From e8ee59c1dcc1438a2d1d4e7b9b199b89be714d13 Mon Sep 17 00:00:00 2001
From: sachaMorin <morin.sacha@gmail.com>
Date: Mon, 25 Sep 2023 16:30:50 -0400
Subject: [PATCH] Include Section 5 code in paper_examples.py

---
 scripts/paper_examples.py | 64 +++++++++++++++++++++++++++++++++++----
 1 file changed, 58 insertions(+), 6 deletions(-)

diff --git a/scripts/paper_examples.py b/scripts/paper_examples.py
index 0ca39a9..7104d38 100644
--- a/scripts/paper_examples.py
+++ b/scripts/paper_examples.py
@@ -1,7 +1,59 @@
-"""All examples from Section 6 of the paper."""
+"""All examples from Sections 5 and 6 of the paper."""
+# SECTION 5.2: ESTIMATORS
+# Section 5 only illustrates the API
+# Importing packages. Not in the paper
+from stepmix.datasets import data_bakk_response
+from stepmix.stepmix import StepMix
+
+# Generating dummy data. Not in the paper
+Y, Z_o, _ = data_bakk_response(
+    n_samples=2000,
+    sep_level=0.9,
+    random_state=42,
+)
+
+# Simple model with categorical MM only
+model = StepMix(n_components=3, measurement="categorical")
+model.fit(Y)
+
+# Model with categorical MM and outcome SM
+model = StepMix(
+    n_components=3,
+    measurement="categorical",
+    structural="gaussian_unit",
+    n_steps=3,
+    assignment="soft",
+    correction="BCH",
+)
+model.fit(Y, Z_o)
+
+# Methods
+model.predict(Y, Z_o)
+model.predict_proba(Y, Z_o)
+model.score(Y, Z_o)
+model.aic(Y, Z_o)
+model.bic(Y, Z_o)
+model.get_mm_df()
+model.get_sm_df()
+model.get_cw_df()
+model.sample(100)
+
+# SECTION 5.3: NONPARAMETRIC BOOTSTRAPPING
+stats_dict = model.bootstrap_stats(
+    Y,
+    Z_o,
+    n_repetitions=10,
+    progress_bar=True,
+)
+
+# SECTION 5.4: ADDITIONAL FEATURES
+# Manually run 3-step with low-level method calls
+model.em(Y)
+soft_assignments = model.predict_proba(Y)
+model.m_step_structural(soft_assignments, Z_o)
 
-######### SUBSECTION 6.1: SINGLE OUTCOME SIMULATION #########
-print("SUBSECTION 6.1: SINGLE OUTCOME SIMULATION")
+# SECTION 6.1: SINGLE OUTCOME SIMULATION
+print("\n\n\nSUBSECTION 6.1: SINGLE OUTCOME SIMULATION")
 print("Printing verbose output and mean parameters of the distal outcome\n")
 
 from stepmix.datasets import data_bakk_response
@@ -26,7 +78,7 @@
 mus = model.get_sm_df()
 print(mus)
 
-######### SUBSECTION 6.2: SINGLE COVARIATE SIMULATION #########
+# SECTION 6.2: SINGLE COVARIATE SIMULATION
 print("\n\n\nSUBSECTION 6.2: SINGLE COVARIATE SIMULATION")
 print("Printing beta parameters of the covariate model\n")
 
@@ -60,7 +112,7 @@
 betas = betas.sub(betas[1], axis=0)
 print(betas)
 
-######### SUBSECTION 6.3: COMPLETE MODEL SIMULATION #########
+# SECTION 6.3: COMPLETE MODEL SIMULATION
 print("\n\n\nSUBSECTION 6.3: COMPLETE MODEL SIMULATION")
 print("Printing mean parameters of the distal outcome\n")
 
@@ -99,7 +151,7 @@
 mus = model.get_sm_df().loc["response"]
 print(mus)
 
-######### SUBSECTION 6.4: APPLICATION EXAMPLE #########
+# SECTION 6.4: APPLICATION EXAMPLE
 print("\n\n\nSUBSECTION 6.4: APPLICATION EXAMPLE")
 print("Printing verbose output\n")