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User Guide

Welcome to AeroViz! This guide will help you get started quickly.

Installation

Using pip

pip install AeroViz

Install from Source

git clone https://github.com/alex870521/AeroViz.git
cd AeroViz
pip install -e .

Dependencies

AeroViz requires Python 3.10+ and the following main dependencies:

  • numpy, pandas, scipy
  • matplotlib
  • xarray (optional, for NetCDF)

Quick Start

1. Reading Data

from datetime import datetime
from pathlib import Path
from AeroViz import RawDataReader

# Read AE33 black carbon data
data = RawDataReader(
    instrument='AE33',
    path=Path('/path/to/data'),
    start=datetime(2024, 1, 1),
    end=datetime(2024, 12, 31),
    mean_freq='1h'
)

# View data
print(data.head())
print(data.columns)

2. Data Processing

from AeroViz import psd_stats, reconstruct_mass

# Size distribution processing
result = psd_stats(df_pnsd)

# Chemical composition processing
result = reconstruct_mass(df_chem)

3. Visualization

from AeroViz import plot

# Time series plot (y = column name or list of columns)
plot.timeseries(data, y='BC')

# Scatter plot (x / y are column names)
plot.scatter(data, x='BC', y='PM25')

Core Concepts

RawDataReader

A unified data reading interface supporting multiple aerosol instruments:

Category Instruments
Black Carbon AE33, AE43, BC1054, MA350
Scattering NEPH, Aurora
Size Distribution SMPS, APS, GRIMM
Chemical IGAC, OCEC, Xact, VOC
Mass TEOM, BAM1020

See RawDataReader Tutorial

Post-Processing Functions

Top-level functions organized into four namespaces:

Namespace Function
size Size distribution processing, merging, conversion
chemistry Mass reconstruction, ion balance, kappa calculation
optical Mie calculation, IMPROVE, RI retrieval
voc OFP, SOAP calculation

See Post-Processing Functions Tutorial

Plot

The visualization module provides various chart types:

  • Basic charts: scatter, bar, box, violin, pie
  • Time analysis: timeseries, timeseries_interactive, diurnal_pattern
  • Advanced charts: contour, corr_matrix, meteorology.wind_rose, meteorology.CBPF

See Visualization Tutorial

Examples

Example Description
Size Distribution Analysis SMPS-APS merging, distribution conversion, statistical calculation
Optical Closure Analysis Mie calculation, IMPROVE, refractive index retrieval
Chemical Composition Analysis Mass reconstruction, ion balance, kappa calculation
VOC Analysis OFP, SOAP calculation

Next Steps