pym3tools 0.1.0

pym3tools

A modern standardized toolkit for processing Moon Mineralogy Mapper (M³) Data in a pure Python 3.13 environment.

What is pym3tools?

pym3tools is a modular data pipeline designed to make fetching, processing and analyzing M³ a breeze in Python. pym3tools incorporates many different processing methods from current planetary science literature, which allows it to serve as a state-of-the-art, standardized processing method, which will help improve the repeatability of geologic results obtained via M³.

Available Modules

Quick Start

Installation

pym3tools is currently only available through PyPI.

pip install pym3tools

File Retrieval from PDS

import pym3tools as m3

# Data covering the Compton Belk'ovich Volcanic Complex
m3_data_ids = [
    "M3G20090531T215442",
    "M3G20090601T021112",
    "M3G20090601T104211",
    "M3G20090601T145212",
    "M3G20090627T201242",
]

# Retrieving Data
root_dir = "./cbvc_data"
for i in m3_data_ids:
    if Path(root_dir, i).exists():
        _ = m3.M3FileManager(root_dir, i)  # Downloads Data
    else:
        m3.file_downloader.create_urls_file(root_dir, i)  # Creates url files

Building a Processing Pipeline

import pym3tools as m3
from pym3tools.level2pipeline import (
    Crop, Georeferemce, TerrainModel, SolarSpectrumRemoval, StatisticalPolish,
    Photometric Correction
)
from rasterio import BoundingBox

# Initializing File Manager
root_dir = "./cbvc_data"
file_manager = m3.M3FileManager(root_dir, "M3G20090531T215442")

# Defining Regional Scope
bbox = BoundingBox(left=87, bottom=48, right=114, top=71)

# Listing steps of the processing pipeline
steps = [
    Crop("cropped", bbox=bbox, save_output=True),
    Georeference("georeferenced", save_output=True),
    TerrainModel("terrain_model", save_output=True),
    SolarSpectrumRemoval("solar_spec_removed", save_output=True),
    StatisticalPolish("statistical_polish", save_output=True),
    ClarkThermalCorrection("thermal_correction", use_pds_temperatures=True, save_output=True),
    PhotometricCorrection("photometric_correction", save_output=True),
]

# Initializing pipeline
pipeline = m3.M3Level2Pipeline(steps, file_manager)

# Running pipeline
pipeline.run()