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use slices instead of vector references

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Daniel Bauer
2018-10-14 15:49:00 +02:00
parent 4f3324a057
commit 652b6c5c81
2 changed files with 9 additions and 30 deletions
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2
src/histogram.rs
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@@ -78,7 +78,7 @@ impl Dataset {
} }
} }
fn expand_index(&self, bin: usize, lengths: &Vec<usize>) -> Vec<usize> { fn expand_index(&self, bin: usize, lengths: &[usize]) -> Vec<usize> {
let mut tmp = bin; let mut tmp = bin;
let mut idx = vec![0; lengths.len()]; let mut idx = vec![0; lengths.len()];
for dimen in (1..lengths.len()).rev() { for dimen in (1..lengths.len()).rev() {

37
src/lib.rs
View File

@@ -40,7 +40,7 @@ impl fmt::Display for Config {
// Checks for convergence between two WHAM iterations. WHAM is considered as // Checks for convergence between two WHAM iterations. WHAM is considered as
// converged if the absolute difference for the calculated bias offset is // converged if the absolute difference for the calculated bias offset is
// smaller then a tolerance value for every simulation window. // smaller then a tolerance value for every simulation window.
fn is_converged(old_F: &Vec<f64>, new_F: &Vec<f64>, tolerance: f64) -> bool { fn is_converged(old_F: &[f64], new_F: &[f64], tolerance: f64) -> bool {
!new_F.iter().zip(old_F.iter()) !new_F.iter().zip(old_F.iter())
.map(|x| { (x.0-x.1).abs() }) .map(|x| { (x.0-x.1).abs() })
.any(|diff| { diff > tolerance }) .any(|diff| { diff > tolerance })
@@ -48,7 +48,7 @@ fn is_converged(old_F: &Vec<f64>, new_F: &Vec<f64>, tolerance: f64) -> bool {
// estimate the probability of a bin of the histogram set based on F values // estimate the probability of a bin of the histogram set based on F values
// This evaluates the first WHAM equation for each bin // This evaluates the first WHAM equation for each bin
fn calc_bin_probability(bin: usize, ds: &Dataset, F: &Vec<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;
for window in 0..ds.num_windows { for window in 0..ds.num_windows {
@@ -63,8 +63,8 @@ fn calc_bin_probability(bin: usize, ds: &Dataset, F: &Vec<f64>) -> f64 {
// estimate the bias offset F of the histogram based on given probabilities // estimate the bias offset F of the histogram based on given probabilities
// This evaluates the second WHAM equation for each window // This evaluates the second WHAM equation for each window
fn calc_window_F(window: usize, ds: &Dataset, P: &Vec<f64>) -> f64 { fn calc_window_F(window: usize, ds: &Dataset, P: &[f64]) -> f64 {
let bf_sum: f64 = (0..ds.num_bins).zip(P.iter()) // zip bins and P let bf_sum: f64 = (0..ds.num_bins).zip(P.iter()) // zip bins and P
.map(|x: (usize, &f64)| { .map(|x: (usize, &f64)| {
x.1 * (-ds.calc_bias(x.0, window)/ds.kT).exp() x.1 * (-ds.calc_bias(x.0, window)/ds.kT).exp()
}).sum(); }).sum();
@@ -74,7 +74,7 @@ fn calc_window_F(window: usize, ds: &Dataset, P: &Vec<f64>) -> f64 {
// One full WHAM iteration includes calculation of new probabilities P and // One full WHAM iteration includes calculation of new probabilities P and
// new bias offsets F based on previous bias offsets F_prev. This updates // new bias offsets F based on previous bias offsets F_prev. This updates
// the values in vectors F and P // the values in vectors F and P
fn perform_wham_iteration(ds: &Dataset, F_prev: &Vec<f64>,F: &mut Vec<f64>, P: &mut Vec<f64>) { fn perform_wham_iteration(ds: &Dataset, F_prev: &[f64], F: &mut [f64], P: &mut [f64]) {
// reset bias offsets // reset bias offsets
for window in 0..ds.num_windows { for window in 0..ds.num_windows {
F[window] = 0.0; F[window] = 0.0;
@@ -113,11 +113,6 @@ fn perform_wham_iteration(ds: &Dataset, F_prev: &Vec<f64>,F: &mut Vec<f64>, P: &
// F[window] = -ds.kT * F[window].ln(); // F[window] = -ds.kT * F[window].ln();
// } // }
// let norm = F[0];
// for window in 0..ds.num_windows {
// F[window] = F[window] - norm;
// }
// evaluate first WHAM equation for each bin to // evaluate first WHAM equation for each bin to
// estimage probabilities based on previous offsets (F_prev) // estimage probabilities based on previous offsets (F_prev)
for bin in 0..ds.num_bins { for bin in 0..ds.num_bins {
@@ -130,15 +125,10 @@ fn perform_wham_iteration(ds: &Dataset, F_prev: &Vec<f64>,F: &mut Vec<f64>, P: &
F[window] = calc_window_F(window, ds, P); F[window] = calc_window_F(window, ds, P);
} }
// normalize F
// let norm = F[0];
// for window in 0..ds.num_windows {
// F[window] = F[window] - norm;
// }
} }
// get average difference between two bias offset sets // get average difference between two bias offset sets
fn diff_avg(F: &Vec<f64>, F_prev: &Vec<f64>) -> f64 { fn diff_avg(F: &[f64], F_prev: &[f64]) -> f64 {
let mut F_sum: f64 = 0.0; let mut F_sum: f64 = 0.0;
for i in 0..F.len() { for i in 0..F.len() {
F_sum += (F[i]-F_prev[i]).abs() F_sum += (F[i]-F_prev[i]).abs()
@@ -148,7 +138,7 @@ fn diff_avg(F: &Vec<f64>, F_prev: &Vec<f64>) -> f64 {
// calculate the normalized free energy from normalized probability values // calculate the normalized free energy from normalized probability values
fn free_energy(ds: &Dataset, P: &mut Vec<f64>, A: &mut Vec<f64>) { fn free_energy(ds: &Dataset, P: &[f64], A: &mut [f64]) {
let mut bin_min = f64::MAX; let mut bin_min = f64::MAX;
// Free energy calculation // Free energy calculation
@@ -163,17 +153,6 @@ fn free_energy(ds: &Dataset, P: &mut Vec<f64>, A: &mut Vec<f64>) {
for bin in 0..ds.num_bins { for bin in 0..ds.num_bins {
A[bin] -= bin_min; A[bin] -= bin_min;
} }
// Normalize P
// let mut P_sum = 0.0;
// for bin in 0..ds.num_bins {
// P_sum += P[bin];
// }
// for bin in 0..ds.num_bins {
// P[bin] /= P_sum;
// }
} }
pub fn run(cfg: &Config) -> Result<(), Box<Error>>{ pub fn run(cfg: &Config) -> Result<(), Box<Error>>{
@@ -237,7 +216,7 @@ pub fn run(cfg: &Config) -> Result<(), Box<Error>>{
Ok(()) Ok(())
} }
fn dump_state(ds: &Dataset, F: &Vec<f64>, F_prev: &Vec<f64>, P: &Vec<f64>, A: &Vec<f64>) { fn dump_state(ds: &Dataset, F: &[f64], F_prev: &[f64], P: &[f64], A: &[f64]) {
let out = std::io::stdout(); let out = std::io::stdout();
let mut lock = out.lock(); let mut lock = out.lock();
writeln!(lock, "# PMF"); writeln!(lock, "# PMF");