Update the sync data v1

xautodl/datasets/math_dynamic_generator.py

@@ -0,0 +1,58 @@
+#####################################################
+# Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2021.03 #
+#####################################################
+import abc
+import numpy as np
+
+
+def assert_list_tuple(x):
+    assert isinstance(x, (list, tuple))
+    return len(x)
+
+
+class DynamicGenerator(abc.ABC):
+    """The dynamic quadratic function, where each param is a function."""
+
+    def __init__(self):
+        self._ndim = None
+
+    def __call__(self, time, num):
+        raise NotImplementedError
+
+
+class GaussianDGenerator(DynamicGenerator):
+    def __init__(self, mean_functors, cov_functors, trunc=(-1, 1)):
+        super(GaussianDGenerator, self).__init__()
+        self._ndim = assert_list_tuple(mean_functors)
+        assert self._ndim == len(
+            cov_functors
+        ), "length does not match {:} vs. {:}".format(self._ndim, len(cov_functors))
+        assert_list_tuple(cov_functors)
+        for cov_functor in cov_functors:
+            assert self._ndim == assert_list_tuple(
+                cov_functor
+            ), "length does not match {:} vs. {:}".format(self._ndim, len(cov_functor))
+        assert (
+            isinstance(trunc, (list, tuple)) and len(trunc) == 2 and trunc[0] < trunc[1]
+        )
+        self._mean_functors = mean_functors
+        self._cov_functors = cov_functors
+        if trunc is not None:
+            assert assert_list_tuple(trunc) == 2 and trunc[0] < trunc[1]
+        self._trunc = trunc
+
+    def __call__(self, time, num):
+        mean_list = [functor(time) for functor in self._mean_functors]
+        cov_matrix = [
+            [abs(cov_gen(time)) for cov_gen in cov_functor]
+            for cov_functor in self._cov_functors
+        ]
+        values = np.random.multivariate_normal(mean_list, cov_matrix, size=num)
+        if self._trunc is not None:
+            np.clip(values, self._trunc[0], self._trunc[1], out=values)
+        return values
+
+    def __repr__(self):
+        return "{name}({ndim} dims, trunc={trunc})".format(
+            name=self.__class__.__name__, ndim=self._ndim, trunc=self._trunc
+        )