Upload Phase1_run_cfa.py with huggingface_hub

Phase1_run_cfa.py

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+import pandas as pd
+from semopy import Model, Optimizer
+
+# Load dataset
+df = pd.read_csv("phase1_clean.csv")
+
+# Extract all column names
+cols = df.columns.tolist()
+
+# Identify operator prefixes (everything before the underscore)
+operators = sorted(list(set([c.split("_")[0] for c in cols])))
+
+# Build CFA model dynamically
+model_lines = []
+for op in operators:
+    items = sorted([c for c in cols if c.startswith(op + "_")])
+    if len(items) > 0:
+        line = f"{op.capitalize()} =~ " + " + ".join(items)
+        model_lines.append(line)
+
+model_desc = "\n".join(model_lines)
+
+# Build model
+model = Model(model_desc)
+
+# IMPORTANT FOR OLD SEMOPY: load dataset BEFORE optimizer
+model.load_dataset(df)
+
+# Fit model
+opt = Optimizer(model)
+opt.optimize()
+
+# Extract loadings from parameter table (old semopy)
+params = model.parameters
+loadings = params[params["op"] == "~"]
+loadings.to_csv("cfa_loadings.csv", index=False)
+
+# Fit indices
+stats = model.calc_stats()
+pd.DataFrame([stats]).to_csv("cfa_fit_indices.csv", index=False)
+
+print("CFA completed successfully.")