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39 lines
1.0 KiB
Python
39 lines
1.0 KiB
Python
# Copyright Jim Bosch 2010-2012.
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# Distributed under the Boost Software License, Version 1.0.
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# (See accompanying file LICENSE_1_0.txt or copy at
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# http://www.boost.org/LICENSE_1_0.txt)
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from __future__ import print_function
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import numpy
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import gaussian
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mu = numpy.zeros(2, dtype=float)
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sigma = numpy.identity(2, dtype=float)
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sigma[0, 1] = 0.15
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sigma[1, 0] = 0.15
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g = gaussian.bivariate_gaussian(mu, sigma)
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r = numpy.linspace(-40, 40, 1001)
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x, y = numpy.meshgrid(r, r)
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z = g(x, y)
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s = z.sum() * (r[1] - r[0])**2
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print("sum (should be ~ 1):", s)
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xc = (z * x).sum() / z.sum()
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print("x centroid (should be ~ %f): %f" % (mu[0], xc))
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yc = (z * y).sum() / z.sum()
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print("y centroid (should be ~ %f): %f" % (mu[1], yc))
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xx = (z * (x - xc)**2).sum() / z.sum()
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print("xx moment (should be ~ %f): %f" % (sigma[0,0], xx))
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yy = (z * (y - yc)**2).sum() / z.sum()
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print("yy moment (should be ~ %f): %f" % (sigma[1,1], yy))
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xy = 0.5 * (z * (x - xc) * (y - yc)).sum() / z.sum()
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print("xy moment (should be ~ %f): %f" % (sigma[0,1], xy))
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