AlkantarClanX12
Current Path : /opt/cloudlinux/venv/lib64/python3.11/site-packages/astroid/brain/ |
Current File : //opt/cloudlinux/venv/lib64/python3.11/site-packages/astroid/brain/brain_scipy_signal.py |
# Licensed under the LGPL: https://www.gnu.org/licenses/old-licenses/lgpl-2.1.en.html # For details: https://github.com/PyCQA/astroid/blob/main/LICENSE # Copyright (c) https://github.com/PyCQA/astroid/blob/main/CONTRIBUTORS.txt """Astroid hooks for scipy.signal module.""" from astroid.brain.helpers import register_module_extender from astroid.builder import parse from astroid.manager import AstroidManager def scipy_signal(): return parse( """ # different functions defined in scipy.signals def barthann(M, sym=True): return numpy.ndarray([0]) def bartlett(M, sym=True): return numpy.ndarray([0]) def blackman(M, sym=True): return numpy.ndarray([0]) def blackmanharris(M, sym=True): return numpy.ndarray([0]) def bohman(M, sym=True): return numpy.ndarray([0]) def boxcar(M, sym=True): return numpy.ndarray([0]) def chebwin(M, at, sym=True): return numpy.ndarray([0]) def cosine(M, sym=True): return numpy.ndarray([0]) def exponential(M, center=None, tau=1.0, sym=True): return numpy.ndarray([0]) def flattop(M, sym=True): return numpy.ndarray([0]) def gaussian(M, std, sym=True): return numpy.ndarray([0]) def general_gaussian(M, p, sig, sym=True): return numpy.ndarray([0]) def hamming(M, sym=True): return numpy.ndarray([0]) def hann(M, sym=True): return numpy.ndarray([0]) def hanning(M, sym=True): return numpy.ndarray([0]) def impulse2(system, X0=None, T=None, N=None, **kwargs): return numpy.ndarray([0]), numpy.ndarray([0]) def kaiser(M, beta, sym=True): return numpy.ndarray([0]) def nuttall(M, sym=True): return numpy.ndarray([0]) def parzen(M, sym=True): return numpy.ndarray([0]) def slepian(M, width, sym=True): return numpy.ndarray([0]) def step2(system, X0=None, T=None, N=None, **kwargs): return numpy.ndarray([0]), numpy.ndarray([0]) def triang(M, sym=True): return numpy.ndarray([0]) def tukey(M, alpha=0.5, sym=True): return numpy.ndarray([0]) """ ) register_module_extender(AstroidManager(), "scipy.signal", scipy_signal)