pm_distExp::getExpRand Interface Reference

Return a scalar (or array of arbitrary rank of) random value(s) from the Exponential distribution, optionally with the specified input location and scale parameters mu, sigma.
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Detailed Description

Return a scalar (or array of arbitrary rank of) random value(s) from the Exponential distribution, optionally with the specified input location and scale parameters mu, sigma.

See the documentation of pm_distExp for more details.

Parameters

[in]	sigma	: The input scalar (or array of the same rank, shape, and size as other array-like arguments), of type real of kind any supported by the processor (e.g., RK, RK32, RK64, or RK128), representing the scale parameter of the distribution.
[in]	mu	: The input scalar (or array of the same rank, shape, and size as other array-like arguments), of the same type and kind as sigma, representing the location parameter of the distribution. (optional, default = 0.)

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 sigma, containing random value(s) from the distribution.

Possible calling interfaces ⛓

use pm_distExp, only: getExpRand
 
rand = getExpRand(sigma, mu = mu)

Warning

The condition 0 < sigma 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

setExpRand

Example usage ⛓

program example
 
    use pm_kind, only: SK, IK
    use pm_io, only: display_type
    use pm_distExp, only: getExpRand
 
    implicit none
 
    integer :: i
    integer(IK) , parameter :: NP = 5_IK
    real :: rand(NP,NP)
 
    type(display_type) :: disp
    disp = display_type(file = "main.out.F90")
 
 
    call disp%skip()
    call disp%show("!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
    call disp%show("! Generate a scalar real random number.")
    call disp%show("!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
    call disp%skip()
 
    call disp%skip()
    call disp%show("rand(1,1) = getExpRand(sigma = 2.) ! random real number with the Exponential mean 2..")
                    rand(1,1) = getExpRand(sigma = 2.)
    call disp%show("rand(1,1)")
    call disp%show( rand(1,1) )
    call disp%skip()
 
    call disp%skip()
    call disp%show("!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
    call disp%show("! Generate a vector of real random numbers.")
    call disp%show("!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
    call disp%skip()
 
    call disp%skip()
    call disp%show("rand(:,1) = getExpRand(sigma = [(10., i = 1,NP)]) ! random real vector with the default Exponential mean (1,1).")
                    rand(:,1) = getExpRand(sigma = [(10., i = 1,NP)])
    call disp%show("rand(:,1)")
    call disp%show( rand(:,1) )
    call disp%skip()
 
    block
        integer :: fileUnit, i
        open(newunit = fileUnit, file = "getExpRand.RK.txt")
        do i = 1, 1000
            write(fileUnit,"(2(g0,:,', '))") getExpRand(sigma = [3., 2.], mu = [0., 2.])
        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 a scalar real random number.
!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
 
rand(1,1) = getExpRand(sigma = 2.) ! random real number with the Exponential mean 2..
rand(1,1)
+0.854733884
 
 
!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
! Generate a vector of real random numbers.
!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
 
rand(:,1) = getExpRand(sigma = [(10., i = 1,NP)]) ! random real vector with the default Exponential mean (1,1).
rand(:,1)
+9.80278683, +13.9602566, +1.23344874, +6.85209036, +4.38768196
 
 

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"$\sigma, \mu = 2., 2.$"
            , r"$\sigma = 3.$"
            ]
 
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[:,0:2]
                    , bins = 50
                    , histtype = "stepfilled"
                    , density = True
                    , alpha = 0.7
                    )
            ax.legend   ( legends
                        , 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 {} Exponential random numbers\nMean = {}".format(len(df.values), np.round(np.mean(np.double(df.values), axis = 0), 2)), 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_distExp

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 1022 of file pm_distExp.F90.

---

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

• src/fortran/main/pm_distExp.F90