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python Programming Glossary: numpy.random.rand

Parallel mapping functions in IPython w/ multiple parameters

http://stackoverflow.com/questions/11371009/parallel-mapping-functions-in-ipython-w-multiple-parameters

arg0 arg0 ... modules 'numpy scipy' examples func lambda x numpy.random.rand 2. z parallel.map r_ 0 1000 func modules 'numpy numpy.random'..

Heatmap in matplotlib with pcolor?

http://stackoverflow.com/questions/14391959/heatmap-in-matplotlib-with-pcolor

column_labels list 'ABCD' row_labels list 'WXYZ' data numpy.random.rand 4 4 Making the heatmap is easy enough in matplotlib from matplotlib..

Share Large, Read-Only Numpy Array Between Multiprocessing Processes

http://stackoverflow.com/questions/17785275/share-large-read-only-numpy-array-between-multiprocessing-processes

num n 20 width n num shared sharedmem.empty n shared numpy.random.rand 1 n 0 print values are s shared processes Process target do_work..

Scipy sparse… arrays?

http://stackoverflow.com/questions/2540059/scipy-sparse-arrays

timings via ipython import numpy scipy.sparse n 100000 x numpy.random.rand n 2 .astype int .astype float # 50 sparse vector x_csr scipy.sparse.csr_matrix..

matplotlib show() doesn't work twice

http://stackoverflow.com/questions/5524858/matplotlib-show-doesnt-work-twice

same figure. import numpy from pylab import figure show X numpy.random.rand 100 1000 xs numpy.mean X axis 1 ys numpy.std X axis 1 fig figure..

Benchmarking (python vs. c++ using BLAS) and (numpy)

http://stackoverflow.com/questions/7596612/benchmarking-python-vs-c-using-blas-and-numpy

of 5 and the matricies m1 and m2 are set up like this m1 numpy.random.rand i i .astype numpy.float32 m2 numpy.random.rand i i .astype numpy.float32.. this m1 numpy.random.rand i i .astype numpy.float32 m2 numpy.random.rand i i .astype numpy.float32 1. Numpy The code used looks like..

How to hash a large object (dataset) in Python?

http://stackoverflow.com/questions/806151/how-to-hash-a-large-object-dataset-in-python

updating using the array import hashlib import numpy a numpy.random.rand 10 100 b a.view numpy.uint8 print a.dtype b.dtype # a and b..