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feat: Engine diagnostics #92

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glen merged 16 commits from Vectornaut/dyna3:diagnostics into main 2025-07-21 04:18:50 +00:00
Conversation 30 Commits 16 Files changed 17 +70 -37
1 changed files with 70 additions and 37 deletions
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Showing only changes of commit 2688b76678 - Show all commits

107
app-proto/src/diagnostics.rs
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@ -2,7 +2,7 @@ use charming::{
Chart,
WasmRenderer,
component::{Axis, DataZoom, Grid},
element::AxisType,
element::{AxisType, Symbol},
series::{Line, Scatter},
};
use sycamore::prelude::*;
@ -50,6 +50,10 @@ fn RealizationStatus() -> View {
}
}
fn into_time_point((step, value): (usize, f64)) -> Vec<Option<f64>> {
vec![Some(step as f64), Some(value)]
}
// the loss history from the last realization
#[component]
fn LossHistory() -> View {
@ -60,38 +64,35 @@ fn LossHistory() -> View {
on_mount(move || {
create_effect(move || {
// get the loss history
let scaled_loss = state.assembly.descent_history.with(
|history| history.scaled_loss.clone()
let scaled_loss: Vec<_> = state.assembly.descent_history.with(
|history| history.scaled_loss
.iter()
.enumerate()
.map(|(step, &loss)| (step, loss))
.map(into_time_point)
.collect()
);
let step_cnt = scaled_loss.len();
// initialize the chart axes and series
const MIN_INTERVAL: f64 = 0.01;
let mut step_axis = Axis::new()
let step_axis = Axis::new()
.type_(AxisType::Category)
.boundary_gap(false);
let scaled_loss_axis = Axis::new()
.type_(AxisType::Value)
.min(0)
.min_interval(MIN_INTERVAL);
let scaled_loss_axis = Axis::new().type_(AxisType::Log);
// load the chart data. when there's no history, we load the data
// point (0, None) to clear the chart. it would feel more natural to
// load empty data vectors, but that turns out not to clear the
// chart: it instead leads to previous data being re-used
let mut scaled_loss_series = Line::new();
if step_cnt > 0 {
step_axis = step_axis.data(
(0..step_cnt).map(|step| step.to_string()).collect()
);
scaled_loss_series = scaled_loss_series.data(scaled_loss);
} else {
step_axis = step_axis.data(vec![0.to_string()]);
scaled_loss_series = scaled_loss_series.data(vec![None::<f64>]);
}
let scaled_loss_series = Line::new().data(
if scaled_loss.len() > 0 {
scaled_loss
} else {
vec![vec![Some(0.0), None::<f64>]]
}
);
let chart = Chart::new()
.animation(false)
.data_zoom(DataZoom::new().y_axis_index(0).right(40).start(0).end(100))
.data_zoom(DataZoom::new().y_axis_index(0).right(40))
.x_axis(step_axis)
.y_axis(scaled_loss_axis)
.grid(Grid::new().top(20).right(80).bottom(30).left(60))
@ -114,41 +115,73 @@ fn SpectrumHistory() -> View {
on_mount(move || {
create_effect(move || {
// get the spectrum of the Hessian at each step
let hess_eigvals = state.assembly.descent_history.with(
// get the spectrum of the Hessian at each step, split into its
// positive and negative parts. throw away eigenvalues that are
// close to zero
const ZERO_THRESHOLD: f64 = 1e-6;
let (
hess_eigvals_pos,
hess_eigvals_neg
): (Vec<_>, Vec<_>) = state.assembly.descent_history.with(
|history| history.hess_eigvals
.iter()
.enumerate()
.map(
|(step, eigvals)| eigvals.iter().map(
move |val| vec![step as f64, *val]
)
|(step, eigvals)| eigvals
.iter()
.filter(|&&val| val.abs() > ZERO_THRESHOLD)
.map(
move |&val| (step, val)
)
)
.flatten()
.collect::<Vec<_>>()
.partition(|&(_, val)| val > 0.0)
);
// initialize the chart axes and series
let step_axis = Axis::new();
let eigval_axis = Axis::new();
let step_axis = Axis::new()
.type_(AxisType::Category)
.boundary_gap(false);
let eigval_axis = Axis::new().type_(AxisType::Log);
// load the chart data. when there's no history, we load the data
// point (0, None) to clear the chart. it would feel more natural to
// load empty data vectors, but that turns out not to clear the
// chart: it instead leads to previous data being re-used
let mut eigval_series = Scatter::new().symbol_size(7);
if hess_eigvals.len() > 0 {
eigval_series = eigval_series.data(hess_eigvals);
} else {
eigval_series = eigval_series.data(vec![None::<f64>, None::<f64>]);
}
let eigval_series_pos = Scatter::new()
.symbol_size(4.5)
.data(
if hess_eigvals_pos.len() > 0 {
hess_eigvals_pos
.into_iter()
.map(into_time_point)
.collect()
} else {
vec![vec![Some(0.0), None::<f64>]]
}
);
let eigval_series_neg = Scatter::new()
.symbol(Symbol::Diamond)
.symbol_size(6.0)
.data(
if hess_eigvals_neg.len() > 0 {
hess_eigvals_neg
.into_iter()
.map(|(step, val)| (step, -val))
.map(into_time_point)
.collect()
} else {
vec![vec![Some(0.0), None::<f64>]]
}
);
let chart = Chart::new()
.animation(false)
.data_zoom(DataZoom::new().y_axis_index(0).right(40).start(0).end(100))
.data_zoom(DataZoom::new().y_axis_index(0).right(40))
.x_axis(step_axis)
.y_axis(eigval_axis)
.grid(Grid::new().top(20).right(80).bottom(30).left(60))
.series(eigval_series);
.series(eigval_series_pos)
.series(eigval_series_neg);
renderer.render(CONTAINER_ID, &chart).unwrap();
});
});