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milancurcicmilancurcic
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Merge pull request #144 from jvdp1/variance_dev
Addition of variance function in stdlib_experimental_stats
2 parents e12ce0f + 01e897c commit 7397e96

9 files changed

+930
-3
lines changed

‎src/CMakeLists.txt

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@@ -6,6 +6,7 @@ set(fppFiles
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stdlib_experimental_optval.fypp
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stdlib_experimental_stats.fypp
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stdlib_experimental_stats_mean.fypp
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stdlib_experimental_stats_var.fypp
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)
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‎src/Makefile.manual

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@@ -5,7 +5,8 @@ SRC = stdlib_experimental_ascii.f90 \
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stdlib_experimental_kinds.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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stdlib_experimental_stats_mean.f90 \
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stdlib_experimental_stats_var.f90
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LIB = libstdlib.a
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@@ -42,6 +43,11 @@ 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_var.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_io.f90: stdlib_experimental_io.fypp
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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
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stdlib_experimental_stats_var.f90: stdlib_experimental_stats_var.fypp

‎src/common.fypp

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@@ -97,6 +97,7 @@ ${prefix + joinstr.join([line.strip() for line in txt.split("\n")]) + suffix}$
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#:endif
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#:enddef
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#! Generates a routine name from a generic name, rank, type and kind
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#!
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#! Args:
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$:"{0}_{1}_{2}{3}_{2}{3}".format(gname, rank, type[0], kind) if suffix == '' else "{0}_{1}_{2}{3}_{4}".format(gname, rank, type[0], kind, suffix)
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#:enddef
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#! Generates an array rank suffix for subarrays reducing the dimension
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#!
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#! Args:
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#! rank (int): Rank of the original variable
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#! selectors (array): Dimension and name of the variable(s)
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#!
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#! Returns:
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#! Array rank suffix string enclosed in braces
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#!
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#! E.g.,
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#! select_subarray(5 , [(4, 'i'), (5, 'j')])}$
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#! -> (:, :, :, i, j)
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#!
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#:def select_subarray(rank, selectors)
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#:assert rank > 0
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#:set seldict = dict(selectors)
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#:call join_lines(joinstr=", ", prefix="(", suffix=")")
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#:for i in range(1, rank + 1)
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$:seldict.get(i, ":")
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#:endfor
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#:endcall
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#:enddef
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#:endmute

‎src/stdlib_experimental_stats.fypp

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@@ -7,7 +7,7 @@ module stdlib_experimental_stats
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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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public :: mean, var
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interface mean
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#:for k1, t1 in RC_KINDS_TYPES
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end interface mean
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interface var
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#:for k1, t1 in RC_KINDS_TYPES
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#:for rank in RANKS
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#:set RName = rname("var_all",rank, t1, k1)
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module function ${RName}$(x, mask) result(res)
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${t1}$, intent(in) :: x${ranksuffix(rank)}$
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logical, intent(in), optional :: mask
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real(${k1}$) :: res
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end function ${RName}$
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#:endfor
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#:endfor
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#:for k1, t1 in INT_KINDS_TYPES
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#:for rank in RANKS
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#:set RName = rname("var_all",rank, t1, k1, 'dp')
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module function ${RName}$(x, mask) result(res)
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${t1}$, intent(in) :: x${ranksuffix(rank)}$
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logical, intent(in), optional :: mask
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real(dp) :: res
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end function ${RName}$
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#:endfor
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#:endfor
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#:for k1, t1 in RC_KINDS_TYPES
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#:for rank in RANKS
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#:set RName = rname("var",rank, t1, k1)
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module function ${RName}$(x, dim, mask) result(res)
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${t1}$, intent(in) :: x${ranksuffix(rank)}$
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integer, intent(in) :: dim
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logical, intent(in), optional :: mask
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real(${k1}$) :: res${reduced_shape('x', rank, 'dim')}$
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end function ${RName}$
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#:endfor
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#:endfor
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#:for k1, t1 in INT_KINDS_TYPES
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#:for rank in RANKS
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#:set RName = rname("var",rank, t1, k1, 'dp')
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module function ${RName}$(x, dim, mask) result(res)
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${t1}$, intent(in) :: x${ranksuffix(rank)}$
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integer, intent(in) :: dim
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logical, intent(in), optional :: mask
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real(dp) :: res${reduced_shape('x', rank, 'dim')}$
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end function ${RName}$
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#:endfor
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#:endfor
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#:for k1, t1 in RC_KINDS_TYPES
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#:for rank in RANKS
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#:set RName = rname("var_mask_all",rank, t1, k1)
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module function ${RName}$(x, mask) result(res)
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${t1}$, intent(in) :: x${ranksuffix(rank)}$
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logical, intent(in) :: mask${ranksuffix(rank)}$
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real(${k1}$) :: res
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end function ${RName}$
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#:endfor
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#:endfor
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#:for k1, t1 in INT_KINDS_TYPES
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#:for rank in RANKS
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#:set RName = rname("var_mask_all",rank, t1, k1, 'dp')
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module function ${RName}$(x, mask) result(res)
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${t1}$, intent(in) :: x${ranksuffix(rank)}$
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logical, intent(in) :: mask${ranksuffix(rank)}$
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real(dp) :: res
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end function ${RName}$
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#:endfor
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#:endfor
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#:for k1, t1 in RC_KINDS_TYPES
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#:for rank in RANKS
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#:set RName = rname("var_mask",rank, t1, k1)
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module function ${RName}$(x, dim, mask) result(res)
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${t1}$, intent(in) :: x${ranksuffix(rank)}$
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integer, intent(in) :: dim
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logical, intent(in) :: mask${ranksuffix(rank)}$
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real(${k1}$) :: res${reduced_shape('x', rank, 'dim')}$
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end function ${RName}$
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#:endfor
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#:endfor
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#:for k1, t1 in INT_KINDS_TYPES
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#:for rank in RANKS
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#:set RName = rname("var_mask",rank, t1, k1, 'dp')
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module function ${RName}$(x, dim, mask) result(res)
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${t1}$, intent(in) :: x${ranksuffix(rank)}$
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integer, intent(in) :: dim
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logical, intent(in) :: mask${ranksuffix(rank)}$
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real(dp) :: res${reduced_shape('x', rank, 'dim')}$
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end function ${RName}$
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#:endfor
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#:endfor
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end interface var
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end module stdlib_experimental_stats

‎src/stdlib_experimental_stats.md

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## Implemented
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* `mean`
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* `var`
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## `mean` - mean of array elements
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reshape(x, [ 2, 3 ] ) > 3.) !returns [ NaN, 4.0, 5.5 ]
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end program demo_mean
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```
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## `var` - variance of array elements
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### Description
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Returns the variance of all the elements of `array`, or of the elements of `array` along dimension `dim` if provided, and if the corresponding element in `mask` is `true`.
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The variance is defined as the best unbiased estimator and is computed as:
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```
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var(x) = 1/(n-1) sum_i (array(i) - mean(array))^2
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```
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### Syntax
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`result = var(array [, mask])`
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`result = var(array, dim [, mask])`
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### Arguments
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`array`: Shall be an array of type `integer`, `real`, or `complex`.
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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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`mask` (optional): Shall be of type `logical` and either by a scalar or an array of the same shape as `array`.
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### Return value
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If `array` is of type `real` or `complex`, 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 variance 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 `ar
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ray` with dimension `dim` dropped is returned.
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If `mask` is specified, the result is the variance of all elements of `array` corresponding to `true` elements of `mask`. If every element of `mask` is `false`, the result is IEEE `NaN`.
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### Example
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```fortran
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program demo_var
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use stdlib_experimental_stats, only: var
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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 *, var(x) !returns 3.5
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print *, var( reshape(x, [ 2, 3 ] )) !returns 3.5
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print *, var( reshape(x, [ 2, 3 ] ), 1) !returns [0.5, 0.5, 0.5]
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print *, var( reshape(x, [ 2, 3 ] ), 1,&
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reshape(x, [ 2, 3 ] ) > 3.) !returns [0., NaN, 0.5]
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end program demo_var
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```
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