add namespace to parameter
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3149a3f958
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7a50028202
@ -102,7 +102,7 @@ class Data(object):
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if ub is None:
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ub = model.ub
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self.para_keys = self.parameter.add_parameter(parameter, var=var, lb=lb, ub=ub)
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self.para_keys = self.parameter.add_parameter(parameter, var=var, lb=lb, ub=ub, names=model.params)
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if fun_kwargs is not None:
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self.fun_kwargs.update(fun_kwargs)
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@ -273,8 +273,12 @@ 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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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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@ -9,6 +9,10 @@ import numpy as np
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class Parameters(dict):
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count = count()
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def __init__(self):
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super().__init__()
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self._namespace = {}
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def __str__(self):
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return 'Parameters:\n' + '\n'.join([str(k)+': '+str(v) for k, v in self.items()])
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@ -22,7 +26,7 @@ class Parameters(dict):
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return super().__getitem__(item)
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@staticmethod
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def _prep_bounds(val, p_len: int) -> list:
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def _prep_bounds(val: list, p_len: int) -> list:
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# helper function to ensure that bounds and variable are of parameter shape
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if isinstance(val, (Number, bool)) or val is None:
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return [val] * p_len
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@ -34,10 +38,10 @@ class Parameters(dict):
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return [val[0]] * p_len
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else:
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raise ValueError('Input {} has wrong dimensions'.format(val))
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raise ValueError(f'Input {val} has wrong dimensions')
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def add_parameter(self, param, var=None, lb=None, ub=None):
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if isinstance(param, Number):
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def add_parameter(self, param: float | list[float], var=None, lb=None, ub=None, names=None) -> list:
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if isinstance(param, (float, int)):
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param = [param]
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p_len = len(param)
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@ -50,26 +54,42 @@ class Parameters(dict):
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new_keys = []
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for i in range(p_len):
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new_idx = next(self.count)
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new_keys.append(new_idx)
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self[new_idx] = Parameter(param[i], var=var[i], lb=lb[i], ub=ub[i])
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if names is not None:
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key = names[i]
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else:
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key = f'_p{new_idx}'
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new_keys.append(key)
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self[key] = Parameter(param[i], var=var[i], lb=lb[i], ub=ub[i])
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return new_keys
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def copy(self):
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p = Parameters()
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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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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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par.eval_allowed = False
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self._namespace[name] = par.value
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par.namespace = self._namespace
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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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p[k] = Parameter(v.value, var=v.var, lb=v.lb, ub=v.ub)
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new_para = v.copy()
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new_para_dict.add(new_para)
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if len(p) == 0:
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return p
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# if len(p) == 0:
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# return p
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max_k = max(p.keys())
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c = next(p.count)
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while c < max_k:
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c = next(p.count)
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# max_k = int(max(p.keys(), key=lambda x: int(k[2:]))[2:])
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# c = next(p.count)
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# while c < max_k:
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# c = next(p.count)
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return p
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return new_para_dict
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def get_state(self):
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return {k: v.get_state() for k, v in self.items()}
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@ -79,33 +99,40 @@ class Parameter:
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"""
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Container for one parameter
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"""
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__slots__ = ['name', 'value', 'error', 'init_val', 'var', 'lb', 'ub', 'scale', 'function']
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def __init__(self, value: float, var: bool = True, lb: float = -np.inf, ub: float = np.inf):
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self.lb = lb if lb is not None else -np.inf
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self.ub = ub if ub is not None else np.inf
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if self.lb <= value <= self.ub:
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self.value = value
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else:
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print(value, self.lb, self.ub)
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raise ValueError('Value of parameter is outside bounds')
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self.init_val = value
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with np.errstate(divide='ignore'):
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# throws RuntimeWarning for zeros
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self.scale = 10**(np.floor(np.log10(np.abs(self.value))))
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if self.scale == 0:
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self.scale = 1.
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def __init__(self, name: str, value: float | str, var: bool = True, lb: float = -np.inf, ub: float = np.inf):
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self.scale = 1
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self.var = bool(var) if var is not None else True
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self.error = None if self.var is False else 0.0
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self.name = ''
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self.name = name
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self.function = ''
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self.lb = lb if lb is not None else -np.inf
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self.ub = ub if ub is not None else np.inf
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self._value = None
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self.namespace = None
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self.eval_allowed = True
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self._expr = None
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def __str__(self):
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if isinstance(value, str):
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self._expr = value
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self.var = False
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else:
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if self.lb <= value <= self.ub:
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self._value = value
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else:
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raise ValueError('Value of parameter is outside bounds')
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self.init_val = value
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with np.errstate(divide='ignore'):
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# throws RuntimeWarning for zeros
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self.scale = 10**(np.floor(np.log10(np.abs(self.value))))
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if self.scale == 0:
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self.scale = 1.
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def __str__(self) -> str:
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start = ''
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if self.name:
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if self.function:
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@ -116,9 +143,15 @@ class Parameter:
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if self.var:
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return start + f'{self.value:.4g} +/- {self.error:.4g}, init={self.init_val}'
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else:
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return start + f'{self.value:} (fixed)'
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ret_string = start + f'{self.value:}'
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if self._expr is None:
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ret_string += ' (fixed)'
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else:
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ret_string += f' (calc: {self._expr})'
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def __add__(self, other: Parameter | float) -> float:
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return ret_string
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def __add__(self, other: Parameter | float | int) -> float:
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if isinstance(other, (float, int)):
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return self.value + other
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elif isinstance(other, Parameter):
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@ -132,8 +165,15 @@ class Parameter:
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return self.value / self.scale
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@scaled_value.setter
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def scaled_value(self, value):
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self.value = value * self.scale
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def scaled_value(self, value: float):
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self._value = value * self.scale
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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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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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@property
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def scaled_error(self):
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@ -148,7 +188,7 @@ class Parameter:
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def get_state(self):
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return {slot: getattr(self, slot) for slot in self.__slots__}
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return {slot: getattr(self, slot) for slot in self.__slots__}
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@staticmethod
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def set_state(state: dict):
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@ -165,3 +205,12 @@ class Parameter:
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name += ' (' + self.function + ')'
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return name
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def copy(self) -> Parameter:
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if self._expr:
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val = self._expr
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else:
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val = self._value
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para_copy = Parameter(name=self.name, value=val, var=self.var, lb=self.lb, ub=self.ub)
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return para_copy
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