| Commit message (Collapse) | Author | Age | Files | Lines |
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Change 'ableit' to 'albeit'.
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* fix bug in doAssertRaises when exception==Exception
* add testcase for doAssertRaises
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* as instructed in #2353, provides a short description why
there are no specialized procs for seq[Rune]
* adds several examples to better explain what some functions do
* small fixes (double backticks, add missing dots, etc.)
* use `rune` instead of "unicode characer"
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(these tests are also covered by the other CIs)
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* Deprecate gc v2
* warnDeprecated now has custom messages
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* fixes #10148
* fix a typo
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* fix off by 1 error in `col` shown by toFileLineCol
* fix test failures
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* Resolve things raised in https://github.com/nim-lang/Nim/issues/10081 ?
CDF is a standard ident in all things related to random numbers/sampling,
and full words "cumulativeDistributionFunction" would be silly long, in
this case, IMO. We use lowercase `cdf` to make it not look like a type,
remove all looping from `sample` letting callers do it. Besides just
side-stepping any `sampleSize` name choice, callers may want to filter
out samples anyway which this makes slightly simpler.
Also add two variants of `cumsum`, value return and in-place update
distinguished by the var-ness of the first argument. Add tests for
`int` and `float` for both `cumsum` and the new `sample`. (The sample
tests exercise the value return mode of `cumsum`.)
Functionality pre-this-PR `sample(a, w)` is now the almost as simple
`for i in 0..<n: sample(a, w.cumsum)`, but this new code factoring is
almost surely better. The statistical tests pass, as before.
* Address Araq comment in https://github.com/nim-lang/Nim/pull/10084
We can always add in some `var` version later if desired to save
memory, but this change now at least firms up the `sample` interface.
* Rename `cumsum` -> `cumsummed` to honor NEP1 style. Re-instate `cumsum` as
the in-place transformation. Test both in `tests/stdlib/tmath.nim` and use
`cumsummed` in the example code for sample since that's a simpler example.
* Fix requests from https://github.com/nim-lang/Nim/pull/10084 :
example in lib/pure/math.nim and comment whitespace in lib/pure/random.nim
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expressions. (#9934)
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deprecated or the whole enum type (#10135)
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* fixes #9798
* Change order of write modules
* Move datInit calls ahead of initStackBottom
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* Show deprecation warning for fields of a deprecated enum
* Add test
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* {.deprecated.} pragma is now supported for enum fields
* Add tests
* Simplify code
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(#10131)
* fix typetraits.`$` regression https://github.com/c-blake/cligen/issues/84
* add test
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* Move typetraits.`$` to system. Fixes #5827.
* revive PR; adjust code to make sure everything works and add tests
* fix tests/concepts/tstackconcept.nim
* address comments
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* Give deprecation warning when type pragmas do not follow the type name
* pragma before generic parameter list in type definition is now deprecated
* Update changelog
* Fix bug where deprecated warning was being shown even though no generic param list was present
* Fix bug
* Use errGenerated
* Best attempt at writing the grammar
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As of hrev52662, TLS support in Haiku is usable again. This has since
been backported to R1/Beta1, so we can flip the switch upstream.
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Fixes #9999.
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* nimsuggest: prevent out-of-bound access
* fixes nim-lang/nimsuggest#76
* undo tester changes
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(#10072)
* Add the ability to sample elements from an openArray according to a parallel
array of weights/unnormalized probabilities (any sort of histogram, basically).
Also add a non-thread safe version for convenience.
* Address Araq comments on https://github.com/nim-lang/Nim/pull/10072
* import at top of file and space after '#'.
* Put in a check for non-zero total weight.
* Clarify constraint on `w`.
* Rename `rand(openArray[T])` to `sample(openArray[T])` to `sample`, deprecating
old name and name new (openArray[T], openArray[U]) variants `sample`.
* Rename caller-provided state version of rand(openArray[T]) and also clean
up doc comments.
* Add test for new non-uniform array sampler. 3 sd bound makes it 99% likely
that it will still pass in the future if the random number generator changes.
We cannot both have a tight bound to check distribution *and* loose check to
ensure resilience to RNG changes. (We cannot *guarantee* resilience, anyway.
There's always a small chance any test hits a legitimate random fluctuation.)
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