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58 lines
1.9 KiB
58 lines
1.9 KiB
from typing import List
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from numpy import (
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vectorize as vectorize,
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)
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from numpy.core.function_base import (
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add_newdoc as add_newdoc,
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)
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from numpy.core.multiarray import (
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add_docstring as add_docstring,
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bincount as bincount,
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)
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from numpy.core.umath import _add_newdoc_ufunc
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__all__: List[str]
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add_newdoc_ufunc = _add_newdoc_ufunc
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def rot90(m, k=..., axes = ...): ...
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def flip(m, axis=...): ...
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def iterable(y): ...
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def average(a, axis=..., weights=..., returned=...): ...
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def asarray_chkfinite(a, dtype=..., order=...): ...
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def piecewise(x, condlist, funclist, *args, **kw): ...
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def select(condlist, choicelist, default=...): ...
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def copy(a, order=..., subok=...): ...
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def gradient(f, *varargs, axis=..., edge_order=...): ...
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def diff(a, n=..., axis=..., prepend = ..., append = ...): ...
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def interp(x, xp, fp, left=..., right=..., period=...): ...
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def angle(z, deg=...): ...
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def unwrap(p, discont = ..., axis=..., *, period=...): ...
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def sort_complex(a): ...
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def trim_zeros(filt, trim=...): ...
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def extract(condition, arr): ...
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def place(arr, mask, vals): ...
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def disp(mesg, device=..., linefeed=...): ...
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def cov(m, y=..., rowvar=..., bias=..., ddof=..., fweights=..., aweights=..., *, dtype=...): ...
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def corrcoef(x, y=..., rowvar=..., bias = ..., ddof = ..., *, dtype=...): ...
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def blackman(M): ...
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def bartlett(M): ...
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def hanning(M): ...
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def hamming(M): ...
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def i0(x): ...
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def kaiser(M, beta): ...
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def sinc(x): ...
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def msort(a): ...
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def median(a, axis=..., out=..., overwrite_input=..., keepdims=...): ...
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def percentile(a, q, axis=..., out=..., overwrite_input=..., interpolation=..., keepdims=...): ...
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def quantile(a, q, axis=..., out=..., overwrite_input=..., interpolation=..., keepdims=...): ...
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def trapz(y, x=..., dx=..., axis=...): ...
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def meshgrid(*xi, copy=..., sparse=..., indexing=...): ...
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def delete(arr, obj, axis=...): ...
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def insert(arr, obj, values, axis=...): ...
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def append(arr, values, axis=...): ...
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def digitize(x, bins, right=...): ...
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