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iterate F without counter for convergence check

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Daniel Bauer
2018-10-18 01:08:32 +02:00
parent a13ebded6d
commit f8cc8b853c
1 changed files with 3 additions and 4 deletions
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7
src/lib.rs
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@@ -50,6 +50,7 @@ fn is_converged(old_F: &[f64], new_F: &[f64], tolerance: f64) -> bool {
fn calc_bin_probability(bin: usize, ds: &Dataset, F: &[f64]) -> f64 { fn calc_bin_probability(bin: usize, ds: &Dataset, F: &[f64]) -> f64 {
let mut denom_sum: f64 = 0.0; let mut denom_sum: f64 = 0.0;
let mut bin_count: f64 = 0.0; let mut bin_count: f64 = 0.0;
// TODO calculate bin_count before wham iterations for performance
for (window, h) in ds.histograms.iter().enumerate() { for (window, h) in ds.histograms.iter().enumerate() {
bin_count += h.bins[bin]; bin_count += h.bins[bin];
let bias = ds.calc_bias(bin, window); let bias = ds.calc_bias(bin, window);
@@ -124,10 +125,8 @@ pub fn run(cfg: &Config) -> Result<(), Box<Error>>{
// convergence. Finally, F is restored. F_prev does not need to be restored because // convergence. Finally, F is restored. F_prev does not need to be restored because
// its overwritten for the next iteration. // its overwritten for the next iteration.
F_tmp.copy_from_slice(&F); F_tmp.copy_from_slice(&F);
for window in 0..histograms.num_windows { for f in F.iter_mut() { *f = -histograms.kT * f.ln() }
F[window] = -histograms.kT * F[window].ln(); for f in F_prev.iter_mut() { *f = -histograms.kT * f.ln() }
F_prev[window] = -histograms.kT * F_prev[window].ln();
}
converged = is_converged(&F_prev, &F, cfg.tolerance); converged = is_converged(&F_prev, &F, cfg.tolerance);
println!("Iteration {}: dF={}", &iteration, &diff_avg(&F_prev, &F)); println!("Iteration {}: dF={}", &iteration, &diff_avg(&F_prev, &F));