completed Makefile

Makefile

@@ -16,7 +16,7 @@ data/raw/pretransformed_heart_disease.csv: scripts/1_download_decode_data.py
 data/processed/train_df.csv data/processed/test_df.csv: scripts/2_data_split_validate.py \
 data/raw/pretransformed_heart_disease.csv
 	python scripts/2_data_split_validate.py \
-		--split=0.1 \
+		--split=0.2 \
 		--raw-data=data/raw/pretransformed_heart_disease.csv \
 		--write-to=data/processed
 
@@ -64,27 +64,27 @@ results/figures/correlation_matrix.png \
 results/tables/cross_val_score.csv \
 results/figures/confusion_matrix.png \
 results/tables/model_metrics.csv
-	quarto render report/adult_income_predictor_report.qmd --to html
-	quarto render report/adult_income_predictor_report.qmd --to pdf
+	quarto render reports/heart_diagnostic_analysis.qmd --to html
+	quarto render reports/heart_diagnostic_analysis.qmd --to pdf
 
-# clean up analysis / nuke everything
+
+# clean up analysis
 clean :
 	rm -rf data/raw/*
-# added this. confirm we do want to delete processed data as well :)
-    rm -rf data/processed/* 
-    rm -rf results/figures/categorical_distributions.png \
-            results/figures/confusion_matrix.png \
-            results/figures/correlation_matrix.png \
-            results/figures/numeric_distributions.png 
-    rm -rf results/models/disease_pipeline.pickle
-    rm -rf results/tables/correlation_matrix.csv \
-            results/tables/cross_val_score.csv \
-            results/tables/cross_val_std.csv \
-            results/tables/high_correlations.csv \
-            results/tables/model_metrics.csv \
- 	rm -rf report/heart_diagnostic_analysis_files.html \
-			report/heart_diagnostic_analysis.pdf \
-			report/heart_diagnostic_analysis           
+	rm -rf data/processed/* 
+	rm -rf results/figures/categorical_distributions.png \
+			results/figures/confusion_matrix.png \
+			results/figures/correlation_matrix.png \
+			results/figures/numeric_distributions.png 
+	rm -rf results/models/disease_pipeline.pickle
+	rm -rf results/tables/correlation_matrix.csv \
+			results/tables/cross_val_score.csv \
+			results/tables/cross_val_std.csv \
+			results/tables/high_correlations.csv \
+			results/tables/model_metrics.csv \
+ 	rm -rf reports/heart_diagnostic_analysis_files.html \
+			reports/heart_diagnostic_analysis.pdf \
+			reports/heart_diagnostic_analysis           
 
 
 

test/test_model_eval.py

@@ -16,6 +16,22 @@
 #Create dummy model
 
 #create dummy X_train, y_train, X_test, y_test data
+valid_data = pd.DataFrame({
+    "Age (in years)": [63, 37, 41],
+    "Sex": ["male", "female", "female"],
+    "Chest pain type": ["typical angina", "non-anginal pain", "atypical angina"],
+    "Resting blood pressure (in mm Hg on admission to the hospital)": [145, 130, 130],
+    "Serum cholesterol (in mg/dl)": [233, 250, 204],
+    "Fasting blood sugar > 120 mg/dl": [True, False, False],
+    "Resting electrocardiographic results": ["normal", "having ST-T wave abnormality", "normal"],
+    "Maximum heart rate achieved": [150, 187, 172],
+    "Exercise-induced angina": ["no", "no", "yes"],
+    "ST depression induced by exercise relative to rest": [2.3, 3.5, 1.4],
+    "Slope of the peak exercise ST segment": ["downsloping", "flat", "upsloping"],
+    "Number of major vessels (0–3) colored by fluoroscopy": [0.0, 0.0, 0.0],
+    "Thalassemia": ["fixed defect", "reversible defect", "normal"],
+    "Diagnosis of heart disease": ["< 50% diameter narrowing", "< 50% diameter narrowing", "> 50% diameter narrowing"]
+})