Change API for PCRGlobWB model class (#85)

* Add PCRGlobWBParameterSet

* Change constructor and setup methods

* Select container based on version argument

* Update notebook and make it work

* Fix absolute paths for additional input data

* update notebook text cells

* Remove container locations from config

* Formatting etc.

* Add (optional) forcing class to constructor

* Add warnings to conda env

* Revert "Add warnings to conda env"

This reverts commit a9cc9d3.

* Switch to using new forcing module

* Docstring for forcing

* Make versions a tuple

* Use docker:// for singularity image path

* Forcing files relative to forcing dir

Co-authored-by: Stefan Verhoeven <[email protected]>

* Update forcing paths in setup of default config and document

* Reduce number of configurable parameters

* Add __str__ methods on the forcing and parametersets

* Catch timeout on singularity spawner

* Remove additional_input_dirs option (and add black formattting)

* Catch all futuretimeouts for starting containers

Co-authored-by: Stefan Verhoeven <[email protected]>

ewatercycle/config/ewatercycle.yaml

@@ -3,5 +3,3 @@ grdc_location: null
 container_engine: null
 singularity_dir: null
 output_dir: null
-pcrglobwb.singularity_image: null
-pcrglobwb.docker_image: null

ewatercycle/forcing/_pcrglobwb.py

@@ -12,18 +12,19 @@
 
 class PCRGlobWBForcing(DefaultForcing):
     """Container for pcrglobwb forcing data."""
+
     def __init__(
         self,
         start_time: str,
         end_time: str,
         directory: str,
         shape: Optional[str] = None,
-        precipitationNC: Optional[str] = 'precipitation.nc',
-        temperatureNC: Optional[str] = 'temperature.nc',
+        precipitationNC: Optional[str] = "precipitation.nc",
+        temperatureNC: Optional[str] = "temperature.nc",
     ):
         """
-            precipitationNC (str): Input file for precipitation data.
-            temperatureNC (str): Input file for temperature data.
+        precipitationNC (str): Input file for precipitation data.
+        temperatureNC (str): Input file for temperature data.
         """
         super().__init__(start_time, end_time, directory, shape)
         self.precipitationNC = precipitationNC
@@ -37,71 +38,96 @@ def generate(  # type: ignore
         end_time: str,
         shape: str,
         start_time_climatology: str,  # TODO make optional, default to start_time
-        end_time_climatology:
-        str,  # TODO make optional, defaults to start_time + 1 year
+        end_time_climatology: str,  # TODO make optional, defaults to start_time + 1 year
         extract_region: dict = None,
-    ) -> 'PCRGlobWBForcing':
+    ) -> "PCRGlobWBForcing":
         """
-            start_time_climatology (str): Start time for the climatology data
-            end_time_climatology (str): End time for the climatology data
-            extract_region (dict): Region specification, dictionary must
-                contain `start_longitude`, `end_longitude`, `start_latitude`,
-                `end_latitude`
+        start_time_climatology (str): Start time for the climatology data
+        end_time_climatology (str): End time for the climatology data
+        extract_region (dict): Region specification, dictionary must
+            contain `start_longitude`, `end_longitude`, `start_latitude`,
+            `end_latitude`
         """
         # load the ESMValTool recipe
         recipe_name = "hydrology/recipe_pcrglobwb.yml"
         recipe = get_recipe(recipe_name)
 
         # model-specific updates to the recipe
-        preproc_names = ('crop_basin', 'preproc_pr', 'preproc_tas',
-                         'preproc_pr_clim', 'preproc_tas_clim')
+        preproc_names = (
+            "crop_basin",
+            "preproc_pr",
+            "preproc_tas",
+            "preproc_pr_clim",
+            "preproc_tas_clim",
+        )
 
         if dataset is not None:
-            recipe.data['diagnostics']['diagnostic_daily'][
-                'additional_datasets'] = [DATASETS[dataset]]
+            recipe.data["diagnostics"]["diagnostic_daily"][
+                "additional_datasets"
+            ] = [DATASETS[dataset]]
 
         basin = Path(shape).stem
-        recipe.data['diagnostics']['diagnostic_daily']['scripts']['script'][
-            'basin'] = basin
+        recipe.data["diagnostics"]["diagnostic_daily"]["scripts"]["script"][
+            "basin"
+        ] = basin
 
         if extract_region is None:
             extract_region = get_extents(shape)
         for preproc_name in preproc_names:
-            recipe.data['preprocessors'][preproc_name][
-                'extract_region'] = extract_region
+            recipe.data["preprocessors"][preproc_name][
+                "extract_region"
+            ] = extract_region
 
-        variables = recipe.data['diagnostics']['diagnostic_daily']['variables']
-        var_names = 'tas', 'pr'
+        variables = recipe.data["diagnostics"]["diagnostic_daily"]["variables"]
+        var_names = "tas", "pr"
 
         startyear = get_time(start_time).year
         for var_name in var_names:
-            variables[var_name]['start_year'] = startyear
+            variables[var_name]["start_year"] = startyear
 
         endyear = get_time(end_time).year
         for var_name in var_names:
-            variables[var_name]['end_year'] = endyear
+            variables[var_name]["end_year"] = endyear
 
-        var_names_climatology = 'pr_climatology', 'tas_climatology'
+        var_names_climatology = "pr_climatology", "tas_climatology"
 
         startyear_climatology = get_time(start_time_climatology)
         for var_name in var_names_climatology:
-            variables[var_name]['start_year'] = startyear_climatology
+            variables[var_name]["start_year"] = startyear_climatology
 
         endyear_climatology = get_time(end_time_climatology)
         for var_name in var_names_climatology:
-            variables[var_name]['end_year'] = endyear_climatology
+            variables[var_name]["end_year"] = endyear_climatology
 
         # generate forcing data and retrieve useful information
         recipe_output = recipe.run()
         # TODO dont open recipe output files, but use standard name from ESMValTool diagnostic
         directory, forcing_files = data_files_from_recipe_output(recipe_output)
 
         # instantiate forcing object based on generated data
-        return PCRGlobWBForcing(directory=directory,
-                                start_time=start_time,
-                                end_time=end_time,
-                                precipitationNC=forcing_files['pr'],
-                                temperatureNC=forcing_files['tas'])
+        return PCRGlobWBForcing(
+            directory=directory,
+            start_time=start_time,
+            end_time=end_time,
+            precipitationNC=forcing_files["pr"],
+            temperatureNC=forcing_files["tas"],
+        )
 
     def plot(self):
-        raise NotImplementedError('Dont know how to plot')
+        raise NotImplementedError("Dont know how to plot")
+
+    def __str__(self):
+        """Nice formatting of the forcing data object."""
+        return "\n".join(
+            [
+                "Forcing data for PCRGlobWB",
+                "--------------------------",
+                f"Directory: {self.directory}",
+                f"Start time: {self.start_time}",
+                f"End time: {self.end_time}",
+                f"Shapefile: {self.shape}",
+                f"Additional information for model config:",
+                f"  - temperatureNC: {self.temperatureNC}",
+                f"  - precipitationNC: {self.precipitationNC}",
+            ]
+        )