Metadata-Version: 2.1
Name: STNSRPM
Version: 0.0.0
Summary: 🌎 Scripts and information to synthetic generation of precipitation based on Point Processes.
Home-page: https://github.com/navass11/STNSRPM/tree/Crear-ejecutable
Author: Javier Diez Sierra
Author-email: javier.diez@unican.es
Maintainer: Manuel del Jesus Peñil
Maintainer-email: manuel.deljesus@unican.es
License: UNKNOWN
Description: [![DOI](https://zenodo.org/badge/XXXXXXXX.svg)](https://zenodo.org/badge/latestdoi/XXXXXXX)
        
        ## Repository supporting the STNSRPM (Spatio-Temporal Newman Scott Rectangular Pulse Model) for synthetic rainfall generation.
        
        This repository contains the utilities for calibrating the STNSRPM and simulate synthetic rainfall series which mimic the observed rainfall statistics (mean, variance, skewness, proportion of dry/wet days, wet/dry transitions probabilities, temporal autocorrelation and spatial correlation) at different temporal aggregations (hourly and daily). The functionality presented here might be very useful to disaggregate rainfall series (from daily to hourly) or for extreme event analysis, among others.
        
        The description of the STNSRPM can be found at [doc](doc).
        
        Overview of STNSRPM: Paper in Environmental Modelling and Software (not available yet)\
        Others papers which make use of the STNSRPM: [Paper in Water](https://www.mdpi.com/2073-4441/11/1/125)
        
        ## Contents
        
        | Directory | Contents |
        | :-------- | :------- |
        | [NSRP](NSRP) | Python code for calibrate the NSRPM (Newman Scott Rectangular Pulse Model) and simulate synthetic rainfall series.
          [STNSRP](STNSRP) | Python code for calibrate the STNSRPM (Spatio-Temporal Newman Scott Rectangular Pulse Model) and simulate multisite rainfall series.
        | [doc](doc) | Description of the model.
        | [notebooks](notebooks) |  Jupyter notebooks with specific examples to calibrate, simulate and validate the STNSRPM.
        
        ## Requirements
        
        Scripts and (jupyter) notebooks are provided in [python](https://www.python.org/) language to ensure reproducibility and reusability of the results. The simplest way to match all these requirements is by using a dedicated [conda](https://docs.conda.io) environment, which can be easily installed by issuing:
        ```sh
        conda create -n STNSRPM
        conda activate STNSRPM
        pip install STNSRPM
        ```
        
        ## Errata and problem reporting
        
        To report an issue with the problem please:
         1. Make sure that the problem has not been reported yet. Check [here](https://github.com/navass11/STNSRPM/issues?q=label%3Aerrata).
         2. Follow [this GitHub issue template](https://github.com/navass11/STNSRPM/issues/new?labels=errata&template=problem-report.md).
        
Platform: UNKNOWN
Requires-Python: >=3.7, <4
Description-Content-Type: text/markdown
Provides-Extra: plotting
