Function cohere

lib/matplotlib/pyplot.py:3295–3327

(
    x: ArrayLike,
    y: ArrayLike,
    NFFT: int = 256,
    Fs: float = 2,
    Fc: int = 0,
    detrend: (
        Literal["none", "mean", "linear"] | Callable[[ArrayLike], ArrayLike]
    ) = mlab.detrend_none,
    window: Callable[[ArrayLike], ArrayLike] | ArrayLike = mlab.window_hanning,
    noverlap: int = 0,
    pad_to: int | None = None,
    sides: Literal["default", "onesided", "twosided"] = "default",
    scale_by_freq: bool | None = None,
    *,
    data: DataParamType = None,
    **kwargs,
)

# Autogenerated by boilerplate.py.  Do not edit as changes will be lost.
@_copy_docstring_and_deprecators(Axes.cohere)
def cohere(
    x: ArrayLike,
    y: ArrayLike,
    NFFT: int = 256,
    Fs: float = 2,
    Fc: int = 0,
    detrend: (
        Literal["none", "mean", "linear"] | Callable[[ArrayLike], ArrayLike]
    ) = mlab.detrend_none,
    window: Callable[[ArrayLike], ArrayLike] | ArrayLike = mlab.window_hanning,
    noverlap: int = 0,
    pad_to: int | None = None,
    sides: Literal["default", "onesided", "twosided"] = "default",
    scale_by_freq: bool | None = None,
    *,
    data: DataParamType = None,
    **kwargs,
) -> tuple[np.ndarray, np.ndarray]:
    return gca().cohere(
        x,
        y,
        NFFT=NFFT,
        Fs=Fs,
        Fc=Fc,
        detrend=detrend,
        window=window,
        noverlap=noverlap,
        pad_to=pad_to,
        sides=sides,
        scale_by_freq=scale_by_freq,
        **({"data": data} if data is not None else {}),
        **kwargs,
    )


# Autogenerated by boilerplate.py.  Do not edit as changes will be lost.