//! Comprehensive benchmarks for RTX Science
//!
//! This benchmark suite evaluates the performance of scientific computing
//! operations including PINNs, molecular simulations, and numerical solvers.

use criterion::{BenchmarkId, Criterion, Throughput, criterion_group, criterion_main};
use rtx_science::prelude::*;
use rtx_tensor::{Device, Tensor};
use std::time::Duration;

/// PINN training benchmark
fn bench_pinn_training(c: &mut Criterion) {
    let rt = tokio::runtime::Runtime::new().unwrap();

    let mut group = c.benchmark_group("PINN Training");
    group.measurement_time(Duration::from_secs(10));

    for &size in &[32, 64, 128] {
        group.throughput(Throughput::Elements(size as u64));
        group.bench_with_input(
            BenchmarkId::new("heat_equation", size),
            &size,
            |b, &size| {
                b.to_async(&rt)
                    .iter(|| async { bench_heat_equation_pinn(size).await.unwrap() });
            },
        );
    }

    group.finish();
}

/// Molecular property prediction benchmark
fn bench_molecular_prediction(c: &mut Criterion) {
    let rt = tokio::runtime::Runtime::new().unwrap();

    let mut group = c.benchmark_group("Molecular Prediction");

    for &batch_size in &[16, 32, 64] {
        group.bench_with_input(
            BenchmarkId::new("gnn_forward", batch_size),
            &batch_size,
            |b, &batch_size| {
                b.to_async(&rt)
                    .iter(|| async { bench_molecular_gnn(batch_size).await.unwrap() });
            },
        );
    }

    group.finish();
}

/// Conservation law validation benchmark
fn bench_conservation_laws(c: &mut Criterion) {
    let rt = tokio::runtime::Runtime::new().unwrap();

    c.bench_function("mass_conservation", |b| {
        b.to_async(&rt)
            .iter(|| async { bench_mass_conservation().await.unwrap() });
    });

    c.bench_function("energy_conservation", |b| {
        b.to_async(&rt)
            .iter(|| async { bench_energy_conservation().await.unwrap() });
    });
}

/// Scientific computing primitives benchmark
fn bench_scientific_computing(c: &mut Criterion) {
    let rt = tokio::runtime::Runtime::new().unwrap();

    let mut group = c.benchmark_group("Scientific Computing");

    for &matrix_size in &[256, 512, 1024] {
        group.throughput(Throughput::Elements((matrix_size * matrix_size) as u64));

        group.bench_with_input(
            BenchmarkId::new("matrix_solve", matrix_size),
            &matrix_size,
            |b, &size| {
                b.to_async(&rt)
                    .iter(|| async { bench_linear_solve(size).await.unwrap() });
            },
        );

        group.bench_with_input(
            BenchmarkId::new("fft_transform", matrix_size),
            &matrix_size,
            |b, &size| {
                b.to_async(&rt)
                    .iter(|| async { bench_fft_transform(size).await.unwrap() });
            },
        );
    }

    group.finish();
}

/// GPU vs CPU performance comparison
fn bench_device_comparison(c: &mut Criterion) {
    let rt = tokio::runtime::Runtime::new().unwrap();

    let mut group = c.benchmark_group("Device Comparison");

    // CPU benchmark
    group.bench_function("cpu_pinn", |b| {
        b.to_async(&rt).iter(|| async {
            let device = Device::cpu();
            bench_device_pinn(&device).await.unwrap()
        });
    });

    // GPU benchmark (if available)
    if Device::cuda(0).is_ok() {
        group.bench_function("gpu_pinn", |b| {
            b.to_async(&rt).iter(|| async {
                let device = Device::cuda(0).unwrap();
                bench_device_pinn(&device).await.unwrap()
            });
        });
    }

    group.finish();
}

/// Molecular dataset processing benchmark
fn bench_molecular_datasets(c: &mut Criterion) {
    let rt = tokio::runtime::Runtime::new().unwrap();

    let mut group = c.benchmark_group("Molecular Datasets");

    group.bench_function("dataset_loading", |b| {
        b.to_async(&rt)
            .iter(|| async { bench_dataset_loading().await.unwrap() });
    });

    group.bench_function("feature_extraction", |b| {
        b.to_async(&rt)
            .iter(|| async { bench_feature_extraction().await.unwrap() });
    });

    group.finish();
}

/// Benchmark helper functions

async fn bench_heat_equation_pinn(hidden_size: usize) -> Result<f64> {
    let device = Device::cpu();
    let heat_eq = HeatEquation::new(0.1);

    let pinn = PINN::builder()
        .device(&device)
        .layers(vec![2, hidden_size, hidden_size, 1])
        .physics_loss(Box::new(heat_eq))
        .build()?;

    // Benchmark forward pass
    let inputs = vec![(0.5, 0.1), (0.3, 0.2), (0.8, 0.4), (0.1, 0.9)];
    let start = std::time::Instant::now();
    let _outputs = pinn.predict(&inputs).await?;
    let elapsed = start.elapsed().as_secs_f64();

    Ok(elapsed)
}

async fn bench_molecular_gnn(batch_size: usize) -> Result<f64> {
    let device = Device::cpu();

    // Create dummy molecular graphs
    let mut molecules = Vec::new();
    for i in 0..batch_size {
        let mol = Molecule::from_smiles(format!("mol_{}", i), "CCO")?;
        molecules.push(mol);
    }

    // Benchmark feature matrix creation
    let start = std::time::Instant::now();
    for mol in &molecules {
        let _features = mol.to_feature_matrix()?;
    }
    let elapsed = start.elapsed().as_secs_f64();

    Ok(elapsed)
}

async fn bench_mass_conservation() -> Result<f64> {
    let device = Device::cpu();
    let conservation = MassConservation::new(1e-6);

    // Create test data
    let coords = Tensor::randn([100, 2], &device)?;
    let solution = Variable::new(Tensor::randn([100], &device)?);
    let du_dx = Variable::new(Tensor::randn([100], &device)?);
    let du_dt = Variable::new(Tensor::randn([100], &device)?);

    let start = std::time::Instant::now();
    let _loss = conservation
        .compute_loss(&coords, &solution, &du_dx, &du_dt)
        .await?;
    let elapsed = start.elapsed().as_secs_f64();

    Ok(elapsed)
}

async fn bench_energy_conservation() -> Result<f64> {
    let device = Device::cpu();
    let conservation = EnergyConservation::new(0.1, 1e-6);

    // Create test data
    let coords = Tensor::randn([100, 2], &device)?;
    let solution = Variable::new(Tensor::randn([100], &device)?);
    let du_dx = Variable::new(Tensor::randn([100], &device)?);
    let du_dt = Variable::new(Tensor::randn([100], &device)?);

    let start = std::time::Instant::now();
    let _loss = conservation
        .compute_loss(&coords, &solution, &du_dx, &du_dt)
        .await?;
    let elapsed = start.elapsed().as_secs_f64();

    Ok(elapsed)
}

async fn bench_linear_solve(size: usize) -> Result<f64> {
    let device = Device::cpu();

    // Create random system Ax = b
    let a = Tensor::randn([size, size], &device)?;
    let b = Tensor::randn([size], &device)?;

    let start = std::time::Instant::now();
    // Placeholder for linear solve - would use actual solver
    let _x = a.matmul(&Tensor::eye([size, size], &device)?)?;
    let elapsed = start.elapsed().as_secs_f64();

    Ok(elapsed)
}

async fn bench_fft_transform(size: usize) -> Result<f64> {
    let device = Device::cpu();

    // Create random signal
    let signal = Tensor::randn([size], &device)?;

    let start = std::time::Instant::now();
    // Placeholder for FFT - would use actual FFT implementation
    let _spectrum = signal.multiply(&signal)?;
    let elapsed = start.elapsed().as_secs_f64();

    Ok(elapsed)
}

async fn bench_device_pinn(device: &Device) -> Result<f64> {
    let heat_eq = HeatEquation::new(0.1);

    let pinn = PINN::builder()
        .device(device)
        .layers(vec![2, 64, 64, 1])
        .physics_loss(Box::new(heat_eq))
        .build()?;

    let inputs = vec![(0.5, 0.1); 100]; // Batch of inputs

    let start = std::time::Instant::now();
    let _outputs = pinn.predict(&inputs).await?;
    let elapsed = start.elapsed().as_secs_f64();

    Ok(elapsed)
}

async fn bench_dataset_loading() -> Result<f64> {
    let start = std::time::Instant::now();
    let _dataset = MolecularDataset::load("benchmark_molecules.csv")?;
    let elapsed = start.elapsed().as_secs_f64();

    Ok(elapsed)
}

async fn bench_feature_extraction() -> Result<f64> {
    let dataset = MolecularDataset::load("benchmark_molecules.csv")?;

    let start = std::time::Instant::now();
    for mol in &dataset.molecules {
        let _features = mol.to_feature_matrix()?;
        let _adjacency = mol.adjacency_matrix();
        let _mw = mol.molecular_weight();
    }
    let elapsed = start.elapsed().as_secs_f64();

    Ok(elapsed)
}

/// Memory usage benchmark
fn bench_memory_usage(c: &mut Criterion) {
    let rt = tokio::runtime::Runtime::new().unwrap();

    let mut group = c.benchmark_group("Memory Usage");

    group.bench_function("large_tensor_ops", |b| {
        b.to_async(&rt)
            .iter(|| async { bench_large_tensor_operations().await.unwrap() });
    });

    group.bench_function("molecular_graph_memory", |b| {
        b.to_async(&rt)
            .iter(|| async { bench_molecular_graph_memory().await.unwrap() });
    });

    group.finish();
}

async fn bench_large_tensor_operations() -> Result<f64> {
    let device = Device::cpu();

    let start = std::time::Instant::now();

    // Create large tensors
    let a = Tensor::randn([1000, 1000], &device)?;
    let b = Tensor::randn([1000, 1000], &device)?;

    // Perform operations
    let _c = a.matmul(&b)?;
    let _d = a.add(&b)?;
    let _e = a.multiply(&b)?;

    let elapsed = start.elapsed().as_secs_f64();
    Ok(elapsed)
}

async fn bench_molecular_graph_memory() -> Result<f64> {
    let start = std::time::Instant::now();

    // Create large molecular dataset
    let mut molecules = Vec::new();
    for i in 0..1000 {
        let mol = Molecule::from_smiles(
            format!("large_mol_{}", i),
            "CCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC",
        )?;
        molecules.push(mol);
    }

    // Extract features
    for mol in &molecules {
        let _features = mol.to_feature_matrix()?;
    }

    let elapsed = start.elapsed().as_secs_f64();
    Ok(elapsed)
}

/// Accuracy vs speed trade-off benchmark
fn bench_accuracy_speed_tradeoff(c: &mut Criterion) {
    let rt = tokio::runtime::Runtime::new().unwrap();

    let mut group = c.benchmark_group("Accuracy vs Speed");

    for &precision in &["single", "double"] {
        group.bench_with_input(
            BenchmarkId::new("pinn_precision", precision),
            &precision,
            |b, &precision| {
                b.to_async(&rt)
                    .iter(|| async { bench_precision_pinn(precision).await.unwrap() });
            },
        );
    }

    group.finish();
}

async fn bench_precision_pinn(precision: &str) -> Result<f64> {
    let device = match precision {
        "single" => Device::cpu(),
        "double" => Device::cpu(), // Would use double precision if available
        _ => Device::cpu(),
    };

    let heat_eq = HeatEquation::new(0.1);
    let pinn = PINN::builder()
        .device(&device)
        .layers(vec![2, 64, 64, 1])
        .physics_loss(Box::new(heat_eq))
        .build()?;

    let inputs = vec![(0.5, 0.1); 50];

    let start = std::time::Instant::now();
    let _outputs = pinn.predict(&inputs).await?;
    let elapsed = start.elapsed().as_secs_f64();

    Ok(elapsed)
}

/// Parallel scaling benchmark
fn bench_parallel_scaling(c: &mut Criterion) {
    let rt = tokio::runtime::Runtime::new().unwrap();

    let mut group = c.benchmark_group("Parallel Scaling");

    for &num_threads in &[1, 2, 4, 8] {
        group.bench_with_input(
            BenchmarkId::new("molecular_parallel", num_threads),
            &num_threads,
            |b, &num_threads| {
                b.to_async(&rt).iter(|| async {
                    bench_molecular_parallel_processing(num_threads)
                        .await
                        .unwrap()
                });
            },
        );
    }

    group.finish();
}

async fn bench_molecular_parallel_processing(num_threads: usize) -> Result<f64> {
    // Set number of threads (placeholder)
    std::env::set_var("RAYON_NUM_THREADS", num_threads.to_string());

    let start = std::time::Instant::now();

    // Create molecules to process in parallel
    let molecules: Vec<_> = (0..100)
        .map(|i| Molecule::from_smiles(format!("mol_{}", i), "CCCCCCCC").unwrap())
        .collect();

    // Process in parallel using rayon
    use rayon::prelude::*;
    let _results: Vec<_> = molecules
        .par_iter()
        .map(|mol| mol.molecular_weight())
        .collect();

    let elapsed = start.elapsed().as_secs_f64();
    Ok(elapsed)
}

criterion_group!(
    benches,
    bench_pinn_training,
    bench_molecular_prediction,
    bench_conservation_laws,
    bench_scientific_computing,
    bench_device_comparison,
    bench_molecular_datasets,
    bench_memory_usage,
    bench_accuracy_speed_tradeoff,
    bench_parallel_scaling
);
criterion_main!(benches);