Add scenarios

.gitignore

@@ -273,6 +273,6 @@ cython_debug/
 
 # TODO: verify with Vic EPA that files can be published
 data/raw/inventories/victoria
-data/processed/input4MIPs
+data/processed
 notebooks/*.ipynb
 notebooks/**/*.ipynb

CHANGELOG.md

@@ -1,3 +1,4 @@
+
 # Changelog
 
 All notable changes to this project will be documented in this file.
@@ -17,6 +18,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Added
 
+- Add `ssp119`, `ssp126` and `ssp245` scenario configurations [#10](https://github.com/climate-resource/spaemis/pull/10)
 - Add `default_scaler` to the configuration for the scaler to be used if no specific scaler configuration is provided [#9](https://github.com/climate-resource/spaemis/pull/9)
 - Move test configuration to `test-data` directory  [#8](https://github.com/climate-resource/spaemis/pull/8)
 - Add functionality to write out a xarray dataset as a set of CSVs that are formatted the same as the input emissions inventory data  [#7](https://github.com/climate-resource/spaemis/pull/7)

src/spaemis/commands/__init__.py

@@ -2,5 +2,6 @@
 CLI commands
 """
 from .base import cli  # noqa
+from .generate_command import run_generate_command  # noqa
 from .gse_emis_command import run_gse_command  # noqa
 from .project_command import run_project_command  # noqa

src/spaemis/commands/generate_command.py

@@ -0,0 +1,58 @@
+"""
+generate CLI command
+"""
+import io
+import logging
+from typing import Dict
+
+import click
+import pandas as pd
+from yaml import safe_load
+
+from spaemis.commands.base import cli
+
+logger = logging.getLogger(__name__)
+
+
+@cli.command(name="generate")
+@click.option("--scaler", default="relative_change", help="Name of the scaler to use")
+@click.option("--scaler-source", help="Source scenario for the scaler")
+@click.option(
+    "--mappings",
+    help="YAML file containing the sector and variable mappings",
+    type=click.File(),
+    required=True,
+)
+def run_generate_command(scaler, scaler_source, mappings):
+    """
+    Generate a scenario configuration file from a set of defaults
+
+    This is helpful for setting up a CSV of scaling options for later tweaking
+    """
+    mappings = safe_load(mappings)
+
+    sector_mapping: Dict[str, str] = mappings["sectors"]
+    variable_mapping: Dict[str, str] = mappings["variables"]
+
+    scaler_information = []
+    for source_variable, target_variable in variable_mapping.items():
+        for source_sector, target_sector in sector_mapping.items():
+            scaler_information.append(
+                {
+                    "variable": source_variable,
+                    "sector": source_sector,
+                    "scaler_name": scaler,
+                    "scaler_variable_id": target_variable,
+                    "scaler_source_id": scaler_source,
+                    "scaler_sector": target_sector,
+                }
+            )
+
+    if not scaler_information:
+        raise click.ClickException("No scaler information generated")
+    scaler_information = pd.DataFrame(scaler_information)
+
+    buff = io.StringIO()
+    scaler_information.to_csv(buff, index=False)
+
+    click.echo(buff.getvalue())

src/spaemis/commands/project_command.py

@@ -8,10 +8,16 @@
 from typing import Dict, Tuple
 
 import click
+import numpy as np
 import xarray as xr
 
 from spaemis.commands.base import cli
-from spaemis.config import DownscalingScenarioConfig, VariableScalerConfig, load_config
+from spaemis.config import (
+    DownscalingScenarioConfig,
+    VariableScalerConfig,
+    converter,
+    load_config,
+)
 from spaemis.inventory import EmissionsInventory, load_inventory, write_inventory_csvs
 from spaemis.scaling import get_scaler_by_config
 
@@ -53,6 +59,29 @@ def scale_inventory(
     return scaled_field.expand_dims(["sector", "year"]).to_dataset(name=cfg.variable)
 
 
+def _create_output_data(options, config, template: xr.Dataset):
+    unique_variables = sorted(set([variable for variable, _ in options]))
+    unique_sectors = sorted(set([sector for _, sector in options]))
+    unique_years = sorted(config.timeslices)
+
+    coords = dict(
+        sector=unique_sectors,
+        year=unique_years,
+        lat=template.lat,
+        lon=template.lon,
+    )
+
+    return xr.Dataset(
+        data_vars={
+            variable: xr.DataArray(
+                np.nan, coords=coords, dims=("sector", "year", "lat", "lon")
+            )
+            for variable in unique_variables
+        },
+        coords=coords,
+    )
+
+
 def calculate_projections(
     config: DownscalingScenarioConfig, inventory: EmissionsInventory
 ) -> xr.Dataset:
@@ -89,7 +118,7 @@ def calculate_projections(
                 ),
             )
 
-    projections = []
+    output_ds = None
 
     for variable_config in scaling_configs.values():
         for slice_year in config.timeslices:
@@ -99,11 +128,14 @@ def calculate_projections(
                 variable_config.sector,
                 slice_year,
             )
+
             res = scale_inventory(variable_config, inventory, slice_year)
-            projections.append(res)
 
-    # Align dims and then merge
-    return xr.merge(xr.align(*projections, join="outer"))
+            if output_ds is None:
+                output_ds = _create_output_data(scaling_configs.keys(), config, res)
+            output_ds.update(res)
+
+    return output_ds
 
 
 @cli.command(name="project")
@@ -112,7 +144,7 @@ def calculate_projections(
     help="Path to a configuration file for the scenario of interest",
     required=True,
 )
-@click.option("-o", "--out_dir", help="Directory to write the updated inventory")
+@click.option("-o", "--out-dir", help="Directory to write the updated inventory")
 def run_project_command(config, out_dir):
     """
     Generate a set of emissions projection using an emissions inventory as a base
@@ -125,8 +157,16 @@ def run_project_command(config, out_dir):
         logger.info(f"Creating output directory: {out_dir}")
         os.makedirs(out_dir, exist_ok=True)
 
+    logger.info("Saving loaded configuration to output directory")
+    with open(os.path.join(out_dir, "config.yaml"), "w") as handle:
+        handle.write(converter.dumps(config, DownscalingScenarioConfig))
+
     dataset = calculate_projections(config, inventory)
 
+    logger.info("Writing output dataset as netcdf")
+    dataset.to_netcdf(os.path.join(out_dir, "projections.nc"))
+
+    logger.info("Writing CSV files")
     for year in config.timeslices:
         target_dir = os.path.join(out_dir, str(year))
         data_to_write = dataset.sel(year=year)

src/spaemis/config.py

@@ -1,12 +1,15 @@
 """
 Description of the configuration
 """
+import os.path
+from typing import Any, ClassVar, List, Literal, Optional, Type, Union, get_args
 
-from typing import Any, ClassVar, Literal, Optional, Type, Union, get_args
-
+import pandas as pd
 from attrs import define
 from cattrs.preconf.pyyaml import make_converter
 
+from spaemis.utils import chdir
+
 converter = make_converter()
 converter.register_unstructure_hook(str, lambda u: str(u))
 
@@ -48,6 +51,27 @@ class VariableScalerConfig:
     method: ScalerMethod
 
 
+def _convert_filename_to_scalers(
+    value: Union[dict, str], _
+) -> List[VariableScalerConfig]:
+    if isinstance(value, str):
+        # load_config updates the current working directory to match the
+        # directory of a loaded config files otherwise a absolute filename is required
+        data = pd.read_csv(value).to_dict(orient="records")
+
+        def extract_scaler_info(data_item):
+            sector_info = {}
+            for key, value in data_item.copy().items():
+                if key.startswith("scaler_"):
+                    sector_info[key[7:]] = value
+                    data_item.pop(key)
+            return {**data_item, "method": sector_info}
+
+        value = [extract_scaler_info(item) for item in data]
+
+    return [converter.structure(item, VariableScalerConfig) for item in value]
+
+
 @define
 class DownscalingScenarioConfig:
     """
@@ -56,15 +80,25 @@ class DownscalingScenarioConfig:
 
     inventory_name: str
     inventory_year: int
-    timeslices: list[int]
-    scalers: list[VariableScalerConfig]
+    timeslices: List[int]
+    scalers: List[VariableScalerConfig]
     default_scaler: Optional[ScalerMethod] = None
 
 
+# Ideally we could use converter.register_structure_hook. See
+# https://github.com/python-attrs/cattrs/issues/206#issuecomment-1013714386
+converter.register_structure_hook_func(
+    lambda t: t == List[VariableScalerConfig], _convert_filename_to_scalers
+)
+
+
 def load_config(config_file: str) -> DownscalingScenarioConfig:
     """
     Load and parse configuration from a file
 
+    Any filenames referenced in the configuration are relative to the configuration file
+    not the current directory.
+
     Parameters
     ----------
     config_file
@@ -75,4 +109,5 @@ def load_config(config_file: str) -> DownscalingScenarioConfig:
         Validated configuration
     """
     with open(config_file) as handle:
-        return converter.loads(handle.read(), DownscalingScenarioConfig)
+        with chdir(os.path.dirname(config_file)):
+            return converter.loads(handle.read(), DownscalingScenarioConfig)

src/spaemis/config/mappings/victoria_mappings.yaml

@@ -0,0 +1,28 @@
+variables:
+  CO: CO-em-anthro
+  NOx: NOx-em-anthro
+  SO2: SO2-em-anthro
+  PM10: BC-em-anthro
+  VOC: BC-em-anthro # Need to download VOC-em-anthro
+sectors:  # Any non-specified sectors are kept constant
+#  aircraft: # We don't easily have aviation pathways from input4MIPs
+  architect_coating: Residential, Commercial, Other
+  bakery: Residential, Commercial, Other
+#  charcoal
+  crematoria: Residential, Commercial, Other
+  cutback_bitumen: Transportation Sector
+  domestic_solvents: Solvents production and application
+  dry_cleaning: Residential, Commercial, Other
+  gas_leak: Energy Sector
+  industry_diffuse: Waste  # or Industrial Sector
+  industry: Industrial Sector
+  motor_vehicles: Transportation Sector
+  panel_beaters: Residential, Commercial, Other
+  petcrematoria: Residential, Commercial, Other
+  pizza: Residential, Commercial, Other
+  printing: Residential, Commercial, Other
+  rail: Transportation Sector
+  servos: Residential, Commercial, Other
+  shipping: International Shipping
+  vicbakery: Residential, Commercial, Other
+  woodheater: Residential, Commercial, Other

src/spaemis/config/scenarios/ssp119.yaml

@@ -0,0 +1,14 @@
+inventory_name: victoria
+inventory_year: 2016
+
+timeslices:
+  - 2020
+  - 2040
+  - 2060
+  - 2080
+  - 2100
+
+default_scaler:
+  name: constant
+
+scalers: ssp119_scalers.csv