[easy] - fixing all expression matrix saves

starfish/core/expression_matrix/test/test_serialization.py

@@ -0,0 +1,30 @@
+import random
+
+from starfish import IntensityTable
+from starfish.core.codebook.test.factories import codebook_array_factory
+from starfish.core.types import Features
+
+NUMBER_SPOTS = 10
+
+
+def test_save_expression_matrix():
+
+    codebook = codebook_array_factory()
+
+    intensities = IntensityTable.synthetic_intensities(
+        codebook,
+        num_z=3,
+        height=100,
+        width=100,
+        n_spots=10
+    )
+    # mock out come cell_ids
+    cell_ids = random.sample(range(1, 20), NUMBER_SPOTS)
+    intensities[Features.CELL_ID] = (Features.AXIS, cell_ids)
+
+    expression_matrix = intensities.to_expression_matrix()
+
+    # test all saving methods
+    expression_matrix.save_anndata("expression.h5")
+    expression_matrix.save_loom("expression")
+    expression_matrix.save("expression")

starfish/core/intensity_table/intensity_table.py

@@ -522,10 +522,11 @@ def to_expression_matrix(self) -> ExpressionMatrix:
         counts = grouped.count().iloc[:, 0].unstack().fillna(0)
         if self.has_physical_coords:
             grouped = self.to_features_dataframe().groupby([Features.CELL_ID])[[
-                Axes.X, Axes.Y, Axes.ZPLANE, Coordinates.X, Coordinates.Y, Coordinates.Z]]
+                Axes.X.value, Axes.Y.value, Axes.ZPLANE.value, Coordinates.X.value,
+                Coordinates.Y.value, Coordinates.Z.value]]
         else:
             grouped = self.to_features_dataframe().groupby([Features.CELL_ID])[[
-                Axes.X, Axes.Y, Axes.ZPLANE]]
+                Axes.X.value, Axes.Y.value, Axes.ZPLANE.value]]
         min_ = grouped.min()
         max_ = grouped.max()
         coordinate_df = min_ + (max_ - min_) / 2