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A 'symbol' argument was added in ABCPolyBase in 1.24 and documented there, but
the docstrings for derived classes (e.g., Polynomial) were not updated.
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Co-authored-by: Charles Harris <charlesr.harris@gmail.com>
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From my regular expression foo, those are the only 9 case whereas there
are about ~2000 usage that do not have spaces.
While this is ok with docutils/sphinx, it does not seem to be
documented, and that means that other parsers will see that as comments,
leading to for example improper syntax highlighting.
This make it also a tiny bit harder to develop alternative rst parsers.
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DOC: fix docstring formatting of polynomial fit method return values.
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Fixes #19897
The 2nd return value of the following methods/functions were badly
formatted and the list was all appearing in a single line. Changed them
to separate points which are rendered nicely.
- numpy.polyfit
- numpy.ma.polyfit
- numpy.polynomial.polynomial.polyfit
- numpy.polynomial.polynomial.Polynomial.fit
- numpy.polynomial.chebyshev.chebfit
- numpy.polynomial.chebyshev.Chebyshev.fit
- numpy.polynomial.hermite.hermfit
- numpy.polynomial.hermite.Hermite.fit
- numpy.polynomial.hermite_e.hermefit
- numpy.polynomial.hermite_e.HermiteE.fit
- numpy.polynomial.laguerre.lagfit
- numpy.polynomial.laguerre.Laguerre.fit
- numpy.polynomial.legendre.legfit
- numpy.polynomial.legendre.Legendre.fit
Also fixed erroneous links to `numpy.full` which were actually referring
to the `full` argument. Changed those to code strings (double backticks)
from single backticks.
Also fixed formatting issues in the 3rd return value of numpy.polyfit
(and hence also numpy.ma.polyfit).
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* DOC: Adjust polyfit doc to clarify the meaning of w
cov='unscaled', in particular, had inconsistently referred to a weight
of 1/sigma**2, while the doc for w says it should be equal to 1/sigma.
This change clarifies w to comport with more typical meanings of
weights in weighted least squares, and makes clear that cov='unscaled'
is appropriate when the weight w**2 = 1/sigma**2.
See Issue #5261 for more discussion of the errors/confusion in
the previous doc string.
* Update doc text for w in all polynomial module fit functions
Co-authored-by: Stefan van der Walt <sjvdwalt@gmail.com>
Co-authored-by: Ross Barnowski <rossbar@berkeley.edu>
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Numpydoc format says that the colon need o be omitted if there is no
type, there were also some empty Examples Sections
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Single backticks default role is reference, while here it seem to be for
verbatim. Fix it in a couple of places.
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* MAINT: Remove nickname from polynomial classes.
The convenience classes derived from ABCPolyBase had a nickname
attribute that was only used internally in the previous
implementation of __str__. After the overhaul of __str__ in #15666,
this attr is no longer used.
* DOC: Add release note.
Add release note to notify users of removal of the abstract
property, and highlight users that may be affected by the
change.
* DOC: fixed rST in release note
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* DOC: Fixes for 18 broken links
This, with PR #16465, should fix nearly all the remaining broken links
on the site. 4 or 5 others should be easy to fix and just
need attention from someone more knowledgeable -- will
open an issue. For release notes with dead links,
I could usually find links on archive.org for roughly contemporary
versions.
* DOC: Update to "Fixes for 18 broken links #16472"
* Obsolete links, previously commented out, now deleted:
https://github.com/numpy/numpy/pull/16472#discussion_r433928958
* Semantic markup for reference to Python class:
https://github.com/numpy/numpy/pull/16472#discussion_r433553928
* Missing :ref: in internal link:
https://github.com/numpy/numpy/pull/16472#discussion_r433554484
Not included: Resolution on using external/internal doc link in .py:
https://github.com/numpy/numpy/pull/16472#discussion_r433554824
* DOC: Add internal link for 'Fixes for 18 broken links' PR #16472
Making reference [1] an internal link in function_base.py => numpy.vectorize.html
* DOC: Redirect 2 link fixes in PR #16472
* governance.rst link reverted
* ununcs.rst `overridden` link goes where it was meant to
per https://github.com/numpy/numpy/pull/16472#pullrequestreview-424666070
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Add missing closing brackets, script to generate the list in the PR gh-16051.
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* DOC: Refactor polynomial docs using automodule.
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As numpy is Python 3 only, these import statements are now unnecessary
and don't alter runtime behavior.
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the vander2d and vander3d functions
The generalization is not exposed in the public API yet, but it could be if the need arises.
The shape / dtype conversion logic is left as is for now, even if it might be broken.
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These ones just generated warnings, not build failures
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These power functions are all the same - the algorithm used does not care about the basis.
`polypow` and `chebpow` have some optimizations in their versions, which this maintains
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This changes the behavior for:
* The `deg` and `axis` arguments of `<type>der`
* The `deg` and `axis` arguments of `<type>int`
* The `deg` argument of `<type>gauss`
* The `deg` argument of `<type>vander2d`
* The `deg` argument of `<type>vander3d`
The old behavior was:
* Raise `ValueError` if the argument is a float, but not an integral one
* Allow a float like `1.0` to mean `1`.
This is inconsistent with most other integer-accepting APIs in numpy, which require these to be actual integers, and raise TypeError when they are not.
The new behavior is:
* Raise `TypeError` if the argument is a float, but not an integral one
* Emit a `DeprecationWarning` if a float like `1.0` is passed, continuing to allow it its old meaning.
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These fitting functions are all the same - the algorithm used does not care about the basis.
This was done using:
* A regex find / replace on all but poly and cheb
* A manual diff showing that cheb differed only by whitespace
* A manual diff showing that poly differed in `deg.ndim == 1` vs `deg.ndim > 0`.
Given that this function only allows `deg.ndim <= 1`, and `ndim >= 0`, these two comparison are equivalent.
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These functions are all the same - the algorithm used does not care about the basis.
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These division functions are all the same - the algorithm used does not care about the basis.
Note that while chebdiv and polydiv could be implemented in terms of this function, their current implementations are more optimal and exploit the properties of a multiplication by a basis polynomial.
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This makes the variable names in polydiv and chebdiv match polyutils._div.
It also brings the order of the special-casing in line to match.
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No point writing the same function 12 times, when you can write it once
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Every implementation is the same right now, other than calling different line / mul functions.
Found by LGTM.
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Every implementation is the same right now, other than calling a different `*vander` function.
Merging these into a single private function taking a callback results in significant deduplication.
Found by LGTM.
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* ported the refguide_check module from SciPy for usage
in NumPy docstring execution/ verification; added the
refguide_check run to Azure Mac OS CI
* adjusted NumPy docstrings such that refguide_check passes
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(#12448)
* Review F401,F841,F842 flake8 errors (unused variables, imports)
* Review comments
* More tests in test_installed_npymath_ini
* Review comments
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ENH: Add support for ipython latex printing to polynomial
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Choices made, and the alternatives rejected (for no particularly strong reason):
1. Show terms in ascending order, to match their internal representation
* alternative: descending, to match convention
2. Shows 0 terms in gray
* alternative: omit entirely
* alternative: show normally to aid comparison
3. Write each term as `basis(ax + b)
* alternative: write as `basis(u) ... where u = ax + b`
* alternative: show the normalized polynomial
In future it would perhaps make sense to expose these options to the end user
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It was not being checked that the `lbnd` and `scl` parameters were
scalars as required.
Closes #9901.
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so it actually displays in the docs
[skip ci]
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Also add a hint to the documentation advising the use of moveaxis over rollaxis.
Tests for rollaxis are left alone.
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Also, update the docs with this new repr
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* Rename chebinterp to chebinterpolation as suggested.
* Make some fixes to the Chebyshev class function.
* Refactor TestInterpolation.
* Add test for the Chebyshev.interpolation class function.
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The chebinterp function interpolates a function at the Chebyshev points
of the first kind using a Chebyshev series. The resulting interpolation
approximates a polynomial fit minimizing the L_inf norm.
This function is useful e.g. for estimating roots before running a
root-finding function.
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Bare except is very rarely the right thing
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