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timtreistimtreis
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fixing seed
1 parent fa2ec17 commit 789ba54

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‎tests/pl/test_render_points.py‎

Lines changed: 127 additions & 25 deletions
Original file line numberDiff line numberDiff line change
@@ -10,7 +10,14 @@
1010
from matplotlib.colors import Normalize
1111
from spatialdata import SpatialData, deepcopy
1212
from spatialdata.models import PointsModel, TableModel
13-
from spatialdata.transformations import Affine, Identity, MapAxis, Scale, Sequence, Translation
13+
from spatialdata.transformations import (
14+
Affine,
15+
Identity,
16+
MapAxis,
17+
Scale,
18+
Sequence,
19+
Translation,
20+
)
1421
from spatialdata.transformations._utils import _set_transformations
1522

1623
import spatialdata_plot # noqa: F401
@@ -58,7 +65,9 @@ def test_plot_coloring_with_palette(self, sdata_blobs: SpatialData):
5865
sdata_blobs["table"].obs["region"] = ["blobs_points"] * sdata_blobs["table"].n_obs
5966
sdata_blobs["table"].uns["spatialdata_attrs"]["region"] = "blobs_points"
6067
sdata_blobs.pl.render_points(
61-
color="genes", groups=["gene_a", "gene_b"], palette=["lightgreen", "darkblue"]
68+
color="genes",
69+
groups=["gene_a", "gene_b"],
70+
palette=["lightgreen", "darkblue"],
6271
).pl.show()
6372

6473
def test_plot_coloring_with_cmap(self, sdata_blobs: SpatialData):
@@ -81,35 +90,51 @@ def test_plot_color_recognises_actual_color_as_color(self, sdata_blobs: SpatialD
8190
def test_plot_points_coercable_categorical_color(self, sdata_blobs: SpatialData):
8291
n_obs = len(sdata_blobs["blobs_points"])
8392
adata = AnnData(
84-
RNG.normal(size=(n_obs, 10)), obs=pd.DataFrame(RNG.normal(size=(n_obs, 3)), columns=["a", "b", "c"])
93+
RNG.normal(size=(n_obs, 10)),
94+
obs=pd.DataFrame(RNG.normal(size=(n_obs, 3)), columns=["a", "b", "c"]),
8595
)
8696
adata.obs["instance_id"] = np.arange(adata.n_obs)
8797
adata.obs["category"] = RNG.choice(["a", "b", "c"], size=adata.n_obs)
8898
adata.obs["instance_id"] = list(range(adata.n_obs))
8999
adata.obs["region"] = "blobs_points"
90-
table = TableModel.parse(adata=adata, region_key="region", instance_key="instance_id", region="blobs_points")
100+
table = TableModel.parse(
101+
adata=adata,
102+
region_key="region",
103+
instance_key="instance_id",
104+
region="blobs_points",
105+
)
91106
sdata_blobs["other_table"] = table
92107

93108
sdata_blobs.pl.render_points("blobs_points", color="category").pl.show()
94109

95110
def test_plot_points_categorical_color(self, sdata_blobs: SpatialData):
96111
n_obs = len(sdata_blobs["blobs_points"])
97112
adata = AnnData(
98-
RNG.normal(size=(n_obs, 10)), obs=pd.DataFrame(RNG.normal(size=(n_obs, 3)), columns=["a", "b", "c"])
113+
RNG.normal(size=(n_obs, 10)),
114+
obs=pd.DataFrame(RNG.normal(size=(n_obs, 3)), columns=["a", "b", "c"]),
99115
)
100116
adata.obs["instance_id"] = np.arange(adata.n_obs)
101117
adata.obs["category"] = RNG.choice(["a", "b", "c"], size=adata.n_obs)
102118
adata.obs["instance_id"] = list(range(adata.n_obs))
103119
adata.obs["region"] = "blobs_points"
104-
table = TableModel.parse(adata=adata, region_key="region", instance_key="instance_id", region="blobs_points")
120+
table = TableModel.parse(
121+
adata=adata,
122+
region_key="region",
123+
instance_key="instance_id",
124+
region="blobs_points",
125+
)
105126
sdata_blobs["other_table"] = table
106127

107128
sdata_blobs["other_table"].obs["category"] = sdata_blobs["other_table"].obs["category"].astype("category")
108129
sdata_blobs.pl.render_points("blobs_points", color="category").pl.show()
109130

110131
def test_plot_datashader_continuous_color(self, sdata_blobs: SpatialData):
111132
sdata_blobs.pl.render_points(
112-
element="blobs_points", size=40, color="instance_id", alpha=0.6, method="datashader"
133+
element="blobs_points",
134+
size=40,
135+
color="instance_id",
136+
alpha=0.6,
137+
method="datashader",
113138
).pl.show()
114139

115140
def test_plot_points_categorical_color_column_matplotlib(self, sdata_blobs: SpatialData):
@@ -131,32 +156,56 @@ def test_plot_datashader_matplotlib_stack(self, sdata_blobs: SpatialData):
131156

132157
def test_plot_datashader_can_color_by_category(self, sdata_blobs: SpatialData):
133158
sdata_blobs.pl.render_points(
134-
color="genes", groups="gene_b", palette="lightgreen", size=20, method="datashader"
159+
color="genes",
160+
groups="gene_b",
161+
palette="lightgreen",
162+
size=20,
163+
method="datashader",
135164
).pl.show()
136165

137166
def test_plot_datashader_can_use_sum_as_reduction(self, sdata_blobs: SpatialData):
138167
sdata_blobs.pl.render_points(
139-
element="blobs_points", size=40, color="instance_id", method="datashader", datashader_reduction="sum"
168+
element="blobs_points",
169+
size=40,
170+
color="instance_id",
171+
method="datashader",
172+
datashader_reduction="sum",
140173
).pl.show()
141174

142175
def test_plot_datashader_can_use_mean_as_reduction(self, sdata_blobs: SpatialData):
143176
sdata_blobs.pl.render_points(
144-
element="blobs_points", size=40, color="instance_id", method="datashader", datashader_reduction="mean"
177+
element="blobs_points",
178+
size=40,
179+
color="instance_id",
180+
method="datashader",
181+
datashader_reduction="mean",
145182
).pl.show()
146183

147184
def test_plot_datashader_can_use_any_as_reduction(self, sdata_blobs: SpatialData):
148185
sdata_blobs.pl.render_points(
149-
element="blobs_points", size=40, color="instance_id", method="datashader", datashader_reduction="any"
186+
element="blobs_points",
187+
size=40,
188+
color="instance_id",
189+
method="datashader",
190+
datashader_reduction="any",
150191
).pl.show()
151192

152193
def test_plot_datashader_can_use_count_as_reduction(self, sdata_blobs: SpatialData):
153194
sdata_blobs.pl.render_points(
154-
element="blobs_points", size=40, color="instance_id", method="datashader", datashader_reduction="count"
195+
element="blobs_points",
196+
size=40,
197+
color="instance_id",
198+
method="datashader",
199+
datashader_reduction="count",
155200
).pl.show()
156201

157202
def test_plot_datashader_can_use_std_as_reduction(self, sdata_blobs: SpatialData):
158203
sdata_blobs.pl.render_points(
159-
element="blobs_points", size=40, color="instance_id", method="datashader", datashader_reduction="std"
204+
element="blobs_points",
205+
size=40,
206+
color="instance_id",
207+
method="datashader",
208+
datashader_reduction="std",
160209
).pl.show()
161210

162211
def test_plot_datashader_can_use_std_as_reduction_not_all_zero(self, sdata_blobs: SpatialData):
@@ -168,34 +217,59 @@ def test_plot_datashader_can_use_std_as_reduction_not_all_zero(self, sdata_blobs
168217
temp.loc[195, "instance_id"] = 13
169218
blob["blobs_points"] = PointsModel.parse(dask.dataframe.from_pandas(temp, 1), coordinates={"x": "x", "y": "y"})
170219
blob.pl.render_points(
171-
element="blobs_points", size=40, color="instance_id", method="datashader", datashader_reduction="std"
220+
element="blobs_points",
221+
size=40,
222+
color="instance_id",
223+
method="datashader",
224+
datashader_reduction="std",
172225
).pl.show()
173226

174227
def test_plot_datashader_can_use_var_as_reduction(self, sdata_blobs: SpatialData):
175228
sdata_blobs.pl.render_points(
176-
element="blobs_points", size=40, color="instance_id", method="datashader", datashader_reduction="var"
229+
element="blobs_points",
230+
size=40,
231+
color="instance_id",
232+
method="datashader",
233+
datashader_reduction="var",
177234
).pl.show()
178235

179236
def test_plot_datashader_can_use_max_as_reduction(self, sdata_blobs: SpatialData):
180237
sdata_blobs.pl.render_points(
181-
element="blobs_points", size=40, color="instance_id", method="datashader", datashader_reduction="max"
238+
element="blobs_points",
239+
size=40,
240+
color="instance_id",
241+
method="datashader",
242+
datashader_reduction="max",
182243
).pl.show()
183244

184245
def test_plot_datashader_can_use_min_as_reduction(self, sdata_blobs: SpatialData):
185246
sdata_blobs.pl.render_points(
186-
element="blobs_points", size=40, color="instance_id", method="datashader", datashader_reduction="min"
247+
element="blobs_points",
248+
size=40,
249+
color="instance_id",
250+
method="datashader",
251+
datashader_reduction="min",
187252
).pl.show()
188253

189254
def test_plot_mpl_and_datashader_point_sizes_agree_after_altered_dpi(self, sdata_blobs: SpatialData):
190255
sdata_blobs.pl.render_points(element="blobs_points", size=400, color="blue").pl.render_points(
191-
element="blobs_points", size=400, color="yellow", method="datashader", alpha=0.8
256+
element="blobs_points",
257+
size=400,
258+
color="yellow",
259+
method="datashader",
260+
alpha=0.8,
192261
).pl.show(dpi=200)
193262

194263
def test_plot_points_transformed_ds_agrees_with_mpl(self):
195264
sdata = SpatialData(
196265
points={
197266
"points1": PointsModel.parse(
198-
pd.DataFrame({"y": [0, 0, 10, 10, 4, 6, 4, 6], "x": [0, 10, 10, 0, 4, 6, 6, 4]}),
267+
pd.DataFrame(
268+
{
269+
"y": [0, 0, 10, 10, 4, 6, 4, 6],
270+
"x": [0, 10, 10, 0, 4, 6, 6, 4],
271+
}
272+
),
199273
transformations={"global": Scale([2, 2], ("y", "x"))},
200274
)
201275
},
@@ -228,12 +302,18 @@ def test_plot_datashader_can_transform_points(self, sdata_blobs: SpatialData):
228302

229303
def test_plot_can_use_norm_with_clip(self, sdata_blobs: SpatialData):
230304
sdata_blobs.pl.render_points(
231-
color="instance_id", size=40, norm=Normalize(3, 7, clip=True), cmap=_viridis_with_under_over()
305+
color="instance_id",
306+
size=40,
307+
norm=Normalize(3, 7, clip=True),
308+
cmap=_viridis_with_under_over(),
232309
).pl.show()
233310

234311
def test_plot_can_use_norm_without_clip(self, sdata_blobs: SpatialData):
235312
sdata_blobs.pl.render_points(
236-
color="instance_id", size=40, norm=Normalize(3, 7, clip=False), cmap=_viridis_with_under_over()
313+
color="instance_id",
314+
size=40,
315+
norm=Normalize(3, 7, clip=False),
316+
cmap=_viridis_with_under_over(),
237317
).pl.show()
238318

239319
def test_plot_datashader_can_use_norm_with_clip(self, sdata_blobs: SpatialData):
@@ -290,7 +370,12 @@ def test_plot_can_annotate_points_with_table_obs(self, sdata_blobs: SpatialData)
290370
obs["extra_feature"] = [1, 2] * 100
291371

292372
table = AnnData(X=feature_matrix, var=pd.DataFrame(index=var_names), obs=obs)
293-
table = TableModel.parse(table, region="blobs_points", region_key="region", instance_key="instance_id")
373+
table = TableModel.parse(
374+
table,
375+
region="blobs_points",
376+
region_key="region",
377+
instance_key="instance_id",
378+
)
294379
sdata_blobs["points_table"] = table
295380

296381
sdata_blobs.pl.render_points("blobs_points", color="extra_feature", size=10).pl.show()
@@ -308,7 +393,12 @@ def test_plot_can_annotate_points_with_table_X(self, sdata_blobs: SpatialData):
308393
obs["region"].astype("category")
309394

310395
table = AnnData(X=feature_matrix, var=pd.DataFrame(index=var_names), obs=obs)
311-
table = TableModel.parse(table, region="blobs_points", region_key="region", instance_key="instance_id")
396+
table = TableModel.parse(
397+
table,
398+
region="blobs_points",
399+
region_key="region",
400+
instance_key="instance_id",
401+
)
312402
sdata_blobs["points_table"] = table
313403

314404
sdata_blobs.pl.render_points("blobs_points", color="feature0", size=10).pl.show()
@@ -327,13 +417,20 @@ def test_plot_can_annotate_points_with_table_and_groups(self, sdata_blobs: Spati
327417
obs["extra_feature_cat"] = ["one", "two"] * 100
328418

329419
table = AnnData(X=feature_matrix, var=pd.DataFrame(index=var_names), obs=obs)
330-
table = TableModel.parse(table, region="blobs_points", region_key="region", instance_key="instance_id")
420+
table = TableModel.parse(
421+
table,
422+
region="blobs_points",
423+
region_key="region",
424+
instance_key="instance_id",
425+
)
331426
sdata_blobs["points_table"] = table
332427

333428
sdata_blobs.pl.render_points("blobs_points", color="extra_feature_cat", groups="two", size=10).pl.show()
334429

335430
def test_plot_can_annotate_points_with_table_layer(self, sdata_blobs: SpatialData):
336431
nrows, ncols = 200, 3
432+
# reset seed for reproducibility
433+
RNG.seed(42)
337434
feature_matrix = RNG.random((nrows, ncols))
338435
var_names = [f"feature{i}" for i in range(ncols)]
339436

@@ -345,7 +442,12 @@ def test_plot_can_annotate_points_with_table_layer(self, sdata_blobs: SpatialDat
345442
obs["region"].astype("category")
346443

347444
table = AnnData(X=feature_matrix, var=pd.DataFrame(index=var_names), obs=obs)
348-
table = TableModel.parse(table, region="blobs_points", region_key="region", instance_key="instance_id")
445+
table = TableModel.parse(
446+
table,
447+
region="blobs_points",
448+
region_key="region",
449+
instance_key="instance_id",
450+
)
349451
sdata_blobs["points_table"] = table
350452
sdata_blobs["points_table"].layers["normalized"] = RNG.random((nrows, ncols))
351453

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