timewise.wise_data_by_visit.WiseDataByVisit¶

class timewise.wise_data_by_visit.WiseDataByVisit(base_name, parent_sample_class, min_sep_arcsec, n_chunks, clean_outliers_when_binning=True, multiply_flux_error=True)[source]¶

WISEData class to bin lightcurve by visit

__init__(base_name, parent_sample_class, min_sep_arcsec, n_chunks, clean_outliers_when_binning=True, multiply_flux_error=True)[source]¶

Methods

`__init__`(base_name, parent_sample_class, ...)
`add_flux_densities_to_saved_lightcurves`(service)	Adds flux densities to all downloaded lightcurves
`add_flux_density`(lightcurve, mag_key, ...[, ...])	Adds flux densities to a lightcurves
`add_luminosity_to_saved_lightcurves`(service)	Add luminosities to all lightcurves, calculated from flux densities and distance or redshift
`bin_lightcurve`(lightcurve)	Combine the data by visits of the satellite of one region in the sky.
`calculate_epochs`(f, e, visit_mask, counts, ...)	Calculates the binned epochs of a lightcurve.
`calculate_metadata`(service[, chunk_number, ...])	Calculates the metadata for all downloaded lightcurves.
`calculate_metadata_single`(lc)	Calculates some metadata, describing the variability of the lightcurves.
`calculate_position_mask`(lightcurve)	Create a mask that based on the position of the single exposures.
`find_color_correction`(w1_minus_w2)	Find the color correction based on the W1-W2 color.
`get_db_name`(table_name[, nice])	Get the right table name
`get_photometric_data`([tables, perc, wait, ...])	Load photometric data from the IRSA server for the matched sample.
`get_position_mask`(service, chunk_number)	Get the position mask for a chunk
`get_unbinned_lightcurves`(chunk_number[, clear])	Get the unbinned lightcurves for a given chunk number.
`get_visit_map`(lightcurve)	Create a map datapoint to visit
`load_data_product`(service[, chunk_number, ...])	Load data product from disk
`luminosity_from_flux_density`(flux_density, band)	Converts a flux density into a luminosity
`match_all_chunks`([table_name, ...])	Match the parent sample to a WISE catalogue and add the result to the parent sample.
`plot_diagnostic_binning`(service, ind[, ...])	Show a skymap of the single detections and which bin they belong to next to the binned lightcurve
`plot_lc`(parent_sample_idx[, service, ...])	Make a pretty plot of a lightcurve
`vegamag_to_flux_density`(vegamag, band[, ...])	This converts the detector level brightness m in Mag_vega to a flux density F

Attributes

`Npoints_key`
`active_tap_phases`
`aperture_corrections`
`band_plot_colors`
`band_wavelengths`
`bands`
`chunk_map`
`constraints`
`done_tap_phases`
`error_key_ext`
`flux_density_key_ext`
`flux_error_factor`
`flux_key_ext`
`luminosity_key_ext`
`mag_key_ext`
`magnitude_zeropoints`
`magnitude_zeropoints_corrections`
`mean_key`
`median_key`
`n_chunks`
`parent_sample`
`parent_sample_wise_skysep_key`
`parent_wise_source_id_key`
`photometry_table_keymap`
`query_types`
`rms_key`
`running_tap_phases`
`service`
`service_url`
`table_names`
`upper_limit_key`
`zeropoint_key_ext`