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Fix clims when plotting shapes element annotations with matplotlib rendering #368

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Fix clims when plotting shapes element annotations with matplotlib rendering #368

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0744fc4
fix clims for shapes
melonora Oct 3, 2024
17b9753
add test for set shape clims
melonora Oct 3, 2024
31cfc57
silence warning
melonora Oct 4, 2024
bff962e
silence warnings
melonora Oct 4, 2024
a89a73e
fix tests
melonora Oct 4, 2024
440100a
remove unnecessary list multiplication
melonora Oct 4, 2024
fcf1549
remove wrong argument and list multiplications
melonora Oct 4, 2024
e652ba2
remove unused arguments
melonora Oct 4, 2024
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11 changes: 2 additions & 9 deletions src/spatialdata_plot/pl/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -32,7 +32,6 @@
LinearSegmentedColormap,
ListedColormap,
Normalize,
TwoSlopeNorm,
to_rgba,
)
from matplotlib.figure import Figure
Expand Down Expand Up @@ -339,7 +338,7 @@ def _get_collection_shape(
c = cmap(c)
else:
try:
norm = colors.Normalize(vmin=min(c), vmax=max(c))
norm = colors.Normalize(vmin=min(c), vmax=max(c)) if norm is None else norm
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In this function Normalize() is initialized without clip, while in _prepare_cmap_norm() the default is to set clip=True. I would choose one of the two as our default choice. The user will be able to specify clip, vcenter, etc by passing a norm object directly.

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hmm let me double check that if we don't pass norm as user, whether ultimately the norm is always created anyway, then we can get rid of normalize instance initiated here.

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ok there is code left over of when vmin and vmax were removed. Not certain whether to address this in a different PR.

except ValueError as e:
raise ValueError(
"Could not convert values in the `color` column to float, if `color` column represents"
Expand All @@ -353,7 +352,7 @@ def _get_collection_shape(
c = cmap(c)
else:
try:
norm = colors.Normalize(vmin=min(c), vmax=max(c))
norm = colors.Normalize(vmin=min(c), vmax=max(c)) if norm is None else norm
except ValueError as e:
raise ValueError(
"Could not convert values in the `color` column to float, if `color` column represents"
Expand Down Expand Up @@ -506,12 +505,6 @@ def _prepare_cmap_norm(

if norm is None:
norm = Normalize(vmin=vmin, vmax=vmax, clip=True)
elif isinstance(norm, Normalize) or not norm:
pass # TODO
elif vcenter is None:
norm = Normalize(vmin=vmin, vmax=vmax, clip=True)
else:
norm = TwoSlopeNorm(vmin=vmin, vmax=vmax, vcenter=vcenter)
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Now that vcenter is removed, it should be removed also from the function signature. Also, kwargs is in the signature but not used, so I would remove it.


na_color, na_color_modified_by_user = _sanitise_na_color(na_color)
cmap.set_bad(na_color)
Expand Down
Binary file modified tests/_images/Labels_can_render_given_scale_of_multiscale_labels.png
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Why are the two files different?

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just different color perhaps due to made changes and then generating the labels with a different color. Other than that there are no changes.

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Binary file added tests/_images/Shapes_can_set_clims_clip.png
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Binary file modified tests/_images/Shapes_colorbar_can_be_normalised.png
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21 changes: 17 additions & 4 deletions tests/pl/test_render_shapes.py
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Expand Up @@ -144,7 +144,7 @@ def test_plot_colorbar_respects_input_limits(self, sdata_blobs: SpatialData):
sdata_blobs.pl.render_shapes("blobs_polygons", color="cluster", groups=["c1"]).pl.show()

def test_plot_colorbar_can_be_normalised(self, sdata_blobs: SpatialData):
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What does groups=["c1"] do here? My understanding is that it doesn't have any effect because:

  • cluster is numerical and not categorical
  • the values of clusters do not include c1

But I may be missing something and be wrong.

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it does nothing. @timtreis is this purely to test that the colorbar stays limited from 1-50?

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I removed the argument now as typically it is used to just color certain categorical values within a column, which from the title of the test function definition is not the intention.

sdata_blobs["table"].obs["region"] = ["blobs_polygons"] * sdata_blobs["table"].n_obs
sdata_blobs["table"].obs["region"] = "blobs_polygons"
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region is the instance_key right? Usually we have the region_key called region and the instance_key called instance_id. I'd consider making a separate PR to fix this repo-wide, unless this is only here, then I'd fix this now. CC @timtreis

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no region is the region_key_key

sdata_blobs["table"].uns["spatialdata_attrs"]["region"] = "blobs_polygons"
sdata_blobs.shapes["blobs_polygons"]["cluster"] = [1, 2, 3, 5, 20]
norm = Normalize(vmin=0, vmax=5, clip=True)
Expand Down Expand Up @@ -186,7 +186,7 @@ def test_plot_can_plot_with_annotation_despite_random_shuffling(self, sdata_blob

def test_plot_can_plot_queried_with_annotation_despite_random_shuffling(self, sdata_blobs: SpatialData):
sdata_blobs["table"].obs["region"] = "blobs_circles"
new_table = sdata_blobs["table"][:5]
new_table = sdata_blobs["table"][:5].copy()
new_table.uns["spatialdata_attrs"]["region"] = "blobs_circles"
new_table.obs["instance_id"] = np.array(range(5))

Expand Down Expand Up @@ -214,7 +214,7 @@ def test_plot_can_plot_queried_with_annotation_despite_random_shuffling(self, sd

def test_plot_can_color_two_shapes_elements_by_annotation(self, sdata_blobs: SpatialData):
sdata_blobs["table"].obs["region"] = "blobs_circles"
new_table = sdata_blobs["table"][:10]
new_table = sdata_blobs["table"][:10].copy()
new_table.uns["spatialdata_attrs"]["region"] = ["blobs_circles", "blobs_polygons"]
new_table.obs["instance_id"] = np.concatenate((np.array(range(5)), np.array(range(5))))

Expand All @@ -230,7 +230,7 @@ def test_plot_can_color_two_shapes_elements_by_annotation(self, sdata_blobs: Spa

def test_plot_can_color_two_queried_shapes_elements_by_annotation(self, sdata_blobs: SpatialData):
sdata_blobs["table"].obs["region"] = "blobs_circles"
new_table = sdata_blobs["table"][:10]
new_table = sdata_blobs["table"][:10].copy()
new_table.uns["spatialdata_attrs"]["region"] = ["blobs_circles", "blobs_polygons"]
new_table.obs["instance_id"] = np.concatenate((np.array(range(5)), np.array(range(5))))

Expand Down Expand Up @@ -316,3 +316,16 @@ def test_plot_datashader_can_color_by_value(self, sdata_blobs: SpatialData):
sdata_blobs["table"].uns["spatialdata_attrs"]["region"] = "blobs_polygons"
sdata_blobs.shapes["blobs_polygons"]["value"] = [1, 10, 1, 20, 1]
sdata_blobs.pl.render_shapes(element="blobs_polygons", color="value", method="datashader").pl.show()

def test_plot_can_set_clims_clip(self, sdata_blobs: SpatialData):
table_shapes = sdata_blobs["table"][:5].copy()
table_shapes.obs.instance_id = list(range(5))
table_shapes.obs["region"] = "blobs_circles"
table_shapes.obs["dummy_gene_expression"] = [i * 10 for i in range(5)]
table_shapes.uns["spatialdata_attrs"]["region"] = "blobs_circles"
sdata_blobs["new_table"] = table_shapes

norm = Normalize(vmin=20, vmax=40, clip=True)
sdata_blobs.pl.render_shapes(
"blobs_circles", color="dummy_gene_expression", norm=norm, table_name="new_table"
).pl.show()
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