Fluxes#

class prose.Fluxes[source]#

Photometric fluxes, from single to multiple stars and apertures.

Can hold other measurements time-series, errors and apertures properties.

Methods

__init__(fluxes[, time, errors, data, ...])

autodiff()

Automatic differential photometry with Broeg et al. 2005.

best_aperture_index([method, sigma])

Find index of best aperture

bin(size[, estimate_error])

Returns a Fluxes instance with binned time series

copy()

Deep copy of the object

diff([comps])

Differential photometry.

errorbar([color, fmt])

Error bar plot of the light curve

estimate_best_aperture([target, method, sigma])

Inplace setting of best aperture.

load()

Load fluxes from file

mask(array)

Mask time-dependant fluxes attributes (time, fluxes, errors, data)

mask_stars(mask[, keep_indexing])

Mask stars fluxes.

plot([marker, color, ls, ax])

Plot light curve

save(path)

Save fluxes to file

sigma_clip_flux([iterations, sigma])

Return a Fluxes instance masked using iteratively sigma clipping.

sigma_clipping_data([iterations])

Return a Fluxes instance masked using iteratively sigma clipped data.

vander(**kwargs)

Attributes

aperture

Index of selected aperture

apertures

Apertures radii

comparisons

Comparison stars indices ordered from most to less weighted

data

A dict of data time-series, each with the same shape as time

dataframe

Pandas dataframe of the fluxes and associated measurements

df

Pandas dataframe of the fluxes and associated measurements

error

Error of the target flux

errors

Errors with same shape as fluxes

flux

Main flux

metadata

Metadata

ndim

Number of dimensions of fluxes

shape

shape of fluxes

target

Index of selected target

time

Array of observed time

weights

Fluxes weights (from differential photometry)

fluxes

Fluxes either as 1, 2, or 3 dimensional arrays, with following dimensions - 1: (time) - 2: (star, time) - 3: (aperture, star, time)