| Server IP : 66.29.132.122 / Your IP : 18.116.60.62 Web Server : LiteSpeed System : Linux business142.web-hosting.com 4.18.0-553.lve.el8.x86_64 #1 SMP Mon May 27 15:27:34 UTC 2024 x86_64 User : admazpex ( 531) PHP Version : 7.2.34 Disable Function : NONE MySQL : OFF | cURL : ON | WGET : ON | Perl : ON | Python : ON | Sudo : OFF | Pkexec : OFF Directory : /proc/self/root/proc/self/root/proc/thread-self/root/proc/thread-self/root/opt/cloudlinux/venv/lib/python3.11/site-packages/astroid/brain/ |
Upload File : |
# 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)