Finalize example vis codes

lib/datasets/math_dynamic_funcs.py

@@ -0,0 +1,66 @@
+#####################################################
+# 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
+
+
+class DynamicFunc(FitFunc):
+    """The dynamic quadratic function, where each param is a function."""
+
+    def __init__(self, freedom: int, params=None):
+        super(DynamicFunc, self).__init__(freedom, None, params)
+        self._timestamp = None
+
+    def __call__(self, x, timestamp=None):
+        raise NotImplementedError
+
+    def _getitem(self, x, weights):
+        raise NotImplementedError
+
+    def set_timestamp(self, timestamp):
+        self._timestamp = timestamp
+
+    def noise_call(self, x, timestamp=None, std=0.1):
+        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
+
+
+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)
+
+    def __call__(self, x, timestamp=None):
+        self.check_valid()
+        if timestamp is None:
+            timestamp = self._timestamp
+        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):
+        return "{name}({a} * x^2 + {b} * x + {c}, timestamp={timestamp})".format(
+            name=self.__class__.__name__,
+            a=self._params[0],
+            b=self._params[1],
+            c=self._params[2],
+            timestamp=self._timestamp,
+        )