Documentation for KeplerFFI
Class that works with Kepler's EXBA data, to identify observed sources using Gaia
catalogs, and create light curves from simple aperture photometry.
__init__(self, channel=53, quarter=5, magnitude_limit=20, gaia_dr=3)
special
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
channel |
int |
Channel number of the EXBA image. |
53 |
quarter |
int |
Quarter number of the EXBA image. |
5 |
magnitude_limit |
float |
Limiting magnitude in g band used when querying Gaia catalogs, default is 20 mag. |
20 |
gaia_dr |
int |
Gaia data release, dafult is EDR3. |
3 |
Attributes:
| Name | Type | Description |
|---|---|---|
quarter |
int |
Channel number of the EXBA image. |
channel |
int |
Quarter number of the EXBA image. |
gaia_dr |
int |
Gaia data release, dafult is EDR3. |
tpfs |
lightkurve.TargetPixelFileCollection |
Collection of 4 TPFs that form the full EXBA mask. |
time |
numpy.ndarray |
Data array containing the time values. |
cadences |
numpy.ndarray |
Data array containing the cadence numbers. |
row |
numpy.ndarray |
Data array containing the valid pixel row numbers. Has shape of [n_pixels]. |
column |
numpy.ndarray |
Data array containing the valid pixel columns numbers. Has shape of [n_pixels]. |
flux |
numpy.ndarray |
Data array containing the valid image fluxes. Has shape of [n_times, n_pixels]. |
flux_err |
numpy.ndarray |
Data array containing the valid image flux errors. Has shape of [n_times, n_pixels]. |
ra |
numpy.ndarray |
Data array containing the valid RA pixel values. Has shape of [n_pixels]. |
dec |
numpy.ndarray |
Data array containing the valid Dec pixel values. Has shape of [n_pixels]. |
dx |
numpy.ndarray |
Distance between pixel and source coordinates, units of pixels. Has shape of [n_sources, n_pixels] |
dy |
numpy.ndarray |
Distance between pixel and source coordinates, units of pixels. Has shape of [n_sources, n_pixels] |
r |
numpy.ndarray |
Radial distance between pixel and source coordinates (polar coordinates), in units of pixels. |
phi |
numpy.ndarray |
Angle between pixel and source coordinates (polar coordinates), in units of radians |
n_sources |
int |
Number of sources in Gaia catalog observed in the EXBA mask. |
n_rows |
int |
Number rows in the EXBA image. |
n_columns |
int |
Number columns in the EXBA image. |
aperture_mask |
numpy.ndarray |
Data array with the source aperture masks. Has shape of [n_sources, n_pixels] |
FLFRCSAP |
numpy.array |
Data array with the completeness metric for every source computed from the photometric aperture. |
CROWDSAP |
numpy.array |
Data array with the contamination metric for every source computed from the photometric aperture. |
_clean_source_list(self, sources, ra, dec)
private
Function to clean surces from the catalog removing sources outside the image
coverage (allowing for sources up to 4" outside the mask), and to remove blended sources (within 2").
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
sources |
pandas.DataFrame |
Catalog with sources to be removed |
required |
ra |
numpy.ndarray |
Data array with values of RA for every pixel in the image. |
required |
dec |
numpy.ndarray |
Data array with values of Dec for every pixel in the image. |
required |
Returns:
| Type | Description |
|---|---|
pandas.DataFrame |
Clean catalog |
_convert_to_wcs(self, tpfs, row, col)
private
Function to convert pixel number to RA and Dec values using the WCS solution
embedded in the TPFs.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
tpfs |
list of TPFs or TargetPixelFileCollection |
A list of TPFs that contain the EXBA tiles. |
required |
row |
numpy.ndarray |
Data aray with the row pixel values to be converted to RA & Dec. |
required |
col |
numpy.ndarray |
Data aray with the column pixel values to be converted to RA & Dec. |
required |
Returns:
| Type | Description |
|---|---|
numpy.ndarray |
Right Ascension coordinate obtained from the WCS solution. |
_do_query(self, ra, dec, epoch=2020, magnitude_limit=20, load=True)
private
Calculate ra, dec coordinates and search radius to query Gaia catalog.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
ra |
numpy.ndarray |
Right ascension coordinate of pixels to do Gaia search |
required |
dec |
numpy.ndarray |
Declination coordinate of pixels to do Gaia search |
required |
epoch |
float |
Epoch of obervation in Julian Days of ra, dec coordinates, will be used to propagate proper motions in Gaia. |
2020 |
magnitude_limit |
int |
Limiting magnitued for query |
20 |
load |
boolean |
Load or not the saved query. Set to False if want to force to run new queries. |
True |
Returns:
| Type | Description |
|---|---|
pandas.DataFrame |
Catalog with query result |
_parse_TPFs_channel(self, tpfs)
private
Function to parse the TPFs containing the EXBA masks (4 per channel) and
tile them.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
tpfs |
list of TPFs or TargetPixelFileCollection |
A list of TPFs that contain the 4 EXBA mask per channel. |
required |
Returns:
| Type | Description |
|---|---|
numpy.ndarray |
Data array containing the time values. |
_preprocess(self, times, cadences, flux, flux_err)
private
Function to clean pixels with nan values and bad cadences. It Returns the same
input arrays but cleaned.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
times |
numpy.ndarray |
Data array with the time values. |
required |
cadences |
numpy.ndarray |
Data array with the cadence numbers. |
required |
flux |
numpy.ndarray |
Data array with the image flux. |
required |
flux_err |
numpy.ndarray |
Data array with the image flux errors. |
required |
Returns:
| Type | Description |
|---|---|
numpy.ndarray |
Data array with the time values. |
apply_CBV(self, do_under=False, plot=True)
Applies CBV corrections to all the light curves in self.lcs. It optimizes
the alpha parameter for each correction, if optimization fails, uses the alpha value calculated for previous light curve. It creates class attributes to access the CBV-corrected light curves, and under/over fitting metrics.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
do_under |
boolean |
Compute or not the under-fitting metric for the CBV correction. |
False |
plot |
boolean |
Plot or not CBVcorrector diagnostic figures. |
True |
create_lcs(self, aperture_mask)
Funciton to create lightkurve.LightCurve with the light curves using aperture
photometry. It creates a class attribute self.lcs that is a
lk.LightCurveCollection with the light curves of all input sources.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
aperture_mask |
numpy.ndarray |
Boolean mask of shape [n_sources, n_pixels] that has the aperture mask to be used to compute photometry for a set of sources. |
required |
do_photometry(self, aperture_mask)
Function to do aperture photometry on a set of sources. It creates/update class
attributes that contains the SAP flux, errors, and aperture masks.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
aperture_mask |
numpy.ndarray |
Boolean mask of shape [n_sources, n_pixels] that has the aperture mask to be used to compute photometry for a set of sources. |
required |
download_exba(channel=1, quarter=5)
staticmethod
Download EXBA fits file to a dedicated quarter/channel directory
It uses a exba_tpfs_info.csv to map the quarter/channel to the corresponding file names in MAST archive.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
channel |
int |
Number of channel to be download, valid numbers are bwtween 1 and 84. |
1 |
quarter |
int |
Number of quarter to be download, valid numbers are bwtween 1 and 17. |
5 |
image_to_fits(self, path=None, overwrite=False)
Creates a FITS file that contains the time-average imagege of the EXBA mask
in a ImageHDU, and the source catalog in a BinTableHDU.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
path |
string |
Directory path where to save the FITS file. |
None |
overwrite |
bool |
Overwrite the output file. |
False |
Returns:
| Type | Description |
|---|---|
ImageHDU |
An Image header unit containing the EXBA flux. |
plot_image(self, frame=0, sources=True, ax=None)
Function to plot the full EXBA image and the Gaia Sources.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
frame |
int |
Frame number. The default is 0, i.e. the first frame. |
0 |
sources |
boolean |
Whether to overplot or not the source catalog |
True |
ax |
matplotlib.axes |
Matlotlib axis can be provided, if not one will be created and returned |
None |
Returns:
| Type | Description |
|---|---|
matplotlib.axes |
Matlotlib axis with the figure |
plot_lightcurve(self, source_idx=0, ax=None)
Creates a figure with the light curve of a given source.
mask.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
source_idx |
int |
Index of the source in |
0 |
ax |
matplotlib.axes |
Matlotlib axis can be provided, if not one will be created and returned. |
None |
Returns:
| Type | Description |
|---|---|
matplotlib.axes |
Matlotlib axis with the figure |
plot_stamp(self, source_idx=0, aperture_mask=False, ax=None)
Creates a figure with the "stamp" image of a given source and its aperture
mask.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
source_idx |
int |
Index of the source in |
0 |
aperture_mask |
boolean |
Plot or not the aperutre mask. |
False |
ax |
matplotlib.axes |
Matlotlib axis can be provided, if not one will be created and returned. |
None |
Returns:
| Type | Description |
|---|---|
matplotlib.axes |
Matlotlib axis with the figure |