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| import scipy | |
| import numpy as np | |
| import imageio.v3 as iio | |
| import matplotlib.pyplot as plt | |
| from matplotlib.widgets import Slider, Button | |
| def xdog(img, sigma, k, p): | |
| img1 = scipy.ndimage.gaussian_filter(img, sigma=sigma) |
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| extends Camera2D | |
| const MIN_ZOOM: float = 1.0 | |
| const MAX_ZOOM: float = 16.0 | |
| const PAN_SPEED: float = 2000 | |
| const ZOOM_SPEED: float = 1.1 | |
| const ZOOM_INTERVAL: float = 0.1 | |
| var zoom_tween: Tween |
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| from pathlib import Path | |
| import numpy as np | |
| import numba as nb | |
| import scipy | |
| import pickle | |
| import matplotlib.pyplot as plt | |
| from matplotlib.collections import PatchCollection | |
| from collections import Counter | |
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| import numba as nb | |
| import numpy as np | |
| from tqdm.auto import tqdm | |
| import dask.array as da | |
| @nb.njit([nb.float64[:](nb.float64[:, :]),]) | |
| def g(x): | |
| res = np.zeros(x.shape[0], dtype=np.float64) | |
| for i in range(res.shape[0]): |
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| import numpy as np | |
| import cvxpy as cp | |
| import time | |
| RAND = np.random.default_rng(seed=42) | |
| def random_matrix(shape, dtype=np.complex128): | |
| M = RAND.random(shape) + 1j * RAND.random(shape) | |
| return M.astype(dtype) |
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