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							| @ -32,3 +32,4 @@ scipy-0.7.2.tar.gz | ||||
| /scipy-1.5.2.tar.gz | ||||
| /scipy-1.5.3.tar.gz | ||||
| /scipy-1.5.4.tar.gz | ||||
| /scipy-1.6.0.tar.gz | ||||
|  | ||||
							
								
								
									
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							| @ -14,8 +14,8 @@ | ||||
| 
 | ||||
| Summary:    Scientific Tools for Python | ||||
| Name:       scipy | ||||
| Version:    1.5.4 | ||||
| Release:    2%{?dist} | ||||
| Version:    1.6.0 | ||||
| Release:    1%{?dist} | ||||
| 
 | ||||
| # BSD -- whole package except: | ||||
| # Boost -- scipy/special/cephes/scipy_iv.c | ||||
| @ -24,10 +24,8 @@ License:    BSD and Boost and Public Domain | ||||
| Url:        http://www.scipy.org/scipylib/index.html | ||||
| Source0:    https://github.com/scipy/scipy/releases/download/v%{version}/scipy-%{version}.tar.gz | ||||
| 
 | ||||
| # https://github.com/scipy/scipy/pull/12899 | ||||
| Patch0:     skip-certain-tests-on-32-bit-arches.patch | ||||
| # https://github.com/scipy/scipy/pull/13130 | ||||
| Patch1:     skip-factorial-float-tests-on-py310.patch | ||||
| # https://github.com/scipy/scipy/pull/13387 | ||||
| Patch0:     wavfile.patch | ||||
| 
 | ||||
| BuildRequires: fftw-devel, suitesparse-devel | ||||
| BuildRequires: %{blaslib}-devel | ||||
| @ -173,6 +171,10 @@ popd | ||||
| %endif | ||||
| 
 | ||||
| %changelog | ||||
| * Mon Jan 04 2021 Nikola Forró <nforro@redhat.com> - 1.6.0-1 | ||||
| - New upstream release 1.6.0 | ||||
|   resolves: #1906692 | ||||
| 
 | ||||
| * Wed Nov 25 2020 Nikola Forró <nforro@redhat.com> - 1.5.4-2 | ||||
| - Skip factorial() float tests on Python 3.10 | ||||
|   resolves: #1898157 | ||||
|  | ||||
							
								
								
									
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							| @ -1 +1 @@ | ||||
| SHA512 (scipy-1.5.4.tar.gz) = d23f68911a8880f87767819750d4d175ba8f9c72fcb9b8080305ee65722c046d4485fde4f0c85cc53c46247dd99813afe675a38b3b0569a683ddc2c2e021b8fc | ||||
| SHA512 (scipy-1.6.0.tar.gz) = 995ffaf56b713cdd4bdb98d8525b892e9ad84a511878b43213cb71a67f34d87c111da36cf1e0b044c75c0d5af64bfde4ad0f3e9c5e71cae2dbf053251f37064e | ||||
|  | ||||
							
								
								
									
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							| @ -0,0 +1,36 @@ | ||||
| commit 09d753f0ae71441906f5cee7a44b2d2b80212082 | ||||
| Author: Nikola Forró <nforro@redhat.com> | ||||
| Date:   Thu Jan 14 14:34:14 2021 +0100 | ||||
| 
 | ||||
|     ENH: Support big-endian platforms and big-endian WAVs | ||||
|      | ||||
|     PR #12287 added support for reading arbitrary-bit-depth WAVs, but | ||||
|     the code doesn't consider big-endian WAVs, and doesn't work as expected | ||||
|     on big-endian platforms due to the use of native-byte-order data-types. | ||||
|     This change fixes that. | ||||
|      | ||||
|     There is also a simple test case that compares euqivalent RIFX | ||||
|     (big-endian) and RIFF (little-endian) files to verify the data read | ||||
|     are the same. | ||||
| 
 | ||||
| diff --git a/scipy/io/wavfile.py b/scipy/io/wavfile.py
 | ||||
| index 9b5845d6b..951f8d201 100644
 | ||||
| --- a/scipy/io/wavfile.py
 | ||||
| +++ b/scipy/io/wavfile.py
 | ||||
| @@ -458,10 +458,13 @@ def _read_data_chunk(fid, format_tag, channels, bit_depth, is_big_endian,
 | ||||
|   | ||||
|          if dtype == 'V1': | ||||
|              # Rearrange raw bytes into smallest compatible numpy dtype | ||||
| -            dt = numpy.int32 if bytes_per_sample == 3 else numpy.int64
 | ||||
| -            a = numpy.zeros((len(data) // bytes_per_sample, dt().itemsize),
 | ||||
| +            dt = f'{fmt}i4' if bytes_per_sample == 3 else f'{fmt}i8'
 | ||||
| +            a = numpy.zeros((len(data) // bytes_per_sample, numpy.dtype(dt).itemsize),
 | ||||
|                              dtype='V1') | ||||
| -            a[:, -bytes_per_sample:] = data.reshape((-1, bytes_per_sample))
 | ||||
| +            if is_big_endian:
 | ||||
| +                a[:, :bytes_per_sample] = data.reshape((-1, bytes_per_sample))
 | ||||
| +            else:
 | ||||
| +                a[:, -bytes_per_sample:] = data.reshape((-1, bytes_per_sample))
 | ||||
|              data = a.view(dt).reshape(a.shape[:-1]) | ||||
|      else: | ||||
|          if bytes_per_sample in {1, 2, 4, 8}: | ||||
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