Add explicit asset timeframe partitions

docs/src/30-concepts.md

@@ -638,12 +638,7 @@ unstacked_map[!,["k=1", "k=2", "k=3"]] = convert.(Float64, unstacked_map[!,["k=1
 unstacked_map # hide
 ```
 
-The file `assets-timeframe-partitions` has the information on how often we want to evaluate the inter-temporal constraints that combine the information of the representative periods. In this example, we define a uniform distribution of one period, meaning that we will check the inter-storage level every day of the week timeframe.
-
-```@example seasonal-storage
-phs_partitions_file = "../../test/inputs/Storage/assets-timeframe-partitions.csv" # hide
-phs_partitions = CSV.read(phs_partitions_file, DataFrame, header = 1) # hide
-```
+The file `assets-timeframe-partitions` has the information on how often we want to evaluate the inter-temporal constraints that combine the information of the representative periods. In this example, the file is missing in the folder, meaning that the default of a `uniform` distribution of one period will be use in the model, see [model parameters](@ref schemas) section. This assumption implies that the model will check the inter-storage level every day of the week timeframe.
 
 !!! info
     For the sake of simplicity, we show how using three representative days can recover part of the chronological information of one week. The same method can be applied to more representative periods to analyze the seasonality across a year or longer timeframe.

docs/src/50-schemas.md

@@ -4,6 +4,12 @@ The optimization model parameters with the input data must follow the schema bel
 
 The schemas can be accessed at any time after loading the package by typing `TulipaEnergyModel.schema_per_table_name` in the Julia console. Here is the complete list of model parameters in the schemas per table (or CSV file):
 
+!!! info "Optional tables/files and their defaults"
+    The following tables/files are allowed to be missing: "assets\_rep\_periods\_partitions", "assets\_timeframe\_partitions", "assets\_timeframe\_profiles", "flows\_rep\_periods\_partitions", "group\_asset", "profiles\_timeframe".
+    - For the partitions tables/files, the default value are `specification = uniform` and `partition = 1` for each asset/flow and year
+    - For the profiles tables/files, the default value is a flat profile of value 1.0 p.u.
+    - If no group table/file is available there will be no group constraints in the model
+
 ```@eval
 using Markdown, TulipaEnergyModel
 

src/tmp.jl

@@ -191,6 +191,25 @@ function tmp_create_partition_tables(connection)
     end
     DuckDB.close(appender)
 
+    DBInterface.execute(
+        connection,
+        "CREATE OR REPLACE TABLE explicit_assets_timeframe_partitions AS
+        SELECT
+            asset.asset,
+            asset_commission.commission_year AS year,
+            COALESCE(atp.specification, 'uniform') AS specification,
+            COALESCE(atp.partition, '1') AS partition,
+        FROM asset AS asset
+        LEFT JOIN asset_commission
+            ON asset.asset = asset_commission.asset
+        LEFT JOIN assets_timeframe_partitions AS atp
+            ON asset.asset = atp.asset
+            AND asset_commission.commission_year = atp.year
+        WHERE
+            asset.is_seasonal
+        ",
+    )
+
     DBInterface.execute(
         connection,
         "CREATE OR REPLACE TABLE asset_timeframe_time_resolution(
@@ -205,7 +224,7 @@ function tmp_create_partition_tables(connection)
     for row in DuckDB.query(
         connection,
         "SELECT asset, sub.year, specification, partition, num_periods AS num_periods
-        FROM assets_timeframe_partitions AS main
+        FROM explicit_assets_timeframe_partitions AS main
         LEFT JOIN (
             SELECT year, MAX(period) AS num_periods
             FROM timeframe_data