2D Pseudocolor Contourf Plotting

Problem

Scientific datasets are often 2D gridded fields, such as concentration, temperature, or flux over longitude and latitude. Direct contourf plots can have poor colorbars, log-scale failures from negative values, mixed land/invalid cells, and axes that are not publication-ready. This skill turns those repetitive formatting steps into a consistent workflow.

How It Works

The skill renders 2D pseudocolor maps with Matplotlib, using contourf or pcolormesh. Key capabilities:
- Colorbar control: supports log / linear levels, with log10 as the default or user-defined levels.
- Colormaps: uses built-in maps or custom segmented color definitions for journal styling.
- Masking: renders mask_value, NaN, or inf regions as a uniform background color.
- Coordinate formatting: optionally labels coordinates as °E / °N and normalizes axis labels, titles, and ticks.
- Output: produces high-resolution figures and supports PNG or PDF export.

Boundaries

Inputs x and y must form a regular grid, and z should have shape (len(y), len(x)). The skill plots Cartesian coordinates only; it does not perform map projection, coastline overlay, or geographic basemaps. In log mode, non-positive values are clipped or masked; for extremely large dynamic ranges, manual levels are recommended. It fits 2D field visualization such as concentration or temperature fields.