Numpy’s meshgrid is very useful for converting two vectors to a coordinate grid. What is the easiest way to extend this to three dimensions? So given three vectors x, y, and z, construct 3x3D arrays (instead of 2x2D arrays) which can be used as coordinates.
I have the following code which is attempting to normalize the values of an m x n array (It will be used as input to a neural network, where m is the number of training examples and n is the number of features).
SciPy appears to provide most (but not all [1]) of NumPy’s functions in its own namespace. In other words, if there’s a function named numpy.foo, there’s almost certainly a scipy.foo. Most of the time, the two appear to be exactly the same, oftentimes even pointing to the same function object.
I’m using Python and Numpy to calculate a best fit polynomial of arbitrary degree. I pass a list of x values, y values, and the degree of the polynomial I want to fit (linear, quadratic, etc.).
I am trying to calculate a distance matrix for a long list of locations identified by Latitude & Longitude using the Haversine formula that takes two tuples of coordinate pairs to produce the distance:
From Numpy’s tutorial, axis can be indexed with integers, like 0 is for column, 1 is for row, but I don’t grasp why they are indexed this way? And How do I figure out each axis’ index when coping with multidimensional array?
I have looked into documentations and also other questions here, but it seems I
have not got the hang of subsetting in numpy arrays yet.
After many attempts trying optimize code, it seems that one last resource would be to attempt to run the code below using multiple cores. I don’t know exactly how to convert/re-structure my code so that it can run much faster using multiple cores. I will appreciate if I could get guidance to achieve the end goal. The end goal is to be able to run this code as fast as possible for arrays A and B where each array holds about 700,000 elements. Here is the code using small arrays. The 700k element arrays are commented out.
I have two large sets of 2D points and I need to calculate a distance matrix.
I have a large array where each row is a time series and thus needs to stay in order.