(cov)
| 56 | |
| 57 | def draw_cov(mu, C, color=None, label=None, nstd=1, alpha=0.5): |
| 58 | def eigsorted(cov): |
| 59 | if torch.is_tensor(cov): |
| 60 | cov = cov.detach().numpy() |
| 61 | vals, vecs = np.linalg.eigh(cov) |
| 62 | order = vals.argsort()[::-1].copy() |
| 63 | return vals[order], vecs[:, order] |
| 64 | |
| 65 | vals, vecs = eigsorted(C) |
| 66 | theta = np.degrees(np.arctan2(*vecs[:, 0][::-1])) |