Exposure Time Calculator¶

Calculating Exposure Times and Limiting Magnitude¶

This file provides a simple functions to calculate exposure times or limiting magnitudes.

ETC.ETC.SNR(info, magnitude=24.5, exptime=565.0, exposures=3, galaxy=True, background=True, diginoise=False)¶

Calculates the signal-to-noise ratio for an object of a given magnitude in a given exposure time and a number of exposures.

Parameters:	info (dict) – instrumental information such as zeropoint and background magnitude (float or ndarray) – input magnitude of an object(s) exptime (float) – exposure time [seconds] exposures (int) – number of exposures [default = 3] galaxy (boolean) – whether the exposure time should be calculated for an average galaxy or a star. If galaxy=True then the fraction of flux within an aperture is lower than in case of a point source. background (boolean) – whether to include background from sky, instrument, and dark current [default=True] diginoise (boolean) – if the readout noise is undersampled or poorly resolved then the effective readout noise should be used [default = False]
Returns:	signal-to-noise ratio
Return type:	float or ndarray

ETC.ETC.SNRproptoPeak(info, exptime=565.0, exposures=1, diginoise=False, server=False)¶

Calculates the relation between the signal-to-noise ratio and the electrons in the peak pixel.

Parameters:	info (dict) – instrumental information such as zeropoint and background exptime (float) – exposure time [seconds] exposures (int) – number of exposures [default = 1] diginoise (bool) – if the readout noise is undersampled or poorly resolved then the effective readout noise should be used [default = False] server (bool) – whether to save the figure in a PNG or PDF format (the former can be used together with the WWW server)
Returns:	signal-to-noise ratio
Return type:	float or ndarray

ETC.ETC.exposureTime(info, magnitude, snr=10.0, exposures=3, fudge=0.7, galaxy=True, diginoise=False)¶

Returns the exposure time for a given magnitude.

Parameters:	info (dict) – information describing the instrument magnitude (float or ndarray) – the magnitude of the object snr (float) – signal-to-noise ratio required [default = 10.0]. exposures (int) – number of exposures that the object is present in [default = 3] fudge (float) – the fudge parameter to which to use to scale the snr to SExtractor required [default = 0.7] galaxy (boolean) – whether the exposure time should be calculated for an average galaxy or a star. If galaxy=True then the fraction of flux within an aperture is lower than in case of a point source. diginoise (boolean) – if the readout noise is undersampled or poorly resolved then the effective readout noise should be used [default = False]
Returns:	exposure time [seconds]
Return type:	float or ndarray

ETC.ETC.galaxyDetection(info, magnitude=24.5, exposures=3, exptime=565)¶

Can be used to study the ghost contribution to the galaxy detection.

Parameters:	info – magnitude – object detection magnitude limit exposures – number of exposures to be combined exptime – individual exposure time
Returns:	number of electrons tolerated in the ghost

ETC.ETC.limitingMagnitude(info, exp=565, snr=10.0, exposures=3, fudge=0.7, galaxy=True, diginoise=False)¶

Calculates the limiting magnitude for a given exposure time, number of exposures and minimum signal-to-noise level to be reached.

Parameters:	info (dict) – instrumental information such as zeropoint and background exp (float or ndarray) – exposure time [seconds] snr (float or ndarray) – the minimum signal-to-noise ratio to be reached. .. Note:: This is couple to the fudge parameter: snr_use = snr / fudge exposures (int) – number of exposures [default = 3] fudge (float) – a fudge factor to divide the given signal-to-noise ratio with to reach to the required snr. This is mostly due to the fact that SExtractor may require a higher snr than what calculated otherwise. galaxy (boolean) – whether the exposure time should be calculated for an average galaxy or a star. If galaxy=True then the fraction of flux within an aperture is lower than in case of a point source. diginoise (boolean) – if the readout noise is undersampled or poorly resolved then the effective readout noise should be used [default = False]
Returns:	limiting magnitude given the input information
Return type:	float or ndarray