lightkurve.targetpixelfile.KeplerTargetPixelFile(path, quality_bitmask='default', **kwargs)¶Bases: lightkurve.targetpixelfile.TargetPixelFile
Class to read and interact with the pixel data products (“Target Pixel Files”) created by NASA’s Kepler pipeline.
This class offers a user-friendly way to open a Kepler Target Pixel File (TPF), access its meta data, visualize its contents, extract light curves with custom aperture masks, estimate centroid positions, and more.
Please consult the TargetPixelFile tutorial in the online documentation for examples on using this class.
HDUListPath to a Kepler Target Pixel file. Alternatively, you can pass a
HDUList object, which is the AstroPy object returned by
the astropy.io.fits.open function.
Bitmask that should be used to ignore bad-quality cadences. If a string is passed, it has the following meaning:
“none”: no cadences will be ignored (equivalent to
quality_bitmask=0).“default”: cadences with severe quality issues will be ignored (equivalent to
quality_bitmask=1130799).“hard”: more conservative choice of flags to ignore (equivalent to
quality_bitmask=1664431). This is known to remove good data.“hardest”: remove all cadences that have one or more flags raised (equivalent to
quality_bitmask=2096639). This mask is not recommended because some quality flags can safely be ignored.
If an integer is passed, it will be used as a bitmask, i.e. it will
have the effect of removing cadences where
(tpf.hdu[1].data['QUALITY'] & quality_bitmask) > 0.
See the KeplerQualityFlags class for details on the bitmasks.
Optional keyword arguments passed on to astropy.io.fits.open.
References
Kepler: A Search for Terrestrial Planets. Kepler Archive Manual. http://archive.stsci.edu/kepler/manuals/archive_manual.pdf
Attributes Summary
Returns an AstroPy Time object for all good-quality cadences. |
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Return the cadence number for all good-quality cadences. |
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K2 Campaign number. |
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Kepler CCD channel number. |
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CCD pixel column number (‘1CRV5P’ header keyword). |
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Declination of target (‘DEC_OBJ’ header keyword). |
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Returns the flux for all good-quality cadences. |
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Returns the background flux for all good-quality cadences. |
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Returns the flux uncertainty for all good-quality cadences. |
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Returns the header of the primary extension. |
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‘Kepler’ or ‘K2’. |
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Kepler CCD module number. |
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Returns a boolean mask flagging cadences whose time is |
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‘short cadence’ or ‘long cadence’. |
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Kepler CCD module output number. |
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Returns the optimal aperture mask used by the pipeline. |
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Returns the column position correction. |
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Returns the row position correction. |
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Returns the quality flag integer of every good cadence. |
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Kepler quarter number. |
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Right Ascension of target (‘RA_OBJ’ header keyword). |
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CCD pixel row number (‘2CRV5P’ header keyword). |
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Return the cube dimension shape. |
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Returns the time for all good-quality cadences. |
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Returns an |
Methods Summary
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Returns an aperture mask creating using the thresholding method. |
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Cut a rectangle out of the Target Pixel File. |
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Returns the flux center of an object inside |
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Returns a LightCurve obtained using aperture photometry. |
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Returns the results of PRF photometry applied to the pixel file. |
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Creates a new Target Pixel File from a set of images. |
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Returns two 3D arrays of RA and Dec values in decimal degrees. |
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Returns a header keyword value. |
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Returns a default |
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Returns an object of KeplerPRF initialized using the necessary metadata in the tpf object. |
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Display an interactive Jupyter Notebook widget to inspect the pixel data. |
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Display a Jupyter Notebook widget showing Gaia DR2 positions on top of the pixels. |
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Plot the pixel data for a single frame (i.e. |
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Prints a description of all non-callable attributes. |
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Returns a |
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Writes the TPF to a FITS file on disk. |
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Performs photometry on the pixel data and returns a LightCurve object. |
Attributes Documentation
astropy_time¶Returns an AstroPy Time object for all good-quality cadences.
cadenceno¶Return the cadence number for all good-quality cadences.
campaign¶K2 Campaign number. (‘CAMPAIGN’ header keyword)
channel¶Kepler CCD channel number. (‘CHANNEL’ header keyword)
column¶CCD pixel column number (‘1CRV5P’ header keyword).
dec¶Declination of target (‘DEC_OBJ’ header keyword).
flux¶Returns the flux for all good-quality cadences.
flux_bkg¶Returns the background flux for all good-quality cadences.
flux_bkg_err¶flux_err¶Returns the flux uncertainty for all good-quality cadences.
hdu¶header¶Returns the header of the primary extension.
mission¶‘Kepler’ or ‘K2’. (‘MISSION’ header keyword)
module¶Kepler CCD module number. (‘MODULE’ header keyword)
nan_time_mask¶Returns a boolean mask flagging cadences whose time is nan.
obsmode¶‘short cadence’ or ‘long cadence’. (‘OBSMODE’ header keyword)
output¶Kepler CCD module output number. (‘OUTPUT’ header keyword)
pipeline_mask¶Returns the optimal aperture mask used by the pipeline.
pos_corr1¶Returns the column position correction.
pos_corr2¶Returns the row position correction.
quality¶Returns the quality flag integer of every good cadence.
quarter¶Kepler quarter number. (‘QUARTER’ header keyword)
ra¶Right Ascension of target (‘RA_OBJ’ header keyword).
row¶CCD pixel row number (‘2CRV5P’ header keyword).
shape¶Return the cube dimension shape.
time¶Returns the time for all good-quality cadences.
wcs¶Returns an astropy.wcs.WCS object with the World Coordinate System
solution for the target pixel file.
astropy.wcs.WCS objectWCS solution
Methods Documentation
create_threshold_mask(self, threshold=3, reference_pixel='center')¶Returns an aperture mask creating using the thresholding method.
This method will identify the pixels in the TargetPixelFile which show
a median flux that is brighter than threshold times the standard
deviation above the overall median. The standard deviation is estimated
in a robust way by multiplying the Median Absolute Deviation (MAD)
with 1.4826.
If the thresholding method yields multiple contiguous regions, then
only the region closest to the (col, row) coordinate specified by
reference_pixel is returned. For exmaple, reference_pixel=(0, 0)
will pick the region closest to the bottom left corner.
By default, the region closest to the center of the mask will be
returned. If reference_pixel=None then all regions will be returned.
A value for the number of sigma by which a pixel needs to be brighter than the median flux to be included in the aperture mask.
(col, row) pixel coordinate closest to the desired region.
For example, use reference_pixel=(0,0) to select the region
closest to the bottom left corner of the target pixel file.
If ‘center’ (default) then the region closest to the center pixel
will be selected. If None then all regions will be selected.
2D boolean numpy array containing True for pixels above the
threshold.
cutout(self, center=None, size=5)¶Cut a rectangle out of the Target Pixel File.
This methods returns a new TargetPixelFile object containing a
rectangle of a given size cut out around a given center.
astropy.SkyCoordCenter of the cutout. If an (int, int) tuple is passed, it will be
interpreted as the (column, row) coordinates relative to
the bottom-left corner of the TPF. If an astropy.SkyCoord is
passed then the sky coordinate will be used instead.
If None (default) then the center of the TPF will be used.
Number of pixels to cut out. If a single integer is passed then a square of that size will be cut. If a tuple is passed then a rectangle with dimensions (column_size, row_size) will be cut.
lightkurve.TargetPixelFile objectNew and smaller Target Pixel File object containing only the data cut out.
estimate_centroids(self, aperture_mask='pipeline', method='moments')¶Returns the flux center of an object inside aperture_mask.
Telescopes tend to smear out the light from a point-like star over multiple pixels. For this reason, it is common to estimate the position of a star by computing the geometric center of its image. Astronomers refer to this position as the centroid of the object, i.e. the term centroid is often used as a generic synonym to refer to the measured position of an object in a telescope exposure.
This function provides two methods to estimate the position of a star:
method='moments' will compute the “center of mass” of the light
based on the 2D image moments of the pixels inside aperture_mask.
method='quadratic' will fit a two-dimensional, second-order
polynomial to the 3x3 patch of pixels centered on the brightest pixel
inside the aperture_mask, and return the peak of that polynomial.
Following Vakili & Hogg 2016 (ArXiv:1610.05873, Section 3.2).
Which pixels contain the object to be measured, i.e. which pixels
should be used in the estimation? If None or ‘all’ are passed,
all pixels in the pixel file will be used. If ‘pipeline’ is passed,
the mask suggested by the official pipeline will be used.
If ‘threshold’ is passed, all pixels brighter than 3-sigma above
the median flux will be used.
Alternatively, users can pass a boolean array describing the
aperture mask such that True means that the pixel will be used.
Defines which method to use to estimate the centroids. ‘moments’ computes the centroid based on the sample moments of the data. ‘quadratic’ fits a 2D polynomial to the data and returns the coordinate of the peak of that polynomial.
Arrays containing the column and row positions for the centroid for each cadence, or NaN for cadences where the estimation failed.
extract_aperture_photometry(self, aperture_mask='pipeline', centroid_method='moments')¶Returns a LightCurve obtained using aperture photometry.
A boolean array describing the aperture such that True means
that the pixel will be used.
If None or ‘all’ are passed, all pixels will be used.
If ‘pipeline’ is passed, the mask suggested by the official pipeline
will be returned.
If ‘threshold’ is passed, all pixels brighter than 3-sigma above
the median flux will be used.
For the details on this arguments, please refer to the documentation
for TargetPixelFile.estimate_centroids.
Array containing the summed flux within the aperture for each cadence.
extract_prf_photometry(self, cadences=None, parallel=True, **kwargs)¶Returns the results of PRF photometry applied to the pixel file.
Cadences to fit. If None (default) then all cadences will be fit.
If True, fitting cadences will be distributed across multiple
cores using Python’s multiprocessing module.
Keywords to be passed to tpf.get_model() to create the
TPFModel object that will be fit.
Object that provides access to PRF-fitting photometry results and various diagnostics.
from_fits_images(images, position, size=(11, 11), extension=1, target_id='unnamed-target', hdu0_keywords=None, **kwargs)¶Creates a new Target Pixel File from a set of images.
This method is intended to make it easy to cut out targets from Kepler/K2 “superstamp” regions or TESS FFI images.
Sorted list of FITS filename paths or ImageHDU objects to get the data from.
Position around which to cut out pixels.
Dimensions (cols, rows) to cut out around position.
If images is a list of filenames, provide the extension number
or name to use. Default: 0.
Unique identifier of the target to be recorded in the TPF.
Additional keywords to add to the first header file.
Extra arguments to be passed to the KeplerTargetPixelFile constructor.
A new Target Pixel File assembled from the images.
get_bkg_lightcurve(self, aperture_mask=None)¶get_coordinates(self, cadence='all')¶Returns two 3D arrays of RA and Dec values in decimal degrees.
If cadence number is given, returns 2D arrays for that cadence. If cadence is ‘all’ returns one RA, Dec value for each pixel in every cadence. Uses the WCS solution and the POS_CORR data from TPF header.
Which cadences to return the RA Dec coordinates for.
Array containing RA values for every pixel, for every cadence.
Array containing Dec values for every pixel, for every cadence.
get_keyword(self, keyword, hdu=0, default=None)¶Returns a header keyword value.
If the keyword is Undefined or does not exist,
then return default instead.
get_model(self, star_priors=None, **kwargs)¶Returns a default TPFModel object for PRF fitting.
The default model only includes one star and only allows its flux
and position to change. A different set of stars can be added using
the star_priors parameter.
Arguments to be passed to the TPFModel constructor, e.g.
star_priors.
Model with appropriate defaults for this Target Pixel File.
get_prf_model(self)¶Returns an object of KeplerPRF initialized using the necessary metadata in the tpf object.
interact(self, notebook_url='localhost:8888', max_cadences=30000, aperture_mask='pipeline', exported_filename=None, transform_func=None, ylim_func=None)¶Display an interactive Jupyter Notebook widget to inspect the pixel data.
The widget will show both the lightcurve and pixel data. By default,
the lightcurve shown is obtained by calling the to_lightcurve() method,
unless the user supplies a custom LightCurve object.
This feature requires an optional dependency, bokeh (v0.12.15 or later).
This dependency can be installed using e.g. conda install bokeh.
At this time, this feature only works inside an active Jupyter Notebook, and tends to be too slow when more than ~30,000 cadences are contained in the TPF (e.g. short cadence data).
Location of the Jupyter notebook page (default: “localhost:8888”) When showing Bokeh applications, the Bokeh server must be explicitly configured to allow connections originating from different URLs. This parameter defaults to the standard notebook host and port. If you are running on a different location, you will need to supply this value for the application to display properly. If no protocol is supplied in the URL, e.g. if it is of the form “localhost:8888”, then “http” will be used.
Raise a RuntimeError if the number of cadences shown is larger than this value. This limit helps keep browsers from becoming unresponsive.
A boolean array describing the aperture such that True means
that the pixel will be used.
If None or ‘all’ are passed, all pixels will be used.
If ‘pipeline’ is passed, the mask suggested by the official pipeline
will be returned.
If ‘threshold’ is passed, all pixels brighter than 3-sigma above
the median flux will be used.
An optional filename to assign to exported fits files containing the custom aperture mask generated by clicking on pixels in interact. The default adds a suffix ‘-custom-aperture-mask.fits’ to the TargetPixelFile basename.
A function that transforms the lightcurve. The function takes in a LightCurve object as input and returns a LightCurve object as output. The function can be complex, such as detrending the lightcurve. In this way, the interactive selection of aperture mask can be evaluated after inspection of the transformed lightcurve. The transform_func is applied before saving a fits file. Default: None (no transform is applied).
A function that returns ylimits (low, high) given a LightCurve object. The default is to return an expanded window around the 10-90th percentile of lightcurve flux values.
Examples
To select an aperture mask for V827 Tau:
>>> import lightkurve as lk
>>> tpf = lk.search_targetpixelfile("V827 Tau", mission="K2").download()
>>> tpf.interact()
To see the full y-axis dynamic range of your lightcurve and normalize the lightcurve after each pixel selection:
>>> ylim_func = lambda lc: (0.0, lc.flux.max())
>>> transform_func = lambda lc: lc.normalize()
>>> tpf.interact(ylim_func=ylim_func, transform_func=transform_func)
interact_sky(self, notebook_url='localhost:8888', magnitude_limit=18)¶Display a Jupyter Notebook widget showing Gaia DR2 positions on top of the pixels.
Location of the Jupyter notebook page (default: “localhost:8888”) When showing Bokeh applications, the Bokeh server must be explicitly configured to allow connections originating from different URLs. This parameter defaults to the standard notebook host and port. If you are running on a different location, you will need to supply this value for the application to display properly. If no protocol is supplied in the URL, e.g. if it is of the form “localhost:8888”, then “http” will be used.
A value to limit the results in based on Gaia Gmag. Default, 18.
plot(self, ax=None, frame=0, cadenceno=None, bkg=False, aperture_mask=None, show_colorbar=True, mask_color='pink', title=None, style='lightkurve', **kwargs)¶Plot the pixel data for a single frame (i.e. at a single time).
The time can be specified by frame index number (frame=0 will show the
first frame) or absolute cadence number (cadenceno).
AxesA matplotlib axes object to plot into. If no axes is provided, a new one will be generated.
Frame number. The default is 0, i.e. the first frame.
Alternatively, a cadence number can be provided. This argument has priority over frame number.
If True, background will be added to the pixel values.
Highlight pixels selected by aperture_mask.
Whether or not to show the colorbar
Color to show the aperture mask
Path or URL to a matplotlib style file, or name of one of matplotlib’s built-in stylesheets (e.g. ‘ggplot’). Lightkurve’s custom stylesheet is used by default.
Keywords arguments passed to lightkurve.utils.plot_image.
AxesThe matplotlib axes object.
prf_lightcurve(self, **kwargs)¶show_properties(self)¶Prints a description of all non-callable attributes.
Prints in order of type (ints, strings, lists, arrays, others).
to_corrector(self, method='pld')¶Returns a Corrector instance to remove systematics.
Currently, only “pld” is supported. This will return a
PLDCorrector class instance.
lightkurve.CorrecterInstance of a Corrector class, which typically provides correct()
and diagnose() methods.
to_fits(self, output_fn=None, overwrite=False)¶Writes the TPF to a FITS file on disk.
to_lightcurve(self, method='aperture', **kwargs)¶Performs photometry on the pixel data and returns a LightCurve object.
See the docstring of aperture_photometry() for valid
arguments if the method is ‘aperture’. Otherwise, see the docstring
of prf_photometry() for valid arguments if the method is ‘prf’.
Photometry method to use.
Extra arguments to be passed to the aperture_photometry or the
prf_photometry method of this class.
Object containing the resulting lightcurve.