I/O controls

The following lists all possible control options for the I/O control block in the define_input() function in the create_inputfile.py scripts. To see the recommended/default usage of these controls for specific fitting cases, see the examples section, or the provided example scripts BASTA/examples/xmlinput/create_inputfile_*.py.

Name of input file

xmlfilename = "input_myfit.xml"

Name and location of the produced input file to be run by BASTA. The only requirement is for it to end on xml. From there the user can freely define name and location of the file, e.g. when producing multiple input file for different frequency fitting methods, whereby the user might want to store them as freqfits/input03_r012.xml.

Name of grid file

define_io["gridfile"] = os.path.join(BASTADIR, "grids", "Garstec_16CygA.hdf5")

Name and location of the grid of stellar models to fit the observed stars to. It must be provided as a hdf5() file, otherwise there are no requirements on location or name.

The default points to the standard location of grids downloaded using the BASTAdownload() command (see Grids of models), that being the grids/ directory within the main BASTA directory. The default grid used (Garstec_16CygA.hdf5) is the small grid computed for the star 16 Cyg A, specifically for the examples given in the examples.

Output directory

define_io["outputpath"] = os.path.join("output", "myfit")

The directory into which the output from the BASTA run will be stored, relative to the location of the input file. If the directory does not exist, it will be created on startup of BASTA.

Observed parameters file

define_io["asciifile"] = os.path.join("data", "16CygA.ascii")

The name and location of the user-provided stellar parameters to be fitted. It must be provided in ASCII format, readable by the numpy.genfromtxt routine. Location is provided relative to the location from which the python script is run. This constitutes the list of stars for which the defined fit is run. For a basic example, see the BASTA/examples/data/16CygA.ascii file, for a single star.

define_io["params"] = (
    "starid",
    "RA",
    "DEC",
    "numax",
    "numax_err",
    "dnu",
    "dnu_err",
    "Teff",
    "Teff_err",
    "FeH",
    "FeH_err",
    "logg",
    "logg_err",
)

The by-column definition of which parameters are in the file. The first entry must be the starid, which is the identifying string/name of the star(s). It must be unique and compatible with the filesystem on which BASTA is run, as by-star output files uses this identifier for the naming of the files.

The remaining names in the params tuple must follow the order in which they are provided in the ASCII file, all columns must be named in the tuple, and the names must match the parameter names in BASTA’s parameter list, where the units assumed by BASTA is also available. The associated error of a parameter must be provided as a distinct column with the same name of the parameter followed by _err.

The only exception is the large frequency separation, \(\Delta\nu\), which here should simply be dnu, as it has multiple purposes depending on the methods employed. If the parameter is fitted directly, the grid value it is compared to is defined in the list of fit parameters.

Note that the provided parameters can exceed the parameters needed by BASTA, as it simply searches this list for what it needs. Therefore, the user can supply a single file with all available information for the given star(s), and use it in multiple different runs of BASTA that needs different parameters, as long as the necessary parameters are provided.

Format options

If the user has a parameter file in a specific format, the following options can be passed to the numpy.genfromtxt routine, to allow BASTA to load it.

define_io["delimiter"] = ","

This can be set to change the assumed delimiter between columns in the ASCII file. It is None by default, which means any consecutive whitespace act as a delimiter.

define_io["missingval"] = -999.999

Placeholder value to indicate missing values. It is generally advised to provide BASTA with a complete table with bad stars removed, but using this key, missing values can be ignored. This might be useful if a large pre-computed table is provided, where some data is not available for all stars.

Be aware that if a parameter to be fitted is missing, the star will be skipped!

define_io["overwriteparams"] = {"dnufit": (100, 2)}

Overwrite the value and error of a given parameter, for every star. Given as dictionary entries in the form {paramerer: (value, error)}.