Module traceon.plotting
The traceon.plotting module uses the vedo plotting library to provide some convenience functions
to show the line and triangle meshes generated by Traceon.
To show a mesh, for example use:
plt.new_figure()
plt.plot_mesh(mesh)
plt.show()
Where mesh is created using the traceon.geometry module.
Functions
def get_current_figure() ‑> Figure-
Get the currently active figure. If no figure has been created yet a new figure will be returned.
Returns
def new_figure(show_legend=True)-
Create a new figure and make it the current figure.
Parameters
show_legend:bool- Whether to show the legend in the corner of the figure
Returns
def plot_charge_density(*args, **kwargs)-
Calls
Figure.plot_charge_density()on the currentFigure def plot_equipotential_lines(*args, **kwargs)-
Calls
Figure.plot_equipotential_lines()on the currentFigure def plot_mesh(*args, **kwargs)-
Calls
Figure.plot_mesh()on the currentFigure def plot_trajectories(*args, **kwargs)-
Calls
Figure.plot_trajectories()on the currentFigure def show()-
Calls
Figure.show()on the currentFigure
Classes
class Figure (show_legend=True)-
Expand source code
class Figure: def __init__(self, show_legend=True): self.show_legend = show_legend self.is_2d = True self.legend_entries = [] self.to_plot = [] def plot_mesh(self, mesh, show_normals=False, **colors): """Plot mesh using the Vedo library. Optionally showing normal vectors. Parameters --------------------- mesh: `traceon.mesher.Mesh` The mesh to plot show_normals: bool Whether to show the normal vectors at every element colors: dict of (string, string) Use keyword arguments to specify colors, for example `plot_mesh(mesh, lens='blue', ground='green')` """ if not len(mesh.triangles) and not len(mesh.lines): raise RuntimeError("Trying to plot empty mesh.") triangle_normals, line_normals = None, None if len(mesh.triangles): meshes, triangle_normals = _get_vedo_triangles_and_normals(mesh, **colors) self.legend_entries.extend(meshes) self.to_plot.append(meshes) if len(mesh.lines): lines, line_normals = _get_vedo_lines_and_normals(mesh, **colors) self.legend_entries.extend(lines) self.to_plot.append(lines) if show_normals: if triangle_normals is not None: self.to_plot.append(triangle_normals) if line_normals is not None: self.to_plot.append(line_normals) self.is_2d &= mesh.is_2d() def plot_equipotential_lines(self, field, surface, N0=75, N1=75, color_map='coolwarm', N_isolines=40, isolines_width=1, isolines_color='#444444'): """Make potential color plot including equipotential lines. Parameters ------------------------------------- field: `traceon.solver.Field` The field used to compute the potential values (note that any field returned from the solver can be used) surface: `traceon.geometry.Surface` The surface in 3D space which will be 'colored in' N0: int Number of pixels to use along the first 'axis' of the surface N1: int Number of pixels to use along the second 'axis' of the surface color_map: str Color map to use to color in the surface N_isolines: int Number of equipotential lines to plot isolines_width: int The width to use for the isolines. Pass in 0 to disable the isolines. isolines_color: str Color to use for the isolines""" grid = _get_vedo_grid(field, surface, N0, N1) isolines = grid.isolines(n=N_isolines).color(isolines_color).lw(isolines_width) # type: ignore grid.cmap(color_map) self.to_plot.append(grid) self.to_plot.append(isolines) def plot_trajectories(self, trajectories, xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, color='#00AA00', line_width=1): """Plot particle trajectories. Parameters ------------------------------------ trajectories: list of numpy.ndarray List of positions as returned by `traceon.tracing.Tracer.__call__` xmin, xmax: float Only plot trajectory points for which xmin <= x <= xmax ymin, ymax: float Only plot trajectory points for which ymin <= y <= ymax zmin, zmax: float Only plot trajectory points for which zmin <= z <= zmax color: str Color to use for the particle trajectories line_width: int Width of the trajectory lines """ for t in trajectories: if not len(t): continue mask = np.full(len(t), True) if xmin is not None: mask &= t[:, 0] >= xmin if xmax is not None: mask &= t[:, 0] <= xmax if ymin is not None: mask &= t[:, 1] >= ymin if ymax is not None: mask &= t[:, 1] <= ymax if zmin is not None: mask &= t[:, 2] >= zmin if zmax is not None: mask &= t[:, 2] <= zmax t = t[mask] if not len(t): continue lines = vedo.shapes.Lines(start_pts=t[:-1, :3], end_pts=t[1:, :3], c=color, lw=line_width) self.to_plot.append(lines) def plot_charge_density(self, excitation, field, color_map='coolwarm'): """Plot charge density using the Vedo library. Parameters --------------------- excitation: `traceon.excitation.Excitation` Excitation applied field: `traceon.solver.FieldBEM` Field that resulted after solving for the applied excitation color_map: str Name of the color map to use to color the charge density values """ mesh = excitation.mesh if not len(mesh.triangles) and not len(mesh.lines): raise RuntimeError("Trying to plot empty mesh.") if len(mesh.triangles): meshes = _get_vedo_charge_density_3d(excitation, field, color_map) self.to_plot.append(meshes) if len(mesh.lines): lines = _get_vedo_charge_density_2d(excitation, field, color_map) self.to_plot.append(lines) self.is_2d &= mesh.is_2d() def show(self): """Show the figure.""" plotter = vedo.Plotter() for t in self.to_plot: plotter += t if self.show_legend: lb = vedo.LegendBox(self.legend_entries) plotter += lb if self.is_2d: plotter.add_global_axes(dict(number_of_divisions=[12, 0, 12], zxgrid=True, xaxis_rotation=90)) else: plotter.add_global_axes(dict(number_of_divisions=[10, 10, 10])) plotter.look_at(plane='xz') plotter.show()Methods
def plot_charge_density(self, excitation, field, color_map='coolwarm')-
Plot charge density using the Vedo library.
Parameters
excitation:Excitation- Excitation applied
field:FieldBEM- Field that resulted after solving for the applied excitation
color_map:str- Name of the color map to use to color the charge density values
def plot_equipotential_lines(self, field, surface, N0=75, N1=75, color_map='coolwarm', N_isolines=40, isolines_width=1, isolines_color='#444444')-
Make potential color plot including equipotential lines.
Parameters
field:Field- The field used to compute the potential values (note that any field returned from the solver can be used)
surface:Surface- The surface in 3D space which will be 'colored in'
N0:int- Number of pixels to use along the first 'axis' of the surface
N1:int- Number of pixels to use along the second 'axis' of the surface
color_map:str- Color map to use to color in the surface
N_isolines:int- Number of equipotential lines to plot
isolines_width:int- The width to use for the isolines. Pass in 0 to disable the isolines.
isolines_color:str- Color to use for the isolines
def plot_mesh(self, mesh, show_normals=False, **colors)-
Plot mesh using the Vedo library. Optionally showing normal vectors.
Parameters
mesh:Mesh- The mesh to plot
show_normals:bool- Whether to show the normal vectors at every element
colors:dictof(string, string)- Use keyword arguments to specify colors, for example
plot_mesh(mesh, lens='blue', ground='green')
def plot_trajectories(self, trajectories, xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, color='#00AA00', line_width=1)-
Plot particle trajectories.
Parameters
trajectories:listofnumpy.ndarray- List of positions as returned by
Tracer.__call__() xmin,xmax:float- Only plot trajectory points for which xmin <= x <= xmax
ymin,ymax:float- Only plot trajectory points for which ymin <= y <= ymax
zmin,zmax:float- Only plot trajectory points for which zmin <= z <= zmax
color:str- Color to use for the particle trajectories
line_width:int- Width of the trajectory lines
def show(self)-
Show the figure.