non-norm simulation finalized

mlconfound/simulate.py

@@ -150,11 +150,13 @@ def simulate_y_c_yhat(w_yc,
     rng = np.random.default_rng(random_state)
     y = rng.normal(0, 1, n)
 
-    c = np.array([rng.normal(w_yc * nonlin_trf_fun(yi), 1, 1) for yi in y]).flatten()
-    c = _scale(c)
-
-    yhat = sinh_arcsinh(np.array([rng.normal(w_yyhat * nonlin_trf_fun(yi) + w_cyhat * nonlin_trf_fun(ci), 1, 1)
-                                  for yi, ci in zip(y, c)]).flatten(), delta=delta, epsilon=epsilon)
-    yhat = _scale(yhat)
+    c = np.array([sinh_arcsinh(rng.normal(0, 1, 1), delta=delta, epsilon=epsilon) + w_yc * nonlin_trf_fun(yi) for yi in y]).flatten()
+    if scale:
+        c = _scale(c)
+
+    yhat = np.array([sinh_arcsinh(rng.normal(0, 1, 1), delta=delta, epsilon=epsilon) + w_yyhat * nonlin_trf_fun(yi) + w_cyhat * nonlin_trf_fun(ci)
+                                  for yi, ci in zip(y, c)]).flatten()
+    if scale:
+        yhat = _scale(yhat)
 
     return y, c, yhat

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "mlconfound"
-version = "0.12.0"
+version = "0.13.0"
 description = "Tools for analyzing and quantifying effects of counfounder variables on machine learning model predictions."
 authors = ["Tamas Spisak <tamas.spisak@uni-due.de>"]
 license = "GPL-3.0-or-later"