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 visits. The visits typically consist of some tens of observations. The individual visits are separated by about six months. The mean flux for one visit is calculated by the weighted mean of the data. The error on that mean is calculated by the root-mean-squared and corrected by the t-value. Outliers per visit are identified if they are more than 20 times the rms away from the mean. In addition to the attributes of timewise.WISEDataBase this class has the following attributes:

Parameters:
  • clean_outliers_when_binning (bool) – whether to remove outliers by brightness when binning

  • mean_key (str) – the key for the mean

  • median_key (str) – the key for the median

  • rms_key (str) – the key for the rms

  • upper_limit_key (str) – the key for the upper limit

  • Npoints_key (str) – the key for the number of points

  • zeropoint_key_ext (str) – the key for the zeropoint

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

Constructor of the WISEDataByVisit class.

Parameters:
  • base_name (str) – the base name of the data directory

  • parent_sample_class (ParentSampleBase) – the parent sample class

  • min_sep_arcsec (float) – query region around source for positional query

  • n_chunks (int) – number of chunks to split the sample into

  • clean_outliers_when_binning (bool) – if True, clean outliers when binning

Methods

__init__(base_name, parent_sample_class, ...)

Constructor of the WISEDataByVisit 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, ra, dec, ...)

Estimated the 90th percentile of the angular separations from the given position.

dump_tap_cache()

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, ...])

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

load_tap_cache()

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

tap_cache_filenames

upper_limit_key

zeropoint_key_ext