pm_distBinom::setBinomLogPMF Interface Reference

Return the natural logarithm of the Probability Mass Function (PMF) of the Binomial distribution for an input nsuc within the discrete integer support of the distribution.
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Detailed Description

Return the natural logarithm of the Probability Mass Function (PMF) of the Binomial distribution for an input nsuc within the discrete integer support of the distribution.

See the documentation of the parent module pm_distBinom for more information.

Parameters

[out]	logPMF	: The output 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), containing the natural logarithm of the PMF of the distribution at the specified nsuc.
[in]	nsuc	: The input scalar (or array of the same rank, shape, and size as other array-like arguments), of type integer of default kind IK, containing the values (numbers of success) at which the PMF must be computed.
[in]	ntry	: The input scalar (or array of the same rank, shape, and size as other array-like arguments), of type integer of default kind IK, containing the total number of trials in the Bernoulli Process.
[in]	logp	: The input scalar (or array of the same rank, shape, and size as other array-like arguments), of the same type and kind as the output argument logPMF, containing the natural logarithm of the probability of success in the Bernoulli Process.
[in]	logq	: The input scalar (or array of the same rank, shape, and size as other array-like arguments), of the same type and kind as the output argument logPMF, containing the natural logarithm of the probability of failure in the Bernoulli Process.

Possible calling interfaces ⛓

use pm_distBinom, only: setBinomLogPMF
 
call setBinomLogPMF(logPMF, nsuc, ntry, logp, logq)

Warning

The condition logp <= 0 must hold for the corresponding input arguments.
The condition logq <= 0 must hold for the corresponding input arguments.
The condition 0 <= nsuc must hold for the corresponding input arguments.
The condition 0 <= ntry must hold for the corresponding input arguments.
The condition nsuc <= ntry must hold for the corresponding input arguments.
The condition abs(1 - exp(logp) - exp(logq)) <= epsilon(logp) 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

getBinomLogPMF

Example usage ⛓

program example
 
    use pm_kind, only: SK, IK, LK
    use pm_kind, only: TKG => RK ! all processor kinds are supported.
    use pm_io, only: display_type
    use pm_distBinom, only: setBinomLogPMF
 
    implicit none
 
    type(display_type) :: disp
    real(TKG), allocatable :: logPMF(:)
    integer(IK), parameter :: ntry(*) = [integer(IK) :: 0, 1, 2, 3, 10, 30]
    disp = display_type(file = "main.out.F90")
 
 
    call disp%skip()
    call disp%show("ntry")
    call disp%show( ntry )
    call disp%show("allocate(logPMF(size(ntry)))")
                    allocate(logPMF(size(ntry)))
    call disp%show("call setBinomLogPMF(logPMF, nsuc = 0_IK, ntry = ntry, logp = log(0.5_TKG), logq = log(0.5_TKG))")
                    call setBinomLogPMF(logPMF, nsuc = 0_IK, ntry = ntry, logp = log(0.5_TKG), logq = log(0.5_TKG))
    call disp%show("logPMF")
    call disp%show( logPMF )
    call disp%skip()
 
    !%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    ! Output an example array for visualization.
    !%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
    block
        use pm_except, only: getNAN
        use pm_arrayRange, only: getRange
        integer(IK), parameter :: ntry = 60
        real(TKG), parameter :: psuc(*) = [real(TKG) :: .1, .5, .9]
        integer(IK), allocatable :: nsuc(:)
        real(TKG) :: logPMF(size(psuc))
        integer(IK) :: fileUnit, i
        nsuc = getRange(0_IK, ntry)
        open(newunit = fileUnit, file = "setBinomLogPMF.IK.txt")
        do i = 1, size(nsuc)
            call setBinomLogPMF(logPMF, nsuc(i), ntry, log(psuc), log(1 - psuc))
            write(fileUnit, "(*(g0,:,' '))") nsuc(i), exp(logPMF)
        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 ⛓

 
ntry
+0, +1, +2, +3, +10, +30
allocate(logPMF(size(ntry)))
call setBinomLogPMF(logPMF, nsuc = 0_IK, ntry = ntry, logp = log(0.5_TKG), logq = log(0.5_TKG))
logPMF
+0.0000000000000000, -0.69314718055994529, -1.3862943611198906, -2.0794415416798357, -6.9314718055994531, -20.794415416798358
 
 

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
 
fontsize = 17
 
kind = "IK"
label = [ r"$n = 60, p = 0.1$"
        , r"$n = 60, p = 0.5$"
        , r"$n = 60, p = 0.9$"
        ]
 
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 i in range(1,len(df.values[0,:]+1)):
 
            plt.plot( df.values[:, 0]
                    , df.values[:,i]
                    , marker = "."
                    )
 
    plt.xticks(fontsize = fontsize - 2)
    plt.yticks(fontsize = fontsize - 2)
    ax.set_xlim([0, None])
    ax.set_xlabel("Success Count", fontsize = fontsize)
    ax.set_ylabel("PMF", fontsize = fontsize)
 
    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.legend   ( label
                , fontsize = fontsize
               #, loc = "center left"
               #, bbox_to_anchor = (1, 0.5)
                )
 
    plt.savefig(fileList[0].replace(".txt",".png"))
 
else:
 
    sys.exit("Ambiguous file list exists.")

Visualization of the example output ⛓

Test:

test_pm_distBinom

Todo:

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

Final Remarks ⛓

---

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For details on the naming conventions, see this page.
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Copyright

Computational Data Science Lab

Author:

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

Definition at line 375 of file pm_distBinom.F90.

---

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

• src/fortran/main/pm_distBinom.F90