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on
Zero
Running
on
Zero
File size: 930 Bytes
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from functools import reduce
from itertools import cycle
from math import factorial
import numpy as np
import scipy.sparse as sp
def difference(derivative, accuracy=1):
# Central differences implemented based on the article here:
# http://web.media.mit.edu/~crtaylor/calculator.html
derivative += 1
radius = accuracy + derivative // 2 - 1
points = range(-radius, radius + 1)
coefficients = np.linalg.inv(np.vander(points))
return coefficients[-derivative] * factorial(derivative - 1), points
def operator(shape, *differences):
# Credit to Philip Zucker for figuring out
# that kronsum's argument order is reversed.
# Without that bit of wisdom I'd have lost it.
differences = zip(shape, cycle(differences))
factors = (sp.diags(*diff, shape=(dim,) * 2) for dim, diff in differences)
return reduce(lambda a, f: sp.kronsum(f, a, format='csc'), factors) |