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23 lines
690 B
23 lines
690 B
4 years ago
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import numpy as np
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def deep_interp_np(x, xp, fp, axis=None):
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if axis is not None:
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fp = fp.swapaxes(0,axis)
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x = np.atleast_1d(x)
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xp = np.array(xp)
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if len(xp) < 2:
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return np.repeat(fp, len(x), axis=0)
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if min(np.diff(xp)) < 0:
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raise RuntimeError('Bad x array for interpolation')
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j = np.searchsorted(xp, x) - 1
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j = np.clip(j, 0, len(xp)-2)
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d = np.divide(x - xp[j], xp[j + 1] - xp[j], out=np.ones_like(x, dtype=np.float64), where=xp[j + 1] - xp[j] != 0)
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vals_interp = (fp[j].T*(1 - d)).T + (fp[j + 1].T*d).T
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if axis is not None:
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vals_interp = vals_interp.swapaxes(0,axis)
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if len(vals_interp) == 1:
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return vals_interp[0]
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else:
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return vals_interp
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