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| """3D format conversion for coordinates and Ambisonics""" | |
| from functools import singledispatch | |
| from typing import List, Tuple, Union | |
| import numpy as np | |
| def convert_ambisonics_a_to_b( | |
| front_left_up: np.ndarray, | |
| front_right_down: np.ndarray, | |
| back_right_up: np.ndarray, | |
| back_left_down: np.ndarray, | |
| ) -> np.ndarray: | |
| """Converts Ambisonics A-format to B-format | |
| Parameters | |
| ---------- | |
| front_left_up : np.ndarray | |
| Front Left Up signal from A-format | |
| front_right_down : np.ndarray | |
| Front Right Down signal from A-format | |
| back_right_up : np.ndarray | |
| Back Right Up signal from A-format | |
| back_left_down : np.ndarray | |
| Back Left Down signal from A-format | |
| Returns | |
| ------- | |
| np.ndarray | |
| B-format outputs (W, X, Y, Z) | |
| """ | |
| front = front_left_up + front_right_down | |
| back = back_left_down + back_right_up | |
| left = front_left_up + back_left_down | |
| right = front_right_down + back_right_up | |
| up = front_left_up + back_right_up # pylint: disable=invalid-name | |
| down = front_right_down + back_left_down | |
| w_channel = front + back | |
| x_channel = front - back | |
| y_channel = left - right | |
| z_channel = up - down | |
| return np.array([w_channel, x_channel, y_channel, z_channel]) | |
| def _(aformat_channels: List[np.ndarray]) -> np.ndarray: | |
| """Converts Ambisonics A-format to B-format. | |
| Parameters | |
| ---------- | |
| aformat_channels : List[np.ndarray] | |
| A list containing the 4 channels of A-format Ambisonics in the following order: | |
| 1. Front Left Up | |
| 2. Front Right Down | |
| 3. Back Right Up | |
| 4. Back Left Down | |
| Returns | |
| ------- | |
| np.ndarray | |
| B-format outputs (W, X, Y, Z) | |
| """ | |
| assert ( | |
| len(aformat_channels) == 4 | |
| ), "Conversion from A-format to B-format requires 4 channels" | |
| return convert_ambisonics_a_to_b.dispatch(np.ndarray)( | |
| front_left_up=aformat_channels[0], | |
| front_right_down=aformat_channels[1], | |
| back_right_up=aformat_channels[2], | |
| back_left_down=aformat_channels[3], | |
| ) | |
| def spherical_to_cartesian( | |
| radius: Union[float, np.ndarray], | |
| azimuth: Union[float, np.ndarray], | |
| elevation: Union[float, np.ndarray], | |
| ) -> Tuple[Union[float, np.ndarray]]: | |
| """Convert three 3D polar coordinates to Cartesian ones. | |
| Parameters | |
| radius: float | np.ndarray. The radii (or rho). | |
| azimuth: float | np.ndarray. The azimuth (also called theta or alpha). | |
| elevation: float | np.ndarray. The elevation (also called phi or polar). | |
| Returns | |
| (x, y, z): Tuple[float | np.ndarray]. The corresponding Cartesian coordinates. | |
| """ | |
| return ( | |
| radius * np.cos(np.deg2rad(azimuth)) * np.cos(np.deg2rad(elevation)), | |
| radius * np.sin(np.deg2rad(azimuth)) * np.cos(np.deg2rad(elevation)), | |
| radius * np.sin(np.deg2rad(elevation)), | |
| ) | |
| def cartesian_to_spherical(intensity_windowed: np.ndarray): | |
| """_summary_ | |
| Parameters | |
| ---------- | |
| intensity_windowed : np.ndarray | |
| _description_ | |
| Returns | |
| ------- | |
| _type_ | |
| _description_ | |
| """ | |
| # Convert to total intensity, azimuth and elevation | |
| intensity = np.sqrt((intensity_windowed**2).sum(axis=0)).squeeze() | |
| azimuth = np.rad2deg( | |
| np.arctan2(intensity_windowed[1], intensity_windowed[0]) | |
| ).squeeze() | |
| elevation = np.rad2deg(np.arcsin(intensity_windowed[2] / intensity)).squeeze() | |
| return intensity, azimuth, elevation | |