Stability updates to calculate_qc_metrics

* More useful error message if requested proportions are out of bounds
* Type stability for input to jitted function

scanpy/preprocessing/_qc.py

@@ -203,11 +203,13 @@ def top_segment_proportions(mtx, ns):
         the 50th most expressed gene.
     """
     # Pretty much just does dispatch
-    assert max(ns) <= mtx.shape[1], "Cumulative proportions can only be calculated to the number of given features"
+    if not (max(ns) <= mtx.shape[1] and min(ns) > 0):
+        raise IndexError("Positions outside range of features.")
     if issparse(mtx):
         if not isspmatrix_csr(mtx):
             mtx = csr_matrix(mtx)
-        return top_segment_proportions_sparse_csr(mtx.data, mtx.indptr, ns)
+        return top_segment_proportions_sparse_csr(mtx.data, mtx.indptr,
+                                                  np.array(ns, dtype=np.int))
     else:
         return top_segment_proportions_dense(mtx, ns)
 

scanpy/tests/test_qc_metrics.py

@@ -1,5 +1,6 @@
 import numpy as np
 import pandas as pd
+import pytest
 import scanpy as sc
 import scanpy
 from scipy import sparse
@@ -126,3 +127,7 @@ def test_qc_metrics_percentage(): # In response to #421
     sc.pp.calculate_qc_metrics(adata_dense, percent_top=(None))
     sc.pp.calculate_qc_metrics(adata_dense, percent_top=[1,2,3,10])
     sc.pp.calculate_qc_metrics(adata_dense, percent_top=[1])
+    with pytest.raises(IndexError):
+        sc.pp.calculate_qc_metrics(adata_dense, percent_top=[1, 2, 3, -5])
+    with pytest.raises(IndexError):
+        sc.pp.calculate_qc_metrics(adata_dense, percent_top=[20, 30, 1001])