fix sparse reading

theislab · Aug 22, 2018 · 59aee04 · 59aee04
1 parent 1279d84
commit 59aee04
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Showing 4 changed files with 10 additions and 6 deletions.
diff --git a/scvelo/plotting/velocity.py b/scvelo/plotting/velocity.py
@@ -4,7 +4,9 @@
 
 def velocity(adata, var_names=None, basis='umap', mode='deterministic', fits='all', layers='all', color=None,
              fontsize=8, color_map='RdBu_r', size=.2, alpha=.5, ax=None, **kwargs):
-    """Plots spliced against unspliced expressions with steady-state fit along with expression and velocity in embedding
+    """Phase and velocity plot for set of genes
+
+    The phase plot shows Plots spliced against unspliced expressions with steady-state fit along with expression and velocity in embedding
 
     Arguments
     ---------

diff --git a/scvelo/preprocessing/__init__.py b/scvelo/preprocessing/__init__.py
@@ -32,11 +32,11 @@ def read_loom_layers(file_name, backup_url=None):
             print("OS error: {0}".format(OSError))
 
     with loompy.connect(file_name, 'r') as lc:
-        X = lc.layer['spliced'][:, :].sparse().T.tocsr()
+        X = lc.layer['spliced'].sparse().T.tocsr()
 
         layers = OrderedDict()
-        layers['spliced'] = lc.layer["spliced"][:, :].sparse().T.tocsr()
-        layers['unspliced'] = lc.layer["unspliced"][:, :].sparse().T.tocsr()
+        layers['spliced'] = lc.layer["spliced"].sparse().T.tocsr()
+        layers['unspliced'] = lc.layer["unspliced"].sparse().T.tocsr()
 
         obs = dict(lc.col_attrs)
         obs['obs_names'] = obs.pop('CellID')

diff --git a/scvelo/preprocessing/fractions.py b/scvelo/preprocessing/fractions.py
@@ -2,7 +2,7 @@
 
 
 def print_fraction_of_abundances(adata, cleanup_layers=True, copy=False):
-    """Computes the fraction of abundances of spliced, unspliced and ambiguous counts
+    """Fraction of spliced/unspliced/ambiguous abundances
 
     Arguments
     ---------

diff --git a/scvelo/tools/velocity_graph.py b/scvelo/tools/velocity_graph.py
@@ -64,7 +64,9 @@ def compute(self, ixs):
 
 
 def velocity_graph(adata, vkey='velocity', n_recurse_neighbors=2, n_neighbors=None, n_jobs=1, sqrt_transform=False, copy=False):
-    """Computes a velocity graph based on cosine similarities between velocities and potential cell state transitions
+    """Computes a velocity graph based on cosine similarities
+
+    The cosine similarities are computed between velocities and potential cell state transitions
 
     Arguments
     ---------