Bugfix log1p for non-float dense arrays

LKremer · Sep 2, 2020 · f704f72 · f704f72
1 parent 43379e0
commit f704f72
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Showing 4 changed files with 17 additions and 4 deletions.
diff --git a/docs/release-latest.rst b/docs/release-latest.rst
@@ -1,6 +1,13 @@
 .. role:: small
 .. role:: smaller
 
+On master
+~~~~~~~~~
+
+.. rubric:: Bugfixes
+
+* Fixed `log1p` inplace on integer dense arrays :pr:`1400` :smaller:`I Virshup`
+
 1.6.0 :small:`2020-08-15`
 ~~~~~~~~~~~~~~~~~~~~~~~~~
 

diff --git a/scanpy/preprocessing/_simple.py b/scanpy/preprocessing/_simple.py
@@ -308,13 +308,17 @@ def log1p_sparse(X, *, base: Optional[Number] = None, copy: bool = False):
 
 @log1p.register(np.ndarray)
 def log1p_array(X, *, base: Optional[Number] = None, copy: bool = False):
-    # Can force arrays to be np.ndarrays, but would be useful
+    # Can force arrays to be np.ndarrays, but would be useful to not
     # X = check_array(X, dtype=(np.float64, np.float32), ensure_2d=False, copy=copy)
     if copy:
         if not np.issubdtype(X.dtype, np.floating):
             X = X.astype(np.floating)
         else:
             X = X.copy()
+    elif not (
+        np.issubdtype(X.dtype, np.floating) or np.issubdtype(X.dtype, np.complex)
+    ):
+        X = X.astype(np.floating)
     np.log1p(X, out=X)
     if base is not None:
         np.divide(X, np.log(base), out=X)

diff --git a/scanpy/tests/helpers.py b/scanpy/tests/helpers.py
@@ -19,7 +19,7 @@ def check_rep_mutation(func, X, **kwargs):
         X=X.copy(),
         layers={"layer": X.copy()},
         obsm={"obsm": X.copy()},
-        dtype=np.float64,
+        dtype=X.dtype,
     )
     adata_X = func(adata, copy=True, **kwargs)
     adata_layer = func(adata, layer="layer", copy=True, **kwargs)

diff --git a/scanpy/tests/test_preprocessing.py b/scanpy/tests/test_preprocessing.py
@@ -38,8 +38,10 @@ def base(request):
     return request.param
 
 
-def test_log1p_rep(count_matrix_format, base):
-    X = count_matrix_format(sp.random(100, 200, density=0.3).toarray())
+def test_log1p_rep(count_matrix_format, base, dtype):
+    X = count_matrix_format(
+        np.abs(sp.random(100, 200, density=0.3, dtype=dtype)).toarray()
+    )
     check_rep_mutation(sc.pp.log1p, X, base=base)
     check_rep_results(sc.pp.log1p, X, base=base)