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Signal correction module for Ariel Data Challenge 2025.

Project description

Ariel Data Preprocessing

PyPI release Unittest

This module contains the FGS1 and AIRS-CH0 signal data preprocessing tools.

Submodules

  1. Signal correction (implemented)
  2. Data reduction (planned)
  3. Signal extraction (planned)

1. Signal correction

Implements the six signal correction steps outline in the Calibrating and Binning Ariel Data notebook shared by the contest organizers.

Example use:

from ariel-data-preprocessing.signal_correction import SignalCorrection

signal_correction = SignalCorrection(
    input_data_path='data/raw',
    output_data_path='data/corrected',
    n_planets=10
)

signal_correction.run()

The signal preprocessing pipeline will write the corrected frames as an hdf5 archive called train.h5 with the following structure:

├── planet_1
|   ├── AIRS-CH0_signal
│   └── FGS1_signal
│
├── planet_1
|   ├── AIRS-CH0_signal
│   └── FGS1_signal
│
.
.
.
└── planet_n
    ├── AIRS-CH0_signal
    └── FGS1_signal

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