I have an array like: a = array([[1,2,3],[3,4,5],[4,5,6]]) What\'s the most effi开发者_运维百科cient way to slice out a 1x2 array out of this that has only the first two columns of \"a\"?
I have a scipy.sparse.dok_matrix (dimensions m x n), wanting to add a flat numpy-array with length m.
I have an array with two columns in numpy. For example: a = array([[1, 5, nan, 6], [10, 6, 6, nan]]) a = transpose(a)
I am trying to plot the following numbers on a log scale as a scatter plot in matplotlib.Both the quantities on the x and y axes have very different scales, and one of the variables has a huge dynamic
I\'m trying to vectorize a for loop that I have inside of a class method. The for loop has the following form: it iterates through a bunch of points and depending on whether a certain variable (called
I am fitting a Gaussian kernel density estimator to a variable that is t开发者_如何学运维he difference of two vectors, called \"diff\", as follows: gaussian_kde_covfact(diff, smoothing_param) -- where
There is a nonzero() method for the csr_matrix of scipy library, however trying to use th开发者_开发百科at function for csr matrices result in an error, according to the manual that should return a tu
What\'s wrong with this snippet of code? import numpy as np from scipy import stats d = np.arange(10.0) cutoffs = [stats.scoreatpercentile(d, pct) for pct in range(0, 100, 20)]
I have a NumPy array [1,2,3,4,5,6,7,8,9,开发者_如何学Python10,11,12,13,14] and want to have an array structured like [[1,2,3,4], [2,3,4,5], [3,4,5,6], ..., [11,12,13,14]].
So, I\'m doing some Kmeans classification using numpy arrays that are quite sparse-- lots and lots of zeroes.I figured that I\'d use scipy\'s \'sparse\' package to reduce the storage overhead, but I\'
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