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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,163 @@ | ||
| import numpy as np | ||
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| from .combine import StackedIndependentGenerator | ||
|
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| __all__ = ["BoundedGenerator"] | ||
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| class BoundedGenerator(StackedIndependentGenerator): | ||
| def __init__(self, generator, bounds: list): | ||
| self.generator = generator | ||
| self.x_name = self.generator.x_name | ||
| if isinstance(bounds, slice): | ||
| self._latex_bounds = self._slice_bounds_to_latex( | ||
| bounds.start, bounds.stop, bounds.step | ||
| ) | ||
| self.nbounds = (bounds.stop - bounds.start) // bounds.step | ||
|
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| else: | ||
| self._latex_bounds = self._bounds_to_latex(bounds) | ||
| self.nbounds = len(bounds) | ||
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| self.bounds = bounds | ||
| self.fit_mu = None | ||
| self.fit_sigma = None | ||
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| def _bounds_to_latex(self, bounds): | ||
| bound_latex = [ | ||
| f"""\\[b_{{{idx}}}(\\mathbf{{{self.x_name}}}) = | ||
| \\begin{{cases}} | ||
| \\mathbf{{{self.x_name}}}, & \\text{{if }} {bound[0]} < \\mathbf{{{self.x_name}}} \\leq {bound[1]} \\\\ | ||
| 0, & \\text{{otherwise}} | ||
| \\end{{cases}}\\]""" | ||
| for idx, bound in enumerate(bounds) | ||
| ] | ||
| return "\n".join(bound_latex) | ||
|
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| def _slice_bounds_to_latex(self, start, stop, step): | ||
| step_str = f"{step}{{\cdot}}" if step != 1 else "" | ||
| nbounds = (stop - start) // step | ||
| if nbounds < 4: | ||
| def_str1 = "0" | ||
| else: | ||
| def_str1 = ", ".join([f"{s}" for s in np.arange(0, 3)]) | ||
| def_str = f"For $i = {def_str1}, \\ldots, {nbounds} $ define:" | ||
| bound_latex = [ | ||
| f"""b_{{i}}(\\mathbf{{{self.x_name}}}) = | ||
| \\begin{{cases}} | ||
| \\mathbf{{{self.x_name}}}, & \\text{{if }} ({start} + {step_str}i) < \\mathbf{{{self.x_name}}} \\leq ({start} + {step_str}(i + 1)) \\\\ | ||
| 0, & \\text{{otherwise}} | ||
| \\end{{cases}}""" | ||
| ] | ||
| return def_str + "\[" + "\n".join(bound_latex) + "\]" | ||
|
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| def __repr__(self): | ||
| str1 = f"{type(self).__name__}({type(self.generator).__name__}({', '.join(list(self.arg_names))}))[n, {self.width}]" | ||
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| return str1 | ||
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| @property | ||
| def mu(self): | ||
| return self.prior_mu if self.fit_mu is None else self.fit_mu | ||
|
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| @property | ||
| def sigma(self): | ||
| return self.prior_sigma if self.fit_sigma is None else self.fit_sigma | ||
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| @property | ||
| def prior_mu(self): | ||
| return np.hstack([self.generator.prior_mu] * self.nbounds) | ||
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| @property | ||
| def prior_sigma(self): | ||
| return np.hstack([self.generator.prior_sigma] * self.nbounds) | ||
|
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| @property | ||
| def arg_names(self): | ||
| return self.generator.arg_names | ||
|
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| @property | ||
| def width(self): | ||
| return self.generator.width * self.nbounds | ||
|
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| @property | ||
| def _equation(self): | ||
| eqn = ["b_{i}(" + eqn + ")" for eqn in self.generator._equation] | ||
| return eqn | ||
|
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| @property | ||
| def equation(self): | ||
| func_signature = ", ".join([f"\\mathbf{{{a}}}" for a in self.arg_names]) | ||
| n = self.nbounds | ||
| return ( | ||
| f"\\[f({func_signature}) = " | ||
| + " + ".join( | ||
| [ | ||
| f"\\sum_{{i=0}}^{{{n}}} w_{{{{i}}, {coeff} }} {e}" | ||
| for coeff, e in enumerate(self._equation) | ||
| ] | ||
| ) | ||
| + "\\]" | ||
| ) | ||
|
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| def to_latex(self): | ||
| return "\n".join([self._latex_bounds, self.equation, self._to_latex_table()]) | ||
|
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| def design_matrix(self, *args, **kwargs): | ||
| if not self.arg_names.issubset(set(kwargs.keys())): | ||
| raise ValueError(f"Expected {self.arg_names} to be passed.") | ||
| x = kwargs.get(self.x_name) | ||
| if isinstance(self.bounds, slice): | ||
| bounds_list = [ | ||
| (a, a + self.bounds.step) | ||
| for a in np.arange( | ||
| self.bounds.start, self.bounds.stop, self.bounds.step | ||
| ) | ||
| ] | ||
| else: | ||
| bounds_list = self.bounds | ||
| return np.hstack( | ||
| [ | ||
| self.generator.design_matrix(x=x) * ((x >= b[0]) & (x < b[1]))[:, None] | ||
| for b in bounds_list | ||
| ] | ||
| ) | ||
|
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| def fit(self, *args, **kwargs): | ||
| self.fit_mu, self.fit_sigma = self._fit(*args, **kwargs) | ||
|
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| @property | ||
| def table_properties(self): | ||
| return [ | ||
| ( | ||
| "w_{{{i}, {idx}}}", | ||
| (self.mu[idx], self.sigma[idx]), | ||
| (self.prior_mu[idx], self.prior_sigma[idx]), | ||
| ) | ||
| for idx in range(self.width) | ||
| ] | ||
|
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| def _to_latex_table(self): | ||
| latex_table = "\\begin{table}[h!]\n\\centering\n" | ||
| latex_table += "\\begin{tabular}{|c|c|c|}\n\\hline\n" | ||
| latex_table += "Coefficient & Best Fit & Prior \\\\\\hline\n" | ||
| idx = 0 | ||
| for tm in self._get_table_matter(): | ||
| latex_table += tm.format( | ||
| idx=idx % self.nbounds, i=(idx - (idx % self.nbounds)) // self.nbounds | ||
| ) | ||
| idx += 1 | ||
| latex_table += "\\end{tabular}\n\\end{table}" | ||
| return latex_table | ||
|
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| def __getitem__(self, key): | ||
| g = self.generator.copy() | ||
| attrs = ["fit_mu", "fit_sigma"] | ||
| for attr in attrs: | ||
| setattr( | ||
| g, attr, getattr(self, attr).reshape((self.nbounds, len(self)))[key] | ||
| ) | ||
| return g | ||
|
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| def __len__(self): | ||
| return self.width // self.nbounds |
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