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python Programming Glossary: numpy.sum

Counting of adjacent cells in a numpy array

http://stackoverflow.com/questions/12612663/counting-of-adjacent-cells-in-a-numpy-array

scipy.signal.convolve2d b numpy.ones 3 3 mode 'same' print numpy.sum c a b 1 a allows us to count each zero while ignoring the ones...

How to calculate the sum of all columns of a 2D numpy array (efficiently)

http://stackoverflow.com/questions/13567345/how-to-calculate-the-sum-of-all-columns-of-a-2d-numpy-array-efficiently

improve this question Check out the documentation for numpy.sum paying particular attention to the axis parameter. To sum over..

How to make several plots on a single page using matplotlib?

http://stackoverflow.com/questions/1358977/how-to-make-several-plots-on-a-single-page-using-matplotlib

7 defaultreallimits 10 60 bins numpy.arange 10 60 10 print numpy.sum relpdf 0 print bins patches plt.bar bins relpdf 0 width 10 facecolor..

Comparing image in url to image in filesystem in python

http://stackoverflow.com/questions/13875989/comparing-image-in-url-to-image-in-filesystem-in-python

ki 0 return None None c1 k 0 l 2 c2 k 1 l 2 window window numpy.sum window mu1 fftconvolve im1 window mode 'valid' mu2 fftconvolve.. ssim_map def nrmse im1 im2 a b im1.shape rmse numpy.sqrt numpy.sum im2 im1 2 float a b max_val max numpy.max im1 numpy.max im2..

Euclidean distance between points in two different Numpy arrays, not within

http://stackoverflow.com/questions/1871536/euclidean-distance-between-points-in-two-different-numpy-arrays-not-within

len xy1 for i xy in enumerate xy1 dists numpy.sqrt numpy.sum xy xy2 2 axis 1 mindist i minid i dists.min dists.argmin Is..

Using strides for an efficient moving average filter

http://stackoverflow.com/questions/4936620/using-strides-for-an-efficient-moving-average-filter

1 if i 0 b numpy.roll b pow filtsize 2 1 i 0 filtered numpy.sum b 1 pow filtsize 2 .reshape a.shape 0 a.shape 1 scipy.misc.imsave..

Fast check for NaN in NumPy

http://stackoverflow.com/questions/6736590/fast-check-for-nan-in-numpy

good. However on my machine it is about 2.5x faster to use numpy.sum in place of numpy.min In 13 timeit np.isnan np.min x 1000 loops..

How do I calculate r-squared using Python and Numpy?

http://stackoverflow.com/questions/893657/how-do-i-calculate-r-squared-using-python-and-numpy

# fit values and mean yhat p x # or p z for z in x ybar numpy.sum y len y # or sum y len y ssreg numpy.sum yhat ybar 2 # or sum.. z for z in x ybar numpy.sum y len y # or sum y len y ssreg numpy.sum yhat ybar 2 # or sum yihat ybar 2 for yihat in yhat sstot numpy.sum.. yhat ybar 2 # or sum yihat ybar 2 for yihat in yhat sstot numpy.sum y ybar 2 # or sum yi ybar 2 for yi in y results 'determination'..