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python Programming Glossary: np.r_

Matplotlib: How to colorize a large number of line segments as independent gradients, efficiently

http://stackoverflow.com/questions/13622909/matplotlib-how-to-colorize-a-large-number-of-line-segments-as-independent-gradi

dist np.hypot np.diff x x.min np.diff y y.min .cumsum t np.r_ 0 dist dist.max ti np.linspace 0 1 num endpoint True xi np.interp.. dist np.hypot np.diff x x.min np.diff y y.min .cumsum t np.r_ 0 dist dist.max ti np.linspace 0 1 num endpoint True xi np.interp.. dist np.hypot np.diff x x.min np.diff y y.min .cumsum t np.r_ 0 dist dist.max ti np.linspace 0 1 num endpoint True xi np.interp..

Why does numpy.r_ use brackets instead of parentheses?

http://stackoverflow.com/questions/16755482/why-does-numpy-r-use-brackets-instead-of-parentheses

I want to just curious For example the proper syntax is np.r_ '0 2' 1 2 3 4 5 6 I would have expected it to be np.r_ '0 2'.. is np.r_ '0 2' 1 2 3 4 5 6 I would have expected it to be np.r_ '0 2' 1 2 3 4 5 6 python numpy share improve this question.. called __call__ and brackets by implementing __getitem__ . np.r_ happens to be of a class that implements __getitem__ to do fancier..

Fastest way to list all primes below N in python

http://stackoverflow.com/questions/2068372/fastest-way-to-list-all-primes-below-n-in-python

in xrange 3 int n 0.5 1 2 if s m 3 2 s m m 3 2 m 0 return np.r_ 2 s s 0 def primesfrom3to n # http stackoverflow.com questions.. 3 int n 0.5 1 2 if sieve i 2 sieve i i 2 i False return np.r_ 2 2 np.nonzero sieve 0 1 1 def primesfrom2to n # http stackoverflow.com.. k k 3 2 k False sieve k k 4 k 2 k i 1 3 2 k False return np.r_ 2 3 3 np.nonzero sieve 0 1 1 if __name__ '__main__' import itertools..

Python/Matplotlib - Is there a way to make a discontinuous axis?

http://stackoverflow.com/questions/5656798/python-matplotlib-is-there-a-way-to-make-a-discontinuous-axis

as plt import numpy as np # If you're not familiar with np.r_ don't worry too much about this. It's just # a series with points.. 0 to 1 spaced at 0.1 and 9 to 10 with the same spacing. x np.r_ 0 1 0.1 9 10 0.1 y np.sin x fig ax ax2 plt.subplots 1 2 sharey.. as plt import numpy as np # If you're not familiar with np.r_ don't worry too much about this. It's just # a series with points..

Removing duplicate columns and rows from a NumPy 2D array

http://stackoverflow.com/questions/8560440/removing-duplicate-columns-and-rows-from-a-numpy-2d-array

import numpy as np def unique a a np.sort a b np.diff a b np.r_ 1 b return a b 0 Now to extend it to 2d you need to change two..