HPCSeries Core

User Guide

  • Installation
    • Requirements
      • System Requirements
    • Installation Methods
      • Via pip (Recommended)
      • From Source
      • Development Installation
      • Using Docker
    • Verification
      • CPU Information
    • Performance Calibration
    • Troubleshooting
      • Import Error: No module named ‘hpcs’
      • Compilation Errors
      • Performance Issues
    • Getting Help
  • Quick Start Guide
    • Basic Usage
      • Import and Simple Operations
      • Performance Comparison
    • Rolling Operations
      • Fast Sliding Window Computations
    • Anomaly Detection
      • Statistical Anomaly Detection
      • Robust Anomaly Detection
    • Robust Statistics
      • Median and MAD
    • 2D Array Operations
      • Axis Reductions
    • Masked Operations
      • Handling Missing Data
    • SIMD Information
      • Query CPU Capabilities
    • Performance Optimization
      • Calibration
      • Best Practices
    • Next Steps
    • Common Patterns
      • Time Series Analysis
      • Sensor Data Processing
      • Financial Data Analysis
  • User Guide
    • Architecture
      • HPCSeries Core v0.7 — Logical Architecture
      • Architectural Intent
      • High-Level Layer Stack
      • Fortran Kernel Subsystems
        • Foundational Layer
        • 1D Time-Series Kernels
        • Robust Statistics Layer
        • Masked Operations Layer
        • 2D & Axis-Aware Kernels
        • Anomaly Detection Layer
      • Parallel & Vectorized Execution
        • SIMD (v0.6+)
        • OpenMP
      • C++ Fast-Path Kernels
      • Stable C ABI Layer
      • Python Binding Layer (v0.7)
      • What HPCSeries Core IS (and Is Not)
        • It IS
        • It is NOT
      • Architectural Stability
      • Design Decisions
        • Why Hybrid Fortran/C/C++?
        • Why Runtime SIMD Dispatch?
        • Why Stable C ABI?
        • Why No GPU in v1.x?
      • Zero-Copy Design
      • Thread Safety
      • See Also
    • Performance Guide
      • Performance Characteristics
        • Speedup vs NumPy
        • Latency Characteristics
      • Calibration
        • What is Calibration?
        • What Calibration Determines
      • OpenMP Configuration
        • Thread Count
        • Thread Affinity
        • Scheduling
      • Array Layout Optimization
        • Contiguous Arrays
        • Memory Alignment
        • Data Types
      • Benchmarking
        • Accurate Timing Principles
      • Performance Tips
      • Common Performance Issues
        • Slower Than Expected
        • High Latency for Small Arrays
        • Memory Bandwidth Bottleneck
      • Performance Monitoring
        • CPU Information
      • Expected Performance
        • Reference Benchmarks
        • Scaling Characteristics
      • Advanced Optimization
        • NUMA Awareness
        • Huge Pages
        • Custom Builds
      • Troubleshooting Performance
        • Debug Mode Check
        • SIMD Verification
        • Thread Utilization
      • See Also
    • Migration Guide
      • From NumPy
        • Basic Reductions
        • Quantiles & Median
        • Z-Score Normalization
        • Axis Operations
        • Masked Arrays
      • From Pandas
        • Rolling Operations
        • GroupBy Operations
        • Hybrid Pandas + HPCSeries
        • When to Use Each
      • API Compatibility Matrix
      • Common Migration Patterns
        • Pattern 1: Time Series Analysis
        • Pattern 2: Feature Engineering
        • Pattern 3: Multi-Sensor Processing
      • Migration Checklist
      • Key Differences Summary
        • Return Types
        • NaN Handling
        • Quantile Scale
        • Window Alignment
      • Performance Expectations
      • Migration Strategy
        • Incremental Approach
        • Gradual Migration
      • See Also
    • Architecture Overview
      • Key Design Principles
    • Contents

Examples & Tutorials

  • Examples & Tutorials
    • Getting Started
    • Notebook Catalog
      • 00. Getting Started
      • 01. Rolling Mean vs Rolling Median
      • 02. Robust Anomaly Detection (Climate Data)
      • 03. Batched IoT Rolling Operations
      • 04. Axis Reductions (Column Statistics)
      • 05. Masked Operations (Missing Data)
      • 06. Performance Calibration
      • 07. C-Optimized Operations
      • 08. NumPy/Pandas Migration Guide
      • 09. Real-World Applications
    • Case Studies
      • Kaggle Competition: Store Sales Forecasting
    • Running in the Cloud
      • Google Colab
      • Binder
    • Contributing Notebooks
    • Support
    • Download All Notebooks

API Reference

  • API Reference
    • Core Module
      • HPCSeries Core v0.9 - Python Bindings
      • Basic Reductions
        • hpcs.sum
        • hpcs.mean
        • hpcs.var
        • hpcs.std
        • hpcs.min
        • hpcs.max
      • Robust Statistics
        • hpcs.median
        • hpcs.mad
        • hpcs.quantile
      • Execution Mode API (v0.8)
        • hpcs.set_execution_mode
        • hpcs.get_execution_mode
        • hpcs.MODE_SAFE
        • hpcs.MODE_FAST
        • hpcs.MODE_DETERMINISTIC
      • Exponential Weighted Statistics (v0.8)
        • hpcs.ewma
        • hpcs.ewvar
        • hpcs.ewstd
      • Time Series Transforms (v0.8)
        • hpcs.diff
        • hpcs.cumulative_min
        • hpcs.cumulative_max
        • hpcs.convolve_valid
      • Advanced Robust Statistics (v0.8)
        • hpcs.trimmed_mean
        • hpcs.winsorized_mean
      • Transforms & Normalization
        • hpcs.zscore
        • hpcs.robust_zscore
        • hpcs.normalize_minmax
        • hpcs.clip
      • Anomaly Detection
        • hpcs.detect_anomalies
        • hpcs.detect_anomalies_robust
      • Rolling Operations
        • hpcs.rolling_sum
        • hpcs.rolling_mean
        • hpcs.rolling_std
        • hpcs.rolling_var
        • hpcs.rolling_median
        • hpcs.rolling_mad
        • hpcs.rolling_zscore
        • hpcs.rolling_robust_zscore
      • Axis Operations
        • hpcs.axis_sum
        • hpcs.axis_mean
        • hpcs.axis_median
        • hpcs.axis_mad
        • hpcs.axis_min
        • hpcs.axis_max
        • hpcs.anomaly_axis
        • hpcs.anomaly_robust_axis
      • Masked Operations
        • hpcs.sum_masked
        • hpcs.mean_masked
        • hpcs.var_masked
        • hpcs.median_masked
        • hpcs.mad_masked
        • hpcs.rolling_mean_masked
        • hpcs.rolling_mean_batched
      • SIMD & CPU Information
        • hpcs.simd_info
        • hpcs.get_simd_width
        • hpcs.get_cpu_info
      • Calibration
        • hpcs.calibrate
        • hpcs.save_calibration_config
        • hpcs.load_calibration_config
    • Detailed API
      • sum()
      • mean()
      • std()
      • var()
      • min()
      • max()
      • median()
      • mad()
      • quantile()
      • zscore()
      • robust_zscore()
      • normalize_minmax()
      • clip()
      • detect_anomalies()
      • detect_anomalies_robust()
      • rolling_sum()
      • rolling_mean()
      • rolling_std()
      • rolling_var()
      • rolling_median()
      • rolling_mad()
      • rolling_zscore()
      • rolling_robust_zscore()
      • axis_sum()
      • axis_mean()
      • axis_median()
      • axis_mad()
      • axis_min()
      • axis_max()
      • anomaly_axis()
      • anomaly_robust_axis()
      • sum_masked()
      • mean_masked()
      • var_masked()
      • median_masked()
      • mad_masked()
      • rolling_mean_masked()
      • rolling_mean_batched()
      • simd_info()
      • get_simd_width()
      • get_cpu_info()
      • calibrate()
      • save_calibration_config()
      • load_calibration_config()
      • set_execution_mode()
      • get_execution_mode()
      • hpcs.MODE_SAFE
      • hpcs.MODE_FAST
      • hpcs.MODE_DETERMINISTIC
      • ewma()
      • ewvar()
      • ewstd()
      • diff()
      • cumulative_min()
      • cumulative_max()
      • convolve_valid()
      • trimmed_mean()
      • winsorized_mean()

Development

  • Contributing
    • Development Setup
    • Running Tests
    • Code Style
    • Documentation
    • Pull Request Process
      • Commit Messages
    • Areas for Contribution
      • High Priority
      • Good First Issues
    • Contact
  • Changelog
    • Version 0.8.0 (2025-01-06)
      • Major Features
    • Version 0.7.0 (2025-12-17)
      • Major Features
      • Performance
      • Documentation
    • Version 0.6.0 (2024-12-01)
      • Features
    • Version 0.5.0 (2024-11-01)
      • Features
    • Version 0.4.0 (2024-10-01)
      • Features
    • Version 0.3.0 (2024-09-01)
      • Features
    • Version 0.2.0 (2024-08-01)
      • Features
    • Version 0.1.0 (2024-07-01)
      • Initial Release
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