Metadata-Version: 2.4
Name: climatic-regions
Version: 0.0.4
Summary: AgERA5 Climatic Regions Embeddings
Author: VITO RS Vegetation team
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.8
Requires-Dist: geopandas>=0.13.2
Requires-Dist: numpy>=1.24.4
Requires-Dist: rasterio>=1.3.11
Requires-Dist: rio-tiler>=7.2.2
Requires-Dist: scikit-image>=0.21.0
Requires-Dist: shapely>=2.0.7
Description-Content-Type: text/markdown

# AgERA5 Climatic Regions Embeddings

## Introduction

Climatic regions embeddings V1 are 6 global rasters variables describing the global meteoreological conditions for the years 2018-2023. They are obtained by aggregating AgERA5 variables across single years and then reducing and normalizing the aggregated varibles to a set of 6 variables.

NOTE: 2023 needs to be recomputed. It is currently a copy of 2022.

## Usage

Load for a lat lon point:
```
from climatic_regions import load_meteo_point

vals = load_meteo_point(lon, lat, year)
```

Load resampled array from bounds:
```
from climatic_regions import load_meteo_embeddings

arr = load_meteo_embeddings(bounds, epsg, year, resolution=10)
```

Covert lat, lon to x, y, z:
```
from climatic_regions import lat_lon_to_unit_sphere, load_xyz

x, y, z = lat_lon_to_unit_sphere(lat, lon)

xyz_arr = load_xyz(bounds, epsg, resolution=10)
```