zoomy-plotting

Publication-ready plotting for Zoomy simulation outputs, with first-class support for 1D/2D/3D meshes and very large timeline datasets.

Why

• Lazy: an HDF5 file with hundreds of snapshots opens cheaply. Only the cells needed for the current plot are read from disk.
• Class-based, one store per session. Pass the store once to a MatplotlibPlotter; plot methods take only (ax, time_step, field, ...).
• Config-driven styling. Every color, linewidth, colormap, and marker size lives in zoomy_plotting.CONFIG. No visual parameter is hardcoded inside the plot functions.
• One API across dimensions. plot_1d / plot_2d / plot_3d share the same signature modulo the 3D viewpoint.

Quick start

import zoomy_plotting as zp
import matplotlib.pyplot as plt

store = zp.read_hdf5("simulation.h5")          # reads metadata only
plotter = zp.MatplotlibPlotter(store)

with zp.apply_style():
    fig, ax = plt.subplots()
    plotter.plot_1d(ax, time_step=0, field=store.field.h)
    plt.show()

store.close()

Field references

All three forms resolve to the same integer index:

plotter.plot_2d(ax, time_step=0, field=store.field.h)   # attribute on Zstruct
plotter.plot_2d(ax, time_step=0, field="h")             # string lookup
plotter.plot_2d(ax, time_step=0, field=0)               # raw index

Styling

Three ways to restyle:

# 1. per-call kwarg override
plotter.plot_2d(ax, time_step=0, field="h", cmap="plasma")

# 2. mutate the singleton config for the rest of the session
zp.CONFIG.cmap = "plasma"
zp.CONFIG.mesh_edgecolor = "gray"

# 3. context manager that reverts on exit
with zp.apply_style(cmap="plasma", mesh_edgecolor="gray"):
    plotter.plot_2d(ax, time_step=0, field="h")

Install

pip install -e .[testing]       # for tests
pip install -e .[plotly]        # optional plotly backend (future PR)
pip install -e .[pyvista]       # optional pyvista backend (future PR)