Jul 22, 2010 · numpy.allclose(arr1, arr2) but it's not quite the same. An alternative, almost the same as your example is: numpy.alltrue(arr1 == arr2) Note that scipy.array is actually a …

Feb 28, 2016 · You referenced the array-like paragraph in numpy documentation. Note its typing information: A simple way to find out if the object can be converted to a numpy array using …

Sep 10, 2009 · The first advice is to organize your data such that the arrays have dimension (3, n) (and are C-contiguous obviously). If adding happens in the contiguous first dimension, things …

Using numpy.average. Also numpy.average can be used with the same syntax: import numpy as np a = np.array([np.arange(0,9).reshape(3,3),np.arange(9,18).reshape(3,3)]) averaged_array …

Most of this DB data isn't going to change so I could write a separate python script to update the file every 24 hours and then use that file for this long running task. The data is being returned …

Nov 15, 2015 · np.array(list_of_arrays).ravel() Although, according to docs. When a view is desired in as many cases as possible, arr.reshape(-1) may be preferable. In other words. …

Apr 22, 2017 · For this case, hstack (because second is already 2D) and c_ (because it concatenates along the second axis) would also work.

First, I created a function that takes two arrays and generate an array with all combinations of values from the two arrays: from numpy import * def comb(a, b): c = [] for i in a: for j in b: …

Dec 17, 2014 · In general you can concatenate a whole sequence of arrays along any axis: numpy.concatenate( LIST, axis=0 ) but you do have to worry about the shape and …

May 10, 2015 · I'm expecting the answer to involve numpy and/or scipy. Right now my arrays are numpy arrays, but I'm open to converting them to a different type. I'm expecting my output to …