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python Programming Glossary: cols

How can I parse the output of /proc/net/dev into key:value pairs per interface using Python?

http://stackoverflow.com/questions/1052589/how-can-i-parse-the-output-of-proc-net-dev-into-keyvalue-pairs-per-interface-u

transmitCols map lambda a trans_ a transmitCols.split cols receiveCols transmitCols faces for line in lines 2 if line.find.. 0 continue face data line.split faceData dict zip cols data.split faces face faceData import pprint pprint.pprint faces..

Using numpy.take for faster fancy indexing

http://stackoverflow.com/questions/14491480/using-numpy-take-for-faster-fancy-indexing

of shape planes 256 n and the image has shape planes rows cols . Both are of dtype 'uint8' matching the 256 axis of the LUT... the LUT. If my lut and img are the following planes rows cols n 3 4000 4000 4 lut np.random.randint 2 31 2 31 1 size planes.. 256 n img np.random.randint 2 31 2 31 1 size planes rows cols 4 .view 'uint8' img img.reshape planes rows cols I can achieve..

sscanf in Python

http://stackoverflow.com/questions/2175080/sscanf-in-python

whole lines open proc net dev .readlines for l in lines 2 cols l.split string.whitespace print len cols 1 Which should be.. for l in lines 2 cols l.split string.whitespace print len cols 1 Which should be returning 17 as explained above. Is there..

How can I efficiently process a numpy array in blocks similar to Matlab's blkproc (blockproc) function

http://stackoverflow.com/questions/5073767/how-can-i-efficiently-process-a-numpy-array-in-blocks-similar-to-matlabs-blkpro

0 0 fun None rows for i in range 0 M.shape 0 blk_size 0 cols for j in range 0 M.shape 1 blk_size 1 cols.append fun M i i.. 0 blk_size 0 cols for j in range 0 M.shape 1 blk_size 1 cols.append fun M i i blk_size 0 j j blk_size 1 rows.append np.concatenate.. M i i blk_size 0 j j blk_size 1 rows.append np.concatenate cols axis 1 return np.concatenate rows axis 0 R np.random.rand 128..

Python/Scipy 2D Interpolation (Non-uniform Data)

http://stackoverflow.com/questions/5146025/python-scipy-2d-interpolation-non-uniform-data

# 1.0000 1.0000 1.0000 1.0000 # Rows Columns z.shape cols array 0.0000 0.1750 0.8170 1.0000 rows array 0.0000 0.2620 0.6121.. 0.6121 1.0000 sp interpolate.RectBivariateSpline rows cols z kx 1 ky 1 s 0 xi np.array 0.00000 0.26200 0.27840 0.33790.. 0.6121 0.6351 0.7118 0.7309 1.0000 1.0000 1.0000 1.0000 cols array 0.0000 0.1750 0.8180 1.0000 0.0000 0.1750 0.8180 1.0000..