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Visualization API Reference

Complete API reference for meteaudata's visualization capabilities.

Plotting Methods

Interactive Plotly-based plotting for time series data:

Display System

Rich metadata exploration and visualization:

Overview

Plotting System

meteaudata provides three main plotting classes:

  1. TimeSeries.plot() - Plot individual time series with automatic styling based on processing type
  2. Signal.plot() - Plot multiple time series from a signal, with dependency graph visualization
  3. Dataset.plot() - Plot multiple signals using subplots for comparison

All plotting methods return Plotly Figure objects that can be customized further.

Display System

All meteaudata objects inherit rich display capabilities:

  • Text Display - Simple text representation with configurable depth
  • HTML Display - Rich HTML with collapsible sections (Jupyter notebooks)
  • Graph Display - Interactive SVG visualization of metadata structure
  • Browser Display - Full-page interactive exploration

Key Features

Automatic Styling: - Processing type-specific markers and modes - Temporal shifting for prediction data - Color cycling for multiple series

Interactivity: - Plotly-based interactive charts - Zoom, pan, and hover capabilities - Exportable to HTML, PNG, PDF

Metadata Integration: - Processing history visualization - Dependency graph generation - Complete audit trail display

Common Parameters

Plotting Parameters

Most plotting methods accept these common parameters:

Parameter Type Description
title str Plot title
x_axis str X-axis label
y_axis str Y-axis label
start str Start date for filtering
end str End date for filtering

Display Parameters

Display methods commonly accept:

Parameter Type Description
format str Output format: 'text', 'html', 'graph'
depth int Display depth for text/HTML
max_depth int Maximum depth for graph display
width int Graph width in pixels
height int Graph height in pixels