How to construct an atm_fields_compact?ΒΆ

An atm_fields_compact is a compact set of atmospheric fields on a common set of grids.

Data is supposed to contain basic atmsopheric fields for a radiative transfer calculation (i.e., temperature, altitude, and gas VMRs) and is stored in a GriddedField4.

The following code snippet demonstrates how to create an atm_fields_compact and write it to an ARTS XML file.

import numpy as np
import typhon

# Initialize an empty GriddedField4 object.
atm_fields_compact = typhon.arts.types.GriddedField4()

# Create required grids.
field_names = ['T', 'z', 'abs_species-H2O']
p_grid = typhon.math.nlogspace(1000e2, 0.01e2, 50)
lat_grid = np.array([])
lon_grid = np.array([])

# Assign the `grids` attribute with a list of the grids created.
atm_fields_compact.grids = [field_names, p_grid, lat_grid, lon_grid]
atm_fields_compact.gridnames = [
    'Fieldnames', 'Pressure', 'Latitude', 'Longitude',

# Create (dummy) data arrays.
T = 300 * np.ones(p_grid.size)
z = np.linspace(0, 80e3, p_grid.size)
vmr = 0.04 * (p_grid / p_grid[0])**1.7

# The data is stored as :arts:`Tensor4` which is represented as a
# four-dimensional ndarray in Python. We stack our (one-dimensional)
# arrays to create the required tensor. The following line adds two
# extra dimension to account for the empty latitude/longitude dimensions.
# The resulting data has the shape `[3, 50, 1, 1]`.
data_tensor = np.stack(
    [x.reshape(-1, 1, 1) for x in (T, z, vmr)]
) = data_tensor

# Manually check if grid and data dimensions match. This is done
# automatically when assigning data or before writing GriddedFields to an
# XML file.

# Write the atm_fields_compact to an XML file that can be read by ARTS., 'atmfield.xml')