From 6ac2d9f055af4d0302cc42875d21ed9a86e4f222 Mon Sep 17 00:00:00 2001 From: RunasSudo Date: Mon, 17 Apr 2023 22:12:07 +1000 Subject: [PATCH] Add test for intcox --- Cargo.toml | 3 + src/intcox.rs | 12 +- src/lib.rs | 1 + src/main.rs | 2 +- tests/intcox.rs | 87 ++++ tests/zeng_mao_lin.csv | 1125 ++++++++++++++++++++++++++++++++++++++++ 6 files changed, 1223 insertions(+), 7 deletions(-) create mode 100644 src/lib.rs create mode 100644 tests/intcox.rs create mode 100644 tests/zeng_mao_lin.csv diff --git a/Cargo.toml b/Cargo.toml index 2da13fc..d648221 100644 --- a/Cargo.toml +++ b/Cargo.toml @@ -12,6 +12,9 @@ rayon = "1.7.0" serde = { version = "1.0.160", features = ["derive"] } serde_json = "1.0.96" +[profile.test] +opt-level = 3 + [profile.perf] inherits = "release" debug = true diff --git a/src/intcox.rs b/src/intcox.rs index 716796a..c70c896 100644 --- a/src/intcox.rs +++ b/src/intcox.rs @@ -162,7 +162,7 @@ impl IntervalCensoredCoxData { } } -fn fit_interval_censored_cox(data_times: DMatrix, mut data_indep: DMatrix, max_iterations: u32, tolerance: f64, reduced: bool, progress_bar: ProgressBar) -> IntervalCensoredCoxResult { +pub fn fit_interval_censored_cox(data_times: DMatrix, mut data_indep: DMatrix, max_iterations: u32, tolerance: f64, reduced: bool, progress_bar: ProgressBar) -> IntervalCensoredCoxResult { // ---------------------- // Prepare for regression @@ -572,11 +572,11 @@ fn profile_log_likelihood_obs(data: &IntervalCensoredCoxData, beta: DVector } #[derive(Serialize, Deserialize)] -struct IntervalCensoredCoxResult { - params: Vec, - params_se: Vec, - ll_model: f64, - ll_null: f64, +pub struct IntervalCensoredCoxResult { + pub params: Vec, + pub params_se: Vec, + pub ll_model: f64, + pub ll_null: f64, // TODO: cumulative hazard, etc. } diff --git a/src/lib.rs b/src/lib.rs new file mode 100644 index 0000000..c250616 --- /dev/null +++ b/src/lib.rs @@ -0,0 +1 @@ +pub mod intcox; diff --git a/src/main.rs b/src/main.rs index b28bb33..f1ee44a 100644 --- a/src/main.rs +++ b/src/main.rs @@ -16,7 +16,7 @@ use clap::{Parser, Subcommand}; -mod intcox; +use hpstat::intcox; #[derive(Parser)] #[command(about="High-performance statistics implementations")] diff --git a/tests/intcox.rs b/tests/intcox.rs new file mode 100644 index 0000000..013ce06 --- /dev/null +++ b/tests/intcox.rs @@ -0,0 +1,87 @@ +// hpstat: High-performance statistics implementations +// Copyright © 2023 Lee Yingtong Li (RunasSudo) +// +// This program is free software: you can redistribute it and/or modify +// it under the terms of the GNU Affero General Public License as published by +// the Free Software Foundation, either version 3 of the License, or +// (at your option) any later version. +// +// This program is distributed in the hope that it will be useful, +// but WITHOUT ANY WARRANTY; without even the implied warranty of +// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +// GNU Affero General Public License for more details. +// +// You should have received a copy of the GNU Affero General Public License +// along with this program. If not, see . + +use std::fs; + +use indicatif::ProgressBar; +use nalgebra::DMatrix; + +use hpstat::intcox::fit_interval_censored_cox; + +#[test] +fn test_intcox_zeng_mao_lin() { + // Compare "Bangkok Metropolitan Administration HIV" data from Zeng, Mao & Lin (2016) with IntCens 0.2 output + + let contents = fs::read_to_string("tests/zeng_mao_lin.csv").unwrap(); + let lines: Vec = contents.trim_end().split("\n").map(|s| s.to_string()).collect(); + + // Read data into matrices + + let mut data_times: DMatrix = DMatrix::zeros( + 2, // Left time, right time + lines.len() - 1 // Minus 1 row for header row + ); + + // Called "Z" in the paper and "X" in the C++ code + let mut data_indep: DMatrix = DMatrix::zeros( + lines[0].split(",").count() - 2, + lines.len() - 1 // Minus 1 row for header row + ); + + // Read data + // FIXME: Parse CSV more robustly + for (i, row) in lines.iter().skip(1).enumerate() { + for (j, item) in row.split(",").enumerate() { + let value = match item { + "inf" => f64::INFINITY, + _ => item.parse().expect("Malformed float") + }; + + if j < 2 { + data_times[(j, i)] = value; + } else { + data_indep[(j - 2, i)] = value; + } + } + } + + // Fit regression + let progress_bar = ProgressBar::hidden(); + //let result = fit_interval_censored_cox(data_times, data_indep, 200, 0.00005, false, progress_bar); + let result = fit_interval_censored_cox(data_times, data_indep, 100, 0.0001, false, progress_bar); + + // ./unireg --in zeng_mao_lin.csv --out out.txt --r 0.0 --model "(Left_Time, Right_Time) = Needle + Needle2 + LogAge + GenderM + RaceO + RaceW + GenderM_RaceO + GenderM_RaceW" --sep , --inf_char inf --convergence_threshold 0.002 + + assert!((result.ll_model - -603.205).abs() < 1.0); + + assert!((result.params[0] - -0.18636961816695094).abs() < 0.01); + assert!((result.params[1] - 0.080478699024478656).abs() < 0.01); + assert!((result.params[2] - -0.71260450817296639).abs() < 0.01); + assert!((result.params[3] - -0.22937443803422858).abs() < 0.01); + assert!((result.params[4] - -0.14101449484871434).abs() < 0.01); + assert!((result.params[5] - -0.43894526362102332).abs() < 0.01); + assert!((result.params[6] - 0.064533885082884768).abs() < 0.01); + assert!((result.params[7] - 0.20970425315378016).abs() < 0.01); + + assert!((result.params_se[0] - 0.41496954829036448).abs() < 0.01); + assert!((result.params_se[1] - 0.15086156546712554).abs() < 0.01); + assert!((result.params_se[2] - 0.36522062865858951).abs() < 0.01); + assert!((result.params_se[3] - 0.32195496906604004).abs() < 0.01); + assert!((result.params_se[4] - 0.3912241733944129).abs() < 0.01); + assert!((result.params_se[5] - 0.41907763222198746).abs() < 0.01); + assert!((result.params_se[6] - 0.45849947730170948).abs() < 0.01); + assert!((result.params_se[7] - 0.48803508171247434).abs() < 0.01); +} diff --git a/tests/zeng_mao_lin.csv b/tests/zeng_mao_lin.csv new file mode 100644 index 0000000..256b140 --- /dev/null +++ b/tests/zeng_mao_lin.csv @@ -0,0 +1,1125 @@ 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