scirs2-integrate 0.4.2

Numerical integration module for SciRS2 (scirs2-integrate)
Documentation
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
//! Specialized visualization tools for different scientific domains
//!
//! This module provides visualization tools for specialized scientific domains
//! including quantum mechanics, fluid dynamics, and financial analysis.

use super::types::*;
use crate::error::{IntegrateError, IntegrateResult};
use scirs2_core::ndarray::{Array1, Array2, Array3, Axis};

/// Quantum state visualization tools
pub struct QuantumVisualizer;

impl QuantumVisualizer {
    /// Create wave function visualization
    pub fn visualize_wavefunction(
        x: &Array1<f64>,
        probability_density: &Array1<f64>,
        time: f64,
    ) -> IntegrateResult<HeatMapPlot> {
        let mut metadata = PlotMetadata::default();
        metadata.title = format!("Quantum State at t = {:.3}", time);
        metadata.xlabel = "Position".to_string();
        metadata.ylabel = "Probability Density".to_string();

        Ok(HeatMapPlot {
            x: x.clone(),
            y: Array1::from_elem(1, 0.0), // 1D visualization
            z: Array2::from_shape_vec((1, probability_density.len()), probability_density.to_vec())
                .map_err(|e| IntegrateError::ComputationError(format!("Shape error: {e}")))?,
            metadata,
        })
    }

    /// Create complex phase visualization
    pub fn visualize_complex_phase(
        real_parts: &[f64],
        imag_parts: &[f64],
        phases: &[f64],
    ) -> IntegrateResult<PhaseSpacePlot> {
        let mut metadata = PlotMetadata::default();
        metadata.title = "Complex Wave Function Phase".to_string();
        metadata.xlabel = "Real Part".to_string();
        metadata.ylabel = "Imaginary Part".to_string();

        Ok(PhaseSpacePlot {
            x: real_parts.to_vec(),
            y: imag_parts.to_vec(),
            colors: Some(phases.to_vec()),
            metadata,
        })
    }

    /// Create expectation value evolution plot
    pub fn visualize_expectation_evolution(
        times: &[f64],
        positions: &[f64],
        momenta: &[f64],
    ) -> IntegrateResult<PhaseSpacePlot> {
        let mut metadata = PlotMetadata::default();
        metadata.title = "Quantum Expectation Values Evolution".to_string();
        metadata.xlabel = "Position Expectation".to_string();
        metadata.ylabel = "Momentum Expectation".to_string();

        Ok(PhaseSpacePlot {
            x: positions.to_vec(),
            y: momenta.to_vec(),
            colors: Some(times.to_vec()),
            metadata,
        })
    }

    /// Create energy level diagram
    pub fn visualize_energy_levels(
        energies: &Array1<f64>,
        wavefunctions: &Array2<f64>,
    ) -> IntegrateResult<VectorFieldPlot> {
        let n_levels = energies.len().min(5); // Show up to 5 levels
        let n_points = wavefunctions.nrows();

        let x_coords = Array1::linspace(-1.0, 1.0, n_points);
        let mut x_grid = Array2::zeros((n_levels, n_points));
        let mut y_grid = Array2::zeros((n_levels, n_points));
        let mut u = Array2::zeros((n_levels, n_points));
        let mut v = Array2::zeros((n_levels, n_points));
        let mut magnitude = Array2::zeros((n_levels, n_points));

        for level in 0..n_levels {
            for i in 0..n_points {
                x_grid[[level, i]] = x_coords[i];
                y_grid[[level, i]] = energies[level];
                u[[level, i]] = wavefunctions[[i, level]];
                v[[level, i]] = 0.0; // No y-component for energy levels
                magnitude[[level, i]] = wavefunctions[[i, level]].abs();
            }
        }

        let mut metadata = PlotMetadata::default();
        metadata.title = "Energy Level Diagram".to_string();
        metadata.xlabel = "Position".to_string();
        metadata.ylabel = "Energy".to_string();

        Ok(VectorFieldPlot {
            x_grid,
            y_grid,
            u,
            v,
            magnitude,
            metadata,
        })
    }
}

/// Fluid dynamics visualization tools
pub struct FluidVisualizer;

impl FluidVisualizer {
    /// Create velocity field visualization
    pub fn visualize_velocity_field(state: &FluidState) -> IntegrateResult<VectorFieldPlot> {
        if state.velocity.len() < 2 {
            return Err(IntegrateError::ValueError(
                "Need at least 2 velocity components".to_string(),
            ));
        }

        let u = &state.velocity[0];
        let v = &state.velocity[1];
        let (ny, nx) = u.dim();

        let mut x_grid = Array2::zeros((ny, nx));
        let mut y_grid = Array2::zeros((ny, nx));
        let mut magnitude = Array2::zeros((ny, nx));

        for i in 0..ny {
            for j in 0..nx {
                x_grid[[i, j]] = j as f64 * state.dx;
                y_grid[[i, j]] = i as f64 * state.dy;
                magnitude[[i, j]] = (u[[i, j]].powi(2) + v[[i, j]].powi(2)).sqrt();
            }
        }

        let mut metadata = PlotMetadata::default();
        metadata.title = format!("Velocity Field at t = {:.3}", state.time);
        metadata.xlabel = "X Position".to_string();
        metadata.ylabel = "Y Position".to_string();

        Ok(VectorFieldPlot {
            x_grid,
            y_grid,
            u: u.clone(),
            v: v.clone(),
            magnitude,
            metadata,
        })
    }

    /// Create pressure field heatmap
    pub fn visualize_pressure_field(state: &FluidState) -> IntegrateResult<HeatMapPlot> {
        let (ny, nx) = state.pressure.dim();
        let x = Array1::from_iter((0..nx).map(|i| i as f64 * state.dx));
        let y = Array1::from_iter((0..ny).map(|i| i as f64 * state.dy));

        let mut metadata = PlotMetadata::default();
        metadata.title = format!("Pressure Field at t = {:.3}", state.time);
        metadata.xlabel = "X Position".to_string();
        metadata.ylabel = "Y Position".to_string();

        Ok(HeatMapPlot {
            x,
            y,
            z: state.pressure.clone(),
            metadata,
        })
    }

    /// Create vorticity visualization
    pub fn visualize_vorticity(state: &FluidState) -> IntegrateResult<HeatMapPlot> {
        if state.velocity.len() < 2 {
            return Err(IntegrateError::ValueError(
                "Need at least 2 velocity components".to_string(),
            ));
        }

        let u = &state.velocity[0];
        let v = &state.velocity[1];
        let (ny, nx) = u.dim();

        let mut vorticity = Array2::zeros((ny, nx));

        // Compute vorticity using finite differences
        for i in 1..ny - 1 {
            for j in 1..nx - 1 {
                let dvdx = (v[[i, j + 1]] - v[[i, j - 1]]) / (2.0 * state.dx);
                let dudy = (u[[i + 1, j]] - u[[i - 1, j]]) / (2.0 * state.dy);
                vorticity[[i, j]] = dvdx - dudy;
            }
        }

        let x = Array1::from_iter((0..nx).map(|i| i as f64 * state.dx));
        let y = Array1::from_iter((0..ny).map(|i| i as f64 * state.dy));

        let mut metadata = PlotMetadata::default();
        metadata.title = format!("Vorticity Field at t = {:.3}", state.time);
        metadata.xlabel = "X Position".to_string();
        metadata.ylabel = "Y Position".to_string();

        Ok(HeatMapPlot {
            x,
            y,
            z: vorticity,
            metadata,
        })
    }

    /// Create streamline visualization  
    pub fn visualize_streamlines(
        state: &FluidState,
        n_streamlines: usize,
    ) -> IntegrateResult<Vec<PhaseSpacePlot>> {
        if state.velocity.len() < 2 {
            return Err(IntegrateError::ValueError(
                "Need at least 2 velocity components".to_string(),
            ));
        }

        let u = &state.velocity[0];
        let v = &state.velocity[1];
        let (ny, nx) = u.dim();

        let mut streamlines = Vec::new();

        // Create evenly spaced starting points
        for i in 0..n_streamlines {
            let start_x = (i as f64 / (n_streamlines - 1) as f64) * (nx - 1) as f64 * state.dx;
            let start_y = 0.5 * (ny - 1) as f64 * state.dy; // Start at middle height

            let mut x_line = vec![start_x];
            let mut y_line = vec![start_y];

            let mut current_x = start_x;
            let mut current_y = start_y;

            // Integrate streamline using simple Euler method
            let dt = 0.01 * state.dx.min(state.dy);
            for _ in 0..1000 {
                // Maximum steps
                let i_idx = (current_y / state.dy) as usize;
                let j_idx = (current_x / state.dx) as usize;

                if i_idx >= ny - 1 || j_idx >= nx - 1 || i_idx == 0 || j_idx == 0 {
                    break;
                }

                let vel_x = u[[i_idx, j_idx]];
                let vel_y = v[[i_idx, j_idx]];

                current_x += vel_x * dt;
                current_y += vel_y * dt;

                x_line.push(current_x);
                y_line.push(current_y);

                // Stop if velocity is too small
                if vel_x.abs() + vel_y.abs() < 1e-6 {
                    break;
                }
            }

            let mut metadata = PlotMetadata::default();
            metadata.title = format!("Streamline {} at t = {:.3}", i, state.time);
            metadata.xlabel = "X Position".to_string();
            metadata.ylabel = "Y Position".to_string();

            streamlines.push(PhaseSpacePlot {
                x: x_line,
                y: y_line,
                colors: None,
                metadata,
            });
        }

        Ok(streamlines)
    }

    /// Create 3D fluid visualization
    pub fn visualize_3d_velocity_magnitude(state: &FluidState3D) -> IntegrateResult<SurfacePlot> {
        if state.velocity.len() < 3 {
            return Err(IntegrateError::ValueError(
                "Need 3 velocity components for 3D".to_string(),
            ));
        }

        let u = &state.velocity[0];
        let v = &state.velocity[1];
        let w = &state.velocity[2];
        let (nz, ny, nx) = u.dim();

        // Take a slice at z = nz/2
        let z_slice = nz / 2;
        let mut x_grid = Array2::zeros((ny, nx));
        let mut y_grid = Array2::zeros((ny, nx));
        let mut magnitude = Array2::zeros((ny, nx));

        for i in 0..ny {
            for j in 0..nx {
                x_grid[[i, j]] = j as f64 * state.dx;
                y_grid[[i, j]] = i as f64 * state.dy;
                let vel_mag = (u[[z_slice, i, j]].powi(2)
                    + v[[z_slice, i, j]].powi(2)
                    + w[[z_slice, i, j]].powi(2))
                .sqrt();
                magnitude[[i, j]] = vel_mag;
            }
        }

        let mut metadata = PlotMetadata::default();
        metadata.title = format!("3D Velocity Magnitude at t = {:.3}", state.time);
        metadata.xlabel = "X Position".to_string();
        metadata.ylabel = "Y Position".to_string();

        Ok(SurfacePlot {
            x: x_grid,
            y: y_grid,
            z: magnitude,
            metadata,
        })
    }
}

/// Financial analysis visualization tools
pub struct FinanceVisualizer;

impl FinanceVisualizer {
    /// Create option price surface
    pub fn visualize_option_surface(
        strikes: &Array1<f64>,
        maturities: &Array1<f64>,
        prices: &Array2<f64>,
    ) -> IntegrateResult<SurfacePlot> {
        let (n_maturities, n_strikes) = prices.dim();
        let mut x_grid = Array2::zeros((n_maturities, n_strikes));
        let mut y_grid = Array2::zeros((n_maturities, n_strikes));

        for i in 0..n_maturities {
            for j in 0..n_strikes {
                x_grid[[i, j]] = strikes[j];
                y_grid[[i, j]] = maturities[i];
            }
        }

        let mut metadata = PlotMetadata::default();
        metadata.title = "Option Price Surface".to_string();
        metadata.xlabel = "Strike Price".to_string();
        metadata.ylabel = "Time to Maturity".to_string();

        Ok(SurfacePlot {
            x: x_grid,
            y: y_grid,
            z: prices.clone(),
            metadata,
        })
    }

    /// Create Greeks surface visualization
    pub fn visualize_greeks_surface(
        strikes: &Array1<f64>,
        spot_prices: &Array1<f64>,
        greek_values: &Array2<f64>,
        greek_name: &str,
    ) -> IntegrateResult<HeatMapPlot> {
        let mut metadata = PlotMetadata::default();
        metadata.title = format!("{} Surface", greek_name);
        metadata.xlabel = "Strike Price".to_string();
        metadata.ylabel = "Spot Price".to_string();

        Ok(HeatMapPlot {
            x: strikes.clone(),
            y: spot_prices.clone(),
            z: greek_values.clone(),
            metadata,
        })
    }

    /// Create volatility smile visualization
    pub fn visualize_volatility_smile(
        strikes: &Array1<f64>,
        implied_volatilities: &Array1<f64>,
        maturity: f64,
    ) -> IntegrateResult<PhaseSpacePlot> {
        let mut metadata = PlotMetadata::default();
        metadata.title = format!("Volatility Smile (T = {:.3})", maturity);
        metadata.xlabel = "Strike Price".to_string();
        metadata.ylabel = "Implied Volatility".to_string();

        Ok(PhaseSpacePlot {
            x: strikes.to_vec(),
            y: implied_volatilities.to_vec(),
            colors: None,
            metadata,
        })
    }

    /// Create risk metrics visualization
    pub fn visualize_risk_metrics(
        time_points: &Array1<f64>,
        var_values: &Array1<f64>,
        cvar_values: &Array1<f64>,
    ) -> IntegrateResult<PhaseSpacePlot> {
        let mut metadata = PlotMetadata::default();
        metadata.title = "Risk Metrics Evolution".to_string();
        metadata.xlabel = "Value at Risk".to_string();
        metadata.ylabel = "Conditional Value at Risk".to_string();

        Ok(PhaseSpacePlot {
            x: var_values.to_vec(),
            y: cvar_values.to_vec(),
            colors: Some(time_points.to_vec()),
            metadata,
        })
    }

    /// Create portfolio performance visualization
    pub fn visualize_portfolio_performance(
        dates: &[String],
        returns: &Array1<f64>,
        benchmark_returns: &Array1<f64>,
    ) -> IntegrateResult<PhaseSpacePlot> {
        // Calculate cumulative returns
        let mut cum_returns = vec![1.0]; // Start with 1.0
        let mut cum_benchmark = vec![1.0];

        for i in 0..returns.len() {
            cum_returns.push(cum_returns[i] * (1.0 + returns[i]));
            cum_benchmark.push(cum_benchmark[i] * (1.0 + benchmark_returns[i]));
        }

        let mut metadata = PlotMetadata::default();
        metadata.title = "Portfolio vs Benchmark Performance".to_string();
        metadata.xlabel = "Portfolio Cumulative Return".to_string();
        metadata.ylabel = "Benchmark Cumulative Return".to_string();

        Ok(PhaseSpacePlot {
            x: cum_returns,
            y: cum_benchmark,
            colors: Some((0..dates.len() + 1).map(|i| i as f64).collect()),
            metadata,
        })
    }
}

/// Create specialized quantum visualization
pub fn specialized_visualizations(
    visualization_type: &str,
    data: &Array2<f64>,
) -> IntegrateResult<HeatMapPlot> {
    match visualization_type {
        "quantum_probability" => {
            let x = Array1::linspace(-5.0, 5.0, data.ncols());
            let probability_density = data.row(0).to_owned();
            QuantumVisualizer::visualize_wavefunction(&x, &probability_density, 0.0)
        }
        _ => Err(IntegrateError::ValueError(format!(
            "Unknown visualization type: {}",
            visualization_type
        ))),
    }
}

/// Create bifurcation diagram generator for specialized systems
pub struct BifurcationDiagramGenerator {
    /// Parameter range for bifurcation analysis
    pub parameter_range: (f64, f64),
    /// Number of parameter samples
    pub n_parameter_samples: usize,
    /// Number of initial transient steps to skip
    pub transient_steps: usize,
    /// Number of sampling steps after transients
    pub sampling_steps: usize,
    /// Tolerance for detecting fixed points
    pub fixed_point_tolerance: f64,
    /// Tolerance for detecting periodic orbits
    pub period_tolerance: f64,
}

impl BifurcationDiagramGenerator {
    /// Create new bifurcation diagram generator
    pub fn new(parameterrange: (f64, f64), n_parameter_samples: usize) -> Self {
        Self {
            parameter_range: parameterrange,
            n_parameter_samples,
            transient_steps: 1000,
            sampling_steps: 500,
            fixed_point_tolerance: 1e-8,
            period_tolerance: 1e-6,
        }
    }

    /// Generate enhanced bifurcation diagram
    pub fn generate_enhanced_diagram<F>(
        &self,
        map_function: F,
        initial_condition: f64,
    ) -> IntegrateResult<BifurcationDiagram>
    where
        F: Fn(f64, f64) -> f64, // (x, parameter) -> x_next
    {
        let mut parameter_values = Vec::new();
        let mut state_values = Vec::new();
        let mut stability_flags = Vec::new();

        let param_step = (self.parameter_range.1 - self.parameter_range.0)
            / (self.n_parameter_samples - 1) as f64;

        for i in 0..self.n_parameter_samples {
            let param = self.parameter_range.0 + i as f64 * param_step;

            // Run transients
            let mut x = initial_condition;
            for _ in 0..self.transient_steps {
                x = map_function(x, param);
            }

            // Sample attractor
            let mut attractor_states = Vec::new();
            for _ in 0..self.sampling_steps {
                x = map_function(x, param);
                attractor_states.push(x);
            }

            // Simple attractor analysis
            let unique_count = self.count_unique_states(&attractor_states);
            let is_stable = unique_count <= 2;

            // Store representative states
            if unique_count == 1 {
                parameter_values.push(param);
                state_values.push(attractor_states[attractor_states.len() - 1]);
                stability_flags.push(is_stable);
            } else {
                // Store multiple points for periodic/chaotic attractors
                let sample_rate = (attractor_states.len() / 10).max(1);
                for (idx, &state) in attractor_states.iter().step_by(sample_rate).enumerate() {
                    if idx < 10 {
                        // Limit number of points per parameter
                        parameter_values.push(param);
                        state_values.push(state);
                        stability_flags.push(is_stable);
                    }
                }
            }
        }

        Ok(BifurcationDiagram {
            parameters: parameter_values,
            states: vec![state_values],
            stability: stability_flags,
            bifurcation_points: vec![], // Simplified - not computing bifurcation points
        })
    }

    fn count_unique_states(&self, states: &[f64]) -> usize {
        let mut unique_states = states.to_vec();
        unique_states.sort_by(|a, b| a.partial_cmp(b).unwrap_or(std::cmp::Ordering::Equal));
        unique_states.dedup_by(|a, b| (*a - *b).abs() < self.fixed_point_tolerance);
        unique_states.len()
    }
}