pytmosph3r.grid

Module Contents

class Grid

Bases: pytmosph3r.log.logger.Logger

Standard logging using logger library

Parameters:

name (str) – Name used for logging

abstract property shape: Tuple

property ndim

walk(dims=None)

Return iterator over multiple dimensions.

Args: dims (array): List of dimensions to iterate over. By default, iterates over all dimensions (defined in the attribute shape of the current object.)

class Grid3D(n_vertical: int | None = None, n_latitudes: int | None = None, n_longitudes: int | None = None, mid_latitudes: numpy.ndarray | None = None, mid_longitudes: numpy.ndarray | None = None)

Bases: Grid

Simple 3D grid based on a 2D longitude/latitude grid and an (abstract) vertical axis. You can overwrite the latitudes and longitudes of your grid points with the mid_latitudes and mid_longitudes parameters. Note that latitudes and longitudes are derived from these and return the boundaries of each cell of the grid.

Parameters:

• n_vertical (int) – Number of vertical points in the grid.

• n_latitudes (int) – Number of latitudinal points in the grid.

• n_longitudes (int) – Number of longitudinal points in the grid.

property regular_latitudes

property to_east: bool

True if longitude is in increasing order.

property to_north: bool

True if latitude is in increasing order.

property shape: Tuple[int, int, int]

Shape of arrays in this grid.

property latitudes: numpy.ndarray

Latitudinal boundaries (deduced from mid_latitudes).

property positive_latitudes: numpy.ndarray

Positive latitudinal boundaries (deduced from mid_latitudes).

property mid_latitudes: numpy.ndarray

Latitudes in the “middle” of each latitude box.

property lat_angle

Angle between two latitudes.

property longitudes: numpy.ndarray

Longitudinal boundaries (unique). Deduced from mid_longitudes.

property half_longitudes

Half-list of longitudinal boundaries to avoid duplication. Deduced from all_longitudes.

property all_longitudes: numpy.ndarray

Longitudinal boundaries (first longitude duplicated to make a full circle). Deduced from longitudes.

property mid_longitudes: numpy.ndarray

List of longitudes (in the “middle” of each longitude box). By default, start at -Pi.

property night_longitudes: List

List of longitudinal indices on the night side. The night side is here defined as the first quarter of longitudinal indices and the last one.

property day_longitudes: List

List of longitudinal indices on the day side. The day side is here defined as the second and third quarters of longitudinal indices.

property lon_angle

Angle between two longitudes.

index_colatitude(colatitude) → int

Returns index corresponding to an angle with the pole 0 (by convention, north).

index_latitude(latitude) → int

Gives the index of the latitude interval containing a latitude (given in radians).

latitude(i)

Boundary angles in rad of latitude box with index i.

index_longitude(longitude) → int

Gives the index of the longitude interval containing a longitude (given in radians).

longitude(i)

Boundary angles in rad of longitude box with index i.

make_3D(obj: numpy.ndarray | dict, axis: List[int] | None = None) → numpy.ndarray

This function will try to transform obj from whatever dimension it is (or a dict of arrays with whatever dimensions) into a 3D array (or a dict with 3D arrays) of the same shape as the grid.

Parameters:

• obj (ndarray | dict) – 1, 2 or 3 dimensional array (or dict with such arrays).

• axis (Optional[List[int]]) – Allow to choose the value of axis. Use [0] to set a 1D pressure

or temperature array seen as an atmospheric column to a 3D one.

Returns:

3D array (or dict with 3D arrays).

Return type:

(ndarray | dict)

horizontal_walk(*args)

Iterator over horizontal grid (latitude, longitude).

horizontal_run(function, *args, **kwargs)

Run a function over horizontal grid (latitude, longitude).

outputs()