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legged_gym/utils/math.py

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+import torch
+from torch import Tensor
+import numpy as np
+from isaacgym.torch_utils import quat_apply, normalize
+from typing import Tuple
+
+# @ torch.jit.script
+def quat_apply_yaw(quat, vec):
+    quat_yaw = quat.clone().view(-1, 4)
+    quat_yaw[:, :2] = 0.
+    quat_yaw = normalize(quat_yaw)
+    return quat_apply(quat_yaw, vec)
+
+# @ torch.jit.script
+def wrap_to_pi(angles):
+    angles %= 2*np.pi
+    angles -= 2*np.pi * (angles > np.pi)
+    return angles
+
+# @ torch.jit.script
+def torch_rand_sqrt_float(lower, upper, shape, device):
+    # type: (float, float, Tuple[int, int], str) -> Tensor
+    r = 2*torch.rand(*shape, device=device) - 1
+    r = torch.where(r<0., -torch.sqrt(-r), torch.sqrt(r))
+    r =  (r + 1.) / 2.
+    return (upper - lower) * r + lower