87 lines
2.8 KiB
Python
87 lines
2.8 KiB
Python
|
#####################################################
|
||
|
|
# Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2021.03 #
|
||
|
|
#####################################################
|
||
|
|
import math
|
||
|
|
import abc
|
||
|
|
import copy
|
||
|
|
import numpy as np
|
||
|
|
from typing import Optional
|
||
|
|
import torch
|
||
|
|
import torch.utils.data as data
|
||
|
|
|
||
|
|
from .math_base_funcs import FitFunc
|
||
|
|
from .math_base_funcs import QuadraticFunc
|
||
|
|
from .math_base_funcs import QuarticFunc
|
||
|
|
|
||
|
|
|
||
|
|
class ConstantFunc(FitFunc):
|
||
|
|
"""The constant function: f(x) = c."""
|
||
|
|
|
||
|
|
def __init__(self, constant=None):
|
||
|
|
param = dict()
|
||
|
|
param[0] = constant
|
||
|
|
super(ConstantFunc, self).__init__(0, None, param)
|
||
|
|
|
||
|
|
def __call__(self, x):
|
||
|
|
self.check_valid()
|
||
|
|
return self._params[0]
|
||
|
|
|
||
|
|
def fit(self, **kwargs):
|
||
|
|
raise NotImplementedError
|
||
|
|
|
||
|
|
def _getitem(self, x, weights):
|
||
|
|
raise NotImplementedError
|
||
|
|
|
||
|
|
def __repr__(self):
|
||
|
|
return "{name}({a})".format(name=self.__class__.__name__, a=self._params[0])
|
||
|
|
|
||
|
|
|
||
|
|
class ComposedSinFunc(FitFunc):
|
||
|
|
"""The composed sin function that outputs:
|
||
|
|
f(x) = amplitude-scale-of(x) * sin( period-phase-shift-of(x) )
|
||
|
|
- the amplitude scale is a quadratic function of x
|
||
|
|
- the period-phase-shift is another quadratic function of x
|
||
|
|
"""
|
||
|
|
|
||
|
|
def __init__(self, **kwargs):
|
||
|
|
super(ComposedSinFunc, self).__init__(0, None)
|
||
|
|
self.fit(**kwargs)
|
||
|
|
|
||
|
|
def __call__(self, x):
|
||
|
|
self.check_valid()
|
||
|
|
scale = self._params["amplitude_scale"](x)
|
||
|
|
period_phase = self._params["period_phase_shift"](x)
|
||
|
|
return scale * math.sin(period_phase)
|
||
|
|
|
||
|
|
def fit(self, **kwargs):
|
||
|
|
num_sin_phase = kwargs.get("num_sin_phase", 7)
|
||
|
|
min_amplitude = kwargs.get("min_amplitude", 1)
|
||
|
|
max_amplitude = kwargs.get("max_amplitude", 4)
|
||
|
|
phase_shift = kwargs.get("phase_shift", 0.0)
|
||
|
|
# create parameters
|
||
|
|
amplitude_scale = QuadraticFunc(
|
||
|
|
[(0, min_amplitude), (0.5, max_amplitude), (1, min_amplitude)]
|
||
|
|
)
|
||
|
|
fitting_data = []
|
||
|
|
temp_max_scalar = 2 ** (num_sin_phase - 1)
|
||
|
|
for i in range(num_sin_phase):
|
||
|
|
value = (2 ** i) / temp_max_scalar
|
||
|
|
next_value = (2 ** (i + 1)) / temp_max_scalar
|
||
|
|
for _phase in (0, 0.25, 0.5, 0.75):
|
||
|
|
inter_value = value + (next_value - value) * _phase
|
||
|
|
fitting_data.append((inter_value, math.pi * (2 * i + _phase)))
|
||
|
|
period_phase_shift = QuarticFunc(fitting_data)
|
||
|
|
self.set(
|
||
|
|
dict(amplitude_scale=amplitude_scale, period_phase_shift=period_phase_shift)
|
||
|
|
)
|
||
|
|
|
||
|
|
def _getitem(self, x, weights):
|
||
|
|
raise NotImplementedError
|
||
|
|
|
||
|
|
def __repr__(self):
|
||
|
|
return "{name}({amplitude_scale} * sin({period_phase_shift}))".format(
|
||
|
|
name=self.__class__.__name__,
|
||
|
|
amplitude_scale=self._params["amplitude_scale"],
|
||
|
|
period_phase_shift=self._params["period_phase_shift"],
|
||
|
|
)
|