Add socmapper test

tests/test_soc_mapper.py

@@ -0,0 +1,71 @@
+# Needed for Github Actions to not fail (see torch bug https://github.com/pytorch/pytorch/issues/121101)
+import torch
+
+torch.set_num_threads(1)
+
+from nlp_link.soc_mapper.soc_map import SOCMapper
+
+
+def test_find_most_likely_soc():
+
+    # Made up top match data
+    match_row = {
+        "job_title": "data scientist",
+        "top_soc_matches": [
+            ["Data scientist", "2433/04", "2433", "2425", 0.95],
+            ["Data scientist computing", "2133/99", "2133", "2135", 0.9],
+            ["Data engineer", "2133/03", "2133", "2135", 0.8],
+            ["Data analyst", "3544/00", "3544", "3539", 0.8],
+            ["Computer scientist", "2133/01", "2133", "2135", 0.7],
+            ["Finance adviser", "2422/02", "2422", "3534", 0.5],
+        ],
+    }
+
+    # When there is a top match over the sim_threshold
+    soc_mapper = SOCMapper(
+        sim_threshold=0.91,
+    )
+
+    result = soc_mapper.find_most_likely_soc(match_row)
+    assert result[1] == "Data scientist"
+
+    # When there is no top match over the sim_threshold but at least minimum_n and over minimum_prop of
+    # the matches over top_n_sim_threshold similarity are the same
+    soc_mapper = SOCMapper(
+        sim_threshold=0.98, top_n_sim_threshold=0.65, minimum_n=3, minimum_prop=0.5
+    )
+
+    result = soc_mapper.find_most_likely_soc(match_row)
+    assert result[0][1] == "2133"
+
+    # When there is no top match over the sim_threshold and there are some
+    # matches over top_n_sim_threshold similarity but not enough (<minimum_n)
+    soc_mapper = SOCMapper(
+        sim_threshold=0.98,
+        top_n_sim_threshold=0.65,
+        minimum_n=6,
+    )
+
+    result = soc_mapper.find_most_likely_soc(match_row)
+
+    assert result == None
+
+    # When there is no top match over the sim_threshold and there are >=minimum_n
+    # matches over top_n_sim_threshold similarity but not enough of them have the same 4 digit soc
+    soc_mapper = SOCMapper(
+        sim_threshold=0.98, top_n_sim_threshold=0.75, minimum_n=3, minimum_prop=0.75
+    )
+
+    result = soc_mapper.find_most_likely_soc(match_row)
+
+    assert result == None
+
+    # When none of the matches are good enough, even for a consensus approach
+    soc_mapper = SOCMapper(
+        sim_threshold=0.98,
+        top_n_sim_threshold=0.98,
+    )
+
+    result = soc_mapper.find_most_likely_soc(match_row)
+
+    assert result == None