63 lines
1.8 KiB
Python
63 lines
1.8 KiB
Python
#####################################################
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# Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2021.03 #
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#####################################################
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import math
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import abc
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import copy
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import numpy as np
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class MathFunc(abc.ABC):
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"""The math function -- a virtual class defining some APIs."""
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def __init__(self, freedom: int, params=None, xstr="x"):
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# initialize as empty
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self._params = dict()
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for i in range(freedom):
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self._params[i] = None
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self._freedom = freedom
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if params is not None:
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self.set(params)
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self._xstr = str(xstr)
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self._skip_check = True
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def set(self, params):
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for key in range(self._freedom):
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param = copy.deepcopy(params[key])
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self._params[key] = param
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def check_valid(self):
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if not self._skip_check:
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for key in range(self._freedom):
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value = self._params[key]
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if value is None:
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raise ValueError("The {:} is None".format(key))
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@property
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def xstr(self):
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return self._xstr
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def reset_xstr(self, xstr):
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self._xstr = str(xstr)
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def output_shape(self, input_shape):
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return input_shape
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@abc.abstractmethod
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def __call__(self, x):
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raise NotImplementedError
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@abc.abstractmethod
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def noise_call(self, x, std):
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clean_y = self.__call__(x)
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if isinstance(clean_y, np.ndarray):
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noise_y = clean_y + np.random.normal(scale=std, size=clean_y.shape)
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else:
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raise ValueError("Unkonwn type: {:}".format(type(clean_y)))
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return noise_y
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def __repr__(self):
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return "{name}(freedom={freedom})".format(
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name=self.__class__.__name__, freedom=freedom
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)
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