관리-도구
편집 파일: brain_scipy_signal.cpython-311.pyc
� �܋f� � �^ � d Z ddlmZ ddlmZ ddlmZ d� Z e e� � de� � dS )z&Astroid hooks for scipy.signal module.� )�register_module_extender��parse)�AstroidManagerc � � t d� � S )Na� # 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]) r � � �q/builddir/build/BUILD/cloudlinux-venv-1.0.6/venv/lib/python3.11/site-packages/astroid/brain/brain_scipy_signal.py� scipy_signalr s � � �G �I � I � Ir z scipy.signalN)�__doc__�astroid.brain.helpersr �astroid.builderr �astroid.managerr r r r r �<module>r s{ �� -� ,� :� :� :� :� :� :� !� !� !� !� !� !� *� *� *� *� *� *�J� J� J�Z � � � �)�)�>�<� H� H� H� H� Hr