"""
This type stub file was generated by pyright.
"""

import numpy as np
from collections.abc import Callable
from typing import Literal
from numpy.typing import ArrayLike

def window_hanning(x: ArrayLike) -> ArrayLike:
    ...

def window_none(x: ArrayLike) -> ArrayLike:
    ...

def detrend(x: ArrayLike, key: Literal["default", "constant", "mean", "linear", "none"] | Callable[[ArrayLike, int | None], ArrayLike] | None = ..., axis: int | None = ...) -> ArrayLike:
    ...

def detrend_mean(x: ArrayLike, axis: int | None = ...) -> ArrayLike:
    ...

def detrend_none(x: ArrayLike, axis: int | None = ...) -> ArrayLike:
    ...

def detrend_linear(y: ArrayLike) -> ArrayLike:
    ...

def psd(x: ArrayLike, NFFT: int | None = ..., Fs: float | None = ..., detrend: Literal["none", "mean", "linear"] | Callable[[ArrayLike, int | None], ArrayLike] | None = ..., window: Callable[[ArrayLike], ArrayLike] | ArrayLike | None = ..., noverlap: int | None = ..., pad_to: int | None = ..., sides: Literal["default", "onesided", "twosided"] | None = ..., scale_by_freq: bool | None = ...) -> tuple[ArrayLike, ArrayLike]:
    ...

def csd(x: ArrayLike, y: ArrayLike | None, NFFT: int | None = ..., Fs: float | None = ..., detrend: Literal["none", "mean", "linear"] | Callable[[ArrayLike, int | None], ArrayLike] | None = ..., window: Callable[[ArrayLike], ArrayLike] | ArrayLike | None = ..., noverlap: int | None = ..., pad_to: int | None = ..., sides: Literal["default", "onesided", "twosided"] | None = ..., scale_by_freq: bool | None = ...) -> tuple[ArrayLike, ArrayLike]:
    ...

complex_spectrum = ...
magnitude_spectrum = ...
angle_spectrum = ...
phase_spectrum = ...
def specgram(x: ArrayLike, NFFT: int | None = ..., Fs: float | None = ..., detrend: Literal["none", "mean", "linear"] | Callable[[ArrayLike, int | None], ArrayLike] | None = ..., window: Callable[[ArrayLike], ArrayLike] | ArrayLike | None = ..., noverlap: int | None = ..., pad_to: int | None = ..., sides: Literal["default", "onesided", "twosided"] | None = ..., scale_by_freq: bool | None = ..., mode: Literal["psd", "complex", "magnitude", "angle", "phase"] | None = ...) -> tuple[ArrayLike, ArrayLike, ArrayLike]:
    ...

def cohere(x: ArrayLike, y: ArrayLike, NFFT: int = ..., Fs: float = ..., detrend: Literal["none", "mean", "linear"] | Callable[[ArrayLike, int | None], ArrayLike] = ..., window: Callable[[ArrayLike], ArrayLike] | ArrayLike = ..., noverlap: int = ..., pad_to: int | None = ..., sides: Literal["default", "onesided", "twosided"] = ..., scale_by_freq: bool | None = ...) -> tuple[ArrayLike, ArrayLike]:
    ...

class GaussianKDE:
    dataset: ArrayLike
    dim: int
    num_dp: int
    factor: float
    data_covariance: ArrayLike
    data_inv_cov: ArrayLike
    covariance: ArrayLike
    inv_cov: ArrayLike
    norm_factor: float
    def __init__(self, dataset: ArrayLike, bw_method: Literal["scott", "silverman"] | float | Callable[[GaussianKDE], float] | None = ...) -> None:
        ...
    
    def scotts_factor(self) -> float:
        ...
    
    def silverman_factor(self) -> float:
        ...
    
    def covariance_factor(self) -> float:
        ...
    
    def evaluate(self, points: ArrayLike) -> np.ndarray:
        ...
    
    def __call__(self, points: ArrayLike) -> np.ndarray:
        ...