def fortney_download():
"""Download the fortney grid data"""
fortney_data = os.path.join(get_env_variables()['fortgrid_dir'],
'fortney_grid.db')
return send_file(fortney_data,
attachment_filename='fortney_grid.db',
as_attachment=True)
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.
"""
utils.check_for_data('fortney')
# Check for Fortney Grid database
print(
os.path.join(utils.get_env_variables()['exoctk_data'],
'fortney/fortney_models.db'))
try:
db = create_engine(
'sqlite:///' +
os.path.join(utils.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 = io.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.
"""
utils.check_for_data('generic')
# Find path to the database.
database_path = os.path.join(utils.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 = io.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
from exoctk.utils import filter_table, get_env_variables, get_target_data, get_canonical_name
from exoctk.modelgrid import ModelGrid
from exoctk.phase_constraint_overlap.phase_constraint_overlap import phase_overlap_constraint, calculate_pre_duration
import log_exoctk
from svo_filters import svo
# FLASK SET UP
app_exoctk = Flask(__name__)
# define the cache config keys, remember that it can be done in a settings file
app_exoctk.config['CACHE_TYPE'] = 'null'
app_exoctk.config['SECRET_KEY'] = 'Thisisasecret!'
# Load the database to log all form submissions
if get_env_variables()['exoctklog_dir'] is None:
dbpath = ':memory:'
else:
dbpath = os.path.realpath(
os.path.join(get_env_variables()['exoctklog_dir'], 'exoctk_log.db'))
if not os.path.isfile(dbpath):
log_exoctk.create_db(dbpath)
try:
DB = log_exoctk.load_db(dbpath)
except IOError:
DB = None
# Redirect to the index
@app_exoctk.route('/')
@app_exoctk.route('/index')
class LimbDarkeningForm(BaseForm):
"""Form validation for the limb_darkening tool"""
# Model grid
modelgrid_dir = get_env_variables()['modelgrid_dir']
default_modelgrid = os.path.join(modelgrid_dir, 'ATLAS9/')
mg = ModelGrid(default_modelgrid, resolution=500)
teff_rng = mg.Teff_vals.min(), mg.Teff_vals.max()
logg_rng = mg.logg_vals.min(), mg.logg_vals.max()
feh_rng = mg.FeH_vals.min(), mg.FeH_vals.max()
modeldir = RadioField(
'modeldir',
default=default_modelgrid,
choices=[(os.path.join(modelgrid_dir, 'ATLAS9/'), 'Kurucz ATLAS9'),
(os.path.join(modelgrid_dir, 'ACES/'), 'Phoenix ACES')],
validators=[InputRequired('A model grid is required!')])
# Stellar parameters
teff = DecimalField(
'teff',
default=3500,
validators=[
InputRequired('An effective temperature is required!'),
NumberRange(
min=float(teff_rng[0]),
max=float(teff_rng[1]),
message=
'Effective temperature must be between {} and {} for this model grid'
.format(*teff_rng))
])
logg = DecimalField(
'logg',
default=4.5,
validators=[
InputRequired('A surface gravity is required!'),
NumberRange(
min=float(logg_rng[0]),
max=float(logg_rng[1]),
message=
'Surface gravity must be between {} and {} for this model grid'
.format(*logg_rng))
])
feh = DecimalField(
'feh',
default=0.0,
validators=[
InputRequired('A surface gravity is required!'),
NumberRange(
min=float(feh_rng[0]),
max=float(feh_rng[1]),
message=
'Metallicity must be between {} and {} for this model grid'.
format(*feh_rng))
])
mu_min = DecimalField('mu_min',
default=0.1,
validators=[
InputRequired('A minimum mu value is required!'),
NumberRange(
min=0.0,
max=1.0,
message='Minimum mu must be between 0 and 1')
])
# LD profile
profiles = MultiCheckboxField(
'profiles',
choices=[(x, x) for x in PROFILES],
validators=[InputRequired('At least one profile is required!')])
# Bandpass
default_filter = 'Kepler.K'
defilt = svo.Filter(default_filter)
bandpass = SelectField('bandpass',
default=default_filter,
choices=[('tophat', 'Top Hat')] +
[(filt, filt) for filt in FILTERS_LIST],
validators=[InputRequired('A filter is required!')])
wave_min = DecimalField(
'wave_min',
default=defilt.wave_min.value,
validators=[
NumberRange(
min=0,
max=30,
message='Minimum wavelength must be between 0 and 30 microns!')
])
wave_max = DecimalField(
'wave_max',
default=defilt.wave_max.value,
validators=[
NumberRange(
min=0,
max=30,
message='Maximum wavelength must be between 0 and 30 microns!')
])
n_bins = IntegerField('n_bins', default=1)
# Form submits
calculate_submit = SubmitField('Calculate Coefficients')
filter_submit = SubmitField('Filter Selected')
modelgrid_submit = SubmitField('Model Grid Selected')
class LimbDarkeningForm(BaseForm):
"""Form validation for the limb_darkening tool"""
# Model grid
modelgrid_dir = get_env_variables()['modelgrid_dir']
default_modelgrid = os.path.join(modelgrid_dir, 'ATLAS9/')
mg = ModelGrid(default_modelgrid, resolution=500)
teff_rng = mg.Teff_vals.min(), mg.Teff_vals.max()
logg_rng = mg.logg_vals.min(), mg.logg_vals.max()
feh_rng = mg.FeH_vals.min(), mg.FeH_vals.max()
modeldir = RadioField(
'modeldir',
default=default_modelgrid,
choices=[(os.path.join(modelgrid_dir, 'ATLAS9/'), 'Kurucz ATLAS9'),
(os.path.join(modelgrid_dir, 'ACES/'), 'Phoenix ACES')],
validators=[InputRequired('A model grid is required!')])
# Stellar parameters
teff = DecimalField(
'teff',
default=3500,
validators=[
InputRequired('An effective temperature is required!'),
NumberRange(
min=float(teff_rng[0]),
max=float(teff_rng[1]),
message=
'Effective temperature must be between {} and {} for this model grid'
.format(*teff_rng))
])
logg = DecimalField(
'logg',
default=4.5,
validators=[
InputRequired('A surface gravity is required!'),
NumberRange(
min=float(logg_rng[0]),
max=float(logg_rng[1]),
message=
'Surface gravity must be between {} and {} for this model grid'
.format(*logg_rng))
])
feh = DecimalField(
'feh',
default=0.0,
validators=[
InputRequired('A surface gravity is required!'),
NumberRange(
min=float(feh_rng[0]),
max=float(feh_rng[1]),
message=
'Metallicity must be between {} and {} for this model grid'.
format(*feh_rng))
])
mu_min = DecimalField('mu_min',
default=0.1,
validators=[
InputRequired('A minimum mu value is required!'),
NumberRange(
min=0.0,
max=1.0,
message='Minimum mu must be between 0 and 1')
])
# Planet parameters
td_rng = [0, 50]
transit_duration = DecimalField(
'transit_duration',
default='',
validators=[
Optional(),
NumberRange(
min=int(td_rng[0]),
max=int(td_rng[1]),
message='Transit duration must be between {} and {}'.format(
*td_rng))
])
op_rng = [0, 1000]
orbital_period = DecimalField(
'orbital_period',
default='',
validators=[
Optional(),
NumberRange(
min=int(op_rng[0]),
max=int(op_rng[1]),
message='Orbital period must be between {} and {}'.format(
*op_rng))
])
rp_rng = [0, 1]
rp_rs = DecimalField(
'rp_rs',
default='',
validators=[
Optional(),
NumberRange(
min=int(rp_rng[0]),
max=int(rp_rng[1]),
message='Planet radius must be between {} and {}'.format(
*rp_rng))
])
a_rng = [0, 100]
a_rs = DecimalField(
'a_rs',
default='',
validators=[
Optional(),
NumberRange(
min=int(a_rng[0]),
max=int(a_rng[1]),
message='Semi-major axis must be between {} and {}'.format(
*a_rng))
])
inc_rng = [0, 180]
inclination = DecimalField(
'inclination',
default='',
validators=[
Optional(),
NumberRange(min=int(inc_rng[0]),
max=int(inc_rng[1]),
message='Inclination must be between {} and {}'.format(
*inc_rng))
])
ecc_rng = [0, 1]
eccentricity = DecimalField(
'eccentricity',
default='',
validators=[
Optional(),
NumberRange(
min=int(ecc_rng[0]),
max=int(ecc_rng[1]),
message='Eccentricity must be between {} and {}'.format(
*ecc_rng))
])
w_rng = [0, 360]
omega = DecimalField(
'omega',
default='',
validators=[
Optional(),
NumberRange(
min=int(w_rng[0]),
max=int(w_rng[1]),
message='Omega must be between {} and {}'.format(*w_rng))
])
# LD profile
profiles = MultiCheckboxField(
'profiles',
choices=[(x, x) for x in PROFILES],
validators=[InputRequired('At least one profile is required!')])
# Bandpass
default_filter = 'NIRSpec.CLEAR.PRISM.S200A1'
defilt = Throughput(default_filter)
bandpass = SelectField('bandpass',
default=default_filter,
choices=[('tophat', 'Top Hat')] +
[(filt, filt) for filt in FILTERS_LIST],
validators=[InputRequired('A filter is required!')])
wave_min = DecimalField(
'wave_min',
default=defilt.wave_min.value,
validators=[
NumberRange(
min=0,
max=30,
message='Minimum wavelength must be between 0 and 30 microns!')
])
wave_max = DecimalField(
'wave_max',
default=defilt.wave_max.value,
validators=[
NumberRange(
min=0,
max=30,
message='Maximum wavelength must be between 0 and 30 microns!')
])
n_bins = IntegerField('n_bins', default=30)
# Form submits
calculate_submit = SubmitField('Calculate Coefficients')
filter_submit = SubmitField('Filter Selected')
modelgrid_submit = SubmitField('Model Grid Selected')
from exoctk.throughputs import Throughput
from matplotlib.backends.backend_pdf import PdfPages
from svo_filters import svo
# FLASK SET UP
app_exoctk = Flask(__name__)
# define the cache config keys, remember that it can be done in a settings file
app_exoctk.config['CACHE_TYPE'] = 'null'
app_exoctk.config['SECRET_KEY'] = 'Thisisasecret!'
# Load the database to log all form submissions
if get_env_variables()['exoctklog_dir'] is None:
dbpath = ':memory:'
else:
dbpath = os.path.realpath(os.path.join(get_env_variables()['exoctklog_dir'], 'exoctk_log.db'))
if not os.path.isfile(dbpath):
log_exoctk.create_db(dbpath)
try:
DB = log_exoctk.load_db(dbpath)
except IOError:
DB = None
# Redirect to the index
@app_exoctk.route('/')
@app_exoctk.route('/index')
def index():