Note

Download full notebook here

FAQs

from picaso import justplotit as jpi
from picaso import justdoit as jdi
import warnings
warnings.filterwarnings('ignore')
import numpy as np
#picaso
from bokeh.io import output_notebook
output_notebook()

WARNING: Failed to load Vega spectrum from /data/reference_data/picaso/ref4/stellar_grids/calspec/alpha_lyr_stis_011.fits; Functionality involving Vega will be severely limited: FileNotFoundError(2, 'No such file or directory') [stsynphot.spectrum]

Loading BokehJS ...

How do I load in target properties from Exo.Mast?

nexsci = jdi.all_planets()

nexsci.head()

	systemid	sy_name	objectid	pl_name	pl_letter	hostid	hostname	hd_name	hip_name	tic_id	...	pl_tsm_solnid	pl_tsmstr	pl_tsmlim	pl_esm	pl_esmerr1	pl_esmerr2	pl_esm_reflink	pl_esm_solnid	pl_esmstr	pl_esmlim
0	1.539830	HD 2039	3.11204	HD 2039 b	b	2.539830	HD 2039	HD 2039	HIP 1931	TIC 281461362	...	NaN	NaN	NaN	0.1	NaN	NaN	<a refstr=CALCULATED_VALUE href=/docs/pscp_cal...	NaN	0.0	0.0
1	1.103446	HAT-P-8	3.11027	HAT-P-8 b	b	2.103446	HAT-P-8	NaN	NaN	TIC 188876052	...	NaN	109.0	0.0	120.0	NaN	NaN	<a refstr=CALCULATED_VALUE href=/docs/pscp_cal...	NaN	120.0	0.0
2	1.643080	K2-43	3.88640	K2-43 b	b	2.643080	K2-43	NaN	NaN	TIC 443616612	...	NaN	60.0	0.0	14.5	NaN	NaN	<a refstr=CALCULATED_VALUE href=/docs/pscp_cal...	NaN	15.0	0.0
3	1.567687	Kepler-1753	3.15620	Kepler-1753 b	b	2.567687	Kepler-1753	NaN	NaN	TIC 158664331	...	NaN	4.0	0.0	0.1	NaN	NaN	<a refstr=CALCULATED_VALUE href=/docs/pscp_cal...	NaN	0.0	0.0
4	1.544946	Kepler-1176	3.24120	Kepler-1176 b	b	2.544946	Kepler-1176	NaN	NaN	TIC 273582656	...	NaN	3.0	0.0	0.1	NaN	NaN	<a refstr=CALCULATED_VALUE href=/docs/pscp_cal...	NaN	0.0	0.0

5 rows × 703 columns

nexsci.loc[nexsci['hostname']=='HAT-P-26']

	systemid	sy_name	objectid	pl_name	pl_letter	hostid	hostname	hd_name	hip_name	tic_id	...	pl_tsm_solnid	pl_tsmstr	pl_tsmlim	pl_esm	pl_esmerr1	pl_esmerr2	pl_esm_reflink	pl_esm_solnid	pl_esmstr	pl_esmlim
288	1.103496	HAT-P-26	3.1101	HAT-P-26 b	b	2.103496	HAT-P-26	NaN	NaN	TIC 420779000	...	NaN	250.0	0.0	32.8	NaN	NaN	<a refstr=CALCULATED_VALUE href=/docs/pscp_cal...	NaN	33.0	0.0

1 rows × 703 columns

#first isolate the row
hatp26_row = nexsci.loc[nexsci['hostname']=='HAT-P-26']

#add it to load planet function with opacity
opa = jdi.opannection(wave_range=[1,5])
hatp26 = jdi.load_planet(hatp26_row,opa , st_metfe=0)#hatp26 is misst st_metfe so we must add it as a keyword

Load planet function adds in: - planet properties and stellar properties - parameterized PT profile

That means you still need to add in the chemistry and cloud parameters

absolute_co=0.55#solar
logfeh = 1.5 #10^1.5 ~ 30x solar
hatp26.chemeq_visscher_2121(absolute_co,logfeh) #adds in template chemistry from sonora
df = hatp26.spectrum(opa, calculation='transmission+thermal')

x,y = jdi.mean_regrid(df['wavenumber'], df['fpfs_thermal'],R=150)
plot = [jpi.spectrum(x,y,plot_width=400, y_axis_type='log',y_axis_label='FpFs')]
x,y = jdi.mean_regrid(df['wavenumber'], df['transit_depth'],R=150)
plot += [jpi.spectrum(x,y,plot_width=400,y_axis_label='(Rp/Rs)^2')]

jpi.show(jpi.row(plot))

How do I access the pressure-temperature profile parameterizations?

#start by loading in some template properties
opa = jdi.opannection(wave_range=[1,5])
hatp26_row = nexsci.loc[nexsci['hostname']=='HAT-P-26']
hatp26 = jdi.load_planet(hatp26_row,opa, st_metfe=0)

How do the input parameters effect the parameterization?

fig = [jpi.figure(width=300, height=300, y_axis_type='log', y_range=[100,1e-6],x_range=[400,1700],
                  y_axis_label='Pressure(bars)',x_axis_label='Temperature (K)',
                 title='Effect of logg1')]
colors = jpi.pals.magma(10)
for i, logg1 in enumerate(np.linspace(-2,2,10)):
    hatp26.guillot_pt(576.17, T_int=100, logg1=logg1, logKir=-1.5)
    fig[0].line(hatp26.inputs['atmosphere']['profile']['temperature'],
            hatp26.inputs['atmosphere']['profile']['pressure'],color=colors[i])

fig += [jpi.figure(width=300, height=300, y_axis_type='log', y_range=[100,1e-6],x_range=[400,1700],
                 x_axis_label='Temperature (K)',title='Effect of LogKir')]
for i,logKir in enumerate(np.linspace(-2,2,10)):
    hatp26.guillot_pt(576.17, T_int=100, logg1=-2, logKir=logKir)
    fig[1].line(hatp26.inputs['atmosphere']['profile']['temperature'],
            hatp26.inputs['atmosphere']['profile']['pressure'], color=colors[i])

fig += [jpi.figure(width=300, height=300, y_axis_type='log', y_range=[100,1e-6],x_range=[400,1700],
                 x_axis_label='Temperature (K)',title='Effect of Tint')]
for i,T_int in enumerate(np.linspace(50,300,10)):
    hatp26.guillot_pt(576.17, T_int=T_int, logg1=-2, logKir=-2)
    fig[2].line(hatp26.inputs['atmosphere']['profile']['temperature'],
            hatp26.inputs['atmosphere']['profile']['pressure'], color=colors[i])

jpi.show(jpi.row(fig))

How do I return the output from photon attenuation plot?

#first isolate the row
hatp26_row = nexsci.loc[nexsci['hostname']=='HAT-P-26']

#add it to load planet function with opacity
opa = jdi.opannection(wave_range=[0.3,1])
hatp26 = jdi.load_planet(hatp26_row,opa ,st_metfe=0)
co_absolute = 0.55
logfeh=2
hatp26.chemeq_visscher_2121(co_absolute,logfeh)
df = hatp26.spectrum(opa, calculation='reflected',full_output=True)

plot,wave,at_pressures_gas,at_pressures_cld,at_pressures_ray = jpi.photon_attenuation(df['full_output'],
                                                                                     return_output=True)

#now you can make your own plot!
fig = jpi.figure(y_axis_type='log',y_range=[10,1e-3],height=250, width=500)
for i,iy,ilab in zip([0,1],[at_pressures_gas,at_pressures_ray ], ['Molecular','Rayleigh']):
    x,y = jpi.mean_regrid(1e4/wave,iy, R=150)
    fig.line(1e4/x,y,legend_label=ilab, line_width=4, color=jpi.Colorblind8[i])
jpi.show(fig)

Can I use the phase angle function to specify a non-zero phase for thermal emission?

The phase angle function computes the incoming and outgoing angles. However, non-zero phase functionality is specific to reflected light observations only. This might be confusing because of course it is possible to observe thermal emission of planet at non-zero phase. However, unlike reflected light, thermal emission radiates from the planet in all directions (regardless of phase angle).

Do not force the code to run at non-zero phase angles for thermal emission.

I’m confused about what opacity file to use

Question: I’m confused about the opacity files. Version 1.0 (opacity.db) is the low res version that covers the “useful” wavelengths (0.3 to 14 micron) while version 2.0 has two files that cover the 0.6-6 micron at higher resolution and 4.8-15 micron. What should I download? And once I download it, where do I put them? If it’s just the one file that seems straightforward in terms of where to put it but what happens when there are two files (or all 3) in the same folder?

Answer:

What do I download?

The low sampled files across a large wavelength range, which is on Zenodo as V1 is great for quick calculations that don’t necessarily need to be accurate. For example: proposals, example models, any testing, retrievals on fake data.

However, when comparing to real data, it’s important to use higher sampling. This tutorial shows users estimated sampling errors. Therefore, it is important to have higher sampling files as well. The higher sampling files are located here under V2.

So depending on your use case, the answer might be: download both!

Where do I put all the files?

PICASO uses the function `justdoit.opannection <https://natashabatalha.github.io/picaso/picaso.html#picaso.justdoit.opannection>`__ to grab the opacity file located in the reference directory `opacities <https://github.com/natashabatalha/picaso/tree/master/reference/opacities>`__. In the installation instructions you will notice there is a step to place the zenodo file here. Just for completeness, internally, we specify the name of this file here.

The general recommendation is to keep one “default” file in your reference/opacities folder so that you do not need to worry about always specifying a file when running the code. Then assign one place, easy to locate, where you include the rest of the files. In order to access these will need to point to this file path using the filename_db keyword in opannection.

Has your question not been answered? Feel free to contact us!

Submit an issue on Github: https://github.com/natashabatalha/picaso/issues