Total Complexity | 5 |
Total Lines | 47 |
Duplicated Lines | 0 % |
Changes | 0 |
1 | # Licensed under a 3-clause BSD style license - see LICENSE |
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2 | """Utility functions used in mutis.""" |
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3 | |||
4 | import numpy as np |
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5 | import scipy as sp |
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6 | |||
7 | __all__ = ["get_grid", "memoize"] |
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8 | |||
9 | |||
10 | def memoize(f): |
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11 | """Decorator for recursive memoization.""" |
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12 | memo = {} |
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13 | |||
14 | def helper(a, b): |
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15 | x = np.array([a, b], dtype="object") |
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16 | y = bytes(x) |
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17 | if y not in memo: |
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18 | memo[y] = f(a, b) |
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19 | return memo[y] |
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20 | |||
21 | return helper |
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22 | |||
23 | |||
24 | @memoize |
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25 | def get_grid(x, y): |
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26 | """Compute a meshgrid with memoization.""" |
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27 | return np.meshgrid(x, y) |
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28 | |||
29 | |||
30 | def interp_smooth_curve(x, y, s, N=None): |
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31 | """Return an interpolated and smoothed curve of len N. A gaussian kernel of std = s (in units of x) is used for smoothing. |
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32 | If N is None, an array of the same length is returned (but interpolated so it is equispaced). |
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33 | """ |
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34 | |||
35 | s = s/np.ptp(x)*len(x) |
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36 | |||
37 | if N is None: |
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38 | N = len(x) |
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39 | |||
40 | spl = sp.interpolate.splrep(x, y) |
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41 | xs = np.linspace(min(x), max(x), N) |
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42 | ys = sp.interpolate.splev(xs, spl) |
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43 | |||
44 | ys = sp.ndimage.gaussian_filter1d(ys, s) |
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45 | |||
46 | return xs, ys |
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