SPI.py

import json
import os
import datetime
import openeo

connection = openeo.connect("openeo.cloud").authenticate_oidc()
now = datetime.datetime.now()
print(connection.root_url + " time: " + str(now))

precipitation_dc = connection.load_collection(
    "AGERA5",
    temporal_extent=["2010-01-01", "2023-04-30"],  # Small sample date
    bands=["precipitation-flux"],
)
precipitation_dc = (precipitation_dc * 0.01)
precipitation_dc = precipitation_dc.filter_spatial(
    geometries="https://raw.githubusercontent.com/georgique/world-geojson/develop/countries/south_africa.json")

# Formula: SPI = (current - median ) / SD
current_band = precipitation_dc.band("precipitation-flux")
mean_band = precipitation_dc.reduce_temporal("mean").band("precipitation-flux")
difference_band = current_band.merge_cubes(mean_band, overlap_resolver="subtract")
sd_band = precipitation_dc.reduce_temporal("sd").band("precipitation-flux")
spi_band = difference_band.merge_cubes(sd_band, overlap_resolver="divide")

# Test in between values:
# precipitation_dc.reduce_temporal("mean").download("precipitation-flux_mean.nc")
# precipitation_dc.reduce_temporal("min").download("precipitation-flux_min.nc")
# precipitation_dc.reduce_temporal("max").download("precipitation-flux_max.nc")
# precipitation_dc.reduce_temporal("sd").download("precipitation-flux_sd.nc")

job = spi_band.execute_batch(
    title="ANIN SPI",
    description="Standardized precipitation index for South Africa",
    filename_prefix="SPI",
    format="netCDF",
)
job.get_results().download_files("ANIN_SPI")  # Can also download result later