mcstools 0.0.5

Read, load, and process Mars Climate Sounder data

mcstools

Tools to read and process Mars Climate Sounder data.

Setup

Download or clone the repo:

$ git clone https://github.com/cloudspotting-on-mars/mcstools

Setup a virtual environment with python3 -m venv env and install with pip install -e .

Download data

See https://pds-atmospheres.nmsu.edu/data_and_services/atmospheres_data/MARS/atmosphere_temp_prof.html

Read a single file

To read in an L1B file as a DataFrame:

from mcstools import L1BReader
reader = L1BReader()
reader.read(path_to_file)

Load Data from PDS

To load data from PDS:

from mcstools import L1BLoader
loader = L1BLoader(pds=True)
loader.load_date_range("2016-01-01", "2016-01-02")

Find and load subset of L2 profiles

from mcstools import L2Loader
loader = L2Loader(pds=True)
ddr1_df = loader.load_date_range("2018-04-18", "2018-04-19", "DDR1")
ddr1_subset = ddr1[ddr1["Profile_lat"].between(-10, 10)]
ddr2 = loader.load("DDR2", profiles=ddr1_subset["Profile_identifier"])

Plot L1B radiances

To view the radiances for a single 4-hour L1B file, run

python mcstools/plotting/l1b_panel.py

That should bring up a dashboard in a browser allowing you to choose a 4-hour file at the top (enter the date in YYMMDDHH0000 format). You can switch between channels using the tabs. The slider on the right allows you to set the colorbar limits (radiance units). There are also tools to zoom in and out, pan, etc.

Preprocess data

To preprocess L1B data and reduce to standard in-track limb views:

from mcstools.preprocess.l1b import L1BStandardInTrack
preprocesser = L1BStandardInTrack()
df = preprocesser.process(df)