Mailman 3 September 2018 - SciPy-User

How to display a RGB image (MFISH)?
by jp April 3, 2023

April 3, 2023

Hi, I have written a script to try to combine five images into a three channels RGB images<http://dip4fish.blogspot.com/2011/05/trying-to-combine-mfish-images-into-rg…> . The resulting RGB image looks like a grey scale image instead of a color one. I have three np.array Rnorm, Gnorm, Bnorm which are copied into a rgb array: *rgb = np.zeros((shape[0],shape[1],3),dtype=float) mxr=np.max(R) mxg=np.max(G) mxb=np.max(B) Rnorm=np.uint8((255*(R/mxr)))Gnorm=np.uint8((255*(R/mxg)))Bnorm=np.uint8((255*(R/mxb)))#copy each RGB component in an RGB array rgb[:,:,0]=Rnorm rgb[:,:,1]=Gnorm rgb[:,:,2]=Bnorm* *pylab.subplot(224, aspect='equal',frameon=False, xticks=[], yticks=[]) pylab.imshow(rgb) pylab.show()* Any advice? Thank you Jean-Patrick

3 4

Invitation to connect on LinkedIn
by Jelle Feringa via LinkedIn July 28, 2022

July 28, 2022

LinkedIn ------------ Jelle Feringa requested to add you as a connection on LinkedIn: ------------------------------------------ Jose, I'd like to add you to my professional network on LinkedIn. - Jelle Accept invitation from Jelle Feringa http://www.linkedin.com/e/-3wy1w2-gpkzwpgn-5n/Q6WKH0LACopGJkAw_6fSqajo6R7VM… View invitation from Jelle Feringa http://www.linkedin.com/e/-3wy1w2-gpkzwpgn-5n/Q6WKH0LACopGJkAw_6fSqajo6R7VM… ------------------------------------------ DID YOU KNOW your LinkedIn profile helps you control your public image when people search for you? Setting your profile as public means your LinkedIn profile will come up when people enter your name in leading search engines. Take control of your image! http://www.linkedin.com/e/-3wy1w2-gpkzwpgn-5n/ewp/inv-22/ -- (c) 2011, LinkedIn Corporation

2 1

Help required regding Eigenvectors
by Sudheer Phani March 14, 2022

March 14, 2022

Hello All, I have been encountering some strange problems with the calculation of eigen vectors using python. The problem is with the sign of the eigen vectors calculated. On Very few occasions the eigen vectors calculated using python have an opposite sign than the actual eigenvectors, though the magnitude is correct. Can any one of you plz help me in this regard and suggest me some solution if you have encoutered similar problems . Any help in this regd is appreciated Thanks in Advace regds Sudheer

5 5

Numpy 1.14.6 release
by Charles R Harris Sept. 23, 2018

Sept. 23, 2018

Hi All, On behalf of the NumPy team, I am pleased to announce the release of NumPy 1.14.6. This is a bug fix release for bugs and regressions reported following the 1.14.5 release. The significant fixes are: - Fix for behavior change in ``ma.masked_values(shrink=True)`` - Fix the new cached allocations machinery to be thread safe. The Python versions supported by this release are 2.7, 3.4-3.7. The wheels are linked with OpenBLAS v0.3.0, which should fix some of the linalg problems reported for earlier releases of NumPy 1.14. Wheels for this release can be downloaded from PyPI <https://pypi.org/project/numpy/1.14.6/>, source archives are available from Github <https://github.com/numpy/numpy/releases/tag/v1.14.6>. Compatibility Note ================== The NumPy 1.14.6 OS X wheels released on PyPI no longer contain 32-bit binaries. See #11625 <https://github.com/numpy/numpy/issues/11625> for the related discussion. Those needing 32-bit support should look elsewhere or build from source. Contributors ============ A total of 4 people contributed to this release. People with a "+" by their names contributed a patch for the first time. - Charles Harris - Eric Wieser - Julian Taylor - Matti Picus Pull requests merged ==================== A total of 4 pull requests were merged for this release. - #11985: BUG: fix cached allocations without the GIL - #11986: BUG: Undo behavior change in ma.masked_values(shrink=True) - #11987: BUG: fix refcount leak in PyArray_AdaptFlexibleDType - #11995: TST: Add Python 3.7 testing to NumPy 1.14. Cheers, Charles Harris

1 0

NumPy 1.15.2 released
by Charles R Harris Sept. 23, 2018

Sept. 23, 2018

Hi All, On behalf of the NumPy team, I am pleased to announce the release of NumPy 1.15.2. This is a bug fix release for bugs and regressions reported following the 1.15.2 release. The fixes are: - the matrix PendingDeprecationWarning is now suppressed in pytest 3.8, - the new cached allocations machinery has been fixed to be thread safe, - the boolean indexing of subclasses now works correctly, - a small memory leak in PyArray_AdaptFlexibleDType has been fixed. The Python versions supported by this release are 2.7, 3.4-3.7. The wheels are linked with OpenBLAS v0.3.0, which should fix some of the linalg problems reported for NumPy 1.14. Wheels for this release can be downloaded from PyPI <https://pypi.org/project/numpy/1.15.2/>, source archives are available from Github <https://github.com/numpy/numpy/releases/tag/v1.15.2> Compatibility Note ================== The NumPy 1.15.x OS X wheels released on PyPI no longer contain 32-bit binaries. That will also be the case in future releases. See `#11625 <https://github.com/numpy/numpy/issues/11625>`__ for the related discussion. Those needing 32-bit support should look elsewhere or build from source. Contributors ============ A total of 4 people contributed to this release. People with a "+" by their names contributed a patch for the first time. * Charles Harris * Julian Taylor * Marten van Kerkwijk * Matti Picus Pull requests merged ==================== A total of 4 pull requests were merged for this release. * `#11902 <https://github.com/numpy/numpy/pull/11902>`__: BUG: Fix matrix PendingDeprecationWarning suppression for pytest... * `#11981 <https://github.com/numpy/numpy/pull/11981>`__: BUG: fix cached allocations without the GIL for 1.15.x * `#11982 <https://github.com/numpy/numpy/pull/11982>`__: BUG: fix refcount leak in PyArray_AdaptFlexibleDType * `#11992 <https://github.com/numpy/numpy/pull/11992>`__: BUG: Ensure boolean indexing of subclasses sets base correctly. Cheers, Charles Harris

1 0

ANN: SfePy 2018.3
by Robert Cimrman Sept. 17, 2018

Sept. 17, 2018

I am pleased to announce release 2018.3 of SfePy. Description ----------- SfePy (simple finite elements in Python) is a software for solving systems of coupled partial differential equations by the finite element method or by the isogeometric analysis (limited support). It is distributed under the new BSD license. Home page: http://sfepy.org Mailing list: https://mail.python.org/mm3/mailman3/lists/sfepy.python.org/ Git (source) repository, issue tracker: https://github.com/sfepy/sfepy Highlights of this release -------------------------- - easier setting of values of variables - new script for outline edge extraction - new example: homogenization of a piezoelectric heterogeneous structure For full release notes see http://docs.sfepy.org/doc/release_notes.html#id1 (rather long and technical). Cheers, Robert Cimrman --- Contributors to this release in alphabetical order: Robert Cimrman Vladimir Lukes

1 0

np.array_equal for sparse arrays
by Michael Lamparski Sept. 13, 2018

Sept. 13, 2018

Hello everyone, I feel like I am missing something. It seems that sparse matrices have no 'any' method or anything useful regarding equality. Is there not a better way to write this? def sparse_equal(a, b): """ Equality test for sparse matrices which performs standard floating point equality, allows mismatched types, considers missing elements equal to zero, and requires identical shape (no broadcasting) """ return a.shape == b.shape and not (a != b).data.any() (I suppose I could also write 'not (a != b).nnz', since the implementation of != appears to eliminate zeros, but I'm not sure if I should be relying on that) --- Michael

1 0

Multiply dense numpy matrix with sparse scipy vector
by list＠emeel.net Sept. 11, 2018

Sept. 11, 2018

Upon profiling, we found that multiplying a dense numpy matrix, e.g. A = np.eye(5) with a sparse scipy vector, e.g. x = scipy.sparse.coo_matrix(np.eye(5)[4]).T did in fact not make use of the sparsity of x when using @. That is: A @ x is not a sparse computation. How can this be done?

1 0