Module: `AA.operational`

Generates operational outputs for a given country, issue month, and indicator.

Usage

Pixi

pixi run python -m AA.operational <ISO> <ISSUE_MONTH> <SPI/DRYSPELL>

Docker

docker run --rm \
  -e AWS_ACCESS_KEY_ID=${AWS_ACCESS_KEY_ID} \
  -e AWS_SECRET_ACCESS_KEY=${AWS_SECRET_ACCESS_KEY} \
  -e AWS_SESSION_TOKEN=${AWS_SESSION_TOKEN} \
  aa-runner:latest \
  python -m AA.operational <ISO> <ISSUE_MONTH> <SPI/DRYSPELL> \
  --data-path <DATA_PATH> --output-path <OUTPUT_PATH>

Arguments

<ISO>: 3-letter ISO code.
<ISSUE_MONTH>: Issue month (e.g., 2025-02).
<SPI/DRYSPELL>: Indicator family.

Inputs & Outputs

Uses outputs from Analytical and/or Triggers stages.
Writes operational products to configured output directory.

See Configuration and Environments for paths and credentials.

`run_aa_probabilities(forecasts, observations, params, period_months)`

Compute probabilities based on recent forecasts for operational routine

Parameters:

Name	Description	Default
`forecasts`	xarray.Dataset, rainfall forecasts dataset	required
`observations`	xarray.Dataset, rainfall observations dataset	required
`params`	Params, parameters class	required
`period_months`	tuple, months of index period (eg (10, 11))	required

Returns: probabilities: xarray.Dataset, raw probabilities for specified period probabilities_bc: xarray.Dataset, bias-corrected probabilities for specified period

`run_full_index_pipeline(forecasts, observations, params, triggers, area, period_name, period_months)`

Run operational pipeline for single index (period)

Parameters:

Name	Description	Default
`forecasts`	xarray.Dataset, rainfall forecasts dataset	required
`observations`	xarray.Dataset, rainfall observations dataset	required
`params`	Params, parameters class	required
`triggers`	pd.DataFrame, selected triggers (output of triggers.py)	required
`area`	hip.analysis.AnalysisArea object with aoi information	required
`period_name`	str, name of index period (eg "ON")	required
`period_months`	tuple, months of index period (eg (10, 11))	required

Returns: probs_df: pandas.DataFrame, probabilities (bc or not depending on analytical output) for all districts merged_df: xarray.Dataset, probabilities merged with selected triggers

Module: AA.operational