pm_arrayRemove Module Reference

This module contains procedures and generic interfaces for removing a pattern from arrays of various types at the specified instances of occurrence of pattern. More...

Data Types
interface	getRemoved
	Generate and return an allocatable array containing the remaining parts of the input array as a sequence after removing the input pattern at the requested occurrences. More...
interface	setRemoved
	Return the remaining parts of the input array as a sequence after removing the input pattern at the requested occurrences. More...

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

Detailed Description

This module contains procedures and generic interfaces for removing a pattern from arrays of various types at the specified instances of occurrence of pattern.

Benchmarks:

Benchmark :: The runtime performance of setRemoved for scalar vs. vector input pattern argument. ⛓

! Test the performance of setRemoved() with a vector `pattern` vs. scalar `pattern`.
program benchmark
 
    use iso_fortran_env, only: error_unit
    use pm_bench, only: bench_type
    use pm_kind, only: IK, LK, RK, SK
 
    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)
    logical(LK)                         :: dummy = .true._LK
    integer(IK) , allocatable           :: Array(:)
    integer(IK) , parameter             :: pattern(1) = 0_IK
    type(bench_type)                    :: bench(NBENCH)
 
    bench(1) = bench_type(name = SK_"scalarPattern", exec = scalarPattern , overhead = setOverhead)
    bench(2) = bench_type(name = SK_"vectorPattern", exec = vectorPattern , overhead = setOverhead)
 
    arraySize = [( 2_IK**isize, isize = 1_IK, NSIZE )]
 
    write(*,"(*(g0,:,' '))")
    write(*,"(*(g0,:,' '))") "scalarPattern() vs. vectorPattern()"
    write(*,"(*(g0,:,' '))")
 
    open(newunit = fileUnit, file = "main.out", status = "replace")
 
        write(fileUnit, "(*(g0,:,','))") "arraySize", (bench(i)%name, i = 1_IK, NBENCH)
 
        loopOverArraySize: do isize = 1, NSIZE
 
            write(*,"(*(g0,:,' '))") "Benchmarking with size", arraySize(isize)
            allocate(Array(arraySize(isize)))
 
            do i = 1_IK, NBENCH
                bench(i)%timing = bench(i)%getTiming(minsec = 0.05_RK)
            end do
 
            deallocate(Array)
            write(fileUnit,"(*(g0,:,','))") arraySize(isize), (bench(i)%timing%mean, i = 1_IK, NBENCH)
 
        end do loopOverArraySize
        write(*,"(*(g0,:,' '))") dummy
        write(*,"(*(g0,:,' '))")
 
    close(fileUnit)
 
contains
 
    !%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    ! procedure wrappers.
    !%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
    subroutine setOverhead()
        call initialize()
        call finalize()
    end subroutine
 
    subroutine initialize()
        Array(:) = 1_IK
    end subroutine
 
    subroutine finalize()
        dummy = dummy .and. size(Array, kind = IK) < 1_IK
    end subroutine
 
    subroutine scalarPattern()
        use pm_arrayRemove, only: setRemoved
        call initialize()
        call setRemoved(Array, pattern(1))
        call finalize()
    end subroutine
 
    subroutine vectorPattern()
        block
            use pm_arrayRemove, only: setRemoved
            call initialize()
            call setRemoved(Array, pattern)
            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 = ["scalarPattern", "vectorPattern"]
 
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("Removing array segments with pattern(1) (scalar) vs. pattern(1:1) (vector).\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.setRemoved-scalarPattern_vs_vectorPattern.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 = "--"
       #, color = "black"
        , linewidth = 2
        )
plt.plot( df["arraySize"].values
        , df["vectorPattern"].values / df["scalarPattern"].values
        , linewidth = 2
        )
 
plt.xticks(fontsize = fontsize)
plt.yticks(fontsize = fontsize)
ax.set_xlabel("Array Size", fontsize = fontsize)
ax.set_ylabel("Runtime compared to scalarPattern()", fontsize = fontsize)
ax.set_title("Runtime Ratio: Remove pattern(1:1) / Remove pattern(1).\nLower means faster. Lower than 1 means faster than scalarPattern.", 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   ( ["scalarPattern", "vectorPattern"]
           #, bbox_to_anchor = (1, 0.5)
           #, loc = "center left"
            , fontsize = fontsize
            )
 
plt.tight_layout()
plt.savefig("benchmark.setRemoved-scalarPattern_vs_vectorPattern.runtime.ratio.png")

Visualization of the benchmark output ⛓

Benchmark moral ⛓

1. The procedures under the generic interface setRemoved take both scalar and vector pattern arguments.
   As evidenced by the above benchmark, when the input pattern is vector of length 1, it is much faster, up to 4X, to pass pattern as a scalar instead of a whole array of length 1.
   Note that this benchmark is likely irrelevant to removing substrings from Fortran strings.
   

Benchmark :: The runtime performance of getRemoved vs. setRemoved ⛓

! Test the performance of `getRemoved()` vs. `setRemoved()`.
program benchmark
 
    use iso_fortran_env, only: error_unit
    use pm_kind, only: IK, LK, RK, SK
    use pm_bench, only: bench_type
 
    implicit none
 
    integer(IK)                         :: i
    integer(IK)                         :: isize
    integer(IK)                         :: fileUnit
    integer(IK) , parameter             :: NSIZE = 12_IK
    integer(IK)                         :: arraySize(NSIZE)
    logical(LK)                         :: dummy = .true._LK
    character(:, SK), allocatable       :: array
    character(*, SK), parameter         :: pattern = "a"
    type(bench_type), allocatable       :: bench(:)
 
    bench = [ bench_type(name = SK_"setRemoved", exec = setRemoved, overhead = setOverhead) &
            , bench_type(name = SK_"getRemoved", exec = getRemoved, overhead = setOverhead) &
            ]
    arraySize = [( 2_IK**isize, isize = 1_IK, NSIZE )]
 
    write(*,"(*(g0,:,' '))")
    write(*,"(*(g0,:,' '))") "setRemoved() vs. getRemoved()"
    write(*,"(*(g0,:,' '))")
 
    open(newunit = fileUnit, file = "main.out", status = "replace")
 
        write(fileUnit, "(*(g0,:,','))") "arraySize", (bench(i)%name, i = 1, size(bench, 1, IK))
 
        loopOverArraySize: do isize = 1, NSIZE
 
            write(*,"(*(g0,:,' '))") "Benchmarking with size", arraySize(isize)
 
            do i = 1, size(bench, 1, IK)
                bench(i)%timing = bench(i)%getTiming(minsec = 0.05_RK)
            end do
 
            write(fileUnit,"(*(g0,:,','))") arraySize(isize), (bench(i)%timing%mean, i = 1, size(bench, 1, IK))
 
        end do loopOverArraySize
        write(*,"(*(g0,:,' '))") dummy
        write(*,"(*(g0,:,' '))")
 
    close(fileUnit)
 
contains
 
    !%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    ! procedure wrappers.
    !%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
    subroutine setOverhead()
        call initialize()
        call finalize()
    end subroutine
 
    subroutine initialize()
        array = repeat(pattern, arraySize(isize))
    end subroutine
 
    subroutine finalize()
        dummy = dummy .and. 0_IK < len(array, IK)
        deallocate(array)
    end subroutine
 
    subroutine setRemoved()
        block
            use pm_arrayRemove, only: setRemoved
            call initialize()
            call setRemoved(array, pattern)
            call finalize()
        end block
    end subroutine
 
    subroutine getRemoved()
        block
            use pm_arrayRemove, only: getRemoved
            call initialize()
            array = getRemoved(array, pattern)
            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 = ["setRemoved", "getRemoved"]
 
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("setRemoved() vs. getRemoved()\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.getRemoved_vs_setRemoved.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 = "--"
       #, color = "black"
        , linewidth = 2
        )
plt.plot( df["arraySize"].values
        , df["getRemoved"].values / df["setRemoved"].values
        , linewidth = 2
        )
 
plt.xticks(fontsize = fontsize)
plt.yticks(fontsize = fontsize)
ax.set_xlabel("Array Size", fontsize = fontsize)
ax.set_ylabel("Runtime compared to setRemoved()", fontsize = fontsize)
ax.set_title("getRemoved / setRemoved\nLower means faster. Lower than 1 means faster than setRemoved().", 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   ( ["setRemoved", "getRemoved"]
           #, bbox_to_anchor = (1, 0.5)
           #, loc = "center left"
            , fontsize = fontsize
            )
 
plt.tight_layout()
plt.savefig("benchmark.getRemoved_vs_setRemoved.runtime.ratio.png")

Visualization of the benchmark output ⛓

Benchmark moral ⛓

1. The procedures under the generic interface getRemoved are functions while the procedures under the generic interface setRemoved are subroutines.
   From the benchmark results, it appears that the functional interface performs slightly less efficiently than the subroutine interface, despite the two algorithms having the same implementation.
2. Note that this benchmark does not even include the cost of repeated reallcations, that is, the allocation of Removed happen only once in all tests.
3. Note that this benchmark considers the worst-case scenario where all elements of the input array match the input pattern and must be therefore, removed.

Test:

test_pm_arrayRemove

Bug:

Status: Unresolved
Source: Intel Classic Fortran Compiler ifort version 2021.2.0
Description: The Intel Classic Fortran Compiler ifort version 2021.2.0 has a bug for useing the following two modules simultaneously in the implementation of the procedures in this module,

use pm_arrayUnique, only: getUnique
use pm_arraySort, only: setSorted

The following is example error message from the Intel Classic Fortran Compiler ifort,

      pm_arrayRemove@routines@setRemoved_D1.inc.F90(196): error #6405: The same named entity from different modules and/or program units cannot be referenced.   [UNIQUE]
                      if (present(unique)) unique_def = unique
      ----------------------------^

Searching this error on the web points to the possibility that the internal representation of entities by Intel Classic Fortran Compiler ifort has a naming conflict.
Remedy (as of ParaMonte Library version 2.0.0): For now, the remedy was to isolate the use of one of the modules to exactly where it is needed, like,

block
    use pm_arrayUnique, only: getUnique
    InstanceNew = getUnique(InstanceNew(1:lenInstanceNew))
end block

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:

Fatemeh Bagheri, Wednesday 12:20 AM, October 13, 2021, Dallas, TX

Variable Documentation

MODULE_NAME

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

Definition at line 105 of file pm_arrayRemove.F90.