From 10d380161120f65c8353e156c173247e8b89d458 Mon Sep 17 00:00:00 2001
From: Luke McCombs <lmccombs@vols.utk.edu>
Date: Sat, 21 Dec 2024 16:16:57 -0500
Subject: [PATCH 1/2] Fix prob_bin behavior
---
pymoo/operators/crossover/sbx.py | 10 ++++------
1 file changed, 4 insertions(+), 6 deletions(-)
diff --git a/pymoo/operators/crossover/sbx.py b/pymoo/operators/crossover/sbx.py
index 41a1c025a..a75948042 100644
--- a/pymoo/operators/crossover/sbx.py
+++ b/pymoo/operators/crossover/sbx.py
@@ -26,8 +26,8 @@ def cross_sbx(X, xl, xu, eta, prob_var, prob_bin, eps=1.0e-14):
cross[:, xl == xu] = False
# assign y1 the smaller and y2 the larger value
- y1 = np.min(X, axis=0)[cross]
- y2 = np.max(X, axis=0)[cross]
+ p1_low = X[0] < X[1]
+ y1, y2 = np.where(p1_low[None, ...], X, X[::-1])[:, cross]
# mask all the values that should be crossovered
_xl = np.repeat(xl[None, :], n_matings, axis=0)[cross]
@@ -61,10 +61,8 @@ def calc_betaq(beta):
c2 = 0.5 * ((y1 + y2) + betaq * delta)
# with the given probability either assign the value from the first or second parent
- b = np.random.random(len(prob_bin)) < prob_bin
- tmp = np.copy(c1[b])
- c1[b] = c2[b]
- c2[b] = tmp
+ b = (np.random.random(len(prob_bin)) < prob_bin) == p1_low[cross]
+ c1, c2 = np.where(b[None, ...], [c1, c2], [c2, c1])
# first copy the unmodified parents
Q = np.copy(X)
From ca8370ed841c22ecd0c1101c607256746d15f7f0 Mon Sep 17 00:00:00 2001
From: Luke McCombs <lmccombs@fastmail.com>
Date: Mon, 13 Jan 2025 13:39:46 -0500
Subject: [PATCH 2/2] Fewer masks
---
pymoo/operators/crossover/sbx.py | 13 +++++++------
1 file changed, 7 insertions(+), 6 deletions(-)
diff --git a/pymoo/operators/crossover/sbx.py b/pymoo/operators/crossover/sbx.py
index a75948042..d56e6973d 100644
--- a/pymoo/operators/crossover/sbx.py
+++ b/pymoo/operators/crossover/sbx.py
@@ -26,8 +26,9 @@ def cross_sbx(X, xl, xu, eta, prob_var, prob_bin, eps=1.0e-14):
cross[:, xl == xu] = False
# assign y1 the smaller and y2 the larger value
- p1_low = X[0] < X[1]
- y1, y2 = np.where(p1_low[None, ...], X, X[::-1])[:, cross]
+ X_cross = X[:, cross]
+ p1_low = X_cross[0] < X_cross[1]
+ y1, y2 = np.where(p1_low[None,], X_cross, X_cross[::-1])
# mask all the values that should be crossovered
_xl = np.repeat(xl[None, :], n_matings, axis=0)[cross]
@@ -61,15 +62,15 @@ def calc_betaq(beta):
c2 = 0.5 * ((y1 + y2) + betaq * delta)
# with the given probability either assign the value from the first or second parent
- b = (np.random.random(len(prob_bin)) < prob_bin) == p1_low[cross]
- c1, c2 = np.where(b[None, ...], [c1, c2], [c2, c1])
+ b = (np.random.random(len(prob_bin)) < prob_bin) == p1_low
+ C = np.stack((c1, c2), 0)
+ C = np.where(b[None,], C, C[::-1])
# first copy the unmodified parents
Q = np.copy(X)
# copy the positions where the crossover was done
- Q[0, cross] = c1
- Q[1, cross] = c2
+ Q[:, cross] = C
Q[0] = repair_clamp(Q[0], xl, xu)
Q[1] = repair_clamp(Q[1], xl, xu)