eval parameter
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@ -103,7 +103,7 @@ class FitRoutine(object):
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linked_sender[v] = set()
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self.parameter.update(v.parameter.copy())
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# set temporaray model
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# set temporary model
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if v.model is None:
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v.model = self.fit_model
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self._no_own_model.append(v)
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@ -111,9 +111,9 @@ class FitRoutine(object):
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# register model
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if v.model not in _found_models:
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_found_models[v.model] = []
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m_param = v.model.parameter.copy()
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self.parameter.update(m_param)
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# m_param = v.model.parameter.copy()
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# self.parameter.update(m_param)
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#
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_found_models[v.model].append(v)
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if v.model not in linked_sender:
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@ -208,6 +208,7 @@ class FitRoutine(object):
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return self.result
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def _prep_data(self, data):
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if data.get_model() is None:
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data._model = self.fit_model
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self._no_own_model.append(data)
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@ -273,12 +274,9 @@ class FitRoutine(object):
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def __cost_scipy(self, p, data, varpars, used_pars):
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for keys, values in zip(varpars, p):
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self.parameter[keys].scaled_value = values
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self.parameter._namespace[keys] = self.parameter[keys].scaled_value
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print(id(self.parameter._namespace), id(self.parameter[keys].namespace))
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self.parameter[keys].namespace[keys] = self.parameter[keys].value
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actual_parameters = [self.parameter[keys].value for keys in used_pars]
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print(actual_parameters)
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return data.cost(actual_parameters)
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def __cost_odr(self, p, data, varpars, used_pars):
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@ -66,6 +66,7 @@ class Parameters(dict):
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def add(self, name: str | Parameter, value: str | float | int = None, *, var=True, lb=-np.inf, ub=np.inf):
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if isinstance(name, Parameter):
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par = name
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name = par.name
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else:
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par = Parameter(name=name, value=value, var=var, lb=lb, ub=ub)
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self[name] = par
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@ -75,7 +76,6 @@ class Parameters(dict):
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par.eval_allowed = True
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def copy(self) -> Parameters:
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print('huhuuhuh')
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new_para_dict = Parameters()
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for k, v in self.items():
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new_para = v.copy()
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@ -171,6 +171,8 @@ class Parameter:
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@property
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def value(self) -> float:
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if self._expr is not None and self.eval_allowed:
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print(self._expr, self.namespace)
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print(eval(self._expr, self.namespace))
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return eval(self._expr, self.namespace)
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elif self._value is not None:
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return self._value
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@ -35,8 +35,8 @@ class Gaussian:
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class Lorentzian:
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type = 'Spectrum'
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name = 'Lorentzian'
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equation = 'A (2/\pi)w/[4*(x-\mu)^{2} + w^{2}] + A_{0}'
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params = ['A', '\mu', 'w', 'A_{0}']
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equation = r'A (2/\pi)w/[4*(x-\mu)^{2} + w^{2}] + A_{0}'
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params = ['A', r'\mu', 'w', 'A_{0}']
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ext_params = None
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bounds = [(0, None), (None, None), (0, None), (None, None)]
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@ -56,15 +56,16 @@ class Lorentzian:
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off (float): baseline
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"""
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print('Lorentzian', a, mu, sigma, off)
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return (a/np.pi) * 2*sigma / (4*(x-mu)**2 + sigma**2) + off
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class PseudoVoigt:
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type = 'Spectrum'
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name = 'Pseudo Voigt'
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equation = 'A [R*2/\pi*w/[4*(x-\mu)^{2} + w^{2}] + ' \
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'(1-R)*sqrt(4*ln(2)/pi)/w*exp(-4*ln(2)[(x-\mu)/w]^{2})] + A_{0}'
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params = ['A', 'R', '\mu', 'w', 'A_{0}']
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equation = r'A [R*2/\pi*w/[4*(x-\mu)^{2} + w^{2}] + ' \
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r'(1-R)*sqrt(4*ln(2)/pi)/w*exp(-4*ln(2)[(x-\mu)/w]^{2})] + A_{0}'
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params = ['A', 'R', r'\mu', 'w', 'A_{0}']
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ext_params = None
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bounds = [(0, None), (0, 1), (None, None), (0, None)]
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