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render_shapes now respects the cmap parameter #436

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Merged
merged 5 commits into from
Apr 22, 2025
Merged

render_shapes now respects the cmap parameter #436

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ea2aa78
cmap works
timtreis Mar 27, 2025
0eddc52
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Mar 27, 2025
216c4b2
added tests
timtreis Mar 27, 2025
383681e
merge
timtreis Mar 27, 2025
faddcd7
fixed hex color bug, added images from runner
timtreis Mar 27, 2025
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107 changes: 87 additions & 20 deletions src/spatialdata_plot/pl/render.py
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Original file line number Diff line number Diff line change
Expand Up @@ -45,6 +45,7 @@
_get_extent_and_range_for_datashader_canvas,
_get_linear_colormap,
_get_transformation_matrix_for_datashader,
_hex_no_alpha,
_is_coercable_to_float,
_map_color_seg,
_maybe_set_colors,
Expand Down Expand Up @@ -191,7 +192,10 @@ def _render_shapes(
lambda x: (np.hstack([x, np.ones((x.shape[0], 1))]) @ tm)[:, :2]
)
transformed_element = ShapesModel.parse(
gpd.GeoDataFrame(data=sdata_filt.shapes[element].drop("geometry", axis=1), geometry=transformed_element)
gpd.GeoDataFrame(
data=sdata_filt.shapes[element].drop("geometry", axis=1),
geometry=transformed_element,
)
)

plot_width, plot_height, x_ext, y_ext, factor = _get_extent_and_range_for_datashader_canvas(
Expand All @@ -208,15 +212,23 @@ def _render_shapes(
aggregate_with_reduction = None
if col_for_color is not None and (render_params.groups is None or len(render_params.groups) > 1):
if color_by_categorical:
agg = cvs.polygons(transformed_element, geometry="geometry", agg=ds.by(col_for_color, ds.count()))
agg = cvs.polygons(
transformed_element,
geometry="geometry",
agg=ds.by(col_for_color, ds.count()),
)
else:
reduction_name = render_params.ds_reduction if render_params.ds_reduction is not None else "mean"
logger.info(
f'Using the datashader reduction "{reduction_name}". "max" will give an output very close '
"to the matplotlib result."
)
agg = _datashader_aggregate_with_function(
render_params.ds_reduction, cvs, transformed_element, col_for_color, "shapes"
render_params.ds_reduction,
cvs,
transformed_element,
col_for_color,
"shapes",
)
# save min and max values for drawing the colorbar
aggregate_with_reduction = (agg.min(), agg.max())
Expand Down Expand Up @@ -246,7 +258,7 @@ def _render_shapes(
agg = agg.where((agg != norm.vmin) | (np.isnan(agg)), other=0.5)

color_key = (
[x[:-2] for x in color_vector.categories.values]
[_hex_no_alpha(x) for x in color_vector.categories.values]
if (type(color_vector) is pd.core.arrays.categorical.Categorical)
and (len(color_vector.categories.values) > 1)
else None
Expand All @@ -257,7 +269,7 @@ def _render_shapes(
if color_vector is not None:
ds_cmap = color_vector[0]
if isinstance(ds_cmap, str) and ds_cmap[0] == "#":
ds_cmap = ds_cmap[:-2]
ds_cmap = _hex_no_alpha(ds_cmap)

ds_result = _datashader_map_aggregate_to_color(
agg,
Expand All @@ -272,7 +284,10 @@ def _render_shapes(
# else: all elements would get alpha=0 and the color bar would have a weird range
if aggregate_with_reduction[0] == aggregate_with_reduction[1]:
ds_cmap = matplotlib.colors.to_hex(render_params.cmap_params.cmap(0.0), keep_alpha=False)
aggregate_with_reduction = (aggregate_with_reduction[0], aggregate_with_reduction[0] + 1)
aggregate_with_reduction = (
aggregate_with_reduction[0],
aggregate_with_reduction[0] + 1,
)

ds_result = _datashader_map_aggregate_to_color(
agg,
Expand Down Expand Up @@ -468,7 +483,9 @@ def _render_points(
# we construct an anndata to hack the plotting functions
if table_name is None:
adata = AnnData(
X=points[["x", "y"]].values, obs=points[coords].reset_index(), dtype=points[["x", "y"]].values.dtype
X=points[["x", "y"]].values,
obs=points[coords].reset_index(),
dtype=points[["x", "y"]].values.dtype,
)
else:
adata_obs = sdata_filt[table_name].obs
Expand Down Expand Up @@ -496,7 +513,9 @@ def _render_points(
sdata_filt.points[element] = PointsModel.parse(points, coordinates={"x": "x", "y": "y"})
# restore transformation in coordinate system of interest
set_transformation(
element=sdata_filt.points[element], transformation=transformation_in_cs, to_coordinate_system=coordinate_system
element=sdata_filt.points[element],
transformation=transformation_in_cs,
to_coordinate_system=coordinate_system,
)

if col_for_color is not None:
Expand Down Expand Up @@ -586,7 +605,11 @@ def _render_points(
"to the matplotlib result."
)
agg = _datashader_aggregate_with_function(
render_params.ds_reduction, cvs, transformed_element, col_for_color, "points"
render_params.ds_reduction,
cvs,
transformed_element,
col_for_color,
"points",
)
# save min and max values for drawing the colorbar
aggregate_with_reduction = (agg.min(), agg.max())
Expand Down Expand Up @@ -642,7 +665,10 @@ def _render_points(
# else: all elements would get alpha=0 and the color bar would have a weird range
if aggregate_with_reduction[0] == aggregate_with_reduction[1] and (ds_span is None or ds_span != [0, 1]):
ds_cmap = matplotlib.colors.to_hex(render_params.cmap_params.cmap(0.0), keep_alpha=False)
aggregate_with_reduction = (aggregate_with_reduction[0], aggregate_with_reduction[0] + 1)
aggregate_with_reduction = (
aggregate_with_reduction[0],
aggregate_with_reduction[0] + 1,
)

ds_result = _datashader_map_aggregate_to_color(
agg,
Expand Down Expand Up @@ -805,7 +831,12 @@ def _render_images(

# norm needs to be passed directly to ax.imshow(). If we normalize before, that method would always clip.
_ax_show_and_transform(
layer, trans_data, ax, cmap=cmap, zorder=render_params.zorder, norm=render_params.cmap_params.norm
layer,
trans_data,
ax,
cmap=cmap,
zorder=render_params.zorder,
norm=render_params.cmap_params.norm,
)

if legend_params.colorbar:
Expand All @@ -832,7 +863,11 @@ def _render_images(
else: # -> use given cmap for each channel
channel_cmaps = [render_params.cmap_params.cmap] * n_channels
stacked = (
np.stack([channel_cmaps[ind](layers[ch]) for ind, ch in enumerate(channels)], 0).sum(0) / n_channels
np.stack(
[channel_cmaps[ind](layers[ch]) for ind, ch in enumerate(channels)],
0,
).sum(0)
/ n_channels
)
stacked = stacked[:, :, :3]
logger.warning(
Expand All @@ -844,7 +879,13 @@ def _render_images(
"Consider using 'palette' instead."
)

_ax_show_and_transform(stacked, trans_data, ax, render_params.alpha, zorder=render_params.zorder)
_ax_show_and_transform(
stacked,
trans_data,
ax,
render_params.alpha,
zorder=render_params.zorder,
)

# 2B) Image has n channels, no palette/cmap info -> sample n categorical colors
elif palette is None and not got_multiple_cmaps:
Expand All @@ -858,7 +899,13 @@ def _render_images(
colored = np.stack([channel_cmaps[ind](layers[ch]) for ind, ch in enumerate(channels)], 0).sum(0)
colored = colored[:, :, :3]

_ax_show_and_transform(colored, trans_data, ax, render_params.alpha, zorder=render_params.zorder)
_ax_show_and_transform(
colored,
trans_data,
ax,
render_params.alpha,
zorder=render_params.zorder,
)

# 2C) Image has n channels and palette info
elif palette is not None and not got_multiple_cmaps:
Expand All @@ -869,16 +916,32 @@ def _render_images(
colored = np.stack([channel_cmaps[i](layers[c]) for i, c in enumerate(channels)], 0).sum(0)
colored = colored[:, :, :3]

_ax_show_and_transform(colored, trans_data, ax, render_params.alpha, zorder=render_params.zorder)
_ax_show_and_transform(
colored,
trans_data,
ax,
render_params.alpha,
zorder=render_params.zorder,
)

elif palette is None and got_multiple_cmaps:
channel_cmaps = [cp.cmap for cp in render_params.cmap_params] # type: ignore[union-attr]
colored = (
np.stack([channel_cmaps[ind](layers[ch]) for ind, ch in enumerate(channels)], 0).sum(0) / n_channels
np.stack(
[channel_cmaps[ind](layers[ch]) for ind, ch in enumerate(channels)],
0,
).sum(0)
/ n_channels
)
colored = colored[:, :, :3]

_ax_show_and_transform(colored, trans_data, ax, render_params.alpha, zorder=render_params.zorder)
_ax_show_and_transform(
colored,
trans_data,
ax,
render_params.alpha,
zorder=render_params.zorder,
)

elif palette is not None and got_multiple_cmaps:
raise ValueError("If 'palette' is provided, 'cmap' must be None.")
Expand Down Expand Up @@ -999,7 +1062,9 @@ def _draw_labels(seg_erosionpx: int | None, seg_boundaries: bool, alpha: float)
# outline-only case
elif render_params.fill_alpha == 0.0 and render_params.outline_alpha > 0.0:
cax = _draw_labels(
seg_erosionpx=render_params.contour_px, seg_boundaries=True, alpha=render_params.outline_alpha
seg_erosionpx=render_params.contour_px,
seg_boundaries=True,
alpha=render_params.outline_alpha,
)
alpha_to_decorate_ax = render_params.outline_alpha

Expand All @@ -1010,7 +1075,9 @@ def _draw_labels(seg_erosionpx: int | None, seg_boundaries: bool, alpha: float)

# ... then overlay the contour
cax_contour = _draw_labels(
seg_erosionpx=render_params.contour_px, seg_boundaries=True, alpha=render_params.outline_alpha
seg_erosionpx=render_params.contour_px,
seg_boundaries=True,
alpha=render_params.outline_alpha,
)

# pass the less-transparent _cax for the legend
Expand All @@ -1035,7 +1102,7 @@ def _draw_labels(seg_erosionpx: int | None, seg_boundaries: bool, alpha: float)
legend_fontweight=legend_params.legend_fontweight,
legend_loc=legend_params.legend_loc,
legend_fontoutline=legend_params.legend_fontoutline,
na_in_legend=legend_params.na_in_legend if groups is None else len(groups) == len(set(color_vector)),
na_in_legend=(legend_params.na_in_legend if groups is None else len(groups) == len(set(color_vector))),
colorbar=legend_params.colorbar,
scalebar_dx=scalebar_params.scalebar_dx,
scalebar_units=scalebar_params.scalebar_units,
Expand Down
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