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authorJaron Kent-Dobias <jaron@kent-dobias.com>2024-08-25 17:08:52 +0200
committerJaron Kent-Dobias <jaron@kent-dobias.com>2024-08-25 17:08:52 +0200
commite1ac241062fbe4632e58ec26052d152f6e5aba4b (patch)
tree35c654cacca8645164eec0852e5ea20cd7b6d164
parent5dca01494df22217e51457377c6d055a6125d647 (diff)
downloadcode-master.tar.gz
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code-master.zip
Small cosmetic tweaks.HEADmaster
-rw-r--r--topology.cpp17
1 files changed, 9 insertions, 8 deletions
diff --git a/topology.cpp b/topology.cpp
index 1d46649..129957e 100644
--- a/topology.cpp
+++ b/topology.cpp
@@ -103,8 +103,8 @@ public:
return {∂L, ∂∂L};
}
- Vector newtonMethod(const Vector& v0, Real γ = 1, Real ε = 1e-12, unsigned maxSteps = 1e2) const {
- Vector v = v0;
+ Vector newtonMethod(const Vector& v₀, Real γ = 1, Real ε = 1e-12, unsigned maxSteps = 1e3) const {
+ Vector v = v₀;
unsigned steps = 0;
Vector ∂L;
@@ -112,6 +112,7 @@ public:
while (std::tie(∂L, ∂∂L) = ∂L_∂∂L(v), ∂L.squaredNorm() > ε) {
if (v.tail(M + 1).squaredNorm() > 1 / ε || steps > N * maxSteps) {
+ std::cerr << "Quit Newton method algorithm after " << steps << "steps" << std::endl;
return Vector::Zero(N + M + 1);
}
@@ -124,18 +125,18 @@ public:
return v;
}
- Vector randomStationaryPoint(Rng& r, Real γ = 1, Real ε = 1e-12, unsigned maxTries = 1e1) const {
+ Vector randomStationaryPoint(Rng& r, Real γ = 1, Real ε = 1e-12, unsigned maxTries = 1e2) const {
Vector v = Vector::Zero(N + M + 1);
unsigned tries = 0;
while (v.squaredNorm() < ε && tries < maxTries) {
- Vector v0(N + M + 1);
- for (Real& v0ᵢ : v0) {
- v0ᵢ = r.variate<Real, std::normal_distribution>();
+ Vector v₀(N + M + 1);
+ for (Real& v₀ᵢ : v₀) {
+ v₀ᵢ = r.variate<Real, std::normal_distribution>();
}
- v0.head(N) = normalize(v0.head(N));
+ v₀.head(N) = normalize(v₀.head(N));
- v = newtonMethod(v0, γ, ε);
+ v = newtonMethod(v₀, γ, ε);
tries++;
}