fixed continuous coverage phenotype. filters now do not mutate tables…

… at all.

phenex/filters/filter.py

@@ -8,6 +8,7 @@ class Filter:
     but cannot trigger recursive execution. Fitlers can add columns but may not remove columns.
     All classes in the filters module should subclass this class. Subclasses must implement
     the _filter method.
+
     """
 
     def __init__(self):
@@ -19,6 +20,7 @@ def filter(self, table: Table) -> Table:
         if not set(input_columns) <= set(table.columns):
             raise ValueError(f"Filter must not remove columns.")
 
+        table = table.select(input_columns)
         return table
 
     def _filter(self, table: Table) -> Table:

phenex/test/phenotype_test_generator.py

@@ -99,7 +99,7 @@ def df_from_test_info(test_info):
             if test_info.get("dates") is not None:
                 df[columnname_date] = test_info["dates"]
             else:
-                test_info[columnname_date] = ibis.null(type=datetime.date)
+                df[columnname_date] = None
 
             if test_info.get("values") is not None:
                 df[columnname_value] = test_info["values"]

phenex/test/phenotypes/test_continuous_coverage_phenotype.py

@@ -2,7 +2,8 @@
 import pandas as pd
 
 from phenex.phenotypes.continuous_coverage_phenotype import ContinuousCoveragePhenotype
-from phenex.codelists import LocalCSVCodelistFactory
+from phenex.phenotypes.codelist_phenotype import CodelistPhenotype
+from phenex.codelists import LocalCSVCodelistFactory, Codelist
 from phenex.filters.date_range_filter import DateRangeFilter
 from phenex.filters.relative_time_range_filter import RelativeTimeRangeFilter
 
@@ -124,11 +125,54 @@ def define_phenotype_tests(self):
                 min_days=test_info.get("coverage_period_min"),
                 when="after",
             )
-            test_info["column_types"] = {f"{test_info['name']}_date": "date"}
 
         return test_infos
 
 
+class ContinuousCoverageWithAnchorPhenotype(ContinuousCoveragePhenotypeTestGenerator):
+    name_space = "ccpt_anchorphenotype"
+
+    def define_input_tables(self):
+        tables = super().define_input_tables()
+
+        tables[0]["df"].drop(columns=["INDEX_DATE"], inplace=True)
+        df = pd.DataFrame()
+        n_patients = tables[0]["df"]["PERSON_ID"].unique().shape[0]
+        c1s = ["c1"] * 12
+        df["CODE"] = c1s + ["c2"] * (n_patients - len(c1s))
+        df["CODE_TYPE"] = "ICD10"
+        df["EVENT_DATE"] = datetime.date(2022, 1, 1)
+        df["PERSON_ID"] = ["P" + str(x) for x in range(n_patients)]
+        tables.append({"name": "CONDITION_OCCURRENCE", "df": df})
+        return tables
+
+    def define_phenotype_tests(self):
+
+        entry = CodelistPhenotype(
+            name="entry",
+            codelist=Codelist(name="c1", codelist={"ICD10": ["c1"]}),
+            domain="CONDITION_OCCURRENCE",
+        )
+
+        cc1 = ContinuousCoveragePhenotype(
+            name="cc_prior_entry",
+            min_days=GreaterThanOrEqualTo(90),
+            when="before",
+            anchor_phenotype=entry,
+        )
+
+        persons = ["P7", "P10", "P11"]
+
+        t1 = {
+            "name": "coverage_min_geq_90",
+            "persons": persons,
+            "phenotype": cc1,
+        }
+
+        test_infos = [t1]
+        return test_infos
+
+
 def test_continuous_coverage_phenotypes():
     spg = ContinuousCoveragePhenotypeTestGenerator()
     spg.run_tests()
@@ -139,6 +183,12 @@ def test_continuous_coverage_return_last():
     spg.run_tests()
 
 
+def test_continuous_coverage_with_anchor_phenotype():
+    spg = ContinuousCoverageWithAnchorPhenotype()
+    spg.run_tests()
+
+
 if __name__ == "__main__":
     test_continuous_coverage_phenotypes()
     test_continuous_coverage_return_last()
+    test_continuous_coverage_with_anchor_phenotype()

phenex/test/util/check_equality.py

@@ -13,6 +13,7 @@ def check_equality(
     result.loc[:, "DUMMY"] = 1
     expected = expected.to_pandas()
     expected.loc[:, "DUMMY"] = 1
+
     full_results = result.merge(
         expected, on=join_on, suffixes=("_result", "_expected"), how="outer"
     )