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Fixed more errors in docs 2
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15 changed files with 99 additions and 84 deletions
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@ -53,9 +53,11 @@ class TanhWarpingFunction(WarpingFunction):
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self.num_parameters = 3 * self.n_terms
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def f(self,y,psi):
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"""transform y with f using parameter vector psi
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"""
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transform y with f using parameter vector psi
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psi = [[a,b,c]]
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f = \sum_{terms} a * tanh(b*(y+c))
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::math::`f = \\sum_{terms} a * tanh(b*(y+c))`
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"""
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#1. check that number of params is consistent
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@ -77,8 +79,7 @@ class TanhWarpingFunction(WarpingFunction):
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"""
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calculate the numerical inverse of f
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== input ==
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iterations: number of N.R. iterations
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:param iterations: number of N.R. iterations
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"""
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@ -165,9 +166,11 @@ class TanhWarpingFunction_d(WarpingFunction):
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self.num_parameters = 3 * self.n_terms + 1
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def f(self,y,psi):
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"""transform y with f using parameter vector psi
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"""
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Transform y with f using parameter vector psi
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psi = [[a,b,c]]
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f = \sum_{terms} a * tanh(b*(y+c))
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:math:`f = \\sum_{terms} a * tanh(b*(y+c))`
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"""
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#1. check that number of params is consistent
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@ -189,8 +192,7 @@ class TanhWarpingFunction_d(WarpingFunction):
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"""
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calculate the numerical inverse of f
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== input ==
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iterations: number of N.R. iterations
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:param max_iterations: maximum number of N.R. iterations
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"""
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@ -214,12 +216,13 @@ class TanhWarpingFunction_d(WarpingFunction):
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def fgrad_y(self, y, psi, return_precalc = False):
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"""
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gradient of f w.r.t to y ([N x 1])
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returns: Nx1 vector of derivatives, unless return_precalc is true,
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then it also returns the precomputed stuff
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:returns: Nx1 vector of derivatives, unless return_precalc is true, then it also returns the precomputed stuff
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"""
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mpsi = psi.copy()
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mpsi = psi.coSpy()
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d = psi[-1]
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mpsi = mpsi[:self.num_parameters-1].reshape(self.n_terms, 3)
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@ -242,7 +245,7 @@ class TanhWarpingFunction_d(WarpingFunction):
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"""
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gradient of f w.r.t to y and psi
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returns: NxIx4 tensor of partial derivatives
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:returns: NxIx4 tensor of partial derivatives
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"""
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