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From: Alexander H. <mat...@2s...> - 2015-03-02 22:15:15
|
instead of having people enter all this info by hand, you should just write a python script that extracts most of the technical details from the current install, prints it out for cut-and paste into the form or directly sends it to your server. ;-) On 3 March 2015 at 02:23, Thomas Robitaille <tho...@gm...> wrote: > Hi everyone, > > If you use scientific Python packages for your research/work, I would > appreciate if you could take a few minutes to fill out the following > survey: > > http://goo.gl/PXzFAk > > The aim of this survey is to find out what versions of Python and > various scientific Python packages people are using, and how people > typically install packages, in order to determine how developers can > better meet the needs of the Scientific Python community (for example, > a common question is which version of Numpy need to be supported by > packages). > > This is a follow-up to a similar survey which I did back in 2012 and > which provided very interesting results that you can read about here: > > http://astrofrog.github.io/blog/2013/01/13/what-python-installations-are-scientists-using > > Please feel free to forward this survey to people in your own > scientific Python communities! > > I will publish the results online in a few weeks. > > Thanks! > Tom > > ------------------------------------------------------------------------------ > Dive into the World of Parallel Programming The Go Parallel Website, sponsored > by Intel and developed in partnership with Slashdot Media, is your hub for all > things parallel software development, from weekly thought leadership blogs to > news, videos, case studies, tutorials and more. Take a look and join the > conversation now. http://goparallel.sourceforge.net/ > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-users |
From: Thomas R. <tho...@gm...> - 2015-03-02 15:23:57
|
Hi everyone, If you use scientific Python packages for your research/work, I would appreciate if you could take a few minutes to fill out the following survey: http://goo.gl/PXzFAk The aim of this survey is to find out what versions of Python and various scientific Python packages people are using, and how people typically install packages, in order to determine how developers can better meet the needs of the Scientific Python community (for example, a common question is which version of Numpy need to be supported by packages). This is a follow-up to a similar survey which I did back in 2012 and which provided very interesting results that you can read about here: http://astrofrog.github.io/blog/2013/01/13/what-python-installations-are-scientists-using Please feel free to forward this survey to people in your own scientific Python communities! I will publish the results online in a few weeks. Thanks! Tom |
From: miaocb <mi...@si...> - 2015-03-02 03:07:16
|
Hi, all The following code repeats the problem. Array ele1 is same as ele2 except that it is transpose of ele0, but the refined triangles using ele1 is incorrect. The problem is also reported at https://github.com/matplotlib/matplotlib/issues/4180 matplotlib version: 1.4.0, the UniformTriRefiner code in version 1.4.3 is the same as 1.4.0。 #!/bin/env python import numpy as np import matplotlib.tri as tri import matplotlib.pyplot as plt x = np.array([ 120.39299774, 120.59100342, 120.42900085, 120.31700134]) y = np.array([ 33.99900055, 34.00899887, 34.18799973, 34.18399811]) ele0 = np.array([[2, 2], [0, 1], [3, 0]]) ele1 = ele0.transpose() # ele1 is same as ele2 except that it is transpose of ele0 ele2 = np.array([[2, 0, 3], [2, 1, 0]]) triang1 = tri.Triangulation(x, y, ele1) triang2 = tri.Triangulation(x, y, ele2) refiner1 = tri.UniformTriRefiner(triang1) refiner2 = tri.UniformTriRefiner(triang2) fine_triang1 = refiner1.refine_triangulation(subdiv=1) fine_triang2 = refiner2.refine_triangulation(subdiv=1) fig = plt.figure() ha1 = fig.add_subplot(121) ha1.set_aspect('equal') plt.triplot(fine_triang1, color='b', linewidth=0.5) plt.triplot(triang1, color='k', linewidth=1) plt.title('refine_triang1 is incorrect') ha2 = fig.add_subplot(122) ha2.set_aspect('equal') plt.triplot(fine_triang2, color='b', linewidth=0.5) plt.triplot(triang2, color='k', linewidth=1) plt.title('refine_triang2 is correct') plt.show() Paul |