ToolBox
- pyLIMA.toolbox.brightness_transformation.error_flux_to_error_magnitude(error_flux, flux)
Return error in magnitudes from error in flux and fluxes
- Parameters:
error_flux (array, an array of errors in flux)
flux (array, the corresponding fluxes)
- Returns:
error_magnitude
- Return type:
array, the error in magnitudes
- pyLIMA.toolbox.brightness_transformation.error_magnitude_to_error_flux(error_magnitude, flux)
Return error in fluxes from error in magnitudes and fluxes
- Parameters:
error_magnitude (array, the error in magnitudes)
flux (array, the corresponding fluxes)
- Returns:
error_flux
- Return type:
array, an array of errors in flux
- pyLIMA.toolbox.brightness_transformation.flux_to_magnitude(flux)
Return magnitude from fluxes
- Parameters:
flux (array, the corresponding fluxes)
- Returns:
magnitude
- Return type:
array, an array of magnitudes
- pyLIMA.toolbox.brightness_transformation.magnitude_to_flux(magnitude)
Return flux from magnitude
- Parameters:
magnitude (array, an array of magnitudes)
- Returns:
flux
- Return type:
array, the corresponding fluxes
- pyLIMA.toolbox.brightness_transformation.noisy_observations(flux, exp_time=None, efficiency=None)
Add Poisson noise to observations
- Parameters:
flux (array, the corresponding fluxes)
exp_time (float, the exposure time in seconds)
- Returns:
flux_observed (array, the observed flux)
err_flux_observed (array, the corresponding uncertainties)
- pyLIMA.toolbox.fake_telescopes.create_a_fake_telescope(lightcurve=None, astrometry=None, name='A Fake Telescope', astrometry_unit='deg')
Create a telescope for plots
- Parameters:
light_curve (array, the lightcurves in magnitude)
astrometry_curve (array, the astrometric time series)
name (str, the telescope name)
astrometry_unit (str, the unit of astrometry)
- Returns:
telescope
- Return type:
object, a telescope object
- pyLIMA.toolbox.limb_darkening_table.read_claret_data(file_name, camera_filter)
Read in claret data from file.
- Parameters:
file_name – Path and name of data file.
camera_filter – Retrieve data for supplied filter.
- Returns:
Generator of claret table.
- pyLIMA.toolbox.plots.plot_light_curve_flux(time, flux, flux_error=None, figure_axe=None)
Plot a lightcurve in flux
- Parameters:
time (array, the time to plot)
flux (array, the flux to plot)
flux_error (array, the flux error)
figure_axe (matplotlib.axe, an axe to plot)
- pyLIMA.toolbox.plots.plot_light_curve_magnitude(time, mag, mag_error=None, figure_axe=None, color=None, linestyle='-', marker=None, name=None)
Plot a lightcurve in magnitude
- Parameters:
time (array, the time to plot)
mag (array, the magnitude to plot)
mag_error (array, the magnitude error)
figure_axe (matplotlib.axe, an axe to plot)
color (str, a color string)
linestyle (str, the matplotlib linestyle desired)
marker (str, the matplotlib marker)
name (str, the points name)
- pyLIMA.toolbox.time_series.clean_time_series(data)
Check an array of non-finite and duplicates values
- Parameters:
data (array, the array to clean)
- Returns:
good_lines (list, the list of index containing correct values)
non_finite_lines (list, the list of index containing non-finite values)
non_unique_lines (list, the list of index containing duplicate values)
- pyLIMA.toolbox.time_series.construct_time_series(data, columns_names, column_units)
Construct an astropy table based on data, column names and columns units
- Parameters:
data (array, the array containing data)
columns_names (array, the columns names)
columns_units (array,the columns units)
- Returns:
table
- Return type:
array, the astropy table