Push fix for adjust_pandemic_response

Add poetry dependency for SCM and move SCM to root

covid19_drdfm/processing.py

@@ -6,7 +6,7 @@
 This model input DataFrame can be generated with a single function:
     - `df = run()`
 """
-import json
+
 from fractions import Fraction
 from functools import reduce
 from pathlib import Path
@@ -105,7 +105,8 @@ def adjust_pandemic_response(df: pd.DataFrame) -> pd.DataFrame:
         pd.DataFrame: Adjusted DataFrame
     """
     govt_fund_dist = get_govt_fund_dist()
-    responses = [f"Pandemic_Response_{x}" for x in [13, 14, 15]]
+    # responses = [f"Pandemic_Response_{x}" for x in [13, 14, 15]]
+    responses = ["ARP", "PPP", "CARES"]
     for r in responses:
         df[r] = df[r].astype(float)
         i = df.index[df[r] > 0][0]

scm.py → covid19_drdfm/scm.py

@@ -3,19 +3,24 @@
 
 from SyntheticControlMethods import Synth, DiffSynth
 
-#Import data
+# Import data
 data_dir = "https://raw.githubusercontent.com/OscarEngelbrektson/SyntheticControlMethods/master/examples/datasets/"
 df = pd.read_csv(data_dir + "smoking_data" + ".csv")
 
 from os import rename
-#Fit Differenced Synthetic Control
-df = df.rename(columns={'cigsale': 'Pandemic'})
+
+# Fit Differenced Synthetic Control
+df = df.rename(columns={"cigsale": "Pandemic"})
 sc = Synth(df, "Pandemic", "state", "year", 1989, "California", n_optim=10, pen="auto")
 
 print(sc.original_data.weight_df)
 print(sc.original_data.comparison_df)
 print(sc.original_data.pen)
 
-#Visualize
-sc.plot(["original", "pointwise", "cumulative"], treated_label="California",
-            synth_label="Synthetic California", treatment_label="Pandemic Response")
+# Visualize
+sc.plot(
+    ["original", "pointwise", "cumulative"],
+    treated_label="California",
+    synth_label="Synthetic California",
+    treatment_label="Pandemic Response",
+)