nemesis-eleos 0.5.9

A Python interface to the NEMESIS spectral inversion tool

Eleos - A Python interface to NEMESIS

Please note, this is a WIP project and features may be added/removed at any time. Full documentation will be added in due course.

Installation

Eleos is available on PyPI so it can be installed as any other python package. On Unix-like systems:

pip install nemesis_eleos

And on Windows:

py -m pip install nemesis_eleos

Eleos only creates file for, and reads files created by, NEMESIS. Therefore, it is not mandatory to have NEMESIS installed for this package to work.

This library was built with the intention of running on the University of Leicester’s HPC system ALICE3. Therefore, functions like cores.generate_alice_job() and cores.run_alice_job are only

guaranteed to work on ALICE3, which uses the SLURM job scheduler. Other HPC facilities withh require their own template submission files in data/statics and functions in cores.

Core Generation Example

This code generates 4 cores, each with a different forward modelling error factor. It retrieves the temeprature profile using a prior from a file (tempapr.dat), the ammonia profile represented as a knee pressure (model 1 in NEMESIS), and an aerosol layer represented as model 32. It then generates a submission script to run NEMESIS using those cores on ALICE.

from eleos import shapes, profiles, cores

# Create the profile shapes - see the class docstring for a brief description or NEMESIS manual for a full description of each one
nh3_shape = shapes.Shape1(knee_pressure=0.1, 
                          deep_vmr=1e-4, 
                          deep_vmr_error=1e-4, 
                          fsh=0.3, 
                          fsh_error=0.3)
aero_shape = shapes.Shape32(base_pressure=0.8, 
                            base_pressure_error=0.5, 
                            opacity=1, 
                            opacity_error=0.3,
                            fsh=0.4,
                            fsh_error=0.2)

# Create the profiles to retrieve
nh3_profile = profiles.GasProfile(gas_name="NH3", 
                                  isotope_id=0, 
                                  shape=nh3_shape)
aero_profile = profiles.AerosolProfile(aerosol_id=1, 
                                       shape=aero_shape)
temp_profile = profiles.TemperatureProfile(filepath="./data/jupiter/tempapr.dat")

# Generate a set of 4 cores. Each one is identical apart from the forward modelling error is multiplied by a factor of n
core_list = []
for n in range(1, 5):
    core = cores.NemesisCore(parent_directory=f"cores/",
                             spx_file="/home/s/scat2/JWST/2022_JupSouthPole/zonal_spectra/sparse_55.0degS.spx",
                             ref_file="data/jupiter/jupiter.ref",
                             profiles=[temp_profile, nh3_profile, aero_profile],
                             fmerror_factor=n)
    core_list.append(core)

# Generate a SLURM job submission script for use on the University of Leicester ALICE3 HPC cluster
cores.generate_alice_job(cores=core_list, username="scat2")

Result Analysis Example

This code takes the result of running NEMESIS on the output of the above example and plots the retrieved spectrum and temperature profile, then saves it to a file.

import matplotlib.pyplot as plt
from eleos import results

# Read in the core after NEMESIS has been run successfully
res = results.NemesisResult("cores/core_1/")

# Create a new Figure object with two Axes
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12,5))

# Plot the model spectrum on one and the retrieved temperature profile oin the other
res.plot_spectrum(ax=ax1)
res.plot_temperature(ax=ax2)

# Save the figure
plt.tight_layout()
fig.savefig("nosync/temp.png", dpi=500)