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CCD now outputs in all param dimensions, including those that aren't transformed
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1 changed files with 16 additions and 4 deletions
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@ -199,12 +199,24 @@ class Model(ParamzModel, Priorizable):
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import paramz
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import paramz
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transformed_points = param_points.copy()
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transformed_points = param_points.copy()
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print transformed_points, point_densities
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#alan's original code to transform those parameters, to the true space of parameters again
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#mike's change: some parameters have no transform, and thus won't be called by any of the
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# Need to transform the points to the space of parameters again
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#iterations through m2.constraints.items(). To handle these we keep track of those parameters
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#not included, and then add them (untransformed) at the end.
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f = np.ones(self.size).astype(bool)
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f = np.ones(self.size).astype(bool)
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f[self.constraints[paramz.transformations.__fixed__]] = paramz.transformations.FIXED
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f[self.constraints[paramz.transformations.__fixed__]] = paramz.transformations.FIXED
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new_t_points = [c.f(transformed_points[:, ind[f[ind]]]) for c, ind in self.constraints.items() if c != paramz.transformations.__fixed__][0]
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new_t_points = []
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todo = range(0,self.size)
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new_t_points = np.zeros_like(transformed_points)
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for c, ind in self.constraints.items():
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print c,ind
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if c != paramz.transformations.__fixed__:
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new_t_points[:,ind] = (c.f(transformed_points[:, ind[f[ind]]]))
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todo.remove(ind)
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for param_ind in todo:
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new_t_points[:,param_ind] = transformed_points[:, param_ind]
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return new_t_points, point_densities
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return new_t_points, point_densities
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