validation integration

workflow/scripts/osemosys_global/validation/main.py

@@ -94,12 +94,18 @@ def get_emission_funcs(datasource: str) -> dict[str, callable]:
 
 if __name__ == "__main__":
     if "snakemake" in globals():
-        raise NotImplementedError
+        datasource = snakemake.wildcards.datasource
+        variable = snakemake.params.variable
+        result_dir = snakemake.params.result_dir
+        validation_data = snakemake.input.validation_data
+        options = {}
+        if snakemake.input.get("iso_codes"):
+            options["iso_codes"] = snakemake.input.iso_codes
     else:
         datasource = "climatewatch"
         variable = "emissions"
         result_dir = "results/India/results"
-        data_file = "resources/data/validation/climate-watch-emissions.csv"
+        validation_data = "resources/data/validation/climate-watch-emissions.csv"
         options = {}
         # options = {"iso_codes": "resources/data/validation/iso.csv"}
 
@@ -123,7 +129,7 @@ def get_emission_funcs(datasource: str) -> dict[str, callable]:
     # perform the validation
 
     try:
-        actual = funcs["getter"](data_file, **options)
+        actual = funcs["getter"](validation_data, **options)
         modelled = pd.read_csv(Path(result_dir, f"{og_result}.csv"))
         modelled = funcs["formatter"](modelled)
     except KeyError as e:

workflow/snakefile

@@ -45,12 +45,15 @@ OTOOLE_YAML = "resources/otoole.yaml"
 OTOOLE_PARAMS = get_otoole_data(OTOOLE_YAML, "param")
 OTOOLE_RESULTS = get_otoole_data(OTOOLE_YAML, "result")
 
+COUNTRIES = config["geographic_scope"]
+
 # rules
 
 include: "rules/preprocess.smk"
 include: "rules/model.smk"
 include: "rules/postprocess.smk"
 include: "rules/retrieve.smk"
+include: "rules/validate.smk"
 
 # handlers 
 
@@ -71,15 +74,29 @@ if not os.path.isdir(Path('results', 'data')):
 
 # target rules
 
+wildcard_constraints:
+    scenario="[A-Za-z0-9]+"
+
 rule all:
     message:
-        'All rules executed successfully...' 
+        'Running workflow...' 
     input:
+        # demand projections
         expand('results/figs/{demand_figure}.png', demand_figure=["regression", "projection"]),
+
+        # model results 
         expand('results/{scenario}/result_summaries/{result_summary}.csv', 
             scenario=config['scenario'], result_summary=result_summaries), 
         expand('results/{scenario}/figures/{result_figure}.html', 
-            scenario=config['scenario'], result_figure = result_figures)
+            scenario=config['scenario'], result_figure = result_figures),
+
+        # validation results 
+        expand("results/{scenario}/validation/{country}/capacity/{dataset}.png",
+            scenario=config['scenario'], country=COUNTRIES, dataset=CAPACITY_VALIDATION),
+        expand("results/{scenario}/validation/{country}/generation/{dataset}.png",
+            scenario=config['scenario'], country=COUNTRIES, dataset=GENERATION_VALIDATION),
+        expand("results/{scenario}/validation/{country}/emissions/{dataset}.png",
+            scenario=config['scenario'], country=COUNTRIES, dataset=EMISSION_VALIDATION),
 
 rule generate_input_data:
     message: