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gnn_tracking.utils.plotting

gnn_tracking.utils.plotting#

Module Contents#

Classes#

EventPlotter

PointCloudPlotter

GraphPlotter

Plotter for graph data.

Functions#

plot_rz(X, idxs, y[, savefig, filename])

plot_3d(X, idxs, y)

class gnn_tracking.utils.plotting.EventPlotter(indir: str | os.PathLike)#
calc_eta(r, z)#
append_coordinates(hits: pandas.DataFrame, truth: pandas.DataFrame, particles: pandas.DataFrame) → pandas.DataFrame#
get_hits(evtid=None)#
plot_ep_rv_uv(evtid=None, savefig=False, filename='')#
class gnn_tracking.utils.plotting.PointCloudPlotter(indir: str | os.PathLike, n_sectors=64)#
plot_ep_rv_uv(i: int, sector: str, axs: Sequence[matplotlib.pyplot.Axes], display=True, pixel_only=False)#
plot_ep_rv_uv_all_sectors(evtid: int, savefig=False, filename='', pixel_only=False)#
plot_ep_rv_uv_with_boundary(evtid: int, sector: int, di, ds, ulim_low=0, ulim_high=0.035, vlim_low=-0.004, vlim_high=0.004, savefig=False, filename='', pixel_only=False)#
class gnn_tracking.utils.plotting.GraphPlotter(indir: str | os.PathLike = '', n_sectors=64)#

Plotter for graph data.

Parameters:

  • indir – Input directory with graphs (if loading by name)

  • n_sectors

configure_plt(style='seaborn-paper')#
plot_ep_rz_uv(*, graph: torch_geometric.data.Data, sector: int, name: str = '', filename='')#
Parameters:

  • graph

  • sector

  • name – If graph is not specified, load from self.indir / name.

  • filename – If specified, save figure to file

Returns:

plot_2d(X, y, edge_index, name='', ax=None, x1_label='', x2_label='', single_particle=False)#
plot_rz(graph: torch_geometric.data.Data, name='', scale=None, savefig=False, filename='', ax=None)#
gnn_tracking.utils.plotting.plot_rz(X, idxs, y, savefig=False, filename='rz.png')#
gnn_tracking.utils.plotting.plot_3d(X, idxs, y)#
Contents