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API Reference

Complete technical reference documentation for AeroViz, a comprehensive Python package for aerosol data processing, analysis, and visualization.

About AeroViz API

AeroViz provides a unified interface for working with aerosol measurement data from multiple instrument types. The API is designed for scientific research applications with emphasis on data quality, reproducibility, and ease of use.

Core Components

Data Input and Processing

RawDataReader
Primary interface for reading and standardizing aerosol instrument data with automatic format detection.

Measurement Instrument Support

AeroViz provides native support for the following categories of aerosol instruments:

Black Carbon and Light Absorption

  • AE33 - Magee Scientific AE33 7-wavelength aethalometer
  • AE43 - Magee Scientific AE43 real-time measurements
  • BC1054 - MetOne BC1054 high-resolution absorption
  • MA350 - AethLabs MA350 multi-angle photometer

Light Scattering Measurements

  • Aurora - Ecotech Aurora 3-wavelength nephelometer
  • NEPH - TSI nephelometer standard processing

Particle Size Distribution

  • SMPS - Scanning Mobility Particle Sizer (10-600 nm)
  • APS - Aerodynamic Particle Sizer (0.5-20 μm)
  • GRIMM - GRIMM Aerosol Spectrometer optical sizing

Chemical Composition Analysis

  • IGAC - Ion chromatography for water-soluble species
  • OCEC - Organic and elemental carbon analysis
  • VOC - Volatile organic compounds monitoring
  • XRF - X-ray fluorescence elemental analysis
  • TEOM - Tapered Element Oscillating Microbalance

Data Processing and Analysis

DataProcess
Advanced data processing engine providing statistical analysis, time series operations, and data transformation capabilities.

Visualization and Plotting

Plot API
Professional-grade plotting interface optimized for scientific publications with publication-ready defaults.

Available Plot Types

  • Scatter Plots - Correlation analysis with statistical regression
  • Regression Analysis - Statistical relationship modeling and fitting
  • Box Plots - Statistical distribution summaries and outlier detection
  • Bar Charts - Categorical data visualization and comparison
  • Violin Plots - Distribution shape analysis and comparison
  • Pie Charts - Proportional data representation

Getting Started

New Users

Begin with the RawDataReader for data input, understand Quality Control procedures, then explore basic plotting capabilities.

Advanced Users

Leverage DataProcess for complex workflows, consult instrument-specific documentation for detailed configurations, and utilize advanced plotting features for publication-quality figures.

Developers

Review the AbstractReader architecture for understanding the framework design, examine existing instrument implementations as templates, and study plotting modules for extending visualization capabilities.

Documentation Standards

API Documentation Convention

All AeroViz API documentation follows NumPy docstring standards and includes:

  • Parameters - Complete parameter descriptions with data types
  • Returns - Detailed return value specifications and formats
  • Examples - Working code examples with expected outputs
  • Notes - Implementation details, limitations, and best practices
  • References - Scientific literature and technical specifications