()
 
    call disp%skip()
    call disp%show("logx(1) = getPowetoLogRand(alpha = -2., logMinX = -2.) ! Poweto distribution.")
                    logx(1) = getPowetoLogRand(alpha = -2., logMinX = -2.) ! Poweto distribution.
    call disp%show("logx(1)")
    call disp%show( logx(1) )
    call disp%skip()
 
    call disp%skip()
    call disp%show("logx(1:3) = getPowetoLogRand(alpha = -[+2., +3., +4.], logMinX = -2.) ! Poweto distribution.")
                    logx(1:3) = getPowetoLogRand(alpha = -[+2., +3., +4.], logMinX = -2.) ! Poweto distribution.
    call disp%show("logx(1:3)")
    call disp%show( logx(1:3) )
    call disp%skip()
 
    call disp%skip()
    call disp%show("logx(1) = getPowetoLogRand(alpha = +2., logMaxX = -2.) ! Poweto distribution.")
                    logx(1) = getPowetoLogRand(alpha = +2., logMaxX = -2.) ! Poweto distribution.
    call disp%show("logx(1)")
    call disp%show( logx(1) )
    call disp%skip()
 
    call disp%skip()
    call disp%show("logx(1:3) = getPowetoLogRand(alpha = [+2., +3., +4.], logMaxX = -2.) ! Poweto distribution.")
                    logx(1:3) = getPowetoLogRand(alpha = [+2., +3., +4.], logMaxX = -2.) ! Poweto distribution.
    call disp%show("logx(1:3)")
    call disp%show( logx(1:3) )
    call disp%skip()
 
    call disp%skip()
    call disp%show("!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
    call disp%show("! Compute random value(s) from the Truncated Poweto distribution.")
    call disp%show("!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
    call disp%skip()
 
    call disp%skip()
    call disp%show("logx(1) = getPowetoLogRand(alpha = -2., logMinX = -2., logMaxX = 5.) ! Truncated Poweto distribution.")
                    logx(1) = getPowetoLogRand(alpha = -2., logMinX = -2., logMaxX = 5.) ! Truncated Poweto distribution.
    call disp%show("logx(1)")
    call disp%show( logx(1) )
    call disp%skip()
 
    call disp%skip()
    call disp%show("logx(1:3) = getPowetoLogRand(alpha = -[+2., +3., +4.], logMinX = -2., logMaxX = 5.) ! Truncated Poweto distribution.")
                    logx(1:3) = getPowetoLogRand(alpha = -[+2., +3., +4.], logMinX = -2., logMaxX = 5.) ! Truncated Poweto distribution.
    call disp%show("logx(1:3)")
    call disp%show( logx(1:3) )
    call disp%skip()
 
    call disp%skip()
    call disp%show("logx(1) = getPowetoLogRand(alpha = +2., logMinX = -2., logMaxX = 5.) ! Truncated Poweto distribution.")
                    logx(1) = getPowetoLogRand(alpha = +2., logMinX = -2., logMaxX = 5.) ! Truncated Poweto distribution.
    call disp%show("logx(1)")
    call disp%show( logx(1) )
    call disp%skip()
 
    call disp%skip()
    call disp%show("logx(1:3) = getPowetoLogRand(alpha = +[+2., +3., +4.], logMinX = -2., logMaxX = 5.) ! Truncated Poweto distribution.")
                    logx(1:3) = getPowetoLogRand(alpha = +[+2., +3., +4.], logMinX = -2., logMaxX = 5.) ! Truncated Poweto distribution.
    call disp%show("logx(1:3)")
    call disp%show( logx(1:3) )
    call disp%skip()
 
    !%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    ! Output an example array for visualization.
    !%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
    block
        use pm_arraySpace, only: setLinSpace
        use pm_arrayResize, only: setResized
        use pm_arrayRefill, only: setRefilled
        real, allocatable :: alpha(:), sigma(:)
        real :: logMinX, logMaxX
        integer(IK) :: fileUnit, i
        alpha = [-2.0, -1., 0., +1., +2.]
        call setRefilled(sigma, 1., size(alpha, 1, IK))
        logMinX = log(3.)
        logMaxX = log(8.)
        open(newunit = fileUnit, file = "getPowetoLogRand.RK.txt")
        do i = 1, 2000
            write(fileUnit, "(*(g0,:,', '))") exp(getPowetoLogRand(alpha, logMinX, logMaxX))
        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 random value(s) from the Poweto distribution.
!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
 
logx(1) = getPowetoLogRand(alpha = -2., logMinX = -2.) ! Poweto distribution.
logx(1)
-1.86170161
 
 
logx(1:3) = getPowetoLogRand(alpha = -[+2., +3., +4.], logMinX = -2.) ! Poweto distribution.
logx(1:3)
-1.05563772, -1.57728815, -1.92279100
 
 
logx(1) = getPowetoLogRand(alpha = +2., logMaxX = -2.) ! Poweto distribution.
logx(1)
-2.27709508
 
 
logx(1:3) = getPowetoLogRand(alpha = [+2., +3., +4.], logMaxX = -2.) ! Poweto distribution.
logx(1:3)
-2.24768949, -2.40717101, -2.11305952
 
 
!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
! Compute random value(s) from the Truncated Poweto distribution.
!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
 
logx(1) = getPowetoLogRand(alpha = -2., logMinX = -2., logMaxX = 5.) ! Truncated Poweto distribution.
logx(1)
-1.57277358
 
 
logx(1:3) = getPowetoLogRand(alpha = -[+2., +3., +4.], logMinX = -2., logMaxX = 5.) ! Truncated Poweto distribution.
logx(1:3)
-1.70083976, -1.90711761, -1.32627130
 
 
logx(1) = getPowetoLogRand(alpha = +2., logMinX = -2., logMaxX = 5.) ! Truncated Poweto distribution.
logx(1)
+4.35019970
 
 
logx(1:3) = getPowetoLogRand(alpha = +[+2., +3., +4.], logMinX = -2., logMaxX = 5.) ! Truncated Poweto distribution.
logx(1:3)
+4.34123898, +4.15473413, +4.04929209
 
 

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"$\alpha = -2., x_{min} = +3., x_{max} = +8$"
            , r"$\alpha = -1., x_{min} = +3., x_{max} = +8$"
            , r"$\alpha = 0.0, x_{min} = +3., x_{max} = +8$"
            , r"$\alpha = +1., x_{min} = +3., x_{max} = +8$"
            , r"$\alpha = +2., x_{min} = +3., x_{max} = +8$"
            ]
 
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 = "step"
                    , density = True
                    , alpha = 1
                    )
            ax.hist ( df.values[:, 1]
                    , bins = 30
                    , histtype = "step"
                    , density = True
                    , alpha = 1
                    )
        else:
            ax.hist ( df.values[:,:]
                    , bins = 50
                    , histtype = "step"
                    , density = True
                    , alpha = 1
                    )
            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_distPoweto

Todo:

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

Final Remarks ⛓

---

If you believe this algorithm or its documentation can be improved, we appreciate your contribution and help to edit this page's documentation and source file on GitHub.
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.
   
2. If you regenerate any parts/ideas from this library in a programming environment other than those currently supported by this ParaMonte library (i.e., other than C, C++, Fortran, MATLAB, Python, R), please also ask the end users to cite this original ParaMonte library.
   

This software is available to the public under a highly permissive license.
Help us justify its continued development and maintenance by acknowledging its benefit to society, distributing it, and contributing to it.

Copyright

Computational Data Science Lab

Author:

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

Definition at line 1303 of file pm_distPoweto.F90.

---

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

• src/fortran/main/pm_distPoweto.F90