I am trying to speed up my Python by translating it into Cython. It uses the function scipy.integrate.quad, which requires a python callable as one of its arguments. Is there any way 开发者_StackOverf
Profiling some computational work I\'m doing showed me that one bottleneck in my program was a function that basically did this (np is numpy, sp is scipy):
In my python environment, the Rpy and Scipy packages are already installed. The pr开发者_开发技巧oblem I want to tackle is such:
I am using the following code which I have found online def c_int_binary_search(seq,t): # do a little type checking in Python
I am new to Python, so forgive me ahead of time if this is an elementary question, but I have searched around and have not found a satisfying answer.
I am 开发者_如何学JAVAcurrently using numpy.polyfit(x,y,deg) to fit a polynomial to experimental data. I would however like to fit a polynomial that uses weighting based on the errors of the points.
I am attempting to generate map overlay images that would assist in identifying hot-spots, that is areas on the map that have high density of data points. None of the approaches that I\'ve tried are f
M开发者_运维百科ATLAB has a nice silhouette function to help evaluate the number of clusters for k-means. Is there an equivalent for Python\'s Numpy/Scipy as well?I present below a sample silhouette i
I need to input 3, 3D points as a matrix into this function; so I made a tuple like this one: initPoints = ([10,20,30],[5,15,25],[100,150,200])
I have a pointlist=[p1,p2,p3...] where p1 = [x1,y1],p2=[x2,y2] ... I want to use scipy.spatial.Delaunay to do trianglation on these point clouds and then plot it
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