aPriori¶

Library initialization and relative imports

Submodules¶

`Field3D`	Class representing a 3D field with various attributes and methods for visualization and data management.
`Scalar3D`	A class representing a 3D scalar field.
`Mesh3D`	A class used to represent a 3D mesh.

`add_variable`(attribute_name, file_name[, species, ...])
`delete_file`(file_path)	Deletes the specified file from the file system.
`download`([repo_url, dest_folder, dataset])	Downloads all files from a specified GitHub repository directory and saves them to the destination folder,
`process_file`(file_path)	Read a binary file and convert its contents into a numpy array.
`filter_gauss`(field, delta[, mode])	Apply a Gaussian filter to a 3D numpy array.
`filter_box`(field, delta[, mode])	Apply a box filter to a 3D numpy array using scipy's convolve function.
`filter_3D`(field, filter_size[, RHO, favre, filter_type])	Apply a 3D filter (Gaussian or box) to a numpy array, with optional Favre filtering.
`save_file`(X, file_name)	Saves the given array to a file in binary format.
`gradient_x`(F, mesh[, filter_size])	Description
`gradient_y`(F, mesh[, filter_size])	Computes the gradient of a 3D, non downsampled, filtered field. Numpy is
`gradient_z`(F, mesh[, filter_size])	Computes the z component of the gradient of a 3D, non downsampled, filtered field.
`contour_plot`(X, Y, Z[, log, colormap, cbar_title, ...])
`parity_plot`(x, y[, rel_error, colormap, x_name, ...])
`cond_mean_plot`(x, y[, num_bins, log, minmax, ...])	Plots the conditional mean of y over x using numpy.
`scatter`(x, y[, logx, logy, c, s, alpha, max_dim, ...])