pm_distGeomCyclic::getGeomCyclicRand Interface Reference

Generate and return a scalar (or array of arbitrary rank of) random value(s) from the Cyclic Geometric distribution.
More...

Detailed Description

Generate and return a scalar (or array of arbitrary rank of) random value(s) from the Cyclic Geometric distribution.

See the documentation of pm_distGeomCyclic for more details.

Parameters

[in]	probSuccess	: 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 probability of success parameter of the distribution.
[in]	period	: The input positive scalar (or array of the same rank, shape, and size as other array-like arguments), of type integer of default kind IK, containing the period of the Cyclic Geometric distribution. The period represents the maximum number of Bernoulli trials in the experiment.

Returns

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

Possible calling interfaces ⛓

use pm_distGeomCyclic, only: getGeomCyclicRand
 
rand = getGeomCyclicRand(probSuccess, period)

Warning

The condition 0 < period must hold for the corresponding input arguments.
The condition 0 < probSuccess .and. probSuccess <= 1 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

setGeomCyclicRand

Example usage ⛓

program example
 
    use pm_kind, only: SK, IK
    use pm_kind, only: RKG => RKS ! all real kinds are supported.
    use pm_distGeomCyclic, only: getGeomCyclicRand
    use pm_arraySpace, only: setLinSpace
    use pm_arraySpace, only: setLogSpace
    use pm_io, only: display_type
 
    implicit none
 
    integer(IK), parameter  :: NP = 1000_IK
    integer(IK) :: rand(NP)
    real(RKG) :: probSuccess(NP)
 
    type(display_type) :: disp
    disp = display_type(file = "main.out.F90")
 
    call setLinSpace(probSuccess, x1 = 0.001_RKG, x2 = 1._RKG)
 
    call disp%skip()
    call disp%show("probSuccess(1)")
    call disp%show( probSuccess(1) )
    call disp%show("rand(1) = getGeomCyclicRand(probSuccess(1), period = 10_IK)")
                    rand(1) = getGeomCyclicRand(probSuccess(1), period = 10_IK)
    call disp%show("rand(1)")
    call disp%show( rand(1) )
    call disp%skip()
 
    call disp%skip()
    call disp%show("probSuccess(1)")
    call disp%show( probSuccess(1) )
    call disp%show("rand(1:2) = getGeomCyclicRand(probSuccess(1), period = 10_IK)")
                    rand(1:2) = getGeomCyclicRand(probSuccess(1), period = 10_IK)
    call disp%show("rand(1:2)")
    call disp%show( rand(1:2) )
    call disp%skip()
 
    call disp%skip()
    call disp%show("probSuccess(1)")
    call disp%show( probSuccess(1) )
    call disp%show("rand(1:2) = getGeomCyclicRand(probSuccess(1), period = 100_IK)")
                    rand(1:2) = getGeomCyclicRand(probSuccess(1), period = 100_IK)
    call disp%show("rand(1:2)")
    call disp%show( rand(1:2) )
    call disp%skip()
 
    call disp%skip()
    call disp%show("probSuccess(NP-2:NP)")
    call disp%show( probSuccess(NP-2:NP) )
    call disp%show("rand(NP-2:NP) = getGeomCyclicRand(probSuccess(NP-2:NP), period = 100_IK)")
                    rand(NP-2:NP) = getGeomCyclicRand(probSuccess(NP-2:NP), period = 100_IK)
    call disp%show("rand(NP-2:NP)")
    call disp%show( rand(NP-2:NP) )
    call disp%skip()
 
    !%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    ! Output an example rand array for visualization.
    !%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
    block
        integer(IK) :: rand(4)
        integer :: fileUnit, i
        open(newunit = fileUnit, file = "getGeomCyclicRand.IK.txt")
        do i = 1, 5000
            rand = getGeomCyclicRand([.05_RKG, .25_RKG, .05_RKG, .25_RKG], period = [10_IK, 10_IK, 10000_IK, 10000_IK])
            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 ⛓

 
probSuccess(1)
+0.100000005E-2
rand(1) = getGeomCyclicRand(probSuccess(1), period = 10_IK)
rand(1)
+6
 
 
probSuccess(1)
+0.100000005E-2
rand(1:2) = getGeomCyclicRand(probSuccess(1), period = 10_IK)
rand(1:2)
+6, +6
 
 
probSuccess(1)
+0.100000005E-2
rand(1:2) = getGeomCyclicRand(probSuccess(1), period = 100_IK)
rand(1:2)
+21, +21
 
 
probSuccess(NP-2:NP)
+0.998000026, +0.999000013, +1.00000000
rand(NP-2:NP) = getGeomCyclicRand(probSuccess(NP-2:NP), period = 100_IK)
rand(NP-2:NP)
+1, +1, +1
 
 

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" : "Cyclic Geometric Random Value ( real/imaginary components )"
        , "IK" : "Cyclic Geometric Random Value ( integer-valued )"
        , "RK" : "Cyclic Geometric Random Value ( real-valued )"
        }
label = [ r"probSuccess = .05, period = 10"
        , r"probSuccess = .25, period = 10"
        , r"probSuccess = .05, period = 10000"
        , r"probSuccess = .25, period = 10000"
        ]
 
for kind in ["IK", "CK", "RK"]:
 
    pattern = "*." + kind + ".txt"
    fileList = glob.glob(pattern)
    if len(fileList) == 1:
 
        df = pd.read_csv(fileList[0], delimiter = ",", header = None)
 
        fig = plt.figure(figsize = 1.25 * np.array([6.4, 4.8]), dpi = 200)
        ax = plt.subplot()
 
        for j in range(len(df.values[0,:])):
            if kind == "CK":
                plt.hist( df.values[:,j]
                        , histtype = "stepfilled"
                        , density = False
                        , alpha = 0.5
                        , bins = 75
                        )
            else:
                plt.hist( df.values[:,j]
                        , histtype = "stepfilled"
                        , density = False
                        , alpha = 0.5
                        , bins = 75
                        )
                ax.legend   ( label
                            , fontsize = fontsize
                            )
        plt.xticks(fontsize = fontsize - 2)
        plt.yticks(fontsize = fontsize - 2)
        ax.set_xlim(0, 10)
        ax.set_xlabel(xlab[kind], fontsize = 17)
        ax.set_ylabel("Count", fontsize = 17)
        ax.set_title("Histograms of {} Cyclic Geometric random values".format(len(df.values[:, 0])), fontsize = 17)
 
        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.savefig(fileList[0].replace(".txt",".png"))
 
    elif len(fileList) > 1:
 
        sys.exit("Ambiguous file list exists.")

Visualization of the example output ⛓

Test:

test_pm_distGeomCyclic

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 1908 of file pm_distGeomCyclic.F90.

---

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

• src/fortran/main/pm_distGeomCyclic.F90