[Numpy-discussion] Array2 subset of array1
Hi, I am new to numpy so any help would be greatly appreciated. I have two arrays: array1 = np.arange(1,100+1) array2 = np.arange(1,50+1) How can I calculate/determine if array2 is a subset of array1 (falls within array 1) Something like : array2 in array1 = TRUE for the case above. Thank ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Array2 subset of array1
On Tue, Aug 5, 2014 at 1:58 PM, Jurgens de Bruin debrui...@gmail.com wrote: Hi, I am new to numpy so any help would be greatly appreciated. I have two arrays: array1 = np.arange(1,100+1) array2 = np.arange(1,50+1) How can I calculate/determine if array2 is a subset of array1 (falls within array 1) Something like : array2 in array1 = TRUE for the case above. Does this work? np.in1d(array2, array1) See: http://docs.scipy.org/doc/numpy/reference/routines.set.html (Note that while in1d does the best it can, set operations on arrays will usually be slower than if you used a more appropriate data type like 'set' or 'dict'.) -n -- Nathaniel J. Smith Postdoctoral researcher - Informatics - University of Edinburgh http://vorpus.org ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Array2 subset of array1
np.all(np.in1d(array1,array2)) On Tue, Aug 5, 2014 at 2:58 PM, Jurgens de Bruin debrui...@gmail.com wrote: Hi, I am new to numpy so any help would be greatly appreciated. I have two arrays: array1 = np.arange(1,100+1) array2 = np.arange(1,50+1) How can I calculate/determine if array2 is a subset of array1 (falls within array 1) Something like : array2 in array1 = TRUE for the case above. Thank ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Array2 subset of array1
On Di, 2014-08-05 at 14:58 +0200, Jurgens de Bruin wrote: Hi, I am new to numpy so any help would be greatly appreciated. I have two arrays: array1 = np.arange(1,100+1) array2 = np.arange(1,50+1) How can I calculate/determine if array2 is a subset of array1 (falls within array 1) Something like : array2 in array1 = TRUE for the case above. Just to be clear. You are looking for the whole of array1 (as a block/subarray) as far as I understand. And there is no obvious numpy way to do this. Depending on your array sizes, you could blow up the first array from (N,) to (N-M+1,M) and then check if any row matches completely. There may be better tricks available though, especially if array1 is large. - Sebastian Thank ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Array2 subset of array1
ah yes, that may indeed be what you want. depending on your datatype, you could access the underlying raw data as a string. b.tostring() in a.tostring() sort of works; but isn't entirely safe, as you may have false positive matches which arnt aligned to your datatype using str.find in combination with dtype.itemsize could solve that problem; though it isn't the most elegant solution id say. also note that you need to check for identical datatypes and memory layout for this to guarantee correct results. On Tue, Aug 5, 2014 at 6:33 PM, Sebastian Berg sebast...@sipsolutions.net wrote: On Di, 2014-08-05 at 14:58 +0200, Jurgens de Bruin wrote: Hi, I am new to numpy so any help would be greatly appreciated. I have two arrays: array1 = np.arange(1,100+1) array2 = np.arange(1,50+1) How can I calculate/determine if array2 is a subset of array1 (falls within array 1) Something like : array2 in array1 = TRUE for the case above. Just to be clear. You are looking for the whole of array1 (as a block/subarray) as far as I understand. And there is no obvious numpy way to do this. Depending on your array sizes, you could blow up the first array from (N,) to (N-M+1,M) and then check if any row matches completely. There may be better tricks available though, especially if array1 is large. - Sebastian Thank ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] ANN: NumPy 1.8.2 release candidate
Hello, I am pleased to announce the first release candidate for numpy 1.8.2, a pure bugfix release for the 1.8.x series. https://sourceforge.net/projects/numpy/files/NumPy/1.8.2rc1/ If no regressions show up the final release is planned this weekend. The upgrade is recommended for all users of the 1.8.x series. Following issues have been fixed: * gh-4836: partition produces wrong results for multiple selections in equal ranges * gh-4656: Make fftpack._raw_fft threadsafe * gh-4628: incorrect argument order to _copyto in in np.nanmax, np.nanmin * gh-4613: Fix lack of NULL check in array_richcompare * gh-4642: Hold GIL for converting dtypes types with fields * gh-4733: fix np.linalg.svd(b, compute_uv=False) * gh-4853: avoid unaligned simd load on reductions on i386 * gh-4774: avoid unaligned access for strided byteswap * gh-650: Prevent division by zero when creating arrays from some buffers * gh-4602: ifort has issues with optimization flag O2, use O1 Source tarballs, windows installers and release notes can be found at https://sourceforge.net/projects/numpy/files/NumPy/1.8.2rc1/ Cheers, Julian Taylor signature.asc Description: OpenPGP digital signature ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] ANN: NumPy 1.8.2 release candidate
On 8/5/2014 12:45 PM, Julian Taylor wrote: Hello, I am pleased to announce the first release candidate for numpy 1.8.2, a pure bugfix release for the 1.8.x series. https://sourceforge.net/projects/numpy/files/NumPy/1.8.2rc1/ If no regressions show up the final release is planned this weekend. The upgrade is recommended for all users of the 1.8.x series. Following issues have been fixed: * gh-4836: partition produces wrong results for multiple selections in equal ranges * gh-4656: Make fftpack._raw_fft threadsafe * gh-4628: incorrect argument order to _copyto in in np.nanmax, np.nanmin * gh-4613: Fix lack of NULL check in array_richcompare * gh-4642: Hold GIL for converting dtypes types with fields * gh-4733: fix np.linalg.svd(b, compute_uv=False) * gh-4853: avoid unaligned simd load on reductions on i386 * gh-4774: avoid unaligned access for strided byteswap * gh-650: Prevent division by zero when creating arrays from some buffers * gh-4602: ifort has issues with optimization flag O2, use O1 Source tarballs, windows installers and release notes can be found at https://sourceforge.net/projects/numpy/files/NumPy/1.8.2rc1/ Cheers, Julian Taylor Hello, thank you. Looks good. All builds and tests pass on Windows (using msvc/MKL). Any chance gh-4722 can make it into the release? Fix seg fault converting empty string to object https://github.com/numpy/numpy/pull/4722 Christoph ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] ANN: NumPy 1.8.2 release candidate
On 05.08.2014 22:32, Christoph Gohlke wrote: On 8/5/2014 12:45 PM, Julian Taylor wrote: Hello, I am pleased to announce the first release candidate for numpy 1.8.2, a pure bugfix release for the 1.8.x series. https://sourceforge.net/projects/numpy/files/NumPy/1.8.2rc1/ If no regressions show up the final release is planned this weekend. The upgrade is recommended for all users of the 1.8.x series. Following issues have been fixed: * gh-4836: partition produces wrong results for multiple selections in equal ranges * gh-4656: Make fftpack._raw_fft threadsafe * gh-4628: incorrect argument order to _copyto in in np.nanmax, np.nanmin * gh-4613: Fix lack of NULL check in array_richcompare * gh-4642: Hold GIL for converting dtypes types with fields * gh-4733: fix np.linalg.svd(b, compute_uv=False) * gh-4853: avoid unaligned simd load on reductions on i386 * gh-4774: avoid unaligned access for strided byteswap * gh-650: Prevent division by zero when creating arrays from some buffers * gh-4602: ifort has issues with optimization flag O2, use O1 Source tarballs, windows installers and release notes can be found at https://sourceforge.net/projects/numpy/files/NumPy/1.8.2rc1/ Cheers, Julian Taylor Hello, thank you. Looks good. All builds and tests pass on Windows (using msvc/MKL). Any chance gh-4722 can make it into the release? Fix seg fault converting empty string to object https://github.com/numpy/numpy/pull/4722 thanks, I missed that one, pretty simple, I'll add it to the final release. signature.asc Description: OpenPGP digital signature ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] ANN: NumPy 1.8.2 release candidate
Hi, On Tue, Aug 5, 2014 at 1:57 PM, Julian Taylor jtaylor.deb...@googlemail.com wrote: On 05.08.2014 22:32, Christoph Gohlke wrote: On 8/5/2014 12:45 PM, Julian Taylor wrote: Hello, I am pleased to announce the first release candidate for numpy 1.8.2, a pure bugfix release for the 1.8.x series. https://sourceforge.net/projects/numpy/files/NumPy/1.8.2rc1/ If no regressions show up the final release is planned this weekend. The upgrade is recommended for all users of the 1.8.x series. Following issues have been fixed: * gh-4836: partition produces wrong results for multiple selections in equal ranges * gh-4656: Make fftpack._raw_fft threadsafe * gh-4628: incorrect argument order to _copyto in in np.nanmax, np.nanmin * gh-4613: Fix lack of NULL check in array_richcompare * gh-4642: Hold GIL for converting dtypes types with fields * gh-4733: fix np.linalg.svd(b, compute_uv=False) * gh-4853: avoid unaligned simd load on reductions on i386 * gh-4774: avoid unaligned access for strided byteswap * gh-650: Prevent division by zero when creating arrays from some buffers * gh-4602: ifort has issues with optimization flag O2, use O1 Source tarballs, windows installers and release notes can be found at https://sourceforge.net/projects/numpy/files/NumPy/1.8.2rc1/ Cheers, Julian Taylor Hello, thank you. Looks good. All builds and tests pass on Windows (using msvc/MKL). Any chance gh-4722 can make it into the release? Fix seg fault converting empty string to object https://github.com/numpy/numpy/pull/4722 thanks, I missed that one, pretty simple, I'll add it to the final release. OSX wheels built and tested and uploaded OK : http://wheels.scikit-image.org https://travis-ci.org/matthew-brett/numpy-atlas-binaries/builds/31747958 Will test against the scipy stack later on today. Cheers, Matthew ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] ANN: NumPy 1.8.2 release candidate
On 5 Aug 2014, at 11:27 pm, Matthew Brett matthew.br...@gmail.com wrote:
OSX wheels built and tested and uploaded OK :
http://wheels.scikit-image.org
https://travis-ci.org/matthew-brett/numpy-atlas-binaries/builds/31747958
Will test against the scipy stack later on today.
Built and tested against the Fink Python installation under OSX.
Seems to resolve one of a couple of f2py test errors appearing with 1.8.1 on
Python 3.3 and 3.4:
==
ERROR: test_return_real.TestCReturnReal.test_all
--
Traceback (most recent call last):
File /sw/lib/python3.4/site-packages/nose/case.py, line 382, in setUp
try_run(self.inst, ('setup', 'setUp'))
File /sw/lib/python3.4/site-packages/nose/util.py, line 470, in try_run
return func()
File /sw/lib/python3.4/site-packages/numpy/f2py/tests/util.py, line 348, in
setUp
module_name=self.module_name)
File /sw/lib/python3.4/site-packages/numpy/f2py/tests/util.py, line 74, in
wrapper
memo[key] = func(*a, **kw)
File /sw/lib/python3.4/site-packages/numpy/f2py/tests/util.py, line 163, in
build_code
module_name=module_name)
File /sw/lib/python3.4/site-packages/numpy/f2py/tests/util.py, line 74, in
wrapper
memo[key] = func(*a, **kw)
File /sw/lib/python3.4/site-packages/numpy/f2py/tests/util.py, line 144, in
build_module
__import__(module_name)
ImportError: No module named ‘c_ext_return_real'
is gone on 3.4 now but still present on 3.3. Two errors of this kind (with
different numbers) remain:
ERROR: test_return_real.TestF90ReturnReal.test_all
--
Traceback (most recent call last):
File /sw/lib/python3.4/site-packages/nose/case.py, line 382, in setUp
try_run(self.inst, ('setup', 'setUp'))
File /sw/lib/python3.4/site-packages/nose/util.py, line 470, in try_run
return func()
File /sw/lib/python3.4/site-packages/numpy/f2py/tests/util.py, line 348, in
setUp
module_name=self.module_name)
File /sw/lib/python3.4/site-packages/numpy/f2py/tests/util.py, line 74, in
wrapper
memo[key] = func(*a, **kw)
File /sw/lib/python3.4/site-packages/numpy/f2py/tests/util.py, line 163, in
build_code
module_name=module_name)
File /sw/lib/python3.4/site-packages/numpy/f2py/tests/util.py, line 74, in
wrapper
memo[key] = func(*a, **kw)
File /sw/lib/python3.4/site-packages/numpy/f2py/tests/util.py, line 144, in
build_module
__import__(module_name)
ImportError: No module named ‘_test_ext_module_5415'
NumPy version 1.8.2rc1
NumPy is installed in /sw/lib/python3.4/site-packages/numpy
Python version 3.4.1 (default, Aug 3 2014, 21:02:44) [GCC 4.2.1 Compatible
Apple LLVM 5.1 (clang-503.0.40)]
nose version 1.3.3
Cheers,
Derek
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Re: [Numpy-discussion] ANN: NumPy 1.8.2 release candidate
Hi, On Tue, Aug 5, 2014 at 2:27 PM, Matthew Brett matthew.br...@gmail.com wrote: Hi, On Tue, Aug 5, 2014 at 1:57 PM, Julian Taylor jtaylor.deb...@googlemail.com wrote: On 05.08.2014 22:32, Christoph Gohlke wrote: On 8/5/2014 12:45 PM, Julian Taylor wrote: Hello, I am pleased to announce the first release candidate for numpy 1.8.2, a pure bugfix release for the 1.8.x series. https://sourceforge.net/projects/numpy/files/NumPy/1.8.2rc1/ If no regressions show up the final release is planned this weekend. The upgrade is recommended for all users of the 1.8.x series. Following issues have been fixed: * gh-4836: partition produces wrong results for multiple selections in equal ranges * gh-4656: Make fftpack._raw_fft threadsafe * gh-4628: incorrect argument order to _copyto in in np.nanmax, np.nanmin * gh-4613: Fix lack of NULL check in array_richcompare * gh-4642: Hold GIL for converting dtypes types with fields * gh-4733: fix np.linalg.svd(b, compute_uv=False) * gh-4853: avoid unaligned simd load on reductions on i386 * gh-4774: avoid unaligned access for strided byteswap * gh-650: Prevent division by zero when creating arrays from some buffers * gh-4602: ifort has issues with optimization flag O2, use O1 Source tarballs, windows installers and release notes can be found at https://sourceforge.net/projects/numpy/files/NumPy/1.8.2rc1/ Cheers, Julian Taylor Hello, thank you. Looks good. All builds and tests pass on Windows (using msvc/MKL). Any chance gh-4722 can make it into the release? Fix seg fault converting empty string to object https://github.com/numpy/numpy/pull/4722 thanks, I missed that one, pretty simple, I'll add it to the final release. OSX wheels built and tested and uploaded OK : http://wheels.scikit-image.org https://travis-ci.org/matthew-brett/numpy-atlas-binaries/builds/31747958 OSX wheel tested OK against current scipy stack for system Python, python.org Python, homebrew, macports: https://travis-ci.org/matthew-brett/scipy-stack-osx-testing/builds/31756325 Cheers, Matthew ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] Preliminary thoughts on implementing __matmul__
Hi All, I've been looking to implement the @ operator from Python 3.5. Looking at the current implementation of the dot function, it only uses a vector inner product, which is either that defined in arraytypes.c.src or a version using cblas defined in _dotblas for the float, cfloat, double, cdouble types. I note that the versions defined in arraytypes.c.src include all the numeric types plus boolean, datetime, timedelta, and object. I'm not clear why datetime and timedelta should have dot products, except perhaps for scalar multiplication. The boolean version has the advantage that it can short circuit. I also note that all the operations proposed for @ can easily be done with einsum except for objects. So I'm wondering if one easy way to implement the functions is to extend einsum to work with objects and make it use blas when available. Another thing that may be worth looking into would be some way to multiply by the complex conjugate, as that is easy to implement at the low level. I'd welcome any thoughts as to how that might be done. Anyway, I'm just looking for a discussion and ideas here. Any input is welcome. Chuck ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
