Documentation for FFIMachine
Subclass of Machine for working with FFI data. It is a subclass of Machine
__init__(self, time, flux, flux_err, ra, dec, sources, column, row, wcs=None, limit_radius=32.0, n_r_knots=10, n_phi_knots=15, time_nknots=10, time_resolution=200, time_radius=8, cut_r=6, rmin=1, rmax=16, sparse_dist_lim=40, quality_mask=None, meta=None)
special
Repeated optional parameters are described in Machine
.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
time |
numpy.ndarray |
Time values in JD |
required |
flux |
numpy.ndarray |
Flux values at each pixels and times in units of electrons / sec. Has shape [n_times, n_rows, n_columns] |
required |
flux_err |
numpy.ndarray |
Flux error values at each pixels and times in units of electrons / sec. Has shape [n_times, n_rows, n_columns] |
required |
ra |
numpy.ndarray |
Right Ascension coordinate of each pixel |
required |
dec |
numpy.ndarray |
Declination coordinate of each pixel |
required |
sources |
pandas.DataFrame |
DataFrame with source present in the images |
required |
column |
np.ndarray |
Data array containing the "columns" of the detector that each pixel is on. |
required |
row |
np.ndarray |
Data array containing the "columns" of the detector that each pixel is on. |
required |
wcs |
astropy.wcs |
World coordinates system solution for the FFI. Used for plotting. |
None |
quality_mask |
np.ndarray or booleans |
Boolean array of shape time indicating cadences with bad quality. |
None |
meta |
dictionary |
Meta data information related to the FFI |
None |
Attributes:
Name | Type | Description |
---|---|---|
meta |
dictionary |
Meta data information related to the FFI |
wcs |
astropy.wcs |
World coordinates system solution for the FFI. Used for plotting. |
flux_2d |
numpy.ndarray |
2D image representation of the FFI, used for plotting. Has shape [n_times, image_height, image_width] |
image_shape |
tuple |
Shape of 2D image |
from_file(fname, extension=1, cutout_size=None, cutout_origin=[0, 0], correct_offsets=False, plot_offsets=False, magnitude_limit=18, dr=3, sources=None, **kwargs)
staticmethod
Reads data from files and initiates a new object of FFIMachine class.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
fname |
str or list of strings |
File name or list of file names of the FFI files. |
required |
extension |
int |
Number of HDU extension to be used, for Kepler FFIs this corresponds to the channel number. For TESS FFIs, it correspond to the HDU extension containing the image data (1). |
1 |
cutout_size |
int |
Size of the cutout in pixels, assumed to be squared |
None |
cutout_origin |
tuple of ints |
Origin pixel coordinates where to start the cut out. Follows matrix indexing |
[0, 0] |
correct_offsets |
boolean |
Check and correct for coordinate offset due to wrong WCS. It is off by default. |
False |
plot_offsets |
boolean |
Create diagnostic plot for oordinate offset correction. |
False |
magnitude_limit |
float |
Limiting magnitude to query Gaia catalog. |
18 |
dr |
int |
Gaia data release to be use, default is 3, options are DR2 and EDR3 |
3 |
sources |
pandas.DataFrame |
Catalog with sources to be extracted by PSFMachine |
None |
**kwargs |
dictionary |
Keyword arguments that defines shape model in a |
{} |
Returns:
Type | Description |
---|---|
Machine object |
A Machine class object built from the FFI. |
load_shape_model(self, input=None, plot=False)
Loads a PRF model from disk.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
input |
str, None |
Input file name. If None, one will be generated. |
None |
plot |
boolean |
Plot the PRF mean model loaded from disk |
False |
plot_image(self, ax=None, sources=False, frame_index=0)
Function to plot the Full Frame Image and Gaia sources.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
ax |
matplotlib.axes |
Matlotlib axis can be provided, if not one will be created and returned. |
None |
sources |
boolean |
Whether to overplot or not the source catalog. |
False |
frame_index |
int |
Time index used to plot the image data. |
0 |
Returns:
Type | Description |
---|---|
matplotlib.axes |
Matlotlib axis with the figure. |
plot_pixel_masks(self, ax=None)
Function to plot the mask used to reject saturated and bright pixels.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
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. |
residuals(self, plot=False, zoom=False, metric='residuals')
Get the residuals (model - image) and compute statistics. It creates a model
of the full image using the mean_model
and the weights computed when fitting
the shape model.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
plot |
bool |
Do plotting. |
False |
zoom |
bool |
If plot is True then zoom into a section of the image for better visualization. |
False |
metric |
string |
Type of metric used to plot. Default is "residuals", "chi2" is also available. |
'residuals' |
Returns:
Type | Description |
---|---|
matplotlib figure |
Figure. |
save_flux_values(self, output=None, format='fits')
Saves the flux values of all sources to a file. For FITS output files a multi-
extension file is created with each extension containing a single cadence/frame.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
output |
str, None |
Output file name. If None, one will be generated. |
None |
format |
str |
Format of the output file. Only FITS is supported for now. |
'fits' |
save_shape_model(self, output=None)
Saves the weights of a PRF fit to disk.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
output |
str, None |
Output file name. If None, one will be generated. |
None |