(self, data: Field, figure, subplot, space: Box, min_val: float, max_val: float, show_color_bar: bool, color: Tensor, alpha: Tensor, err: Tensor)
| 593 | return data.spatial_rank == 2 |
| 594 | |
| 595 | def plot(self, data: Field, figure, subplot, space: Box, min_val: float, max_val: float, show_color_bar: bool, color: Tensor, alpha: Tensor, err: Tensor): |
| 596 | dims = space.vector.item_names |
| 597 | vector = data.geometry.shape['vector'] |
| 598 | channels = channel(data.points).without('vector') |
| 599 | legend_patches = [] |
| 600 | # if (color == None).all: |
| 601 | # color = math.range_tensor(channels) |
| 602 | for idx, idx_n in zip(channels.meshgrid(), channels.meshgrid(names=True)): |
| 603 | col = color[idx] |
| 604 | PointCloud2D._plot_points(subplot, data[idx], dims, vector, col, alpha[idx], err[idx], min_val, max_val, index_label(idx_n)) |
| 605 | if col.rank < color.rank or ((color == None).all and channels.volume > 1): # There are multiple colors |
| 606 | legend_patches = True |
| 607 | if legend_patches: |
| 608 | if not has_legend_like([index_label(idx_n) for idx_n in channels.meshgrid(names=True)], figure): |
| 609 | subplot.legend() |
| 610 | |
| 611 | @staticmethod |
| 612 | def _plot_points(axis: Axes, data: Field, dims: tuple, vector: Shape, color: Tensor, alpha: Tensor, err: Tensor, min_val, max_val, label): |
nothing calls this directly
no test coverage detected