SWW Plotter

SWW_plotter provides a Python interface for visualising ANUGA simulation output files (.sww format). It loads the full time series from the SWW file into memory so any frame can be plotted or saved without re-running the simulation.

For plotting during a running simulation, use Domain Plotter instead.

Features

Plot and animate results from ANUGA SWW files: depth, stage, speed.
Configurable colourmap, transparency, and optional OpenStreetMap basemap.
Compute water volumes and cross-section flows from stored results.

Basic usage

# Run this code in a Jupyter notebook environment
import anuga
import matplotlib.pyplot as plt

# Allow inline jshtml animations in Jupyter notebooks
%matplotlib inline
from matplotlib import rc
rc('animation', html='jshtml')

# Create SWW plotter object by opening an SWW file
splotter = anuga.SWW_plotter('domain.sww')

# Find min and max depth for plotting
vmin = splotter.depth.min()
vmax = splotter.depth.max()

# Plot depth at last frame
splotter.plot_depth_frame(-1, vmin=vmin, vmax=vmax)

# Plot speed at second frame, collect fig, ax and change title
fig, ax = splotter.plot_speed_frame(1)
ax.set_title('Speed at second frame')

# Plot mesh
splotter.plot_mesh()

# Save depth frames for all time steps
for frame in range(len(splotter.time)):
    print(f'Processing frame {frame+1} of {len(splotter.time)}')
    splotter.save_depth_frame(frame, vmin=vmin, vmax=vmax)

# Assemble saved frames into an animation
anim = splotter.make_depth_animation()

# Save animation to file
anim.save('depth_animation.mp4', writer='ffmpeg', fps=5)

# Display inline in Jupyter
anim

# Calculate water volume over entire domain
volume = splotter.water_volume()
print('Water volume at each time step:', volume)

# Calculate flow through a polyline
polyline = [[759195.0, 5912922.0],
            [759250.0, 5912892.0]]
flow = splotter.get_flow_through_cross_section(polyline)
print('Flow through cross section at each time step:', flow)

Visualisation options

All plot_* and save_* frame methods accept these optional keyword arguments in addition to frame, figsize, dpi, vmin, and vmax:

Argument	Default	Description
`cmap`	`'viridis'`	Any matplotlib colormap name, e.g. `'plasma'`, `'Blues'`, `'jet'`.
`basemap`	`False`	If `True`, overlay a tile basemap behind the quantity plot. Requires the `contextily` package and the SWW file to contain a valid EPSG code. Dry cells are left transparent so the map shows through.
`basemap_provider`	`'OpenStreetMap.Mapnik'`	Dot-notation provider string. Any key from `anuga.utilities.animate.BASEMAP_PROVIDERS` is accepted, or any `contextily` provider path. Useful alternatives: `'Esri.WorldImagery'` (satellite), `'Esri.WorldShadedRelief'` (hillshade), `'Esri.WorldTopoMap'` (topographic), `'OpenTopoMap'` (OSM-based topo), `'CartoDB.Positron'` (light minimal).
`alpha`	`1.0`	Opacity of the wet-area colour layer (0 = fully transparent, 1 = fully opaque). Values around `0.6` work well when `basemap=True` so the underlying map remains visible.

Example: custom colormap

splotter = anuga.SWW_plotter('domain.sww')
vmax = splotter.depth.max()

for frame in range(len(splotter.time)):
    splotter.save_depth_frame(frame, vmin=0.0, vmax=vmax, cmap='plasma')

anim = splotter.make_depth_animation()

Example: OSM basemap

When the SWW file was produced from a georeferenced domain (i.e. it stores an EPSG code), an OpenStreetMap basemap can be composited automatically. Install contextily first:

conda install contextily
# or
pip install contextily

splotter = anuga.SWW_plotter('domain.sww')
vmax = splotter.depth.max()

for frame in range(len(splotter.time)):
    splotter.save_depth_frame(frame, vmin=0.0, vmax=vmax,
                              basemap=True, alpha=0.6, cmap='Blues')

anim = splotter.make_depth_animation()

If contextily is not installed, or the SWW file has no EPSG code, a warning is issued and the basemap is skipped — the frames are still generated without it.

See Also

SWW_plotter([swwfile, plot_dir, min_depth, ...])

A class to wrap ANUGA swwfile centroid values for stage, height, elevation xmomentum and ymomentum, and triangulation information.