opticam.utils.data_checks
Functions
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Check that the data are self-consistent. |
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Parse the header info results. |
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Given a binning mode string, extract the x and y binning scales as integers. |
Module Contents
- opticam.utils.data_checks.scan_data(out_directory, data_directory, instrument, barycenter=True, verbose=True, return_output=False, logger=None, number_of_processors=cpu_count() // 2)
Check that the data are self-consistent.
Parameters
- out_directoryPath | str
The path to the directory in which output files will be saved.
- data_directoryPath | str
The path to the directory containing the data.
- instrumentInstrument
The instrument that produced the data.
- barycenterbool, optional
Whether to apply a Barycentric correction to the image time stamps, by default True. Only relevant if return_output=True.
- verbosebool, optional
Whether to print any output info, by default True.
- return_outputbool, optional
Whether to return any output, by default False.
- loggerLogger | None, optional
The logger, by default None.
- number_of_processors_type_, optional
The number of processors to use, by default cpu_count() // 2.
Returns
- None | tuple[dict[str, list[MEFSlice]], int, dict[str, float], list[MEFSlice], float]:
If return_output=True, the files grouped by camera, binning scale, Barycentric MJD dates, ignored files, and the reference date are returned. Otherwise, nothing is returned.
- Parameters:
out_directory (pathlib.Path | str)
data_directory (pathlib.Path | str)
instrument (opticam.instruments.Instrument)
barycenter (bool)
verbose (bool)
return_output (bool)
logger (logging.Logger | None)
- Return type:
None | tuple[dict[str, list[opticam.mef_slice.MEFSlice]], int, dict[str, float], list[opticam.mef_slice.MEFSlice], float]
- opticam.utils.data_checks.parse_header_results(results, files, out_directory, logger)
Parse the header info results.
Parameters
- resultstuple[list[float], list[float], list[str], list[str], list[float]]
The header info results.
- fileslist[MEFSlice]
The list of MEFSlice instances representing each image.
- out_directorystr
The directory path to which any output files will be saved.
- loggerLogger | None
The logger.
Returns
- tuple[str, dict[str, float], dict[str, str], dict[str, str], list[MEFSlice]]
The binning scale, BMJD dates, cameras, filters, and ignored files.
Raises
- ValueError
If more than three filters are detected.
- ValueError
If more than one binning mode is detected.
- Parameters:
results (tuple[list[float], list[float], list[str], list[str], list[float]])
files (list[opticam.mef_slice.MEFSlice])
out_directory (pathlib.Path)
logger (logging.Logger | None)
- Return type:
tuple[str, dict[str, float], dict[str, str], dict[str, str], list[opticam.mef_slice.MEFSlice]]
- opticam.utils.data_checks.get_binning_scale(binning)
Given a binning mode string, extract the x and y binning scales as integers.
Parameters
- binningstr
The binning mode string (e.g., “2x2”, “1 2”, etc.). The first number is assumed to be the binning scale in x, while the second number is assumed to be the binning scale in y.
Returns
- int
The binning scale.
- Parameters:
binning (str)
- Return type:
int