def fits_osiris_allclose(a, b):
"""Assert that two OSIRIS fits files are close."""
a = fits.open(a)
b = fits.open(b)
try:
del a[0].header['COMMENT']
del b[0].header['COMMENT']
report = StringIO()
diff = FITSDiff(
a, b,
ignore_keywords=["COMMENT"],
ignore_comments=["SIMPLE"],
ignore_fields=[],
ignore_blanks=True,
ignore_blank_cards=True,
tolerance=1e-5)
diff.report(fileobj=report)
assert diff.identical, report.getvalue()
finally:
a.close()
b.close()
def fits_osiris_allclose(a, b):
"""Assert that two OSIRIS fits files are close."""
a = fits.open(a)
b = fits.open(b)
try:
del a[0].header['COMMENT']
del b[0].header['COMMENT']
report = StringIO()
diff = FITSDiff(a,
b,
ignore_keywords=["COMMENT"],
ignore_comments=["SIMPLE"],
ignore_fields=[],
ignore_blanks=True,
ignore_blank_cards=True,
tolerance=1e-5)
diff.report(fileobj=report)
assert diff.identical, report.getvalue()
finally:
a.close()
b.close()
def exotransmit_portal():
"""
Run Exo-Transmit taking inputs from the HTML form and plot the results
"""
if exotransmit_dir is None:
return render_template(
'tor_error.html',
tor_err=
"There seems to be no directory in place for exo-transmit...")
# Grab the inputs arguments from the URL
args = flask.request.args
# Get all the form arguments in the url with defaults
eos, tp, g, R_p, R_s, P, Rayleigh, invalid = _param_validation(args)
if invalid:
return flask.render_template('exotransmit_validation.html',
invalid=invalid)
if args:
x, y = exotransmit_run(eos, tp, g, R_p, R_s, P, Rayleigh)
else:
x, y = np.loadtxt(os.path.join(exotransmit_dir, 'Spectra/default.dat'),
skiprows=2,
unpack=True)
tab = at.Table(data=[x / 1e-6, y / 100])
fh = StringIO()
tab.write(fh, format='ascii.no_header')
table_string = fh.getvalue()
fig = figure(plot_width=1100, plot_height=400, responsive=False)
fig.line(x / 1e-6, y / 100, color='Black', line_width=0.5)
fig.xaxis.axis_label = 'Wavelength (um)'
fig.yaxis.axis_label = 'Transit Depth'
js_resources = INLINE.render_js()
css_resources = INLINE.render_css()
script, div = components(fig)
html = flask.render_template(
'exotransmit_portal.html',
plot_script=script,
plot_div=div,
js_resources=js_resources,
css_resources=css_resources,
eos_files=os.listdir(os.path.join(exotransmit_dir, 'EOS')),
tp_files=os.listdir(os.path.join(exotransmit_dir, 'T_P')),
tp=tp,
eos=eos,
g=g,
R_p=R_p,
R_s=R_s,
P=P,
Rayleigh=Rayleigh,
table_string=table_string)
return encode_utf8(html)
def contam_visibility():
"""The contamination and visibility form page"""
# Load default form
form = fv.ContamVisForm()
form.calculate_contam_submit.disabled = False
if request.method == 'GET':
# http://0.0.0.0:5000/contam_visibility?ra=24.354208334287005&dec=-45.677930555343636&target=WASP-18%20b
target_name = request.args.get('target')
form.targname.data = target_name
ra = request.args.get('ra')
form.ra.data = ra
dec = request.args.get('dec')
form.dec.data = dec
return render_template('contam_visibility.html', form=form)
# Reload page with stellar data from ExoMAST
if form.resolve_submit.data:
if form.targname.data.strip() != '':
# Resolve the target in exoMAST
try:
form.targname.data = get_canonical_name(form.targname.data)
data, url = get_target_data(form.targname.data)
# Update the coordinates
ra_deg = data.get('RA')
dec_deg = data.get('DEC')
# Set the form values
form.ra.data = ra_deg
form.dec.data = dec_deg
form.target_url.data = url
except:
form.target_url.data = ''
form.targname.errors = [
"Sorry, could not resolve '{}' in exoMAST.".format(
form.targname.data)
]
# Send it back to the main page
return render_template('contam_visibility.html', form=form)
# Reload page with appropriate mode data
if form.mode_submit.data:
# Update the button
if form.inst.data != 'NIRISS':
form.calculate_contam_submit.disabled = True
else:
form.calculate_contam_submit.disabled = False
# Send it back to the main page
return render_template('contam_visibility.html', form=form)
if form.validate_on_submit() and (form.calculate_submit.data
or form.calculate_contam_submit.data):
try:
# Log the form inputs
try:
log_exoctk.log_form_input(request.form, 'contam_visibility',
DB)
except:
pass
# Make plot
title = form.targname.data or ', '.join(
[form.ra.data, form.dec.data])
pG, pB, dates, vis_plot, table = vpa.using_gtvt(
str(form.ra.data), str(form.dec.data),
form.inst.data.split(' ')[0])
# Make output table
vers = '0.3'
today = datetime.datetime.now()
fh = StringIO()
fh.write('# Hi! This is your Visibility output file for... \n')
fh.write('# Target: {} \n'.format(form.targname.data))
fh.write('# Instrument: {} \n'.format(form.inst.data))
fh.write('# \n')
fh.write(
'# This file was generated using ExoCTK v{} on {} \n'.format(
vers, today))
fh.write('# Visit our GitHub: https://github.com/ExoCTK/exoctk \n')
fh.write('# \n')
table.write(fh, format='csv', delimiter=',')
visib_table = fh.getvalue()
# Format x axis
day0 = datetime.date(2019, 6, 1)
dtm = datetime.timedelta(days=367)
#vis_plot.x_range = Range1d(day0, day0 + dtm)
# TODO: Fix this so bad PAs are included
pB = []
# Make plot
TOOLS = 'crosshair, reset, hover, save'
fig = figure(tools=TOOLS,
plot_width=800,
plot_height=400,
x_axis_type='datetime',
title=title)
fh = StringIO()
table.write(fh, format='ascii')
visib_table = fh.getvalue()
# Format x axis
day0 = datetime.date(2019, 6, 1)
dtm = datetime.timedelta(days=367)
# Get scripts
vis_js = INLINE.render_js()
vis_css = INLINE.render_css()
vis_script, vis_div = components(vis_plot)
# Contamination plot too
if form.calculate_contam_submit.data:
# First convert ra and dec to HH:MM:SS
ra_deg, dec_deg = float(form.ra.data), float(form.dec.data)
sc = SkyCoord(ra_deg, dec_deg, unit='deg')
ra_dec = sc.to_string('hmsdms')
ra_hms, dec_dms = ra_dec.split(' ')[0], ra_dec.split(' ')[1]
# Make field simulation
contam_cube = fs.sossFieldSim(ra_hms,
dec_dms,
binComp=form.companion.data)
contam_plot = cf.contam(
contam_cube,
title,
paRange=[int(form.pa_min.data),
int(form.pa_max.data)],
badPA=pB,
fig='bokeh')
# Get scripts
contam_js = INLINE.render_js()
contam_css = INLINE.render_css()
contam_script, contam_div = components(contam_plot)
else:
contam_script = contam_div = contam_js = contam_css = ''
return render_template('contam_visibility_results.html',
form=form,
vis_plot=vis_div,
vis_table=visib_table,
vis_script=vis_script,
vis_js=vis_js,
vis_css=vis_css,
contam_plot=contam_div,
contam_script=contam_script,
contam_js=contam_js,
contam_css=contam_css)
except IOError: #Exception as e:
err = 'The following error occurred: ' + str(e)
return render_template('groups_integrations_error.html', err=err)
return render_template('contam_visibility.html', form=form)
def contam_visibility():
"""The contamination and visibility form page"""
# Load default form
form = fv.ContamVisForm()
form.calculate_contam_submit.disabled = False
if request.method == 'GET':
# http://0.0.0.0:5000/contam_visibility?ra=24.354208334287005&dec=-45.677930555343636&target=WASP-18%20b
target_name = request.args.get('target')
form.targname.data = target_name
ra = request.args.get('ra')
form.ra.data = ra
dec = request.args.get('dec')
form.dec.data = dec
return render_template('contam_visibility.html', form=form)
# Reload page with stellar data from ExoMAST
if form.resolve_submit.data:
if form.targname.data.strip() != '':
# Resolve the target in exoMAST
try:
form.targname.data = get_canonical_name(form.targname.data)
data, url = get_target_data(form.targname.data)
# Update the coordinates
ra_deg = data.get('RA')
dec_deg = data.get('DEC')
# Set the form values
form.ra.data = ra_deg
form.dec.data = dec_deg
form.target_url.data = url
except Exception:
form.target_url.data = ''
form.targname.errors = [
"Sorry, could not resolve '{}' in exoMAST.".format(
form.targname.data)
]
# Send it back to the main page
return render_template('contam_visibility.html', form=form)
# Reload page with appropriate mode data
if form.mode_submit.data:
# Update the button
if (form.inst.data == 'MIRI') or (form.inst.data == 'NIRSpec'):
form.calculate_contam_submit.disabled = True
else:
form.calculate_contam_submit.disabled = False
# Send it back to the main page
return render_template('contam_visibility.html', form=form)
if form.validate_on_submit() and (form.calculate_submit.data
or form.calculate_contam_submit.data):
try:
# Log the form inputs
try:
log_exoctk.log_form_input(request.form, 'contam_visibility',
DB)
except Exception:
pass
# Make plot
title = form.targname.data or ', '.join(
[str(form.ra.data), str(form.dec.data)])
pG, pB, dates, vis_plot, table, badPAs = vpa.using_gtvt(
str(form.ra.data),
str(form.dec.data),
form.inst.data.split(' ')[0],
targetName=str(title))
# Make output table
fh = StringIO()
table.write(fh, format='csv', delimiter=',')
visib_table = fh.getvalue()
# Get scripts
vis_js = INLINE.render_js()
vis_css = INLINE.render_css()
vis_script, vis_div = components(vis_plot)
# Contamination plot too
if form.calculate_contam_submit.data:
# First convert ra and dec to HH:MM:SS
ra_deg, dec_deg = float(form.ra.data), float(form.dec.data)
sc = SkyCoord(ra_deg, dec_deg, unit='deg')
ra_dec = sc.to_string('hmsdms')
ra_hms, dec_dms = ra_dec.split(' ')[0], ra_dec.split(' ')[1]
# Make field simulation
contam_cube = fs.fieldSim(ra_hms,
dec_dms,
form.inst.data,
binComp=form.companion.data)
contam_plot = cf.contam(
contam_cube,
form.inst.data,
targetName=str(title),
paRange=[int(form.pa_min.data),
int(form.pa_max.data)],
badPAs=badPAs,
fig='bokeh')
# Get scripts
contam_js = INLINE.render_js()
contam_css = INLINE.render_css()
contam_script, contam_div = components(contam_plot)
else:
contam_script = contam_div = contam_js = contam_css = ''
return render_template('contam_visibility_results.html',
form=form,
vis_plot=vis_div,
vis_table=visib_table,
vis_script=vis_script,
vis_js=vis_js,
vis_css=vis_css,
contam_plot=contam_div,
contam_script=contam_script,
contam_js=contam_js,
contam_css=contam_css)
except Exception as e:
err = 'The following error occurred: ' + str(e)
return render_template('groups_integrations_error.html', err=err)
return render_template('contam_visibility.html', form=form)
def fortney():
"""
Pull up Forntey Grid plot the results and download
"""
# Grab the inputs arguments from the URL
args = flask.request.args
temp, chem, cloud, pmass, m_unit, reference_radius, r_unit, rstar, rstar_unit = _param_fort_validation(args)
# get sqlite database
try:
db = create_engine('sqlite:///' + FORTGRID_DIR)
header = pd.read_sql_table('header', db)
except:
raise Exception('Fortney Grid File Path is incorrect, or not initialized')
if args:
rstar = float(rstar)
rstar = (rstar * u.Unit(rstar_unit)).to(u.km)
reference_radius = float(reference_radius)
rplan = (reference_radius * u.Unit(r_unit)).to(u.km)
# clouds
if cloud.find('flat') != -1:
flat = int(cloud[4:])
ray = 0
elif cloud.find('ray') != -1:
ray = int(cloud[3:])
flat = 0
elif int(cloud) == 0:
flat = 0
ray = 0
else:
flat = 0
ray = 0
print('No cloud parameter not specified, default no clouds added')
# chemistry
if chem == 'noTiO':
noTiO = True
if chem == 'eqchem':
noTiO = False
# grid does not allow clouds for cases with TiO
flat = 0
ray = 0
fort_grav = 25.0 * u.m / u.s**2
temp = float(temp)
df = header.loc[(header.gravity == fort_grav) & (header.temp == temp) &
(header.noTiO == noTiO) & (header.ray == ray) &
(header.flat == flat)]
wave_planet = np.array(pd.read_sql_table(df['name'].values[0], db)['wavelength'])[::-1]
r_lambda = np.array(pd.read_sql_table(df['name'].values[0], db)['radius']) * u.km
# All fortney models have fixed 1.25 radii
z_lambda = r_lambda - (1.25 * u.R_jup).to(u.km)
# Scale with planetary mass
pmass = float(pmass)
mass = (pmass * u.Unit(m_unit)).to(u.kg)
# Convert radius to m for gravity units
gravity = constants.G * (mass) / (rplan.to(u.m))**2.0
# Scale lambbda (this technically ignores the fact that scaleheight
# is altitude dependent) therefore, it will not be valide for very
# very low gravities
z_lambda = z_lambda * fort_grav / gravity
# Create new wavelength dependent R based on scaled ravity
r_lambda = z_lambda + rplan
# Finally compute (rp/r*)^2
flux_planet = np.array(r_lambda**2 / rstar**2)
x = wave_planet
y = flux_planet[::-1]
else:
df = pd.read_sql_table('t1000g25_noTiO', db)
x, y = df['wavelength'], df['radius']**2.0 / 7e5**2.0
tab = at.Table(data=[x, y])
fh = StringIO()
tab.write(fh, format='ascii.no_header')
table_string = fh.getvalue()
fig = figure(plot_width=1100, plot_height=400)
fig.line(x, 1e6 * (y - np.mean(y)), color='Black', line_width=0.5)
fig.xaxis.axis_label = 'Wavelength (um)'
fig.yaxis.axis_label = 'Rel. Transit Depth (ppm)'
js_resources = INLINE.render_js()
css_resources = INLINE.render_css()
script, div = components(fig)
html = flask.render_template('fortney.html',
plot_script=script,
plot_div=div,
js_resources=js_resources,
css_resources=css_resources,
temp=list(map(str, header.temp.unique())),
table_string=table_string
)
return encode_utf8(html)
def fortney_grid(args, write_plot=False, write_table=False):
"""
Function to grab a Fortney Grid model, plot it, and make a table.
Parameters
----------
args : dict
Dictionary of arguments for the Fortney Grid. Must include :
temp
chem
cloud
pmass
m_unit
reference_radius
r_unit
rstar
rstar_unit
write_plot : bool, optional
Whether or not to save the bokeh plot, defaults to False.
write_table : bool, optional
Whether or not to save the ascii table, defaults to False.
Returns
-------
fig : bokeh object
The unsaved bokeh plot.
fh : ascii table object
The unsaved ascii table.
temp_out : list of str of int
The list of temperatures in the model grid.
"""
# Check for Fortney Grid database
print(
os.path.join(get_env_variables()['exoctk_data'],
'fortney/fortney_models.db'))
try:
db = create_engine('sqlite:///' + os.path.join(
get_env_variables()['exoctk_data'], 'fortney/fortney_models.db'))
header = pd.read_sql_table('header', db)
except:
raise Exception(
'Fortney Grid File Path is incorrect, or not initialized')
if args:
rstar = float(args['rstar'])
rstar = (rstar * u.Unit(args['rstar_unit'])).to(u.km)
reference_radius = float(args['reference_radius'])
rplan = (reference_radius * u.Unit(args['r_unit'])).to(u.km)
temp = float(args['temp'])
# clouds
cloud = args['cloud']
if cloud.find('flat') != -1:
flat = int(cloud[4:])
ray = 0
elif cloud.find('ray') != -1:
ray = int(cloud[3:])
flat = 0
elif int(cloud) == 0:
flat = 0
ray = 0
else:
flat = 0
ray = 0
print('No cloud parameter not specified, default no clouds added')
# chemistry
chem = args['chem']
if chem == 'noTiO':
noTiO = True
if chem == 'eqchem':
noTiO = False
# grid does not allow clouds for cases with TiO
flat = 0
ray = 0
fort_grav = 25.0 * u.m / u.s**2
df = header.loc[(header.gravity == fort_grav) & (header.temp == temp) &
(header.noTiO == noTiO) & (header.ray == ray) &
(header.flat == flat)]
wave_planet = np.array(
pd.read_sql_table(df['name'].values[0], db)['wavelength'])[::-1]
r_lambda = np.array(
pd.read_sql_table(df['name'].values[0], db)['radius']) * u.km
# All fortney models have fixed 1.25 radii
z_lambda = r_lambda - (1.25 * u.R_jup).to(u.km)
# Scale with planetary mass
pmass = float(args['pmass'])
mass = (pmass * u.Unit(args['m_unit'])).to(u.kg)
# Convert radius to m for gravity units
gravity = constants.G * (mass) / (rplan.to(u.m))**2.0
# Scale lambbda (this technically ignores the fact that scaleheight
# is altitude dependent) therefore, it will not be valide for very
# very low gravities
z_lambda = z_lambda * fort_grav / gravity
# Create new wavelength dependent R based on scaled ravity
r_lambda = z_lambda + rplan
# Finally compute (rp/r*)^2
flux_planet = np.array(r_lambda**2 / rstar**2)
x = wave_planet
y = flux_planet[::-1]
else:
df = pd.read_sql_table('t1000g25_noTiO', db)
x, y = df['wavelength'], df['radius']**2.0 / 7e5**2.0
tab = at.Table(data=[x, y])
fh = StringIO()
tab.write(fh, format='ascii.no_header')
if write_table:
tab.write('fortney.dat', format='ascii.no_header')
fig = figure(plot_width=1100, plot_height=400)
fig.line(x, 1e6 * (y - np.mean(y)), color='Black', line_width=0.5)
fig.xaxis.axis_label = 'Wavelength (um)'
fig.yaxis.axis_label = 'Rel. Transit Depth (ppm)'
if write_plot:
output_file('fortney.html')
save(fig)
# Return temperature list for the fortney grid page
temp_out = list(map(str, header.temp.unique()))
return fig, fh, temp_out
def generic_grid(input_args, write_plot=False, write_table=False):
"""
Build a plot and table from the generic grid results.
Parameters
----------
input_args : dict
A dictionary of the form output from the generic grid form.
If manual input must include :
r_star : The radius of the star.
r_planet : The radius of the planet.
gravity : The gravity.
temperature : The temperature.
condensation : local or rainout
metallicity
c_o : carbon/oxygen ratio
haze
cloud
write_plot : bool, optional
Whether to write the plot out. Defaults to False.
write_table : bool, optional
Whether to write the table out. Defaults to Fals.
Returns
-------
plot : bokeh object
Unsaved bokeh plot.
table : ascii table object
Unsaved ascii table.
closest_match : dict
A dictionary with the parameters/model name of the closest
match in the grid.
error_message : str
An error message, or lack therof.
"""
# Find path to the database.
database_path = os.path.join(get_env_variables()['exoctk_data'],
'generic/generic_grid_db.hdf5')
# Build rescaled model
solution, inputs, closest_match, error_message = rescale_generic_grid(
input_args, database_path)
# Build file out
tab = at.Table(data=[solution['wv'], solution['spectra']])
fh = StringIO()
tab.write(fh, format='ascii.no_header')
if write_table:
tab.write('generic.dat')
# Plot
fig = figure(title='Rescaled Generic Grid Transmission Spectra'.upper(),
plot_width=1100,
plot_height=400)
fig.x_range.start = 0.3
fig.x_range.end = 5
fig.line(solution['wv'], solution['spectra'], color='Black', line_width=1)
fig.xaxis.axis_label = 'Wavelength (um)'
fig.yaxis.axis_label = 'Transit Depth (Rp/R*)^2'
if write_plot:
output_file('generic.html')
save(fig)
return fig, fh, closest_match, error_message