Advanced Topics

Machine learning, Python integration, and advanced features.

Python Integration

XDL provides seamless integration with Python 3.13:

; Import Python modules
math_mod = python_import("math")
result = python_call(math_mod, "sqrt", 16.0)
print, "sqrt(16) =", result

; Use NumPy
numpy = python_import("numpy")
arr = python_call(numpy, "array", [1, 2, 3, 4, 5])

See Python Integration Guide for details.

Machine Learning

XDL includes machine learning capabilities:

Features

• Neural Networks - Deep learning models
• Classical ML - Regression, classification, clustering
• Model Training - Automatic differentiation, optimizers
• Inference - Fast model inference with GPU

Documentation

• ML Implementation Plan - Roadmap
• ML Complete Reference - API reference
• ML Status - Current status
• ML Advanced Features - Advanced features
• ML Final Summary - Overview
• ML Phase 11 - Advanced deep learning

Example

; Train neural network
model = create_model([784, 128, 64, 10])
train_model, model, X_train, y_train, epochs=10

; Make predictions
predictions = predict(model, X_test)

Advanced Visualization

Complex visualization techniques:

• Advanced Visualization - Integration guide
• Advanced Reference - API reference
• 3D Plotting Complete - Complete 3D plotting guide
• 3D Plotting with GUI - GUI integration

Features

• Custom Shaders - WebGL/OpenGL shaders
• Volume Rendering - 3D volumetric data
• Animation - Animated visualizations
• Interactive Graphics - User interaction

Signal Processing

Advanced signal processing:

• Moving Average - Signal filtering
• Moving Average Implementation - Details

Example

; Apply moving average filter
signal = randomn(1000)
filtered = moving_average(signal, window=10)
plot, signal
oplot, filtered, color='red'

Physics Simulations

Scientific simulation examples:

• Rayleigh-Taylor Demo - Physics simulation
• Rayleigh-Taylor Details - Implementation

Rayleigh-Taylor Instability

; Simulate fluid dynamics
density = initialize_density(nx, ny)
velocity = initialize_velocity(nx, ny)

for t = 0, n_steps do begin
  update_density, density, velocity, dt
  update_velocity, velocity, density, dt
  visualize, density
endfor

Advanced Arrays

Complex array operations:

• Array Features - Array capabilities
• Multi-dimensional Arrays - N-D arrays

Operations

; Advanced indexing
subset = array[where(array gt threshold)]

; Broadcasting
result = array + scalar  ; Broadcasts scalar

; Reshaping
reshaped = reform(array, new_dims)

GIS Support

Geographic Information Systems:

• GIS Setup - GIS configuration

Features:

• Map projections
• Coordinate transformations
• Spatial analysis
• GIS data formats

Nested Functions

Advanced function features:

• Nested Functions Plan - Implementation

; Nested function definitions
function outer, x
  function inner, y
    return, y * 2
  end
  return, inner(x) + 1
end

Performance Optimization

Tips for high-performance XDL code:

• Use GPU acceleration for large arrays
• Vectorize operations instead of loops
• Pre-allocate arrays when possible
• Use appropriate data types
• Profile your code

See GPU Performance for GPU optimization tips.