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46 lines
1.4 KiB
Python
46 lines
1.4 KiB
Python
from wafo.transform.models import TrHermite, TrOchi, TrLinear
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import numpy as np
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from numpy.testing import assert_array_almost_equal
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def test_trhermite():
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std = 7. / 4
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g = TrHermite(sigma=std, ysigma=std)
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assert(np.abs(g.dist2gauss() - 0.88230868748851554) < 1e-7)
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assert(g.mean == 0.0)
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assert(g.sigma == 1.75)
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vals = g.dat2gauss([0, 1, 2, 3])
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true_vals = np.array([0.04654321, 1.03176393, 1.98871279, 2.91930895])
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assert((np.abs(vals - true_vals) < 1e-7).all())
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def test_trochi():
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std = 7. / 4
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g = TrOchi(sigma=std, ysigma=std)
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assert_array_almost_equal(g.dist2gauss(), 1.4106988010566603)
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assert_array_almost_equal(g.mean, 0.0)
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assert_array_almost_equal(g.sigma, 1.75)
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vals = g.dat2gauss([0, 1, 2, 3])
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true_vals = np.array([6.21927960e-04, 9.90237621e-01, 1.96075606e+00,
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2.91254576e+00])
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assert_array_almost_equal(vals, true_vals)
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# assert((np.abs(vals - true_vals) < 1e-7).all())
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def test_trlinear():
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std = 7. / 4
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g = TrLinear(sigma=std, ysigma=std)
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assert(g.dist2gauss() == 0.0)
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assert(g.mean == 0.0)
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assert(g.sigma == 1.75)
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vals = g.dat2gauss([0, 1, 2, 3])
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true_vals = np.array([0., 1., 2., 3.])
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assert((np.abs(vals - true_vals) < 1e-7).all())
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if __name__ == '__main__':
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import nose
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nose.run()
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