Py Dict Structure of JWST Output¶
The PandExo output is organized into Python Dictionaries. See example notebooks for an explanation of how to manipulate these and plot the most common outputs. Below is a breakdown of everything contained in the PandExo output dictionary.
FinalSpectrum (contains 4 keys)¶
spectrum_w_rand: Planet spectrum with random noise added in units of (Rp/Rs)2 or (Fp/Fs)
spectrum: Planet spectrum with no random noise
error_w_floor: Error with user defined noise floor. If no floor was specified, there is no floor.
wave: wavelength (microns)
OriginalInput (contains 2 keys)¶
model_wave: original wavelength input by user
model_spec: original spectrum input by user
Warning (contains 6 keys)¶
Num Groups Reset?: Before PandExo simulates in and out of transit observations, it computes a single integration with 2 groups in order to figure out how many additional groups it can add before hitting saturation. If it computes a number less than 2, it resets the number of groups to 2.
Group Number Too Low?: Prints out warning if number of groups is less than 5 and the saturation level less than 60%.
Group Number Too High?: Prints out warning if number of groups per integration exceeds 65536
Saturated?: This is an output directly taken from Pandeia’s “hard saturation” flag. If there are any saturated pixels, it will alert you here. You can also see the saturation profile.
Non linear?: This is an output directly taken from Pandeia’s “soft saturation” flag.
% full well high?: If you’ve set the saturation level over 80%, it will warn you.
print dict['Warning']['Num Groups Reset?']
PandeiaOutTrans (contains 9 keys)¶
This is the raw output of Pandeia’s simulation of the out of transit observation. For a complete breakdown of these outputs go to STScI’s Pandeia Documentation.
RawData (contains 6 keys)¶
var_in: The variance of only the in transit data
wave: wavelength vector
flux_in: Flux of the in transit data in units of e-/s
flux_out: Flux of the out of transit data in units of e-/s
error_no_floor: Error without any noise floor
var_out: The variance of only the out of transit data
Timing (contains 10 keys)¶
Seconds per Frame
Number of Transits
Observing Efficiency (%) = (num groups - 1)/(num groups + 1)
Num Integrations Out of Transit
On Source Time
Exposure Time Per Integration (secs)
Reset time Plus TA time (hrs): Target acquisition time is assumed to be 30 minutes
Num Integrations In Transit
Num Groups per Integration
Num Integrations per Occultation
print dict['Timing']['Seconds per Frame']
Input (contains 10 keys)¶
Saturation Level (electons)
print dict['Input']['Target Mag']
Timing, Warning, and Input Divs (all contain html script)¶
Here are the html scripts for the three tables that are rendered on the website output page.