pyqcoda 1.0.3

Temporal disaggregation of daily precipitation into hourly using Q-CODA.

pyqcoda

pyqcoda is a Python library for temporal disaggregation of daily precipitation into hourly time series using Q-CODA (Quasi-Comonotonicity-based Disaggregation Algorithm), a combination of comonotonicity transformation and an iterative adjusted k-nearest neighbors (KNN) algorithm. It is tailored for hydrological and climate data processing tasks where hourly data is required but only daily observations are available.

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🌧️ Overview

• Input:

  • train_data.csv: Hourly precipitation data with columns datetime (hourly resolution) and precipitation (mm).
  • test_data.csv: Daily precipitation data with the same column names but daily resolution (datetime at 00:00:00 for each day).

• Output:

  • A pandas DataFrame (or CSV) with hourly precipitation disaggregated from the daily values in test_data, using statistical patterns learned from train_data.

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✨ Features

• Disaggregates daily totals into 24-hour precipitation series.
• Preserves sub-daily maxima in reconstructed data.
• Season-aware (DJF, MAM, JJA, SON) to capture seasonal variability.
• Combines comonotonicity with KNN-based iterative adjustments.
• Suitable for hydrological modeling and climate studies.

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📦 Installation

From PyPI (recommended)

pip install pyqcoda

From Github

git clone https://github.com/carloscorreag/pyqcoda.git
cd pyqcoda
pip install .

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🚀 Usage example

import pandas as pd
from pyqcoda import pyqcoda

# 1. Load your training (hourly) and testing (daily) datasets
df_train = pd.read_csv("train_data.csv", index_col=0, parse_dates=True)
df_test = pd.read_csv("test_data.csv", index_col=0, parse_dates=True)

# 2. Instantiate pyqcoda and disaggregate
qc = pyqcoda()
simulated_series = qc.disaggregate(df_train, df_test)

# 3. Convert results to hourly DataFrame
df_hourly = qc.get_hourly_dataframe(simulated_series)

# 4. Save output
df_hourly.to_csv("disaggregated_output.csv")
print("Hourly disaggregated precipitation saved to disaggregated_output.csv")

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🔧 Requirements

• Python 3.7+
• pandas ≥ 1.2.4
• numpy ≥ 1.21.6
• scikit-learn ≥ 1.0.2

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📄 License

This project is licensed under the MIT License — see the LICENSE file for details.

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📖 Citation

Correa, C. (2025). pyqcoda: Temporal disaggregation of daily precipitation into hourly using Q-CODA.