desc.plotting.plot_section

desc.plotting.plot_section(eq, name, grid=None, log=False, norm_F=False, ax=None, return_data=False, **kwargs)[source]

Plot Poincare sections.

Parameters:

eq (Equilibrium) – Object from which to plot.
name (str) – Name of variable to plot.
grid (Grid, optional) – Grid of coordinates to plot at.
log (bool, optional) – Whether to use a log scale.
norm_F (bool, optional) – Whether to normalize a plot of force error to be unitless. Vacuum equilibria are normalized by the gradient of magnetic pressure, while finite beta equilibria are normalized by the pressure gradient.
ax (matplotlib AxesSubplot, optional) – Axis to plot on.
return_data (bool) – if True, return the data plotted as well as fig,ax
**kwargs (fig,ax and plotting properties) –
Specify properties of the figure, axis, and plot appearance e.g.:
```
plot_X(figsize=(4,6),label="your_label")
```
Valid keyword arguments are:

figsize: tuple of length 2, the size of the figure (to be passed to matplotlib) component: str, one of [None, ‘R’, ‘phi’, ‘Z’], For vector variables, which

element to plot. Default is the norm of the vector.

cmap: str, matplotib colormap scheme to use, passed to ax.contourf levels: int or array-like, passed to contourf nzeta: int, number of equispaced zeta planes to plot sections at (default 1

for axisymmetry and 6 for non-axisymmetry)

title_font_size: integer, font size of the title xlabel_fontsize: float, fontsize of the xlabel ylabel_fontsize: float, fontsize of the ylabel

Returns:

fig (matplotlib.figure.Figure) – Figure being plotted to.
ax (matplotlib.axes.Axes or ndarray of Axes) – Axes being plotted to.
plot_data (dict) – dictionary of the data plotted only returned if return_data=True plot_data keys:

”R”,”Z” cylindrical coordinates key of the name of variable plotted “normalization”: normalization used in the plot,

if norm_F=False or F is not plotted, this is just equal to 1.

Examples

from desc.plotting import plot_section
fig, ax = plot_section(eq, "J^rho")