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Import StatsBase into Statistics #2
base: StatsBase2021
Are you sure you want to change the base?
Commits on Mar 29, 2014
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Commits on Mar 31, 2014
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eliminate StoredArray (fix #6212, #987); UniformScaling is no longer …
…an AbstractArray (#5810)
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Commits on Apr 1, 2014
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still not clear what to do with floating point in StepRange
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allow constructing StepRange by length
It turns out there are many cases that are drastically easier this way. Tests not passing yet, but getting there.
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Commits on Apr 8, 2014
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Make histrange us the extrema function
And add a simple test for hist()
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Commits on Apr 11, 2014
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Change @test_throws to only check for a single exception type
Also update test suite to follow suit
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Change syntax to @test_throws ExceptionType Expression
Also split out parseint loops in strings.jl to better separate out exception types
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Commits on Apr 16, 2014
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Commits on Apr 27, 2014
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Commits on May 12, 2014
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Commits on May 26, 2014
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Rename varzm_pairwise -> sumabs2_pairwise
Also some minor reorganization
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Commits on May 28, 2014
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Commits on May 29, 2014
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Tweaks to sum across dimensions
- Implement sum(fn, A, region) - Implement Base.sumabs across dimensions - Use pairwise summation/BLAS for sums across first dimension
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Commits on Jun 7, 2014
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Commits on Jun 9, 2014
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Commits on Jun 10, 2014
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Commits on Jun 20, 2014
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Commits on Jul 2, 2014
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Simplify implementation of centralize_sumabs2
Also fix a bounds violation when computing the variance of a vector with a single element
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Commits on Jul 3, 2014
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Commits on Aug 13, 2014
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Commits on Aug 21, 2014
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kshramt committed
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Commits on Sep 26, 2014
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Commits on Oct 6, 2014
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Commits on Oct 7, 2014
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Remove checknan option to median and update docs
Fixes #8598, closes #8605, ref #6820
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Commits on Oct 23, 2014
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Commits on Nov 17, 2014
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Document return type for middle(x)
The special cases give the same result as the general rule, but are faster. Fix the docs and explain the rule as regards the result type.
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Commits on Nov 25, 2014
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Commits on Dec 8, 2014
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Merge pull request #8077 from kshramt/kshramt/overflow
Avoid `Real` overflow in `middle`
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Commits on Jan 19, 2015
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Try and remove as many generic error() messages from base as possible
* throw more specific Exception types * make error messages more consistent * give more context for the error when possible * update tests
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Commits on Jan 27, 2015
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Export mapreducedim. Update documentation.
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Commits on Feb 1, 2015
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Commits on Feb 3, 2015
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Use stagedfunctions instead of @ngenerate and @nsplat
This commit tackles all files except multidimensional.jl
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Commits on Feb 9, 2015
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Merge branch 'master' into jcb/sanecat
Conflicts: base/LineEdit.jl base/abstractarray.jl base/array.jl base/dates/periods.jl base/inference.jl base/io.jl base/linalg/factorization.jl base/linalg/triangular.jl base/show.jl base/string.jl deps/libmojibake src/julia-parser.scm src/julia-syntax.scm src/uv_constants.h test/arrayops.jl test/blas.jl test/collections.jl test/combinatorics.jl test/core.jl test/dates/conversions.jl test/dates/ranges.jl test/hashing.jl test/linalg4.jl test/math.jl test/perf/sparse/perf.jl test/random.jl test/sorting.jl test/statistics.jl test/suitesparse.jl
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Commits on Feb 10, 2015
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Merge pull request #9884 from JuliaLang/anj/darrayops
Add mapreducedim for DArrays
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Commits on Feb 17, 2015
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Commits on Mar 8, 2015
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begin removing lowercase conversion functions (#1470)
not quite done with renaming [ci skip]
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Commits on Apr 19, 2015
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Change
i=1:length(A)
toi in eachindex(A)
This fixes performance problems for many SubArray operations
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Commits on Apr 20, 2015
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Rename stagedfunction → @generated function
This fixes the long-standing name "bug". Note that it only affects surface syntax. Internally, generated functions still use the old language (e.g., Expr(:stagedfunction, ...), isstaged, stagedcache, etc). This adds a temporary deprecation to the `stagedfunction` keyword -- the keyword should be entirely removed before the 0.4 release.
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Commits on May 1, 2015
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adds_license_headers [skip ci]
JuliaLang#11073 (comment) JuliaLang#11023 Related pullrequests are: JuliaLang#11079 JuliaLang#11084
peter1000 committedMay 1, 2015 Configuration menu - View commit details
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Commits on Jun 15, 2015
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Commits on Jul 6, 2015
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Test cases for mean handling NaN
Test cases for the behavior of #6486
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Commits on Jul 14, 2015
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Commits on Jul 30, 2015
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Commits on Jul 31, 2015
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Merge pull request #12379 from JuliaLang/ksh/statstests
Tests and a bugfix for statistics
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Commits on Oct 8, 2015
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Make cov and cor similar to mean and var by removing keyword arguments.
This fixes #13081 and the type instability that motivated that issue.
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Commits on Oct 9, 2015
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A few fixes of the deprecations of the keyword versions of cov and cor.
Also make sure that all methods are tested.
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Commits on Dec 16, 2015
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Commits on Apr 21, 2016
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Deprecate AndFun, OrFun, XorFun, AddFun, DotAddFun, SubFun, DotSubFun, MulFun, DotMulFun, RDivFun, DotRDivFun, LDivFun, IDivFun, DotIDivFun, ModFun, RemFun, DotRemFun, PowFun, MaxFun, MinFun, LessFun, MoreFun, DotLSFun, and DotRSFun. Rewrite specialization of BitArray map! to use function types and a helper type BitChunkFunctor for operations without a named function.
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Commits on May 25, 2016
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Fixes numerical accuracy issues in quantile.
Fixes issue JuliaStats/StatsBase.jl#164, and another when `p < eps()`.
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Replace deprecated Array(T..., dims...) with Array{T...}(dims...) in …
…/base/ (#16498) * Replace deprecated Array(T..., dims...) with Array{T...}(dims...) for arrays. * Replace deprecated Array(T..., dims...) with Array{T...}(dims...) in base/pkg/. * Replace deprecated Array(T..., dims...) with Array{T...}(dims...) in base/linalg/. * Replace deprecated Array(T..., dims...) with Array{T...}(dims...) in base/strings/. * Replace deprecated Array(T..., dims...) with Array{T...}(dims...) in base/unicode/. * Replace deprecated Array(T..., dims...) with Array{T...}(dims...) in base/grisu/. * Replace deprecated Array(T..., dims...) with Array{T...}(dims...) in base/fft/. * Replace deprecated Array(T..., dims...) with Array{T...}(dims...) in base/ for files starting b-e. * Replace deprecated Array(T..., dims...) with Array{T...}(dims...) in base/docs/. * Replace deprecated Array(T..., dims...) with Array{T...}(dims...) in base/ for files starting with f-i. * Replace deprecated Array(T..., dims...) with Array{T...}(dims...) in base/dSFMT.jl, base/Enums.jl, and base/LineEdit.jl. * Replace deprecated Array(T..., dims...) with Array{T...}(dims...) in base/ for files starting with l-m. * Replace deprecated Array(T..., dims...) with Array{T...}(dims...) in base/ for files starting with p-r. * Replace deprecated Array(T..., dims...) with Array{T...}(dims...) in base/ for files starting with s-t. * Replace deprecated Array(T..., dims...) with Array{T...}(dims...) in base/special/. * Additional changes from Array(T, dim) to Array{T}(dim). * Further changes. * fix constructors.rst
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Commits on May 26, 2016
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Merge pull request #16572 from JuliaLang/sb/quantile-acc
Fixes numerical accuracy issues in quantile.
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Commits on May 27, 2016
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deprecate histogram functionality (#16450)
* deprecate histogram functionality * move hist exports to deprecated.jl * remove hist from tests * remove hist and friends from docs
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Commits on Jun 7, 2016
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the external abi is to call var, the internal abi doesn' need to branch to alternative functions based on whether mean is given as zero that simply made the dispatch less straightforward to understand even though doing an exact comparison to 0 isn't generally reliable ref #6273, which initially introduced these functions as the public API, before changing them to be the internal implementation
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Commits on Jun 8, 2016
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RFC: Function argument to
mean
, akin tosum
(#16691)* Added a function argument to mean * Test function argument to mean * Fixed tests and function call in fallback method * Fixed test to address issue * Changed == to === in tests * Addressed type instability in fallback method * Removed extra function call * Document mean(f::Function, v) * Moved the docs into a docstring
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Merge pull request #16764 from JuliaLang/jn/notequal
change identity comparisons to use isequal
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Commits on Jun 12, 2016
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Commits on Jun 27, 2016
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Make
median
non-mutating on arrays.Due to a change in the behaviour of `mapslices` (#16260), `median(X,k)` would mutate the underlying array. Fixes #17153.
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Commits on Jun 28, 2016
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replace
@test_approx_eq
with ≈ (#17151)Also fix bug in hex2num, exposed due to ≈ not being broken like `@test_approx_eq`.
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Merge pull request #17154 from JuliaLang/sb/median-slice
Make `median` non-mutating on arrays.
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Commits on Jul 4, 2016
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Commits on Jul 17, 2016
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Avoid that cor(x,x) != 1 by trading a sqrt for two / and use clamp to
avoid that cor(x,y) > 1. Make sure that the loop vectorizes Convert corzm into corm to avoid allocation of tempraries.
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Add test for Issue #17153 and PR #17154 (#17164)
* Add test for Issue #17153 and PR #17154 * Fix whitespaces
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Commits on Jul 19, 2016
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Merge pull request #17228 from JuliaLang/teh/safe_size_length
Make unvetted `size` throw an error for arrays with non-1 indexing
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Commits on Jul 23, 2016
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Commits on Jul 25, 2016
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Merge pull request #17464 from JuliaLang/anj/covzm
Avoid that cor(x,x) != 1...
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Commits on Aug 5, 2016
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Operations between Float16 and Integer now return Float16
Previously we would promote to Float32 leading to subtle type instabilities when Float16 was used for computations instead of a pure data-storage format. By defining `promote_type(Float16, Integer) = Float16` this incurs an overhead by first converting the `Integer` argument to `Float16` and then `Float32` for mathematical operations, that are performed in Float32.
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Move math docs out of HelpDB, more examples, fix typos (#17791)
* Move math docs out of HelpDB, more examples, fix typos Found a series of typos in `cov` and friends. Added more notes about `NaN` and Julia. Made the function signatures reflect what's actually in the code. More examples for quite a few functions. * Move quadgk docs out, update formatting * Moved special functions out of HelpDB, insert some links * Updated docs for some array ops as well * Updated in response to feedback Removed calls to `rand` in doctests. Made examples better. Cleaned up function signatures.
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Commits on Aug 6, 2016
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Merge pull request #17297 from JuliaGPU/vc/fp16
Operations between Float16 and Integer now return Float16
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Commits on Sep 3, 2016
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Commits on Sep 18, 2016
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Generalize broadcast to handle tuples and scalars (#16986)
* Generalized broadcast arguments * Naming fixes * Add some tests * News and documentation
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RFC:add functionality for quantiles of vectors of infinity (#19574)
* add functionality for quantiles of vectors of infinity * fixed spacing
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Quantiles of vector of infinities (#19659)
Use naive interpolation formula in quantile when either endpoint of the interval is infinite, giving correct results when endpoints are infinite or NaN.
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Move the deprecation of midpoints to 0.6 section, (#20058)
and actually deprecate it - this was moved to deprecated.jl in #16450, but not actually deprecated
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WIP: add oneunit(x) for dimensionful version of one(x) (#20268)
add oneunit(x) for dimensionful version of one(x), and change one -> oneunit where appropriate.
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* grabbag of doctests * fix doctest block * highlight ix * some fixups * fix noop thingy
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RFC: tests for dimensional correctness of Base (#20484)
* tests for dimensional correctness of Base * missing promotion for colon(start, step, stop) * fix sqrtm for dimensionful * stats dimensionful tests, fixed units of momenttype
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Make cor work again for complex input (#21205)
Also fix inconsistency in `cov` of vectors. Fixes #21093
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Merge pull request #21472 from JuliaLang/tk/https-links
Change all julialang.org links to https
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Merge pull request #20921 from JuliaLang/sjk/quantile
Allow quantile function to accept tuples
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Make
cov
's corrected argument a keyword argument and cleanup docstr……ings for `cov` and `cor` (#21709) * Make cov()'s corrected argument a keyword argument and cleanup docstrings For consistency with var and std. Also remove methods which are no longer needed now that deprecations have been removed. Add types to signatures in docstrings. * Cleanup unneeded cor() methods and docstrings Remove methods which are no longer needed now that deprecations have been removed. Add types to signatures in docstrings.
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Remove momenttype and use reduction initialization infrastructure (#2…
…2937) for determining the return type. Adjust return type determination in _quantile Fixes #22901
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Add tests for mean and var on arrays with unitful elements. (#22956)
Fix var along a dimension for arrays with unitful elements.
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Fix promotion in cov and mean to handle integer and rational matrices…
… (#23285) Fixes #8080
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Rename select* functions to partialsort*
The new name is more explicit, more consistent with sort and with one of the most commonly used names for this operation (from the C++ stdlib). It also does not conflict with other meanings e.g. for POSIX sockets and SQL.
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Rename Range to AbstractRange (#23570)
* Rename Range to AbstractRange * Change "a" to "an" before AbstractRange * Update syntax files under contrib/ Rename Range to AbstractRange, and Range1 to UnitRange (which should have been done before). * Add deprecation and NEWS entry * Fix incorrect replacements * Address review comments
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Deprecate
+
/-
methods forarray+scalar
etc (#22932)The elementwise definition is incorrect for linear algebra.
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Make var and std work for Vector{Vector{T}} (#23897)
* Make var and std work for Vector{Vector{T}} by removing Number restriction from some signatures as well as using broadcasting in std. Fixes #23884 * Make cov work for Vector{Vector}
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Rewrite A[ct]_(mul|ldiv|rdiv)_B[ct][!] calls in base/statistics.jl as…
… *, /, \, mul!, ldiv!, or rdiv!.
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Merge pull request #24969 from Sacha0/lazyjazz
[WIP] lazier, less-jazzy linalg internals
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Andy Ferris committed
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Replace Nullable{T} with Union{T, Void} or Union{Some{T}, Void} (#23642)
Also add coalesce() function to return first non-nothing value and unwrap Some objects. Use the notnothing() function internally where it makes sense to assert that the result is different from nothing. Use custom MaybeValue wrapper for ProductIterator to work around a performance regression due to type instability (information about whether a value is present or not is carried separately).
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Make CartesianRange an AbstractArray and deprecate sub2ind and ind2su…
…b (#25113) * Make CartesianRange an AbstractArray and deprecate sub2ind and ind2sub * Rename CartesianRange->CartesianIndices
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rename some copy! methods to copyto! (#24808)
When the deprecation gets lifted, they will be re-enabled with a new meaning.
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make
using A.B
only for modules,using A: B
only for single bindi……ngs (#25306) part of #8000
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Correct return type for
std
along region (#25304)* Correct return type for std along region * Use isa instead of typeof
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Merge pull request #25450 from Sacha0/decollect
presently possible rewrites for potential collect deprecation
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Pkg3-style code loading, DEPOT_PATH, tests
Developed together with vtjnash
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Make mean() fallback method use the same type as sum() for accumulation
This prevents overflow for small types, and makes it consistent with mean() methods for AbstractArray.
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update doc string syntax (#25938)
- disallow extra lines between a docstring and the documented object - parse an extra expression after a newline in calls to `@doc` - deprecate special parsing of `doc" "` - deprecate `->` for doc strings
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Fix std(::AbstractArray{<:AbstractFloat}) (#26186)
Issue #25989 accidentally broke `std(rand(10))`. This fixes it.
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rename uninitialized to undef (#26316)
* uninit is dead, long live undef * UnInitialized -> UndefInitializer + show method * also deprecate Uninitialized
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Customizable lazy fused broadcasting in pure Julia
This patch represents the combined efforts of four individuals, over 60 commits, and an iterated design over (at least) three pull requests that spanned nearly an entire year (closes #22063, #23692, #25377 by superceding them). This introduces a pure Julia data structure that represents a fused broadcast expression. For example, the expression `2 .* (x .+ 1)` lowers to: ```julia julia> Meta.@lower 2 .* (x .+ 1) :($(Expr(:thunk, CodeInfo(:(begin Core.SSAValue(0) = (Base.getproperty)(Base.Broadcast, :materialize) Core.SSAValue(1) = (Base.getproperty)(Base.Broadcast, :make) Core.SSAValue(2) = (Base.getproperty)(Base.Broadcast, :make) Core.SSAValue(3) = (Core.SSAValue(2))(+, x, 1) Core.SSAValue(4) = (Core.SSAValue(1))(*, 2, Core.SSAValue(3)) Core.SSAValue(5) = (Core.SSAValue(0))(Core.SSAValue(4)) return Core.SSAValue(5) end))))) ``` Or, slightly more readably as: ```julia using .Broadcast: materialize, make materialize(make(*, 2, make(+, x, 1))) ``` The `Broadcast.make` function serves two purposes. Its primary purpose is to construct the `Broadcast.Broadcasted` objects that hold onto the function, the tuple of arguments (potentially including nested `Broadcasted` arguments), and sometimes a set of `axes` to include knowledge of the outer shape. The secondary purpose, however, is to allow an "out" for objects that _don't_ want to participate in fusion. For example, if `x` is a range in the above `2 .* (x .+ 1)` expression, it needn't allocate an array and operate elementwise — it can just compute and return a new range. Thus custom structures are able to specialize `Broadcast.make(f, args...)` just as they'd specialize on `f` normally to return an immediate result. `Broadcast.materialize` is identity for everything _except_ `Broadcasted` objects for which it allocates an appropriate result and computes the broadcast. It does two things: it `initialize`s the outermost `Broadcasted` object to compute its axes and then `copy`s it. Similarly, an in-place fused broadcast like `y .= 2 .* (x .+ 1)` uses the exact same expression tree to compute the right-hand side of the expression as above, and then uses `materialize!(y, make(*, 2, make(+, x, 1)))` to `instantiate` the `Broadcasted` expression tree and then `copyto!` it into the given destination. All-together, this forms a complete API for custom types to extend and customize the behavior of broadcast (fixes #22060). It uses the existing `BroadcastStyle`s throughout to simplify dispatch on many arguments: * Custom types can opt-out of broadcast fusion by specializing `Broadcast.make(f, args...)` or `Broadcast.make(::BroadcastStyle, f, args...)`. * The `Broadcasted` object computes and stores the type of the combined `BroadcastStyle` of its arguments as its first type parameter, allowing for easy dispatch and specialization. * Custom Broadcast storage is still allocated via `broadcast_similar`, however instead of passing just a function as a first argument, the entire `Broadcasted` object is passed as a final argument. This potentially allows for much more runtime specialization dependent upon the exact expression given. * Custom broadcast implmentations for a `CustomStyle` are defined by specializing `copy(bc::Broadcasted{CustomStyle})` or `copyto!(dest::AbstractArray, bc::Broadcasted{CustomStyle})`. * Fallback broadcast specializations for a given output object of type `Dest` (for the `DefaultArrayStyle` or another such style that hasn't implemented assignments into such an object) are defined by specializing `copyto(dest::Dest, bc::Broadcasted{Nothing})`. As it fully supports range broadcasting, this now deprecates `(1:5) + 2` to `.+`, just as had been done for all `AbstractArray`s in general. As a first-mover proof of concept, LinearAlgebra uses this new system to improve broadcasting over structured arrays. Before, broadcasting over a structured matrix would result in a sparse array. Now, broadcasting over a structured matrix will _either_ return an appropriately structured matrix _or_ a dense array. This does incur a type instability (in the form of a discriminated union) in some situations, but thanks to type-based introspection of the `Broadcasted` wrapper commonly used functions can be special cased to be type stable. For example: ```julia julia> f(d) = round.(Int, d) f (generic function with 1 method) julia> @inferred f(Diagonal(rand(3))) 3×3 Diagonal{Int64,Array{Int64,1}}: 0 ⋅ ⋅ ⋅ 0 ⋅ ⋅ ⋅ 1 julia> @inferred Diagonal(rand(3)) .* 3 ERROR: return type Diagonal{Float64,Array{Float64,1}} does not match inferred return type Union{Array{Float64,2}, Diagonal{Float64,Array{Float64,1}}} Stacktrace: [1] error(::String) at ./error.jl:33 [2] top-level scope julia> @inferred Diagonal(1:4) .+ Bidiagonal(rand(4), rand(3), 'U') .* Tridiagonal(1:3, 1:4, 1:3) 4×4 Tridiagonal{Float64,Array{Float64,1}}: 1.30771 0.838589 ⋅ ⋅ 0.0 3.89109 0.0459757 ⋅ ⋅ 0.0 4.48033 2.51508 ⋅ ⋅ 0.0 6.23739 ``` In addition to the issues referenced above, it fixes: * Fixes #19313, #22053, #23445, and #24586: Literals are no longer treated specially in a fused broadcast; they're just arguments in a `Broadcasted` object like everything else. * Fixes #21094: Since broadcasting is now represented by a pure Julia datastructure it can be created within `@generated` functions and serialized. * Fixes #26097: The fallback destination-array specialization method of `copyto!` is specifically implemented as `Broadcasted{Nothing}` and will not be confused by `nothing` arguments. * Fixes the broadcast-specific element of #25499: The default base broadcast implementation no longer depends upon `Base._return_type` to allocate its array (except in the empty or concretely-type cases). Note that the sparse implementation (#19595) is still dependent upon inference and is _not_ fixed. * Fixes #25340: Functions are treated like normal values just like arguments and only evaluated once. * Fixes #22255, and is performant with 12+ fused broadcasts. Okay, that one was fixed on master already, but this fixes it now, too. * Fixes #25521. * The performance of this patch has been thoroughly tested through its iterative development process in #25377. There remain [two classes of performance regressions](#25377) that Nanosoldier flagged. * #25691: Propagation of constant literals sill lose their constant-ness upon going through the broadcast machinery. I believe quite a large number of functions would need to be marked as `@pure` to support this -- including functions that are intended to be specialized. (For bookkeeping, this is the squashed version of the [teh-jn/lazydotfuse](JuliaLang/julia#25377) branch as of a1d4e7ec9756ada74fb48f2c514615b9d981cf5c. Squashed and separated out to make it easier to review and commit) Co-authored-by: Tim Holy <tim.holy@gmail.com> Co-authored-by: Jameson Nash <vtjnash@gmail.com> Co-authored-by: Andrew Keller <ajkeller34@users.noreply.github.com>
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Deprecate linearindices in favor of LinearIndices (#26775)
* Deprecate linearindices in favor of LinearIndices LinearIndices is strictly more powerful than linearindices: these two functions return arrays holding the same elements, but the former also preserves the shape and indices of the original array. Also improve docstrings. * Add efficient LinearIndices iteration * Work around invalidation and minor LinearIndices simplifications * Alternative fix using eachindex + adjust failing test * Fix accumulate/cumsum performance regression by adding getindex(::LinearIndices, ::AbstractRange) Plus two small fixes.
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This changes the iteration protocol from `start`/`next`/`done` to `iterate`. The new lowering of a for loop is as follows: ``` for x in itr ... end ``` becomes ``` next = iterate(itr) while next !== nothing x, state = next::Tuple{Any, Any} ... next = iterate(itr, state) end ``` The semantics are as apparent from the above lowering. `iterate` returns either `nothing` or a tuple of value and state. The state is passed to any subsequent operation. The first iteration is indicated, by not passing the second, state argument to the `iterate` method. Adaptors in both directions are provided to keep the legacy iteration protocol working for now. However, performance of the legacy iteration protocol will be severely pessimized. As an optional add-on for mutable iterators, a new `isdone` function is provided. This function is intended as an O(1) approximate query for iterator completion, where such a calculation is possible without mutation and/or is significantly faster than attempting to obtain the element itself. The function makes use of 3-value logic. `missing` is always an acceptable answer, in which case the caller should go ahead and attempt the iteration to obtain a definite result. If the result is not `missing`, it must be exact (i.e. if true, the next call to iterate must return `nothing`, if false it must not return nothing).
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move cor, cov, std, stdm, var, varm and linreg to StatsBase (#27152)
fix JuliaLang/julia#25571 (comment) (included in JuliaStats/StatsBase.jl#379) fix #23769 (included in JuliaStats/StatsBase.jl#379) fix #27140
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use offset axes for offset arrays (#27038)
* Better support for non-Int axes * Fix offset unique test: This is an interesting case: it just falls out that unique across dimensions now preserves offset-ness of the non-uniqued dimensions * Simplify similar(::Type{T}, ...) and require T<:AbstractArray for the default definition * Use the same extension system for `reshape` as `similar`. * Fixup Offset similar(::Type, ...) definition to match
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comparison against nothing should use
egal
Avoids requiring dynamic dispatch, and especially in the compiler, and avoids compiling numerous copies of this comparison method
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Revert "move cor, cov, std, stdm, var, varm and linreg to StatsBase (…
…#27152)" This reverts commit 746d08fdfe65888ca8a30e8cfa3ef2b439251d22.
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move base/statistics.jl to Statistics stdlib
fix #27374
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Fix handling of missing values in median and quantile and improve docs
Ensure we always return missing or throw an error in the presence of missing values Support skipmissing(v) by supporting any iterator and calling collect on it, which makes median and quantile consistent with mean and sum. Improve docstrings for stats functions by adding examples and making them more consistent.
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Test: unexport guardsrand (#27942)
This is mostly superseded by the new behavior of at-testset, which reinitializes the state of the GLOBAL_RNG.
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Rename realmin/max -> floatmin/max (#28302)
The names `realmin`/`realmax`, don't make too much sense in our terminology. These function are floating-point property queries, querying in particular the largest/smallest positive normalized floating point value. `posnormfloatmin` isn't a great name however, so simply `floatmin` was suggested. This has the advantage that it's suggestive of the fact that it's a floating point type query, even if it's not quite the minimum floating point value or even the minimum positive floating point value, but that's what docs are for. In any case, they're better than real. We have a good number of subtypes of `Real` for which these functions make no sense. In libc, these are called FLT_MIN/FLT_MAX or DBL_MIN/DBL_MAX.
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Remove many stdlib deprecations (#28450)
* Remove Dates deprecations. * Remove Base64 deprecations. * Remove CRC32c deprecations. * Remove DelimitedFiles deprecations. * Remove FileWatching deprecations. * Remove InteractiveUtils deprecations. * Remove Libdl deprecations. * Remove Markdown deprecations. * Remove Mmap deprecations. * Remove Printf deprecations. * Remove Profile deprecations. * Remove REPL deprecations. * Remove Serialization deprecations. * Remove SharedArrays deprecations. * Remove Sockets deprecations. * Remove Statistics deprecations.
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fix doc-string references to bit-rotted variables x(->v) and v(->itr)…
… in var, varm, std, stdm, & quantiles
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Fix quantile doctest formatting (#29573)
An errant space was causing the online documentation to render the docstring incorrectly: https://docs.julialang.org/en/v1/stdlib/Statistics/index.html#Statistics.quantile
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Compat admonitions and NEWS for Julia 1.1 (#30230)
Addition of NEWS and compat admonitions for important changes between Julia 1.0 and 1.1, including: - Custom .css-style for compat admonitions. - Information about compat annotations to CONTRIBUTING.md. - NEWS.md entry for PRs #30090, #30035, #30022, #29978, #29969, #29858, #29845, #29754, #29638, #29636, #29615, #29600, #29506, #29469, #29316, #29259, #29178, #29153, #29033, #28902, #28761, #28745, #28708, #28696, #29997, #28790, #29092, #29108, #29782 - Compat annotation for PRs #30090, #30013, #29978, #29890, #29858, #29827, #29754, #29679, #29636, #29623, #29600, #29440, #29316, #29259, #29178, #29157, #29153, #29033, #28902, #28878, #28761, #28708, #28156, #29733, #29670, #29997, #28790, #29092, #29108, #29782, #25278 - Documentation for broadcasting CartesianIndices (#30230). - Documentation for Base.julia_cmd(). - Documentation for colon constructor of CartesianIndices (#29440). - Documentation for ^(::Matrix, ::Number) and ^(::Number, ::Matrix). - Run NEWS-update.jl. Co-authored-by: Morten Piibeleht <morten.piibeleht@gmail.com> Co-authored-by: Fredrik Ekre <ekrefredrik@gmail.com>
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Add missing test dependency on Random to Statistics (#32383)
Statistics uses Random in its tests but doesn't declare it as a test dependency in its Project.toml.
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[Statistics] fix type determination in corm (#32271)
* [Statistics] fix type determination in corm * remove obsolete typeof * use first element(s) for type initialization * add test for inhomogeneous data and for overflow * fix test with NaN
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Add docstest=only option to docs/make.jl (#32376)
* Bump Documenter to 0.23.1 * Documenter now requires docstring doctests to have their own metadata in the corresponding module. Remove all the now redundant at-meta blocks from the standard library .md files and add the necessary module-level metadata in make.jl
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Refactoring: Use accessor methods when manipulating sparse matrices/v…
…ectors (#32953) * Use accessor methods when touching SparseMatrixCSC
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Add missing shape checks for the means argument to var[m] and std[m] (#…
…32) We use `@inbounds`, but the shape of the `means` argument was never checked for the general `AbstractArray` method. With an incorrect shape, invalid results or crashes would happen. To avoid breaking existing code which was working, allow trailing singleton dimensions. Sync the `SparseMatrixCSV` method, which makes it less strict.
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Force specialization for _mean's dims argument (#38)
Ensures we get the specialization we want when passing `dims=(:)`. Fixes #37.
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Fix bug in quantile for case of 1 element vector (#42)
* Fix bug in quantile for case of 1 element vector * add tests * make the implementation type-stable * Remove ) Co-authored-by: Milan Bouchet-Valat <nalimilan@club.fr>
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relax type definition of middle (#28)
* relax type definition of middle this adds support for computing the median of unitful types, see PainterQubits/Unitful.jl#202 * updates docs and add tests for middle on non-reals
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stdlib modules need to use a custom rule, otherwise the code with which Julia was built is used.
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change real to float in cor of a single collection (#61)
As in `cor` we get square root I think it is safe to assume that the result should be floating point. An example of current surprising behavior: ``` julia> cor([im]) true ```
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Fix NaN and missing detection in quantile() (#72)
When `sort=false`, we only partially sort the input, so `NaN`/`missing` is not guaranteed to be in the last position. Also avoid throwing errors for non-`Number` types, for which `isnan` may not be defined.
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Fix detection of NaN in median() (#73)
There is no reliable way to know only from the array eltype whether entries support `isnan` or not. Better leave to the compiler to optimize out the `isa Number` check when possible.
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