Observation

class prose.Observation

Class to load and analyze photometry products

Parameters:

• photfile (str) – path of the .phot file to load

• time_verbose (bool, optional) – whether time conversion success should be verbose

Methods

__init__(photfile[, time_verbose])	param photfile: path of the .phot file to load
assert_stack()
best_polynomial([add, verbose])	Return the best systematics polynomial model orders.
binn(dt[, std, keep_coords])
broeg2005([inplace, cut, nans])	The Broeg et al. 2005 differential photometry algorithm.
compute_bjd([version])	Compute BJD_tdb based on current time
copy()
diff(comps[, inplace])	Differential photometry based on a set of comparison stars
dm_bic(dm)
dm_ll(dm)
flip_correction([inplace])	Align all differential fluxes using a step model of the meridian flip
folder_to_phot([confirm])	replace all the phot file parent folder content by the phot file
keep_good_stars([threshold, ...])	Keep only stars with a median flux higher than threshold*sky.
lc_widget([width])	[notebook/jupyter feature] displays a widget to play with light curve aperture and binning
load(filepath)
lstsq(X[, star, split])	Given a design matrix return the fitted trend
mask(mask[, dim])
noise_stats([bins, verbose])
pick_best_aperture([method, return_criterion])
plate_solve()	Plate solve the current py::stack
plot([star, meridian_flip, bins, color, std])	Plot observation light curve
plot_comps_lcs([n, ylim])	Plot comparison stars light curves along target star light curve
plot_detrended([star, bins, color, std, ...])
plot_meridian_flip()	Plot vertical line marking the meridian flip time if any
plot_precision([bins, aperture])	Plot observation precision estimate against theorethical error (background noise, photon noise and CCD equation)
plot_psf_model([star, size, cmap, c, model, ...])	Plot a PSF model fit of the a PSF
plot_radial_psf([star, n, zscale, aperture, ...])	Plot star cutout overalid with aperture and radial flux.
plot_raw_diff()	Plot raw target flux and differantial flux
plot_summary([ylim, zscale])
plot_systematics([fields, ylim, ...])	Plot systematics measurements along target light curve
plot_systematics_signal(systematics[, ...])	Plot a systematics and signal model over diff_flux.
polynomial(**orders)	Return a design matrix representing a polynomial model
polynomial_trend([bic, verbose])
pont2006([plot])
query_catalog(name[, correct_pm])
save([destination, verbose])	Save current observation
set_attribute(file, **kwargs)
set_catalog_target(catalog_name, designation)
set_gaia_target(gaia_id[, verbose, raise_far])
show_stars([view, n, flip, comp_color, ...])	Show detected stars over stack image
sigma_clip([sigma, star])	Sigma clipping
step([t0])	Two parameter step model model.
to_csv(destination[, sep, old])	Export a typical csv of the observation's data
transit(t0, duration[, depth])	A simple transit model
where(condition)	return filtered observation given a boolean mask of time

Attributes

X
aperture
comparison_raw_fluxes
date
detrended_diff_flux
diff_error
diff_flux
has_diff
has_stack
label	{telescope}_{date}_{name}_{filter}
mean_epsf	rtype: The mean of the image effective PSF in pixels
mean_target_psf	rtype: An estimation of the fwhm of the target psf using a Gaussian 2D model in pixels
meridian_flip	Meridian flip time.
night_date
optimal_aperture	rtype: The optimal aperture radius in pixels
raw_error
raw_flux
simbad	simbad query url for specified target
simbad_url	[notebook feature] clickable simbad query url for specified target
stack
target
trend
wcs
x
xlabel	Plot xlabel (time) according to its units