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moved bias calculation methods to histogram and implemented cyclic conditions

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This commit is contained in:
Daniel Bauer
2018-10-06 12:30:19 +02:00
parent c8b8e29c9c
commit 05c795b83c
5 changed files with 122 additions and 58 deletions
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42
src/lib.rs
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@@ -26,6 +26,7 @@ pub struct Config {
pub tolerance: f32,
pub max_iterations: usize,
pub temperature: f32,
pub cyclic: bool,
}
impl fmt::Display for Config {
@@ -49,29 +50,17 @@ fn is_converged(old_F: &Vec<f32>, new_F: &Vec<f32>, tolerance: f32) -> bool {
true
}
// Harmonic bias calculation: bias = 0.5*k(dx)^2
fn calc_bias(k: f32, x0: f32, x: f32) -> f32 {
let dx = (x-x0).abs();
0.5*k*dx*dx
}
// get center x value for a bin
fn get_x_for_bin(bin: usize, min: f32, width: f32) -> f32 {
min + width * ((bin as f32) + 0.5)
}
// estimate the probability of a bin of the histogram set based on F values
// This evaluates the first WHAM equation for each bin
fn calc_bin_probability(bin: usize, hs: &HistogramSet, F: &Vec<f32>) -> f32 {
let mut denom_sum = 0.0;
let mut bin_count = 0.0;
let x = get_x_for_bin(bin, hs.hist_min, hs.bin_width);
for window in 0..hs.num_windows {
let h: &Histogram = &hs.histograms[window];
if let Some(count) = h.get_bin_count(bin) {
bin_count += count;
}
let bias = calc_bias(hs.bias_fc[window], hs.bias_x0[window], x);
let bias = hs.calc_bias(bin, window);
let bias_offset = ((F[window] - bias) / hs.kT).exp();
denom_sum += (h.num_points as f32) * bias_offset;
}
@@ -83,8 +72,7 @@ fn calc_bin_probability(bin: usize, hs: &HistogramSet, F: &Vec<f32>) -> f32 {
fn calc_window_F(window: usize, hs: &HistogramSet, P: &Vec<f32>) -> f32 {
let mut ln_sum = 0.0;
for bin in 0..hs.num_bins {
let x = get_x_for_bin(bin, hs.hist_min, hs.bin_width);
let bias = calc_bias(hs.bias_fc[window], hs.bias_x0[window], x);
let bias = hs.calc_bias(bin, window);
ln_sum += P[bin] * (-bias/hs.kT).exp()
}
-hs.kT * ln_sum.ln()
@@ -247,7 +235,7 @@ fn dump_state(hs: &HistogramSet, F: &Vec<f32>, F_prev: &Vec<f32>, P: &Vec<f32>,
println!("# PMF");
println!("#x\t\tFree Energy\t\tP(x)");
for bin in 0..hs.num_bins {
let x = get_x_for_bin(bin, hs.hist_min, hs.bin_width);
let x = hs.get_x_for_bin(bin);
println!("{:9.5}\t{:9.5}\t{:9.5}", x, A[bin], P[bin]);
}
println!("# Bias offsets");
@@ -275,18 +263,10 @@ mod tests {
assert!(!converged);
}
#[test]
fn calc_bias() {
let x0 = 10.0;
let x = 5.0;
let k = 500.0;
assert_eq!(6250.0, super::calc_bias(k, x0, x));
}
fn create_test_hs() -> HistogramSet {
let h1 = Histogram::new(0, 2, 10, vec![3.0, 4.0, 3.0]);
let h2 = Histogram::new(0, 3, 20, vec![3.0, 2.0, 5.0, 10.0]);
HistogramSet::new(4, 1.0, 0.0, 4.0, vec![1.0, 2.0], vec![10.0, 10.0], 2.479, vec![h1, h2])
HistogramSet::new(4, 1.0, 0.0, 4.0, vec![1.0, 2.0], vec![10.0, 10.0], 2.479, vec![h1, h2], false)
}
fn assert_near(a: f32, b: f32, tolerance: f32) {
@@ -303,7 +283,6 @@ mod tests {
let F = super::calc_window_F(window, &hs, &probability);
assert_near(expected[window], F, 0.001);
}
}
#[test]
@@ -324,17 +303,6 @@ mod tests {
}
}
#[test]
fn get_x_for_bin() {
let min = 0.0;
let width = 1.0;
let expected = vec!(0.5, 1.5, 2.5, 3.5, 4.5);
for i in 0..5 {
let x = super::get_x_for_bin(i, min, width);
assert_eq!(expected[i], x);
}
}
#[test]
fn perform_wham_iteration() {
let hs = create_test_hs();