CMFGEN

Database from John Hillier’s CMFGEN, a radiative transfer code designed to solve the radiative transfer and statistical equilibrium equations in spherical geometry.

Note:

In this example, the data was downloaded from the CMFGEN website and extracted to the /tmp/atomic folder.

Parsers

The CMFGEN parsers retrieves data from text files preserving its original form (no unit conversions) and stores it in DataFrames. Currently, just osc, col and pho files are supported.

Levels, Lines and Collisions

Energy levels and spectral lines are stored in the osc files, while collisions strengths are provided by the col files.

import pathlib
from carsus.io.cmfgen import CMFGENEnergyLevelsParser, CMFGENOscillatorStrengthsParser, CMFGENCollisionalStrengthsParser

cmfgen_path = '../../../carsus-data-cmfgen/atomic/'
if not pathlib.Path(cmfgen_path).exists():
    cmfgen_path = "/tmp/atomic/"

si2_lvl = CMFGENEnergyLevelsParser(cmfgen_path+'SIL/II/16sep15/si2_osc_kurucz')

si2_osc = CMFGENOscillatorStrengthsParser(cmfgen_path+'SIL/II/16sep15/si2_osc_kurucz')

si2_col = CMFGENCollisionalStrengthsParser(cmfgen_path+'SIL/II/16sep15/si2_col')

Header information is stored in the header attribute and the DataFrame in the base attribute:

si2_col.header

si2_lvl.base

Photoionization Cross-sections

Photoionization cross-sections are provided by the pho files.

from carsus.io.cmfgen import CMFGENPhoCrossSectionsParser

si2_cross_sections = CMFGENPhoCrossSectionsParser(cmfgen_path+'SIL/II/16sep15/phot_nahar_A')

si2_cross_sections.header

In this case, base is a list containing many DataFrames. Also, each individual DataFrame contains information relative to that specific target under the attribute attr.

type(si2_cross_sections.base)

len(si2_cross_sections.base)

si2_cross_sections.base[0]

si2_cross_sections.base[0].attrs

Batch Convert Files to HDF5

To convert multiple CMFGEN files to the HDF5 format import the hdf_dump function.

Note:

This feature has been temporary disabled.

from carsus.io.cmfgen import hdf_dumphdf_dump('/tmp/atomic/', ['osc', 'OSC', 'Osc'], CMFGENEnergyLevelsParser(), chunk_size=10, ignore_patterns=['ERROR_CHK'])

Required parameters are cmfgen_dir, patterns and parser, while chunk_size and ignore_patterns are optional.

CMFGENReader

The CMFGENReader provides processed levels, lines, ionization_energies, cross_sections and collisions tables to work with. You can provide temperatures for the collisions dataframe using the temperature_grid option.

from carsus.io.cmfgen import CMFGENReader

cmfgen_reader = CMFGENReader.from_config('Si 0-1', cmfgen_path, ionization_energies=True, cross_sections=True, collisions=True, drop_mismatched_labels=True)

cmfgen_reader.levels

cmfgen_reader.lines

cmfgen_reader.cross_sections

cmfgen_reader.ionization_energies

The values in the collisions dataframe are thermally-averaged effective collision strengths divided by the statistical weights of the lower levels. Please see Eq. A1 and A2 of [PrzybillaButler04] for definitions. More information about the collisions table is stored inside the collisional_metadata attribute.

cmfgen_reader.collisions

cmfgen_reader.collisional_metadata