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Fix the bug of incorrent result in qini for multiple models #520

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Jun 24, 2022
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Fix the bug of incorrent result in qini for multiple models #520

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30 changes: 20 additions & 10 deletions causalml/metrics/visualize.py
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Original file line number Diff line number Diff line change
Expand Up @@ -235,24 +235,34 @@ def get_qini(

qini = []
for i, col in enumerate(model_names):
df = df.sort_values(col, ascending=False).reset_index(drop=True)
df.index = df.index + 1
df["cumsum_tr"] = df[treatment_col].cumsum()
sorted_df = df.sort_values(col, ascending=False).reset_index(drop=True)
sorted_df.index = sorted_df.index + 1
sorted_df["cumsum_tr"] = sorted_df[treatment_col].cumsum()

if treatment_effect_col in df.columns:
if treatment_effect_col in sorted_df.columns:
# When treatment_effect_col is given, use it to calculate the average treatment effects
# of cumulative population.
l = df[treatment_effect_col].cumsum() / df.index * df["cumsum_tr"]
l = (
sorted_df[treatment_effect_col].cumsum()
/ sorted_df.index
* sorted_df["cumsum_tr"]
)
else:
# When treatment_effect_col is not given, use outcome_col and treatment_col
# to calculate the average treatment_effects of cumulative population.
df["cumsum_ct"] = df.index.values - df["cumsum_tr"]
df["cumsum_y_tr"] = (df[outcome_col] * df[treatment_col]).cumsum()
df["cumsum_y_ct"] = (df[outcome_col] * (1 - df[treatment_col])).cumsum()
sorted_df["cumsum_ct"] = sorted_df.index.values - sorted_df["cumsum_tr"]
sorted_df["cumsum_y_tr"] = (
sorted_df[outcome_col] * sorted_df[treatment_col]
).cumsum()
sorted_df["cumsum_y_ct"] = (
sorted_df[outcome_col] * (1 - sorted_df[treatment_col])
).cumsum()

l = (
df["cumsum_y_tr"]
- df["cumsum_y_ct"] * df["cumsum_tr"] / df["cumsum_ct"]
sorted_df["cumsum_y_tr"]
- sorted_df["cumsum_y_ct"]
* sorted_df["cumsum_tr"]
/ sorted_df["cumsum_ct"]
)

qini.append(l)
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