pm_arrayShuffle Module Reference

This module contains procedures and generic interfaces for shuffling arrays of various types. More...

Data Types
interface	getShuffled
	Perform an unbiased random shuffling of the input array, known as the Knuth or Fisher-Yates shuffle, and generate and return the new reshuffled array. More...
interface	setShuffled
	Perform an unbiased random shuffling of the input array, known as the Knuth or Fisher-Yates shuffle. More...

Variables
character(*, SK), parameter	MODULE_NAME = "@pm_arrayShuffle"

Detailed Description

This module contains procedures and generic interfaces for shuffling arrays of various types.

Benchmarks:

Benchmark :: The runtime performance of getShuffled vs. setShuffled ⛓

program benchmark
 
    use pm_kind, only: IK, LK, RK, SK
    use iso_fortran_env, only: error_unit
    use pm_bench, only: bench_type
 
    implicit none
 
    integer(IK)                         :: i
    integer(IK)                         :: isize
    integer(IK)                         :: fileUnit
    integer(IK) , parameter             :: NSIZE = 15_IK
    integer(IK) , parameter             :: NBENCH = 2_IK
    integer(IK)                         :: arraySize(NSIZE)
    real(RK)                            :: dummy = 0._RK
    real(RK)    , allocatable           :: Array(:)
    type(bench_type)                    :: bench(NBENCH)
 
    bench(1) = bench_type(name = SK_"setShuffled", exec = setShuffled, overhead = setOverhead)
    bench(2) = bench_type(name = SK_"getShuffled", exec = getShuffled, overhead = setOverhead)
 
    arraySize = [( 2_IK**isize, isize = 1_IK, NSIZE )]
 
    write(*,"(*(g0,:,' '))")
    write(*,"(*(g0,:,' '))") "setShuffled() vs. getShuffled()"
    write(*,"(*(g0,:,' '))")
 
    open(newunit = fileUnit, file = "main.out", status = "replace")
 
        write(fileUnit, "(*(g0,:,','))") "arraySize", (bench(i)%name, i = 1, NBENCH)
 
        loopOverArraySize: do isize = 1, NSIZE
 
            write(*,"(*(g0,:,' '))") "Benchmarking with size", arraySize(isize)
 
            allocate(Array(arraySize(isize)))
            call random_number(Array)
            do i = 1, NBENCH
                bench(i)%timing = bench(i)%getTiming(minsec = 0.07_RK)
            end do
            deallocate(Array)
 
            write(fileUnit,"(*(g0,:,','))") arraySize(isize), (bench(i)%timing%mean, i = 1, NBENCH)
 
        end do loopOverArraySize
        write(*,"(*(g0,:,' '))") dummy
        write(*,"(*(g0,:,' '))")
 
    close(fileUnit)
 
contains
 
    !%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    ! procedure wrappers.
    !%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
    subroutine setOverhead()
        call finalize()
    end subroutine
 
    subroutine finalize()
        dummy = dummy + Array(1)
    end subroutine
 
    subroutine setShuffled()
        block
            use pm_arrayShuffle, only: setShuffled
            call setShuffled(Array)
            call finalize()
        end block
    end subroutine
 
    subroutine getShuffled()
        block
            use pm_arrayShuffle, only: getShuffled
            Array = getShuffled(Array)
            call finalize()
        end block
    end subroutine
 
end program benchmark

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

Postprocessing of the benchmark output ⛓

#!/usr/bin/env python
 
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
 
fontsize = 14
 
methods = ["setShuffled", "getShuffled"]
 
df = pd.read_csv("main.out")
 
 
 
ax = plt.figure(figsize = 1.25 * np.array([6.4,4.6]), dpi = 200)
ax = plt.subplot()
 
for method in methods:
    plt.plot( df["arraySize"].values
            , df[method].values
            , linewidth = 2
            )
 
plt.xticks(fontsize = fontsize)
plt.yticks(fontsize = fontsize)
ax.set_xlabel("Array Size", fontsize = fontsize)
ax.set_ylabel("Runtime [ seconds ]", fontsize = fontsize)
ax.set_title("setShuffled() vs. getShuffled().\nLower is better.", fontsize = fontsize)
ax.set_xscale("log")
ax.set_yscale("log")
plt.minorticks_on()
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   ( methods
           #, loc='center left'
           #, bbox_to_anchor=(1, 0.5)
            , fontsize = fontsize
            )
 
plt.tight_layout()
plt.savefig("benchmark.getShuffled_vs_setShuffled.runtime.png")
 
 
 
ax = plt.figure(figsize = 1.25 * np.array([6.4,4.6]), dpi = 200)
ax = plt.subplot()
 
plt.plot( df["arraySize"].values
        , np.ones(len(df["arraySize"].values))
       #, linestyle = "--"
        , linewidth = 2
        )
plt.plot( df["arraySize"].values
        , df["getShuffled"].values / df["setShuffled"].values
        , linewidth = 2
        )
 
plt.xticks(fontsize = fontsize)
plt.yticks(fontsize = fontsize)
ax.set_xlabel("Array Size", fontsize = fontsize)
ax.set_ylabel("Runtime compared to setShuffled()", fontsize = fontsize)
ax.set_title("getShuffled() to setShuffled() Runtime Ratio.\nLower means faster. Lower than 1 means faster than setShuffled().", fontsize = fontsize)
ax.set_xscale("log")
#ax.set_yscale("log")
plt.minorticks_on()
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   ( ["setShuffled()", "getShuffled()", "Direct Method"]
           #, bbox_to_anchor = (1, 0.5)
           #, loc = "center left"
            , fontsize = fontsize
            )
 
plt.tight_layout()
plt.savefig("benchmark.getShuffled_vs_setShuffled.runtime.ratio.png")

Visualization of the benchmark output ⛓

Benchmark moral ⛓

1. The procedures under the generic interface getShuffled are functions while the procedures under the generic interface setShuffled are subroutines.
   The current implementation of the functional interface requires making a copy of the input array that is subsequently passed to the subroutine interface for random shuffling.
   As such, the observed performance degradation is expected.
   Note that an extra copy of the output array to the user-specified object is also needed, making the functional interface two-copies more expensive than the subroutine interface.
   

See also

pm_arrayRemap
pm_arrayChange
pm_arrayChoice
pm_arrayShuffle
pm_distUnif

Test:

test_pm_arrayShuffle

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, September 1, 2017, 12:20 AM, Institute for Computational Engineering and Sciences (ICES), The University of Texas at Austin

Variable Documentation

MODULE_NAME

character(*,SK), parameter pm_arrayShuffle::MODULE_NAME = "@pm_arrayShuffle"

Definition at line 67 of file pm_arrayShuffle.F90.