refactor(code): Move finding table validities into model module

All findings tables can use the validities functionality to add strength of
evidence (internal/external) to themselves. Generalized the function to
work for any main findings csv (to dataframe) table not just institional
findings.

src/model/strength_of_findings.py

@@ -0,0 +1,51 @@
+import math
+
+from pandas import DataFrame
+
+from src import prep_data
+
+
+def _binned_strength(strength: float) -> str:
+    if strength < 3.0:
+        return r"\-"
+    if strength < 6.0:
+        return r"\+"
+    return r"\++"
+
+
+def _combined_validities(
+    apply_to: DataFrame, by_intervention: DataFrame, column: str = "internal_validity"
+):
+    if not isinstance(apply_to, str):
+        return
+    combined = 0.0
+    for study in apply_to.split(";"):
+        new = by_intervention.loc[by_intervention["citation"] == study, column]
+        if len(new) > 0 and not math.isnan(new.iat[0]):
+            combined += new.iat[0]
+    if combined:
+        return _binned_strength(combined)
+    return r"\-"
+
+
+def add_validities(
+    findings_df: DataFrame, studies_by_intervention: DataFrame
+) -> DataFrame:
+    valid_subset = (
+        prep_data.calculate_validities(studies_by_intervention)[
+            ["internal_validity", "external_validity", "citation"]
+        ]
+        .fillna(1.0)
+        .drop_duplicates(subset=["citation"])
+        .sort_values("internal_validity")
+    )
+
+    def apply_internal(df):
+        return _combined_validities(df, valid_subset, "internal_validity")
+
+    def apply_external(df):
+        return _combined_validities(df, valid_subset, "external_validity")
+
+    findings_df["internal_validity"] = findings_df["studies"].apply(apply_internal)
+    findings_df["external_validity"] = findings_df["studies"].apply(apply_external)
+    return findings_df