aPriori.DNS¶

DNS.py: the core module of the aPrioriDNS package.

Classes¶

`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.

Functions¶

`add_variable`(attribute_name, file_name[, species, ...])
`compute_cell_volumes`(x, y, z)	Compute the volumes of the cells in a 3D mesh grid.
`delete_existing_files`(paths[, delete, context])	Checks if any of the given paths exist. If so, prompts the user once to confirm deletion.
`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,
`downsample`(array, N)
`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.
`generate_mask`(start, shape, delta)	Computes the downsampled mask of a 3D field.
`check_same_shape`(*args)	Checks if the shape of the input arguments *args is the same
`check_input_string`(input_string, valid_strings, input_name)	Checks if the value of input_string is contained in the list valid_strings.
`plot_power_spectrum`(field[, C])	Plots the power spectrum of a 3D field.
`process_chunk_LFR`(j, T_chunk, P_chunk, Y_chunk, ...)
`process_chunk_PSR`(j, T_j, P_j, RHO_j, Tau_c_j, ...)
`section_and_average`(x, y, n_sections)	Divides the given array into sections and computes the average for each section.
`read_variable_in_chunks`(file_path, chunk_size)	Generator to read a binary file in chunks.
`process_species_in_chunks`(file_paths, species_file, ...)	Reads species mass fractions in chunks from the specified files.
`x_midplane`(array)
`y_midplane`(array)
`z_midplane`(array)