Clean up/speed up numpy array construction

sdfordham · Dec 31, 2023 · 244dac9 · 244dac9
1 parent e8a919a
commit 244dac9
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Showing 4 changed files with 9 additions and 8 deletions.
diff --git a/pysyncon/augsynth.py b/pysyncon/augsynth.py
@@ -48,7 +48,8 @@ def fit(self, dataprep: Dataprep, lambda_: Optional[float] = None) -> None:
         else:
             self.lambda_ = lambda_
 
-        V_mat = np.diag([1.0 / X0.shape[0]] * X0.shape[0])
+        n_r, _ = X0.shape
+        V_mat = np.diag(np.full(n_r, 1 / n_r))
         W, _ = self.w_optimize(V_mat=V_mat, X0=X0.to_numpy(), X1=X1.to_numpy())
 
         W_ridge = self.solve_ridge(

diff --git a/pysyncon/base.py b/pysyncon/base.py
@@ -310,10 +310,10 @@ def w_optimize(
         def fun(x):
             return q.T @ x + 0.5 * x.T @ P @ x
 
-        bounds = Bounds(lb=np.array([0.0] * n_c).T, ub=np.array([1.0] * n_c).T)
-        constraints = LinearConstraint(A=np.array([1.0] * n_c), lb=1.0, ub=1.0)
+        bounds = Bounds(lb=np.full(n_c, 0.0), ub=np.full(n_c, 1.0))
+        constraints = LinearConstraint(A=np.full(n_c, 1.0), lb=1.0, ub=1.0)
 
-        x0 = np.array([1 / n_c] * n_c)
+        x0 = np.full(n_c, 1 / n_c)
         res = minimize(
             fun=fun,
             x0=x0,

diff --git a/pysyncon/penalized.py b/pysyncon/penalized.py
@@ -44,13 +44,13 @@ def w_optimize(
         def fun(x):
             return (X1 - X0 @ x).T @ (X1 - X0 @ x) + lambda_ * (r.T @ x)
 
-        bounds = Bounds(lb=np.array([0.0] * n_c).T, ub=np.array([1.0] * n_c).T)
-        constraints = LinearConstraint(A=np.array([1.0] * n_c), lb=1.0, ub=1.0)
+        bounds = Bounds(lb=np.full(n_c, 0.0), ub=np.full(n_c, 1.0))
+        constraints = LinearConstraint(A=np.full(n_c, 1.0), lb=1.0, ub=1.0)
 
         if initial:
             x0 = initial
         else:
-            x0 = np.array([1 / n_c] * n_c)
+            x0 = np.full(n_c, 1 / n_c)
 
         res = minimize(fun=fun, x0=x0, bounds=bounds, constraints=constraints)
         W, loss_W = res["x"], res["fun"]

diff --git a/pysyncon/synth.py b/pysyncon/synth.py
@@ -141,7 +141,7 @@ def fit(
             x0 = [1 / n_r] * n_r
         elif optim_initial == "ols":
             X_arr = np.hstack([X0_arr, X1_arr.reshape(-1, 1)])
-            X_arr = np.hstack([np.array([1] * X_arr.shape[1], ndmin=2).T, X_arr.T])
+            X_arr = np.hstack([np.full((X_arr.shape[1], 1), 1), X_arr.T])
             Z_arr = np.hstack([Z0_arr, Z1_arr.reshape(-1, 1)])
 
             try: