autodl-projects/xautodl/datasets/math_dynamic_funcs.py

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#####################################################
# Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2021.03 #
#####################################################
import math
import abc
import copy
import numpy as np
from .math_base_funcs import FitFunc
class DynamicFunc(FitFunc):
"""The dynamic quadratic function, where each param is a function."""
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def __init__(self, freedom: int, params=None, xstr="x"):
if params is not None:
for param in params:
param.reset_xstr("t") if isinstance(param, FitFunc) else None
super(DynamicFunc, self).__init__(freedom, None, params, xstr)
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def __call__(self, x, timestamp):
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raise NotImplementedError
def _getitem(self, x, weights):
raise NotImplementedError
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def noise_call(self, x, timestamp, std):
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clean_y = self.__call__(x, timestamp)
if isinstance(clean_y, np.ndarray):
noise_y = clean_y + np.random.normal(scale=std, size=clean_y.shape)
else:
raise ValueError("Unkonwn type: {:}".format(type(clean_y)))
return noise_y
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class DynamicLinearFunc(DynamicFunc):
"""The dynamic linear function that outputs f(x) = a * x + b.
The a and b is a function of timestamp.
"""
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def __init__(self, params=None, xstr="x"):
super(DynamicLinearFunc, self).__init__(3, params, xstr)
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def __call__(self, x, timestamp):
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a = self._params[0](timestamp)
b = self._params[1](timestamp)
convert_fn = lambda x: x[-1] if isinstance(x, (tuple, list)) else x
a, b = convert_fn(a), convert_fn(b)
return a * x + b
def __repr__(self):
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return "{name}({a} * {x} + {b})".format(
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name=self.__class__.__name__,
a=self._params[0],
b=self._params[1],
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x=self.xstr,
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)
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class DynamicQuadraticFunc(DynamicFunc):
"""The dynamic quadratic function that outputs f(x) = a * x^2 + b * x + c.
The a, b, and c is a function of timestamp.
"""
def __init__(self, params=None):
super(DynamicQuadraticFunc, self).__init__(3, params)
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def __call__(
self,
x,
):
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self.check_valid()
a = self._params[0](timestamp)
b = self._params[1](timestamp)
c = self._params[2](timestamp)
convert_fn = lambda x: x[-1] if isinstance(x, (tuple, list)) else x
a, b, c = convert_fn(a), convert_fn(b), convert_fn(c)
return a * x * x + b * x + c
def __repr__(self):
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return "{name}({a} * x^2 + {b} * x + {c})".format(
name=self.__class__.__name__,
a=self._params[0],
b=self._params[1],
c=self._params[2],
)
class DynamicSinQuadraticFunc(DynamicFunc):
"""The dynamic quadratic function that outputs f(x) = sin(a * x^2 + b * x + c).
The a, b, and c is a function of timestamp.
"""
def __init__(self, params=None):
super(DynamicSinQuadraticFunc, self).__init__(3, params)
def __call__(
self,
x,
):
self.check_valid()
a = self._params[0](timestamp)
b = self._params[1](timestamp)
c = self._params[2](timestamp)
convert_fn = lambda x: x[-1] if isinstance(x, (tuple, list)) else x
a, b, c = convert_fn(a), convert_fn(b), convert_fn(c)
return math.sin(a * x * x + b * x + c)
def __repr__(self):
return "{name}({a} * x^2 + {b} * x + {c})".format(
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name=self.__class__.__name__,
a=self._params[0],
b=self._params[1],
c=self._params[2],
)