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addition of stdlib_experimental_stats mean
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‎.github/workflows/CI.yml

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@@ -39,6 +39,9 @@ jobs:
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if: contains(matrix.os, 'ubuntu')
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run: ci/install_cmake.sh
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- name: Install fypp
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run: pip install --upgrade fypp
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- name: Install GFortran Linux
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if: contains( matrix.os, 'ubuntu')
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run: |

‎CMakeLists.txt

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@@ -15,6 +15,7 @@ endif()
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include(CheckFortranSourceCompiles)
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include(CheckFortranSourceRuns)
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check_fortran_source_compiles("error stop i; end" f18errorstop SRC_EXT f90)
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check_fortran_source_compiles("real, allocatable :: array(:, :, :, :, :, :, :, :, :, :); end" f03rank SRC_EXT f90)
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check_fortran_source_runs("use, intrinsic :: iso_fortran_env, only : real128; real(real128) :: x; x = x+1; end" f03real128)
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add_subdirectory(src)

‎Makefile.manual

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FC = gfortran
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FFLAGS = -Wall -Wextra -Wimplicit-interface -fPIC -g -fcheck=all
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FYPPFLAGS=
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export FC
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export FFLAGS
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export FYPPFLAGS
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.PHONY: all clean test
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‎src/CMakeLists.txt

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### Pre-process: .fpp -> .f90 via Fypp
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# Create a list of the files to be preprocessed
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set(fppFiles
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stdlib_experimental_stats.fypp
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stdlib_experimental_stats_mean.fypp
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)
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# Pre-process
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foreach(infileName IN LISTS fppFiles)
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# Generate output file name
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string(REGEX REPLACE ".fypp\$" ".f90" outfileName "${infileName}")
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# Create the full path for the new file
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set(outfile "${CMAKE_CURRENT_BINARY_DIR}/${outfileName}")
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# Generate input file name
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set(infile "${CMAKE_CURRENT_SOURCE_DIR}/${infileName}")
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# Custom command to do the processing
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if(f03rank)
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add_custom_command(
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OUTPUT "${outfile}"
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COMMAND fypp "${infile}" "${outfile}"
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MAIN_DEPENDENCY "${infile}"
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VERBATIM)
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else()
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add_custom_command(
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OUTPUT "${outfile}"
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COMMAND fypp -DVERSION90 "${infile}" "${outfile}"
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MAIN_DEPENDENCY "${infile}"
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VERBATIM)
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endif()
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# Finally add output file to a list
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set(outFiles ${outFiles} "${outfile}")
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endforeach(infileName)
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set(SRC
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stdlib_experimental_ascii.f90
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stdlib_experimental_io.f90
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stdlib_experimental_error.f90
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stdlib_experimental_kinds.f90
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stdlib_experimental_optval.f90
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stdlib_experimental_system.F90
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${outFiles}
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)
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add_library(fortran_stdlib ${SRC})

‎src/Makefile.manual

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@@ -3,7 +3,9 @@ SRC = stdlib_experimental_ascii.f90 \
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stdlib_experimental_io.f90 \
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stdlib_experimental_optval.f90 \
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stdlib_experimental_kinds.f90 \
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f18estop.f90
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f18estop.f90 \
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stdlib_experimental_stats.f90 \
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stdlib_experimental_stats_mean.f90
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LIB = libstdlib.a
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@@ -26,6 +28,8 @@ clean:
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%.o: %.f90
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$(FC) $(FFLAGS) -c $<
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%.f90: %.fypp
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fypp $(FYPPFLAGS) $< $@
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# Fortran module dependencies
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f18estop.o: stdlib_experimental_error.o
@@ -34,3 +38,9 @@ stdlib_experimental_io.o: \
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stdlib_experimental_optval.o \
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stdlib_experimental_kinds.o
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stdlib_experimental_optval.o: stdlib_experimental_kinds.o
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stdlib_experimental_stats_mean.o: \
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stdlib_experimental_optval.o \
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stdlib_experimental_kinds.o \
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stdlib_experimental_stats.o
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stdlib_experimental_stats.f90: stdlib_experimental_stats.fypp
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stdlib_experimental_stats_mean.f90: stdlib_experimental_stats_mean.fypp

‎src/stdlib_experimental_stats.fypp

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module stdlib_experimental_stats
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#:set VERSION90 = defined('VERSION90')
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#:set REALKINDS = ["sp", "dp", "qp"]
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#:set INTKINDS = ["int8", "int16", "int32", "int64"]
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#:set REALTYPES = ["real({})".format(k) for k in REALKINDS]
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#:set INTTYPES = ["integer({})".format(k) for k in INTKINDS]
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#:set iktr = list(zip(range(len(REALKINDS)), REALKINDS, REALTYPES))
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#:set ikti = list(zip(range(len(INTKINDS)), INTKINDS, INTTYPES))
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use stdlib_experimental_kinds, only: sp, dp, qp, &
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int8, int16, int32, int64
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implicit none
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private
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! Public API
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public :: mean
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interface mean
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#:for i1, k1, t1 in iktr
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module function mean_1_${k1}$_${k1}$(x) result(res)
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${t1}$, intent(in) :: x(:)
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${t1}$ :: res
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end function mean_1_${k1}$_${k1}$
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#:endfor
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#:for i1, k1, t1 in ikti
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module function mean_1_${k1}$_dp(x) result(res)
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${t1}$, intent(in) :: x(:)
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real(dp) :: res
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end function mean_1_${k1}$_dp
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#:endfor
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#:for i1, k1, t1 in iktr
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module function mean_2_all_${k1}$_${k1}$(x) result(res)
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${t1}$, intent(in) :: x(:,:)
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${t1}$ :: res
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end function mean_2_all_${k1}$_${k1}$
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#:endfor
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#:for i1, k1, t1 in ikti
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module function mean_2_all_${k1}$_dp(x) result(res)
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${t1}$, intent(in) :: x(:,:)
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real(dp) :: res
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end function mean_2_all_${k1}$_dp
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#:endfor
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#:for i1, k1, t1 in iktr
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module function mean_2_${k1}$_${k1}$(x, dim) result(res)
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${t1}$, intent(in) :: x(:,:)
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integer, intent(in) :: dim
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${t1}$ :: res(size(x)/size(x, dim))
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end function mean_2_${k1}$_${k1}$
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#:endfor
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#:for i1, k1, t1 in ikti
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module function mean_2_${k1}$_dp(x, dim) result(res)
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${t1}$, intent(in) :: x(:,:)
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integer, intent(in) :: dim
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real(dp) :: res(size(x)/size(x, dim))
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end function mean_2_${k1}$_dp
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#:endfor
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#:def ranksuffix(rank)
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#{if rank > 0}#(${":" + ",:" * (rank - 1)}$)#{endif}#
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#:enddef
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#:if VERSION90
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#:set ranks = range(3,8)
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#:else
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#:set ranks = range(3,16)
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#:endif
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#:for i1, k1, t1 in iktr
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#:for rank in ranks
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module function mean_${rank}$_all_${k1}$_${k1}$(x) result(res)
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${t1}$, intent(in) :: x${ranksuffix(rank)}$
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${t1}$ :: res
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end function mean_${rank}$_all_${k1}$_${k1}$
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#:endfor
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#:endfor
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#:for i1, k1, t1 in ikti
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#:for rank in ranks
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module function mean_${rank}$_all_${k1}$_dp(x) result(res)
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${t1}$, intent(in) :: x${ranksuffix(rank)}$
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real(dp) :: res
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end function mean_${rank}$_all_${k1}$_dp
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#:endfor
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#:endfor
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#:for i1, k1, t1 in iktr
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#:for rank in ranks
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module function mean_${rank}$_${k1}$_${k1}$(x, dim) result(res)
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${t1}$, intent(in) :: x${ranksuffix(rank)}$
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integer, intent(in) :: dim
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${t1}$ :: res( &
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#:for imerge in range(1,rank-1)
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merge(size(x,${imerge}$),size(x,${imerge + 1}$),mask = ${imerge}$ < dim ), &
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#:endfor
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merge(size(x,${rank-1}$),size(x,${rank}$),mask = ${rank-1}$ < dim ) )
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end function mean_${rank}$_${k1}$_${k1}$
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#:endfor
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#:endfor
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#:for i1, k1, t1 in ikti
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#:for rank in ranks
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module function mean_${rank}$_${k1}$_dp(x, dim) result(res)
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${t1}$, intent(in) :: x${ranksuffix(rank)}$
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integer, intent(in) :: dim
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real(dp) :: res( &
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#:for imerge in range(1,rank-1)
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merge(size(x,${imerge}$),size(x,${imerge + 1}$),mask = ${imerge}$ < dim ), &
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#:endfor
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merge(size(x,${rank-1}$),size(x,${rank}$),mask = ${rank-1}$ < dim ) )
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end function mean_${rank}$_${k1}$_dp
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#:endfor
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#:endfor
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end interface
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end module

‎src/stdlib_experimental_stats.md

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# Descriptive statistics
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## Implemented
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* `mean`
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## `mean` - mean of array elements
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### Description
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Returns the mean of all the elements of `array`, or of the elements of `array` along dimension `dim` if provided.
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### Syntax
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`result = mean(array)`
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`result = mean(array, dim)`
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### Arguments
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`array`: Shall be an array of type `integer`, or `real`.
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`dim`: Shall be a scalar of type `integer` with a value in the range from 1 to n, where n is the rank of `array`.
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### Return value
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If `array` is of type `real`, the result is of the same type as `array`.
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If `array` is of type `integer`, the result is of type `double precision`.
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If `dim` is absent, a scalar with the mean of all elements in `array` is returned. Otherwise, an array of rank n-1, where n equals the rank of `array`, and a shape similar to that of `array` with dimension `dim` dropped is returned.
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### Example
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```fortran
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program test
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use stdlib_experimental_stats, only: mean
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implicit none
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real :: x(1:6) = [ 1., 2., 3., 4., 5., 6. ]
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print *, mean(x) !returns 21.
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print *, mean( reshape(x, [ 2, 3 ] )) !returns 21.
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print *, mean( reshape(x, [ 2, 3 ] ), 1) !returns [ 3., 7., 11. ]
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end program
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```

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