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DOC: update 0.14.0 release notes. #3286

Merged
merged 2 commits into from
Feb 9, 2014
Merged

DOC: update 0.14.0 release notes. #3286

merged 2 commits into from
Feb 9, 2014

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rgommers
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@rgommers rgommers commented Feb 5, 2014

@pv, @jnothman: could one of you suggest wording for the sparse matrix improvements?

@ev-br, @pv: same question for the BPoly/PPoly stuff

Anything else notable that I missed?

@rgommers rgommers added this to the 0.14.0 milestone Feb 5, 2014


New features
============

``scipy.interpolate`` improvements
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Note: the new features list is probably easier to read if there is only one level of sections below it.
I.e., only ------- titles and not ^^^^^^. I.e., I'd do away with the "scipy.XXX improvements" titles.

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Agreed, I don't like the current formatting much. Will change it for the whole file.

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Coverage Status

Changes Unknown when pulling c1f31ab on rgommers:014-relnotes into * on scipy:master*.

- sparse matrices can now be indexed with 64-bit integers, and are therefore no
longer limited to ``2^31`` nonzero elements.
- ``__numpy_ufunc__`` in combination with numpy 1.9
- performance optimizations
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"""
Significant performance improvement in CSR, CSC, and DOK indexing speed.
"""
NB. the PR with the DOK changes is still waiting for review...

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pv commented Feb 5, 2014

More stuff:

  • Condition number estimate for matrix exponential, scipy.linalg.expm_cond.
  • Evaluation of bivariate spline derivatives in scipy.interpolate
  • More controllable error estimation in scipy.optimize.curve_fit

Backward incompatible changes:

  • Eigenvectors in the case of generalized eigenvalue problem are normalized to unit vectors in 2-norm, rather than following the LAPACK normalization convention.

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rgommers commented Feb 8, 2014

Thanks @pv, all comments addressed.

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Coverage Status

Coverage remained the same when pulling 8a536bd on rgommers:014-relnotes into 63f951e on scipy:master.

pv added a commit that referenced this pull request Feb 9, 2014
DOC: update 0.14.0 release notes.
@pv pv merged commit 47a89d5 into scipy:master Feb 9, 2014
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pv commented Feb 9, 2014

Merging.


- Significant performance improvement in CSR, CSC, and DOK indexing speed.
- When using Numpy >= 1.9 (to be released in MM 2014), sparse matrices function
correctly when given to arguments of ``np.dot``, ``np.multiply`` and other
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We now know that ufuncs do not work for sparse matrices with duplicate indices at present... I'm not sure if this strong a statement is appropriate unless that is fixed before the release.

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On one hand, it's not a regression.

BrianNewsom pushed a commit to BrianNewsom/scipy that referenced this pull request Feb 11, 2014
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4 participants