This repository contains small collection of scripts that can be used to Compute Tide Time Series by employing the python pyTMD module.
- PyTMD Project Homepage: https://pytmd.readthedocs.io/en/latest/
- PyTMD GitHub: https://github.com/tsutterley/pyTMD
Other Resources:
Installation:
Setup minimal conda installation using Miniconda
Create Python Virtual Environment
Install Python Dependencies
conda install -y pip numpy matplotlib cartopy pandas geopandas jupyter netcdf4 xarray conda install -c conda-forge pytmd
or run ./install_dependencies.sh
Test Python Dependencies Installation
python test_requirements_installation.py
Execution:
- compute_pt_tide_time_series.py
Compute Tide Time Series at a selected geographic location
python compute_pt_tide_time_series.py ./parameters.yml -68.72 -5.32
- compute_shp_tide_time_series.py
Compute Hourly Tide Time Series at the selected locations listed inside a ESRI shapefile
python compute_shp_tide_time_series.py ./parameters.yml
parameters.yaml - Parameters File Content.
model: Model - [CATS2008, FES2014, AOTIM5]
path: Absolute Path to Model's data directory
shp: ./data/Antarctic_GZ_tide/Antarctic_GZ_tide.shp
out_path: Absolute Path to Output directory
out_format: ascii/txt/netcdf
date1: Initial Date MM/DD/YYYY
date2: Final Date MM/DD/YYYY
nproc: Number of Maximum simultaneous processes - integer
- pyTMD: Python-based tidal prediction software that reads OTIS, GOT and FES formatted tidal solutions.
- numpy: The fundamental package for scientific computing with Python.
- xarray: xarray: N-D labeled arrays and datasets in Python.
- pandas: Python Data Analysis Library.
- geopandas: Python tools for geographic data.
- rasterio: access to geospatial raster data.
- fiona: reads and writes geographic data files.
- shapely: Manipulation and analysis of geometric objects in the Cartesian plane.
- cartopy: Python package designed to produce maps and other geospatial data analyses.
- matplotlib: Library for creating static, animated, and interactive visualizations in Python.
The content of this project is licensed under the Creative Commons Attribution 4.0 Attribution license and the source code is licensed under the MIT license.