In [1]:
# Makes print and division act like Python 3
from __future__ import print_function, division
# Import the usual libraries
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
# Enable inline plotting
%matplotlib inline
from IPython.display import display, Latex, clear_output
from matplotlib.backends.backend_pdf import PdfPages
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import pynrc
from pynrc import nrc_utils
from pynrc.nrc_utils import S, source_spectrum
pynrc.setup_logging('WARNING', verbose=False)
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# Observation Definitions
from pynrc.nb_funcs import make_key, obs_wfe, obs_optimize, model_info
# Functions to run a series of operations
from pynrc.nb_funcs import do_opt, do_contrast, do_gen_hdus, do_sat_levels
# Plotting routines
from pynrc.nb_funcs import plot_contrasts, plot_contrasts_mjup, planet_mags, plot_planet_patches
from pynrc.nb_funcs import update_yscale, do_plot_contrasts, do_plot_contrasts2
from pynrc.nb_funcs import plot_hdulist, plot_images, plot_images_swlw
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from pynrc.nb_funcs import update_yscale
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# Various Bandpasses
bp_v = S.ObsBandpass('v')
bp_k = pynrc.bp_2mass('k')
bp_w1 = pynrc.bp_wise('w1')
bp_w2 = pynrc.bp_wise('w2')
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# Argument list:(Name, dist, age, sptype, mag)
args_sources = [('proximaCen', 1.30, 4850, 'M5V', 4.38, bp_k)]
ref_sources = [('proximaCen', 'M5V', 4.4, bp_k)]
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# Directory housing VOTables
# http://vizier.u-strasbg.fr/vizier/sed/
votdir = 'votables/'
# Directory to save plots and figures
outdir = 'MDwarfs/'
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# List of filters
args_filter = [('F444W', None, None),
# ('F444W', None, None),
('F444W', 'MASK430R', 'CIRCLYOT')]
subsize = 320
filt_keys = []
for filt,mask,pupil in args_filter:
filt_keys.append(make_key(filt, mask=mask, pupil=pupil))
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save_figs = False
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# Fit spectrum to SED photometry
i=0
name_sci, dist_sci, age_sci, spt_sci, mag_sci, bp_sci = args_sources[i]
vot = votdir + name_sci.replace(' ' ,'') + '.vot'
args = (name_sci, spt_sci, mag_sci, bp_sci, vot)
kwargs = {'Teff':3042, 'metallicity':5.2, 'log_g':0.21}
src = source_spectrum(*args, **kwargs)
src.fit_SED(use_err=False, robust=True, wlim=[1,4])
# Final source spectrum
sp_sci = src.sp_model
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sp_ref = sp_sci
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# Create a dictionary that holds the obs_coronagraphy class for each filter
wfe_drift = 0
obs_dict = obs_wfe(wfe_drift, args_filter, sp_sci, dist_sci, sp_ref=None,
wind_mode='WINDOW', subsize=subsize, verbose=False)
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# Update detector readout
for key in filt_keys:
obs = obs_dict[key]
if 'none' in key:
pattern, ng, nint_sci, nint_ref = ('RAPID',10,600,600)
obs.update_detectors(xpix=160, ypix=160)
obs.nrc_ref.update_detectors(xpix=160, ypix=160)
elif ('MASK210R' in key) or ('MASKSWB' in key):
pattern, ng, nint_sci, nint_ref = ('BRIGHT2',10,20,20)
else:
pattern, ng, nint_sci, nint_ref = ('MEDIUM8',10,17,17)
obs.update_detectors(read_mode=pattern, ngroup=ng, nint=nint_sci)
obs.nrc_ref.update_detectors(read_mode=pattern, ngroup=ng, nint=nint_ref)
print(key)
print(obs.multiaccum_times)
_ = obs.sensitivity(nsig=5, units='vegamag', verbose=True)
print('')
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sat_dict = {}
for k in filt_keys:
print('\n{}'.format(k))
obs = obs_dict[k]
dsat_asec = do_sat_levels(obs, satval=0.9, plot=False)
sat_dict[k] = dsat_asec
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# Determine contrast curves for various WFE drift values
wfe_list = [0,2,5]
nsig = 5
roll = 10
# (Roll1 - Ref) + (Roll2 - Ref)
#curves_ref = do_contrast(obs_dict, wfe_list, filt_keys, nsig=nsig, roll_angle=roll, opt_diff=False)
# (Roll1 - Roll2) + (Roll2 - Roll1)
curves_roll = do_contrast(obs_dict, wfe_list, filt_keys, nsig=nsig, roll_angle=roll, no_ref=True, opt_diff=False)
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# key1, key2 = ('F444W_MASK430R_CIRCLYOT', 'F444W_MASK430R_CIRCLYOT') #filt_keys[-2:][::-1]
key1, key2 = ('F444W_none_none', 'F444W_MASK430R_CIRCLYOT')
#for curves in [curves_ref, curves_roll]:
for curves in [curves_roll]:
lab1 = 'Direct (F444W)'
lab2 = 'Coron (F444W)'
fig, axes_all = do_plot_contrasts2(key1, key2, curves, nsig, obs_dict, wfe_list, age_sci,
sat_dict=sat_dict, label1=lab1, label2=lab2,
yr=[24,10], yscale2='log', yr2=[3e-1, 100], xr=[0,10],
linder_models=True, mass_list=[2.0,1.0,0.7], av_vals=None)
fname = "{}_compare.pdf".format(name_sci.replace(" ", ""))
#fig.savefig(outdir+fname)
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