[SMS-263] commodity construction

feo/osemosys/defaults.py

@@ -1,11 +1,11 @@
-import os
-from typing import Dict, List, Union
+from typing import Dict
 
-import yaml
 from pydantic import Field
 from pydantic_settings import BaseSettings
 
-from feo.osemosys.schemas.base import OSeMOSYSBase, OSeMOSYSData
+
+class Defaults(BaseSettings):
+    equals_one_tolerance: float = Field(0.01)
 
 
 class DefaultsLinopy(BaseSettings):
@@ -15,83 +15,24 @@ class DefaultsLinopy(BaseSettings):
 
     otoole_name_defaults: Dict = Field(
         default={
-            "AvailabilityFactor": OSeMOSYSData(data=1),
-            "CapacityFactor": OSeMOSYSData(data=1),
-            "CapacityToActivityUnit": OSeMOSYSData(data=1),
-            "DepreciationMethod": OSeMOSYSData(data="straight-line"),
-            "DiscountRate": OSeMOSYSData(data=0.1),
-            "ResidualCapacity": OSeMOSYSData(data=0),
-            "SpecifiedAnnualDemand": OSeMOSYSData(data=0),
+            "AvailabilityFactor": 1,
+            "CapacityFactor": 1,
+            "CapacityToActivityUnit": 1,
+            "DepreciationMethod": "straight-line",
+            "DiscountRate": 0.1,
+            "ResidualCapacity": 0,
+            "SpecifiedAnnualDemand": 0,
         }
     )
 
     otoole_name_storage_defaults: Dict = Field(
         default={
-            "DiscountRateStorage": OSeMOSYSData(data=0.1),
-            "ResidualStorageCapacity": OSeMOSYSData(data=0),
-            "StorageLevelStart": OSeMOSYSData(data=0),
+            "DiscountRateStorage": 0.1,
+            "ResidualStorageCapacity": 0,
+            "StorageLevelStart": 0,
         }
     )
 
 
-defaults = DefaultsLinopy()
-
-
-class DefaultsOtoole(OSeMOSYSBase):
-    """
-    Class to contain all data from from otoole config yaml, including default values
-    """
-
-    values: Dict[str, Dict[str, Union[str, int, float, List]]]
-
-    @classmethod
-    def from_otoole_yaml(cls, root_dir):
-        """Instantiate a single DefaultsOtoole dict from config.yaml file
-
-        Contains information for each parameter on:
-        indices - column names
-        type - param
-        dtype - data type
-        default - default values
-        (short_name - optional shortened parameter name)
-
-        And information for each set on:
-        dtype - data type
-        type - set
-
-        Args:
-            root_dir (str): Path to the root of the otoole csv directory
-
-        Returns:
-            DefaultsOtoole: A single DefaultsOtoole instance
-        """
-
-        # ###########
-        # Load Data #
-        # ###########
-
-        # Find otoole config yaml file in root_dir
-        yaml_files = [
-            file for file in os.listdir(root_dir) if file.endswith(".yaml") or file.endswith(".yml")
-        ]
-        if len(yaml_files) == 0:
-            return None
-        elif len(yaml_files) > 1:
-            raise ValueError(">1 otoole config YAML files found in the directory, only 1 required")
-        yaml_file = yaml_files[0]
-
-        # Read in otoole config yaml data
-        with open(os.path.join(root_dir, yaml_file)) as file:
-            yaml_data = yaml.safe_load(file)
-
-        # #######################
-        # Define class instance #
-        # #######################
-
-        return cls(
-            id="DefaultValues",
-            # TODO
-            long_name=None,
-            description=None,
-            values=yaml_data,
-        )
+defaults = Defaults()
+defaults_linopy = DefaultsLinopy()

feo/osemosys/schemas/base.py

@@ -1,25 +1,77 @@
-from typing import Dict, Union
+from typing import Annotated, Dict, Mapping, Union
 
-from pydantic import BaseModel
+import numpy as np
+import pandas as pd
+from pydantic import AfterValidator, BaseModel, BeforeValidator, model_validator
+
+from feo.osemosys.defaults import defaults
+from feo.osemosys.utils import isnumeric
 
 # ####################
 # ### BASE CLASSES ###
 # ####################
 
 
+def values_sum_one(values: Mapping) -> bool:
+    assert sum(values.values()) == 1.0, "Mapping values must sum to 1.0."
+    return values
+
+
+def nested_sum_one(values: Mapping) -> bool:
+    # breakpoint()
+    if isinstance(values, OSeMOSYSData):
+        data = values.data
+    elif isinstance(values, dict):
+        data = values
+
+    if data is None:
+        return values
+
+    # check for single value
+    if isnumeric(data):
+        if float(data) == 1.0:
+            return values
+
+    # else use pandas json_normalize to make flat dataframe of nested dictionary
+    df = pd.json_normalize(data).T
+    assert (
+        df.index.str.split(".").str.len().unique().size == 1
+    ), "Nested dictionary must have consistent depth"
+    cols = [f"L{ii}" for ii in range(1, max(df.index.str.split(".").str.len()) + 1)]
+    df[cols] = pd.DataFrame(df.index.str.split(".").to_list(), index=df.index)
+
+    if not np.allclose(
+        df.groupby(cols[:-1])[0].sum(),
+        1.0,
+        atol=defaults.equals_one_tolerance,
+    ):
+        raise ValueError("Nested data must sum to 1.0 along the last indexing level.")
+    return values
+
+
+MappingSumOne = Annotated[Mapping, AfterValidator(values_sum_one)]
+DataVar = float | int | str
+IdxVar = str | int
+
+
 class OSeMOSYSBase(BaseModel):
     """
     This base class forces all objects to have a string id;
     a long, human-readable name; and a description.
     """
 
     id: str
-    long_name: str | None
-    description: str | None
+    long_name: str
+    description: str
 
-
-DataVar = float | int | str
-IdxVar = str | int
+    @model_validator(mode="before")
+    @classmethod
+    def backfill_missing(cls, values):
+        if "long_name" not in values:
+            values["long_name"] = values["id"]
+        if "description" not in values:
+            values["description"] = "No description provided."
+        return values
 
 
 class OSeMOSYSData(BaseModel):
@@ -65,10 +117,11 @@ class OSeMOSYSData(BaseModel):
 
     To define different
 
-
-
     """
 
+    def __init__(self, *args, **data):
+        super().__init__(data=args[0] if args else data)
+
     data: Union[
         DataVar,  # {data: 6.}
         Dict[IdxVar, DataVar],
@@ -79,7 +132,10 @@ class OSeMOSYSData(BaseModel):
     ]
 
 
-class OSeMOSYSDataInt(BaseModel):
+OSeMOSYSData_SumOne = Annotated[OSeMOSYSData, BeforeValidator(nested_sum_one)]
+
+
+class OSeMOSYSData_Int(BaseModel):
     data: Union[
         int,  # {data: 6.}
         Dict[IdxVar, int],
@@ -88,3 +144,14 @@ class OSeMOSYSDataInt(BaseModel):
         Dict[IdxVar, Dict[IdxVar, Dict[IdxVar, Dict[IdxVar, int]]]],
         Dict[IdxVar, Dict[IdxVar, Dict[IdxVar, Dict[IdxVar, Dict[IdxVar, int]]]]],
     ]
+
+
+class OSeMOSYSData_Bool(BaseModel):
+    data: Union[
+        bool,  # {data: 6.}
+        Dict[IdxVar, bool],
+        Dict[IdxVar, Dict[IdxVar, bool]],
+        Dict[IdxVar, Dict[IdxVar, Dict[IdxVar, bool]]],
+        Dict[IdxVar, Dict[IdxVar, Dict[IdxVar, Dict[IdxVar, bool]]]],
+        Dict[IdxVar, Dict[IdxVar, Dict[IdxVar, Dict[IdxVar, Dict[IdxVar, bool]]]]],
+    ]