Add ISCO hierarchy download and creation

metric_template_1.py

@@ -16,6 +16,8 @@
 import evaluate
 import datasets
 import ham
+import os
+import isco
 
 
 # TODO: Add BibTeX citation
@@ -56,6 +58,9 @@ Examples:
 
 # TODO: Define external resources urls if needed
 BAD_WORDS_URL = "http://url/to/external/resource/bad_words.txt"
+ISCO_HIERARCHY_URL = (
+    "https://storage.googleapis.com/isco-public/tables/ISCO_structure.csv"
+)
 
 
 @evaluate.utils.file_utils.add_start_docstrings(_DESCRIPTION, _KWARGS_DESCRIPTION)
@@ -87,7 +92,15 @@ class MetricTemplate1(evaluate.Metric):
     def _download_and_prepare(self, dl_manager):
         """Optional: download external resources useful to compute the scores"""
         # TODO: Download external resources if needed
-        pass
+
+        # Download and prepare the ISCO structure csv file
+        isco_csv = dl_manager.download_and_extract(ISCO_HIERARCHY_URL)
+        print(f"ISCO CSV file downloaded")
+        self.isco_hierarchy = isco.create_hierarchy(
+            os.path.join(isco_csv, "isco_structure.csv")
+        )
+        print("ISCO hierarchy created")
+        print(self.isco_hierarchy)
 
     def _compute(self, predictions, references):
         """Returns the scores"""
@@ -103,9 +116,10 @@ class MetricTemplate1(evaluate.Metric):
         )
 
         # Example usage:
-        hierarchy = {"G": ["E"], "E": ["B"], "F": ["C"], "C": ["B"], "B": []}
+        # hierarchy = {"G": ["E"], "E": ["B"], "F": ["C"], "C": ["B"], "B": []}
         # true_labels = [{'G'}]
         # predicted_labels = [{'F'}]
+        hierarchy = self.isco_hierarchy
         hP, hR = ham.hierarchical_precision_recall(references, predictions, hierarchy)
         hF = ham.hierarchical_f_measure(hP, hR)
         print(