plasma-plots 0.2.5

plasma-plots 0.2.5

Features

• Point sets: plasma_plots.pyvista_plots.pyvista_points(points, ...) draws labelled point
  sets, such as samples, grid nodes or crossings: (n, 3) or component-major (3, n) arrays
  ((n, 2) in the z = 0 plane), a list of them or a dict by label. Each set gets a color from
  Matplotlib's cycle and a legend entry; vectors= adds an arrow at every point, e.g. normals,
  scaled by vector_scale, and scalars= colors the points by a value.
• One legend per scene: pyvista_surfaces and pyvista_points drawn into the same
  plotter= continue one color cycle and share one legend that lists every labelled surface
  and point set.

Documentation

• The 3-D views guide has a "Points and normals" subsection with an interactive scene.
• Per-level isosurface colors and opacity: plot.isosurface (and pyvista_isosurface)
  takes opacity and the new colors as one value or a list with one per level, e.g. an opaque
  surface inside a translucent shell. Explicit colors replace the scalar bar with a legend of
  the levels, named by the new labels. For 2-D fields they apply to the contour lines.

Documentation

plasma-plots 0.2.3

plasma-plots 0.2.3

Features

New modules in plasma_plots.theory, plain numpy and in SI units like theory.parameters:

• sheaths: Bohm speed and current, floating potential (with secondary emission),
  Child–Langmuir space-charge-limited flow (with injection speed), Langmuir–Blodgett flow between
  coaxial cylinders and concentric spheres, Child–Langmuir and matrix sheath widths, OML probe
  currents, ambipolar and Bohm diffusion, Paschen breakdown and mean free paths.
• beams: perveance, the Child–Langmuir current through an aperture, K-V rms envelopes (closed
  form in a drift, RK4 with space charge and focusing), thermal beam divergence, the Pierce angle,
  the Davisson–Calbick aperture lens, beam attenuation and stripping, space-charge compensation
  time, and emittance_growth_space_charge.
• magnetron: the Hull cutoff of planar and coaxial gaps, Brillouin flow, Hall parameter,
  critical ionisation velocity, E×B speed, the Simon–Hoh and gradient-drift modes, and
  lower_hybrid_drift.
• collisions: the NRL Coulomb logarithm and collision frequencies, Spitzer resistivity, the
  Spitzer and Stix slowing down of a fast ion, its critical energy and stopping, the pitch-angle
  evolution of a slowing-down ion, and the shielded beam-driven current.
• negative_ions: cross sections and Maxwellian rate coefficients for the destruction of H⁻
  (electron detachment, mutual neutralization, collisions with H and H₂), the Debye length and Bohm
  speed of an electronegative plasma, H⁻ survival through a gas layer and surface-production
  current.
• equilibria: the Harris current sheet, the Bennett pinch, Solov'ev tokamak equilibria
  (Cerfon–Freidberg shapes), Lundquist force-free fields and the Taylor state. Each is checked
  against its own force balance.
• kinetic.electron_cyclotron_drift: the electron cyclotron drift (modified two-stream)
  dispersion relation for electrons drifting across B, as branches.
• special.bessel_j: Bessel functions of integer order in plain numpy.

Documentation

• The theory guide has figures for the sheath, beam, magnetron and collision modules.
• The new Gallery shows example scripts and the figures they make, including Child–Langmuir
  against Langmuir–Blodgett, Paschen curves, K-V envelopes, fast-ion slowing down, the Hull cutoff
  and gradient-drift growth.

Documentation

plasma-plots 0.2.2

plasma-plots 0.2.2

Features

• Convergence fits on the asymptotic range: plot_convergence and
  array.plasma.plot.convergence(...) take last=n, which fits the order to the last n
  samples only, or, with order, draws the reference slope through the last sample over the
  last n samples. Use it when the coarse resolutions are not yet asymptotic.
• Profiles by category, on log axes: array.plasma.plot.profiles(...) takes logx, logy
  and cmap, and plots a categorical dimension (e.g. species) as one distinctly coloured line
  per category, in both the Matplotlib and Plotly backends. Dimensionless profiles are labeled
  without a unit.

Documentation

• The docs use the shared starlight-theme
  (v0.3.1).

Documentation

plasma-plots 0.2.1

plasma-plots 0.2.1

Features

• Rank boundaries on lineouts: plot_lineout and array.plasma.plot.lineout(...) take
  rank_boundaries (a sequence of coordinate values) and rank_boundary_color (default red),
  drawing dashed vertical lines the same way plot_slice's overlays={"rank_boundaries": ...}
  already did, so a 1-D profile of data split by mpiarray
  can mark its rank boundaries too.
• overlays={"rank_boundaries": ...} takes an mpiarray Layout directly, on plot_slice,
  plot_panels, InteractiveSliceViewer, animate_slices and save_frames: its axis for each
  drawn dimension is found by name among the plotted array's own dimensions (the sweep
  dimension excluded), so the layout needs no dimension names of its own and
  Layout.boundary_values no longer has to be called by hand. A plain {name: values} dict
  still works as before.

Documentation

plasma-plots 0.1.1

plasma-plots 0.1.1

Features

• New backend="tikz": every still plot can be drawn as TikZ/pgfplots code with LaTeX
  text, converted by maxplotlib. Save the
  result as .tikz, .tex or .pdf (compiled with pdflatex); see the
  LaTeX figures guide.
• plasma-plots plot and quicklook pick backend="tikz" for a .tex or .tikz
  output. Animations and Plotly figures have no TikZ version and are reported as errors.

Installation and optional dependencies

Requires Python 3.10+ (was 3.11+); CI covers Python 3.10 to 3.14.

New extra	Purpose
tikz	TikZ/pgfplots figures via maxplotlibx>=0.2.0 (and pdflatex to compile)

tikz cannot yet be installed together with profiling or gallery:
scope-profiler pins maxplotlibx==0.1.9.

Documentation

plasma-plots 0.1.0

plasma-plots 0.1.0

First public release. This is an experimental alpha: APIs and command-line
options may change as the package matures.

Features

• Plot labeled xarray DataArrays and Datasets using .plasma.plot, with
  time series, lineouts, slices, panels, vector fields, spectra and particle orbits.
• Analyze growth/damping rates, frequencies, spectra, moments and spatial averages.
• Integrate with Struphy Output through out.plot and out.analysis, including
  energy diagnostics, equilibrium plots and explicitly requested profiling plots.
• Save Matplotlib figures and animations, display interactive slider viewers,
  use Plotly browser figures, and render optional PyVista 3-D scenes.
• Use plasma-plots info, plot, movie and quicklook from the shell.
  --show displays without requiring -o; use both to display and save.
  Quicklook supports --products and --select and excludes expensive Gantt charts.
• Automatically post-process Struphy runs when needed and reuse existing products.
• Inspect method signatures and examples with plasma-plots help METHOD or
  plasma-plots plot PATH PRODUCT METHOD --help, without processing data.
• Convert GVEC and DESC equilibria into the package's xarray conventions.

Installation and optional dependencies

Requires Python 3.11+; CI covers Python 3.11 and 3.12.

pip install plasma-plots
pip install "plasma-plots[netcdf]"
pip install "plasma-plots[netcdf,plotly]"

The base package needs Matplotlib, NumPy, xarray and ipywidgets.

Extra	Purpose
netcdf	netCDF3/netCDF4 input via netCDF4
plotly	Interactive Plotly figures and Kaleido static exports
pyvista	PyVista 3-D rendering and imageio
profiling	Profiling plots via scope-profiler[pproc]
desc	DESC equilibrium evaluation via desc-opt
gallery	Plotly/Kaleido and scope-profiler gallery exports
dev	pytest, Ruff, h5py and griffe tooling

Install Struphy, GVEC or Zarr separately when using those integrations.
MP4 export needs ffmpeg; GUI rendering needs a working display/backend;
Kaleido static exports need compatible Chrome.

Struphy compatibility

Validated against Struphy commit
caddd229a3fcba1fada577d1af46d012e93d8b49,
which reports version 3.3.0 and is pinned as this repository's submodule.
Use this exact revision to reproduce the tested integration. This is not a
claim of compatibility with every package or revision named 3.3.0.
Struphy is not required to plot ordinary xarray data.

Known limits

• The API is experimental; no long-term compatibility promise is made for 0.1.0.
• Complex derived data, custom Python callbacks and composed figures still belong
  in Python scripts.
• Optional renderers and file backends must be installed separately using the
  extras above; the base package does not install the complete scientific stack.

Documentation