physped.utils package

Submodules

physped.utils.config_utils module

Module to define utility functions for the configuration.

physped.utils.config_utils.apply_periodic_conditions_to_the_angle_theta(theta: float)

Apply periodic conditions to the angle theta.

Parameters:

theta (float) – The angle theta.

Returns:

The angle theta after applying the periodic conditions.

Return type:

float

physped.utils.config_utils.create_grid_name(grid_list: list)

physped.utils.config_utils.initialize_hydra_config(env_name: str) → DictConfig

Function to initialize the Hydra configuration.

Parameters:

env_name – The name of the environment. For example: ‘narrow_corridor’, ‘intersecting_paths’, ‘asdz_pf12’, ‘asdz_pf34’, ‘utrecht_pf5’.

Returns:

The Hydra configuration.

physped.utils.config_utils.log_configuration(config: dict) → None

physped.utils.config_utils.register_new_resolvers(replace=False)

physped.utils.config_utils.set_plot_style(config: DictConfig, use_latex: bool = False) → None

Function to set the plot style.

Parameters:

• use_latex – Whether to use LaTeX for the plot style or not.

• False. (Defaults to)

physped.utils.functions module

physped.utils.functions.cartesian_to_polar_coordinates(x: float, y: float) → tuple

Convert cartesian coordinates to polar coordinates.

Parameters: - x: The x-coordinate. - y: The y-coordinate.

Returns: - A tuple with the polar coordinates

physped.utils.functions.compose_functions(*functions: Callable[[Any], Any]) → Callable[[Any], Any]

physped.utils.functions.get_bin_middle(bins: ndarray) → ndarray

Return the middle of the input bins.

Parameters:

bins – The input bins.

Returns:

The middle of the input bins.

physped.utils.functions.get_slice_of_multidimensional_matrix(a: ndarray, slice_x: Tuple, slice_y: Tuple, slice_theta: Tuple, slice_r: Tuple) → ndarray

Get a slice of a multidimensional matrix.

Parameters: a (ndarray): The input multidimensional matrix. slice_x (tuple): The range of indices to slice along the x-axis. slice_y (tuple): The range of indices to slice along the y-axis. slice_theta (tuple): The range of indices to slice along the theta-axis. slice_r (tuple): The range of indices to slice along the r-axis.

Returns: ndarray: The sliced multidimensional matrix.

Raises: ValueError: If the slice values are not in ascending order.

physped.utils.functions.periodic_angular_conditions(angle: ndarray, angular_bins: ndarray) → ndarray

Apply periodic boundary conditions to a list of angular coordinates.

Parameters:

• angle – A list of angular coordinates.

• angular_bins – An array of bin edges defining the angular grid cells.

Returns:

The angular coordinates cast to the angular grid.

physped.utils.functions.polar_to_cartesian_coordinates(rho: float, phi: float) → tuple

Convert polar coordinates to cartesian coordinates.

Parameters: rho: The radial distance from the origin to the point. phi: The angle in radians.

Returns: - A tuple containing the cartesian coordinate.s

physped.utils.functions.test_weighted_mean_of_two_matrices(first_matrix: ndarray, counts_first_matrix: ndarray) → None

Test function for weighted_mean_of_two_matrices.

This function tests whether the weighted average of two matrices is equal to the input values.

Parameters: first_matrix (numpy.ndarray): The first input matrix. counts_first_matrix (numpy.ndarray): The counts matrix corresponding to the first input matrix.

physped.utils.functions.weighted_mean_of_matrix(field: ndarray, histogram: ndarray, axes: Tuple = (2, 3, 4)) → ndarray

Calculate the weighted mean of a matrix based on a given histogram.

Parameters:

• field (np.ndarray) – The input matrix.

• histogram (np.ndarray) – The histogram used for weighting.

• axes (Tuple) – The axes along which to calculate the mean.

• is (Default)

Returns:

The weighted mean of the matrix.

Return type:

np.ndarray

physped.utils.functions.weighted_mean_of_two_matrices(first_matrix: ndarray, counts_first_matrix: ndarray, second_matrix: ndarray, counts_second_matrix: ndarray) → ndarray

Calculates the weighted mean of two matrices.

Parameters:

• first_matrix (numpy.ndarray) – First input matrix.

• counts_first_matrix (numpy.ndarray) – Counts for the first input matrix.

• second_matrix (numpy.ndarray) – Second input matrix.

• counts_second_matrix (numpy.ndarray) – Counts for the second input

• matrix.

Returns:

Weighted mean of the two input matrices.

Return type:

numpy.ndarray

Module contents