Which either means that my code is stupid or scipy is extremely well made. SciPy produces the exact same result in blink of the eye. My python code takes like 5 minutes to complete on 3000 vertices, while searing my CPU. Newer versions of fastdist (> 1.0.0) also add partial implementations of trics which also show significant speed improvements. fastdist is a replacement for that shows significant speed improvements by using numba and some optimization. Is my approach too simpleminded and naive and scipy uses some hardcore advanced mathematics, which i am not aware of? Or can it be many times faster just because the same algorithm is written in C and then called by scipy from python? fastdist: Faster distance calculations in python using numba. This sourceforge project contains only old. NOTE: the project has moved to - go there to find latest versions. #(_("Calculating distance %d of %d (SciPy not installed => using SLOW AF fallback method)"%(i,len(verts))), True) for j in range( i, len( verts)):ĭ = D = self. Download SciPy: Scientific Library for Python for free. empty(( len( verts), len( verts)), dtype = np. # Pairwise distance between verts #Use SciPy, otherwise use fallback try:
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