def pandeia_instrument(self):
if hasattr(self, "_instrument"):
return self._instrument
from pandeia.engine.calc_utils import build_default_calc
from pandeia.engine.instrument_factory import InstrumentFactory
translate_instrument = {
'wfi': 'wfirstimager',
'nircamlong': 'nircam',
'nircamshort': 'nircam',
'miri': 'miri'
}
conf = build_default_calc(
self.TELESCOPE.lower(),
translate_instrument.get(self.INSTRUMENT.lower(),
self.INSTRUMENT.lower()),
self.MODE)['configuration']
conf['instrument']['filter'] = self.filter.lower()
self.logger.info("Creating Instrument with Configuration {}".format(
conf['instrument']))
self._instrument = InstrumentFactory(config=conf)
return self._instrument
def run_calc(self, b):
c = build_default_calc("wfirst", "wfirstimager", "imaging")
c['configuration']['detector']['nexp'] = self.nexps.value
c['configuration']['detector']['ngroup'] = self.ngroups.value
c['configuration']['detector']['nint'] = self.nints.value
c['configuration']['detector']['readmode'] = self.readmode.value
c['configuration']['detector']['subarray'] = self.subarray.value
c['configuration']['instrument']['filter'] = self.filt.value
src = c['scene'][0]
if self.src_select.value == "extended":
src['shape']['geometry'] = 'sersic'
a = self.ext_scale.value
e = self.ellip.value
b = (1.0 - e) * a
s_idx = self.sersic_idx[self.sersic.value]
# if gaussian, convert a/b to sigma
if s_idx == 0.5:
a *= np.sqrt(2.0)
b *= np.sqrt(2.0)
src['shape']['major'] = a
src['shape']['minor'] = b
src['shape']['sersic_index'] = s_idx
src['position']['orientation'] = self.posang.value
src['spectrum']['redshift'] = self.redshift.value
src['spectrum']['normalization']['norm_flux'] = self.flux.value
src['spectrum']['normalization']['norm_fluxunit'] = self.units.value
src['spectrum']['normalization']['norm_wave'] = self.wave.value
sed = self.sed_select.value
if sed == "power-law":
src['spectrum']['sed']['sed_type'] = "powerlaw"
src['spectrum']['sed']['index'] = self.pl_index.value
if sed == "blackbody":
src['spectrum']['sed']['sed_type'] = "blackbody"
src['spectrum']['sed']['temp'] = self.bb_temp.value
if sed == "star":
src['spectrum']['sed']['sed_type'] = "phoenix"
src['spectrum']['sed']['key'] = self.star_config[self.stars.value]
if sed == "extragalactic":
src['spectrum']['sed']['sed_type'] = "brown"
src['spectrum']['sed']['key'] = self.gal_config[self.galaxies.value]
c['strategy']['aperture_size'] = self.ap_size.value
ann = [self.ann_inner.value, self.ann_outer.value]
c['strategy']['sky_annulus'] = ann
self.r = perform_calculation(c, dict_report=True)
self.calc_input = c
self.plot_form.visible = True
self.esn.value = "%.2f" % self.r['scalar']['sn']
self.eflux.value = "%.2f" % self.r['scalar']['flux']
self.etime.value = "%.2f" % self.r['scalar']['on_source_time']
self.tab_form.visible = True
self.update_plots()
def target_acq(instrument, both_spec, warning):
"""Contains functionality to compute optimal TA strategy
Takes pandexo normalized flux from create_input and checks for saturation, or
if SNR is below the minimum requirement for each. Then adds warnings and 2d displays
and target acq info to final output dict
Parameters
----------
instrument : str
possible options are niriss, nirspec, miri and nircam
both_spec : dict
output dictionary from **create_input**
warning : dict
output dictionary from **add_warnings**
Retruns
-------
"""
out_spectrum = np.array([both_spec['wave'], both_spec['flux_out_trans']])
#this automatically builds a default calculation
#I got reasonable answers for everything so all you should need to do here is swap out (instrument = 'niriss', 'nirspec','miri' or 'nircam')
c = build_default_calc(telescope='jwst',
instrument=instrument,
mode='target_acq',
method='taphot')
c['scene'][0]['spectrum']['sed'] = {
'sed_type': 'input',
'spectrum': out_spectrum
}
c['scene'][0]['spectrum']['normalization']['type'] = 'none'
rphot = perform_calculation(c, dict_report=True)
#check warnings (pandeia doesn't return values for these warnings, so try will fail if all good)
try:
warnings['TA Satruated?'] = rphot['warnings']['saturated']
except:
warnings['TA Satruated?'] = 'All good'
try:
warnings['TA SNR Threshold'] = rphot['warnings']['ta_snr_threshold']
except:
warnings['TA SNR Threshold'] = 'All good'
#build TA dict
ta = {
'sn': rphot['scalar']['sn'],
'ngroup': rphot['input']['configuration']['detector']['ngroup'],
'saturation': rphot['2d']['saturation']
}
def run_engine(self):
c = build_default_calc("wfirst", "wfirstimager", "imaging")
c['configuration']['detector']['nexp'] = self.nexps.value
c['configuration']['detector']['ngroup'] = self.ngroups.value
c['configuration']['detector']['nint'] = self.nints.value
c['configuration']['detector']['readmode'] = self.readmode.value
c['configuration']['detector']['subarray'] = self.subarray.value
c['configuration']['instrument']['filter'] = self.filt.value
src = c['scene'][0]
if self.src_select.value == "extended":
src['shape']['geometry'] = 'sersic'
a = self.ext_scale.value
e = self.ellip.value
b = (1.0 - e) * a
s_idx = self.sersic_idx[self.sersic.value]
# if gaussian, convert a/b to sigma
if s_idx == 0.5:
a *= np.sqrt(2.0)
b *= np.sqrt(2.0)
src['shape']['major'] = a
src['shape']['minor'] = b
src['shape']['sersic_index'] = s_idx
src['position']['orientation'] = self.posang.value
src['spectrum']['redshift'] = self.redshift.value
src['spectrum']['normalization']['norm_flux'] = self.flux.value
src['spectrum']['normalization']['norm_fluxunit'] = self.units.value
src['spectrum']['normalization']['norm_wave'] = self.wave.value
sed = self.sed_select.value
if sed == "power-law":
src['spectrum']['sed']['sed_type'] = "powerlaw"
src['spectrum']['sed']['index'] = self.pl_index.value
if sed == "blackbody":
src['spectrum']['sed']['sed_type'] = "blackbody"
src['spectrum']['sed']['temp'] = self.bb_temp.value
if sed == "star":
src['spectrum']['sed']['sed_type'] = "phoenix"
src['spectrum']['sed']['key'] = self.star_config[self.stars.value]
if sed == "extragalactic":
src['spectrum']['sed']['sed_type'] = "brown"
src['spectrum']['sed']['key'] = self.gal_config[self.galaxies.value]
c['strategy']['aperture_size'] = self.ap_size.value
c['strategy']['sky_annulus'] = self.background_annulus.value
self._calculation_result = perform_calculation(c, dict_report=True)
self.calculation_input = c
def process_config(raw_config, target_scene, reference_scene):
"""
Process a variable that might be a file name, full JWST configuration dictionary, or instrument
configuration dictionary, along with optional target and reference scenes.
"""
if isinstance(raw_config, str):
# A JSON file. In this case, it should be a full pandeia config dictionary
if os.path.isfile(raw_config):
config = load_calculation(raw_config)
else:
error_str = "Error: File {} not found".format(
configuration_dict_or_filename)
raise FileNotFoundError(error_str)
elif isinstance(raw_config, dict) and "configuration" in raw_config:
# It's a dictionary. It contains a "configuration" key. Assume full pandeia dictionary.
config = deepcopy(raw_config)
elif isinstance(raw_config, dict):
instrument = raw_config["instrument"]["instrument"]
config = build_default_calc(jwst, instrument, "coronagraphy")
config['configuration']["instrument"] = deepcopy(raw_config)
if target_scene is None:
print(
"Warning: input configuration had no scene info, and no separate target scene was provided. Using default coronagraphy target scene."
)
else:
error_str = "Invalid input {}".format(configuration_dict_or_filename)
raise ValueError(error_str)
if target_scene is not None:
if isinstance(target_scene, list):
config['scene'] = deepcopy(target_scene)
else:
config['scene'] = [deepcopy(target_scene)]
if reference_scene is not None:
if isinstance(reference_scene, list):
config['strategy']['psf_subtraction_source'] = deepcopy(
reference_scene[0])
else:
config['strategy']['psf_subtraction_source'] = deepcopy(
reference_scene)
return config
'background', 'extinction'):
shutil.copytree(join(pandeia_refdata, folder_name),
join(destination, folder_name))
# Patch the data package's config file for WFIRST WFI
shutil.copy(
join(dirname(__file__), 'data_patch', 'wfirstimager_config.json'),
join(destination, 'wfirst', 'wfirstimager', 'config.json'))
log("New data package in", destination)
return destination
if __name__ == "__main__":
# Make package
data_dir = make_data_package(log=print, overwrite=True)
# Test package
os.environ['pandeia_refdata'] = data_dir
from pandeia.engine.perform_calculation import perform_calculation
from pandeia.engine.calc_utils import build_default_calc
calc = build_default_calc("wfirst", "wfirstimager", "imaging")
result = perform_calculation(calc, dict_report=True)
print("Successfully performed the default calculation for wfirstimager")
if sys.version_info > (3, 2):
archive_name = shutil.make_archive('pandeia_wfirst_data',
'gztar',
root_dir=dirname(data_dir),
base_dir=basename(data_dir))
print("Compressed WFIRST Pandeia data into {}".format(archive_name))
def sn_user_spec(inputs, disperser = 'prism', filt = 'clear', ngroup = 19, nint = 2, nexp = 36):
wl = inputs['wl'] #in microns
spec = inputs['spec'] #in mJy
xoff = inputs['xoff']
yoff = inputs['yoff']
configuration=build_default_calc('jwst','nirspec','msa')
configuration['configuration']['instrument']['disperser']=disperser
configuration['configuration']['instrument']['filter']=filt
#E - I *think* shutter location is just so that the detector gap is placed in the correct place
configuration['configuration']['instrument']['shutter_location']='q3_345_20'#'q4_345_20'
#exposure specifications from DEEP APT file
configuration['configuration']['detector']['ngroup']=ngroup
configuration['configuration']['detector']['nint']=nint
#PRISM
configuration['configuration']['detector']['nexp']=nexp
configuration['configuration']['detector']['readmode']='nrsirs2'
configuration['strategy']['dithers'][0]['on_source'] = inputs['onSource']
configuration['configuration']['instrument']['slitlet_shape'] = inputs['slitletShape']
#default configuration['configuration'] has 1x3 shutter config
scene = {}
if (inputs['re_circ'] > 0):
sersic=inputs['sersic_n']
re = inputs['re_maj']
ellip=1.-inputs['axis_ratio']
pa=inputs['position_angle']
major_axis = re
minor_axis = re*inputs['axis_ratio']
#pandeia used to use scale lengths, but now is fine with half-light radii
scene['shape']={'geometry':'sersic','major': major_axis,'minor':minor_axis,'sersic_index':sersic}
# #pandiea wants scale lengths not half-light radii
# major_axis,minor_axis=majorminor(sersic,rc,ellip)
# scene['position'] = {'x_offset':xoff, 'y_offset': yoff, 'orientation': pa, 'position_parameters':['x_offset','y_offset','orientation']}
# scene['shape']={'geometry':'sersic','major': major_axis,'minor':minor_axis,'sersic_index':sersic}
# print scene['shape']
else:
pa=inputs['position_angle']
#this is the dummy trigger to go for a point source
scene['position'] = {'x_offset':xoff, 'y_offset': yoff, 'orientation': pa, 'position_parameters':['x_offset','y_offset','orientation']}
scene['shape']={'geometry':'point'}
scene['spectrum'] = {}
scene['spectrum']['name'] = "continuum_spectrum"
scene['spectrum']['redshift'] = 0 #because otherwise it shifts the wavelength array...
#it doesn't seem to do anything with the normalization of the
#source spectrum, however?!
tempIdx = np.where((wl >= filterWlDict[filt]['low']) & (wl <= filterWlDict[filt]['high']))[0]
scene['spectrum']['sed'] = {'sed_type': 'input', 'spectrum': [wl[tempIdx], spec[tempIdx]], 'unit':'mJy'}
scene['spectrum']['normalization'] = {}
scene['spectrum']['normalization'] = {'type': 'none'}
if args.addLines:
emission_line_array = []
for i,f in enumerate(inputs['flux']):
flux=f
wave=inputs['wave'][i]
if wave > filterWlDict[filt]['low'] and wave < filterWlDict[filt]['high']:
emission_line={}
emission_line['emission_or_absorption']='emission'
emission_line['center']=wave
#TODO: check units...
emission_line['strength']=flux
emission_line['profile']='gaussian'
#assume the line is basically unresolved, i.e. 50 km/s (FWHM)
emission_line['width']=50.#50.
emission_line_array.append(emission_line)
scene['spectrum']['lines']=emission_line_array
configuration['scene'][0]=scene
report=perform_calculation(configuration)
return report
def run_calc(self, b):
# notify the user that we're calculating.
self.computing_notice.layout.display = 'inline'
calc_mode = self.mode_select.value.lower()
calc_strat = self.strat_select[calc_mode].value.lower()
c = build_default_calc("wfirst",
"wfirstimager",
calc_mode,
method=calc_strat)
c['configuration']['detector']['nexp'] = self.mode_config[
calc_mode].nexps.value
c['configuration']['detector']['ngroup'] = self.mode_config[
calc_mode].ngroups.value
c['configuration']['detector']['nint'] = self.mode_config[
calc_mode].nints.value
c['configuration']['detector']['readmode'] = self.mode_config[
calc_mode].readmode.value
c['configuration']['detector']['subarray'] = self.mode_config[
calc_mode].subarray.value
c['configuration']['instrument']['filter'] = self.mode_config[
calc_mode].filt.value
c['scene'] = []
for source in self.sources:
s = build_default_source(
geometry=geom_mapping[source.src_select.value])
if source.src_select.value == "Power":
s['shape']['r_core'] = source.r_core.value
s['shape']['power_index'] = source.power.value
elif source.src_select.value == "Flat":
s['shape']['major'] = source.major.value
s['shape']['minor'] = source.minor.value
s['shape']['norm_method'] = norm_mapping[
source.norm_flat.value]
s['position']['orientation'] = source.pos_a.value
elif source.src_select.value == "2D Gaussian":
s['shape']['major'] = source.major.value
s['shape']['minor'] = source.minor.value
s['shape']['norm_method'] = norm_mapping[source.norm.value]
s['position']['orientation'] = source.pos_a.value
elif source.src_select.value == "Sersic (Effective Radius)":
s['shape']['major'] = source.major.value
s['shape']['minor'] = source.minor.value
s['shape']['norm_method'] = norm_mapping[source.norm.value]
s['shape']['sersic_index'] = source.sersic.value
s['position']['orientation'] = source.pos_a.value
elif source.src_select.value == "Sersic (Scale Radius)":
s['shape']['major'] = source.major.value
s['shape']['minor'] = source.minor.value
s['shape']['norm_method'] = norm_mapping[source.norm.value]
s['shape']['sersic_index'] = source.sersic.value
s['position']['orientation'] = source.pos_a.value
else:
pass
s['position']['x_offset'] = source.pos_x.value
s['position']['y_offset'] = source.pos_y.value
s['spectrum']['redshift'] = source.redshift.value
s['spectrum']['normalization']['norm_flux'] = source.flux.value
s['spectrum']['normalization'][
'norm_fluxunit'] = source.funits.value
s['spectrum']['normalization']['norm_wave'] = source.wave.value
sed = source.sed_select.value
if sed == "power-law":
s['spectrum']['sed']['sed_type'] = "powerlaw"
s['spectrum']['sed']['index'] = source.pl_index.value
if sed == "blackbody":
s['spectrum']['sed']['sed_type'] = "blackbody"
s['spectrum']['sed']['temp'] = source.bb_temp.value
if sed == "phoenix":
s['spectrum']['sed']['sed_type'] = "phoenix"
s['spectrum']['sed']['key'] = source.phoenix_config[
source.phoenix.value]
if sed == "extragalactic":
s['spectrum']['sed']['sed_type'] = "brown"
s['spectrum']['sed']['key'] = source.gal_config[
source.galaxies.value]
if sed == "star":
s['spectrum']['sed']['sed_type'] = "hst_calspec"
s['spectrum']['sed']['key'] = source.star_config[
source.star.value]
c['scene'].append(s)
c['strategy']['aperture_size'] = self.strat_config[
calc_strat].ap_size.value
ann = [
self.strat_config[calc_strat].ann_inner.value,
self.strat_config[calc_strat].ann_outer.value
]
c['strategy']['sky_annulus'] = ann
if calc_strat == 'specapphot':
c['strategy']['reference_wavelength'] = self.strat_config[
calc_strat].reference_wavelength.value
self.r = perform_calculation(c, dict_report=True)
self.calc_input = c
self.esn.value = "%.2f" % self.r['scalar']['sn']
self.eflux.value = "%.2f" % self.r['scalar']['extracted_flux']
self.etime.value = "%.2f" % self.r['scalar']['total_exposure_time']
self.update_plots()
# Now set the result form to be shown
self.computing_notice.layout.display = 'none'
self.result_form.layout.display = 'inline'