Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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116 lines
3.8 KiB
116 lines
3.8 KiB
4 years ago
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import numpy.polynomial as poly
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from numpy.testing import assert_equal
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class TestStr:
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def test_polynomial_str(self):
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res = str(poly.Polynomial([0, 1]))
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tgt = 'poly([0. 1.])'
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assert_equal(res, tgt)
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def test_chebyshev_str(self):
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res = str(poly.Chebyshev([0, 1]))
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tgt = 'cheb([0. 1.])'
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assert_equal(res, tgt)
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def test_legendre_str(self):
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res = str(poly.Legendre([0, 1]))
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tgt = 'leg([0. 1.])'
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assert_equal(res, tgt)
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def test_hermite_str(self):
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res = str(poly.Hermite([0, 1]))
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tgt = 'herm([0. 1.])'
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assert_equal(res, tgt)
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def test_hermiteE_str(self):
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res = str(poly.HermiteE([0, 1]))
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tgt = 'herme([0. 1.])'
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assert_equal(res, tgt)
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def test_laguerre_str(self):
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res = str(poly.Laguerre([0, 1]))
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tgt = 'lag([0. 1.])'
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assert_equal(res, tgt)
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class TestRepr:
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def test_polynomial_str(self):
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res = repr(poly.Polynomial([0, 1]))
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tgt = 'Polynomial([0., 1.], domain=[-1, 1], window=[-1, 1])'
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assert_equal(res, tgt)
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def test_chebyshev_str(self):
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res = repr(poly.Chebyshev([0, 1]))
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tgt = 'Chebyshev([0., 1.], domain=[-1, 1], window=[-1, 1])'
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assert_equal(res, tgt)
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def test_legendre_repr(self):
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res = repr(poly.Legendre([0, 1]))
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tgt = 'Legendre([0., 1.], domain=[-1, 1], window=[-1, 1])'
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assert_equal(res, tgt)
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def test_hermite_repr(self):
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res = repr(poly.Hermite([0, 1]))
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tgt = 'Hermite([0., 1.], domain=[-1, 1], window=[-1, 1])'
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assert_equal(res, tgt)
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def test_hermiteE_repr(self):
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res = repr(poly.HermiteE([0, 1]))
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tgt = 'HermiteE([0., 1.], domain=[-1, 1], window=[-1, 1])'
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assert_equal(res, tgt)
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def test_laguerre_repr(self):
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res = repr(poly.Laguerre([0, 1]))
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tgt = 'Laguerre([0., 1.], domain=[0, 1], window=[0, 1])'
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assert_equal(res, tgt)
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class TestLatexRepr:
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"""Test the latex repr used by Jupyter"""
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def as_latex(self, obj):
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# right now we ignore the formatting of scalars in our tests, since
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# it makes them too verbose. Ideally, the formatting of scalars will
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# be fixed such that tests below continue to pass
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obj._repr_latex_scalar = lambda x: str(x)
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try:
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return obj._repr_latex_()
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finally:
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del obj._repr_latex_scalar
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def test_simple_polynomial(self):
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# default input
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p = poly.Polynomial([1, 2, 3])
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assert_equal(self.as_latex(p),
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r'$x \mapsto 1.0 + 2.0\,x + 3.0\,x^{2}$')
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# translated input
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p = poly.Polynomial([1, 2, 3], domain=[-2, 0])
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assert_equal(self.as_latex(p),
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r'$x \mapsto 1.0 + 2.0\,\left(1.0 + x\right) + 3.0\,\left(1.0 + x\right)^{2}$')
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# scaled input
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p = poly.Polynomial([1, 2, 3], domain=[-0.5, 0.5])
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assert_equal(self.as_latex(p),
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r'$x \mapsto 1.0 + 2.0\,\left(2.0x\right) + 3.0\,\left(2.0x\right)^{2}$')
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# affine input
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p = poly.Polynomial([1, 2, 3], domain=[-1, 0])
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assert_equal(self.as_latex(p),
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r'$x \mapsto 1.0 + 2.0\,\left(1.0 + 2.0x\right) + 3.0\,\left(1.0 + 2.0x\right)^{2}$')
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def test_basis_func(self):
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p = poly.Chebyshev([1, 2, 3])
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assert_equal(self.as_latex(p),
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r'$x \mapsto 1.0\,{T}_{0}(x) + 2.0\,{T}_{1}(x) + 3.0\,{T}_{2}(x)$')
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# affine input - check no surplus parens are added
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p = poly.Chebyshev([1, 2, 3], domain=[-1, 0])
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assert_equal(self.as_latex(p),
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r'$x \mapsto 1.0\,{T}_{0}(1.0 + 2.0x) + 2.0\,{T}_{1}(1.0 + 2.0x) + 3.0\,{T}_{2}(1.0 + 2.0x)$')
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def test_multichar_basis_func(self):
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p = poly.HermiteE([1, 2, 3])
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assert_equal(self.as_latex(p),
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r'$x \mapsto 1.0\,{He}_{0}(x) + 2.0\,{He}_{1}(x) + 3.0\,{He}_{2}(x)$')
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