Add code for conversion of 2021 inventory

code/convert_CT_data_2021.py

@@ -0,0 +1,84 @@
+# convert 2021 inventory to PRIMAP2 format
+
+#imports
+import primap2 as pm2
+import pandas as pd
+import os
+import sys
+from pathlib import Path
+
+# configuration
+### folders and filenames
+input_folder = Path("../downloaded_data/2021")
+input_file = "climatetrace_emissions_by_subsector_timeseries_interval_year_since_2015_to_2020.csv"
+output_folder = Path("../data_primap2/2021")
+output_filename = "ClimateTRACE_Inventory_2021"
+compression = dict(zlib=True, complevel=9)
+
+### primap2 format definitions
+coords_terminologies = {
+    "area": "ISO3",
+    "category": "ClimateTrace2021",
+    "scenario": "ReleaseDate",
+}
+
+coords_defaults = {
+    "source": "Climate Trace",
+    "provenance": "measured",
+    "scenario": "2021",
+    "entity": "KYOTOGHG (AR4GWP100)",
+    # GWPs are unclear as they only state that it's 100 year potentials but not from which AR
+    "unit": "t CO2 / yr"
+}
+
+coords_cols = {
+    "category": "sector",
+    "area": "country",
+}
+
+meta_data = {
+    "references": "https://www.climatetrace.org/inventory",
+    "rights": "",
+    "contact": "johannes.guetschow@pik-potsdam.de",
+    "title": "Climate Trace Emissions Inventory 2021",
+    "comment": "Read fom csv file by Johannes Gütschow",
+    "institution": "Climate Trace - www.climatetrace.org",
+}
+
+# change working directory to script directory for proper folder names
+script_path = os.path.abspath(sys.argv[0])
+script_dir_name = os.path.dirname(script_path)
+os.chdir(script_dir_name)
+
+# read the data
+ct_data = pd.read_csv(input_folder / input_file)
+
+# convert dates to just years
+ct_data["start"] = ct_data["start"].replace(r"([0-9]{4})\-[0-9]{2}\-[0-9]{2}", r"\1", regex=True)
+
+# combine sector information in one column
+ct_data["sector"] = ct_data["sector"] + " - " + ct_data["subsector"]
+
+# drop old columns and rename columns
+ct_data = ct_data.drop(columns = ["end", "subsector", "country_full"])
+ct_data = ct_data.rename(columns={"Tonnes Co2e": "data", "start": "time"})
+
+# convert to primap2 format
+ct_data_if = pm2.pm2io.convert_long_dataframe_if(
+    ct_data,
+    coords_cols=coords_cols,
+    coords_defaults=coords_defaults,
+    coords_terminologies=coords_terminologies,
+    meta_data=meta_data,
+    convert_str=True
+    )
+
+# write the result in IF
+if not output_folder.exists():
+    output_folder.mkdir()
+pm2.pm2io.write_interchange_format(output_folder / output_filename, ct_data_if)
+
+# Convert to native pm2 format and write result
+ct_data_pm2 = pm2.pm2io.from_interchange_format(ct_data_if)
+encoding = {var: compression for var in ct_data_pm2.data_vars}
+ct_data_pm2.pr.to_netcdf(output_folder / (output_filename + ".nc"), encoding=encoding)