From e315f9ff54bfac1375d086c975d133c01308ccba Mon Sep 17 00:00:00 2001
From: Elias Pipping <elias.pipping@fu-berlin.de>
Date: Mon, 31 Oct 2011 14:41:08 +0100
Subject: [PATCH] Clean up qualifiers
---
src/samplefunctional.hh | 16 ++++++++--------
1 file changed, 8 insertions(+), 8 deletions(-)
diff --git a/src/samplefunctional.hh b/src/samplefunctional.hh
index 1f5c409e..a32e9664 100644
--- a/src/samplefunctional.hh
+++ b/src/samplefunctional.hh
@@ -26,7 +26,7 @@ template <int dim> class SampleFunctional {
MyNonlinearity<dim> const &phi)
: A(A), b(b), phi(phi) {}
- double operator()(const SmallVector v) const {
+ double operator()(SmallVector const v) const {
SmallVector y;
A.mv(v, y); // y = Av
y /= 2; // y = 1/2 Av
@@ -34,7 +34,7 @@ template <int dim> class SampleFunctional {
return y * v + phi(v); // <1/2 Av - b,v> + H(|v|)
}
- void descentDirection(const SmallVector x, SmallVector &ret) const {
+ void descentDirection(SmallVector const x, SmallVector &ret) const {
// Check the squared norm rather than each component because
// negative_projection() divides by it
if (x.two_norm2() == 0.0) {
@@ -87,21 +87,21 @@ template <int dim> class SampleFunctional {
private:
// Gradient of the smooth part
- SmallVector smoothGradient(const SmallVector x) const {
+ SmallVector smoothGradient(SmallVector const x) const {
SmallVector y;
A.mv(x, y); // y = Av
y -= b; // y = Av - b
return y;
}
- SmallVector upperGradient(const SmallVector x) const {
+ SmallVector upperGradient(SmallVector const x) const {
SmallVector y;
phi.upperGradient(x, y);
y += smoothGradient(x);
return y;
}
- SmallVector lowerGradient(const SmallVector x) const {
+ SmallVector lowerGradient(SmallVector const x) const {
SmallVector y;
phi.lowerGradient(x, y);
y += smoothGradient(x);
@@ -109,8 +109,8 @@ template <int dim> class SampleFunctional {
}
// No normalising is done!
- SmallVector negative_projection(const SmallVector z,
- const SmallVector x) const {
+ SmallVector negative_projection(SmallVector const z,
+ SmallVector const x) const {
SmallVector y = z;
y.axpy(-(z * x) / x.two_norm2(), x);
return y;
@@ -118,7 +118,7 @@ template <int dim> class SampleFunctional {
};
template <class Functional>
-void minimise(const Functional J, typename Functional::SmallVector &x,
+void minimise(Functional const J, typename Functional::SmallVector &x,
size_t steps = 1,
Bisection const &bisection =
Bisection(0.0, // acceptError: Stop if the search interval has
--
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