Removed deprication warning in latest version of pyarrow.

aertslab · Nov 5, 2018 · b8a3176 · b8a3176
1 parent e1b4dc2
commit b8a3176
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Showing 4 changed files with 18 additions and 22 deletions.
diff --git a/requirements.txt b/requirements.txt
@@ -9,7 +9,7 @@ pandas>=0.20.1
 cloudpickle
 dask>=0.18.1
 distributed>=1.21.6
-pyarrow
+pyarrow>=0.11.1
 arboreto
 boltons
 setuptools

diff --git a/src/pyscenic/rnkdb.py b/src/pyscenic/rnkdb.py
@@ -253,10 +253,10 @@ def genes(self) -> Tuple[str]:
         return tuple(reader.get_column_name(idx) for idx in range(self.total_genes) if reader.get_column_name(idx) != INDEX_NAME)
 
     def load_full(self) -> pd.DataFrame:
-        return FeatherReader(self._fname).read().set_index(INDEX_NAME)
+        return FeatherReader(self._fname).read_pandas().set_index(INDEX_NAME)
 
     def load(self, gs: Type[GeneSignature]) -> pd.DataFrame:
-        return FeatherReader(self._fname).read(columns=(INDEX_NAME,) + gs.genes).set_index(INDEX_NAME)
+        return FeatherReader(self._fname).read_pandas(columns=(INDEX_NAME,) + gs.genes).set_index(INDEX_NAME)
 
 
 class MemoryDecorator(RankingDatabase):

diff --git a/tests/test_aucell.py b/tests/test_aucell.py
@@ -26,31 +26,27 @@ def gs():
                                   gene_separator="\t", field_separator="\t", )
 
 
-def test_create_rankings():
-    ex_mtx = exp_matrix()
-    df_rnk = create_rankings(ex_mtx)
-    n_genes = ex_mtx.shape[1]
+def test_create_rankings(exp_matrix):
+    df_rnk = create_rankings(exp_matrix)
+    n_genes = exp_matrix.shape[1]
     assert len(df_rnk.sum(axis=1).unique()) == 1
     assert (df_rnk + 1).sum(axis=1).unique()[0] == (n_genes * (n_genes+1))/2.0
 
 
-def test_aucell_w1():
-    ex_mtx = exp_matrix()
-    percentiles = derive_auc_threshold(ex_mtx)
-    aucs_mtx = aucell(ex_mtx, gs(), auc_threshold=percentiles[0.01], num_workers=1)
+def test_aucell_w1(exp_matrix, gs):
+    percentiles = derive_auc_threshold(exp_matrix)
+    aucs_mtx = aucell(exp_matrix, gs, auc_threshold=percentiles[0.01], num_workers=1)
 
 
-def test_aucell_w2():
-    ex_mtx = exp_matrix()
-    percentiles = derive_auc_threshold(ex_mtx)
-    aucs_mtx = aucell(ex_mtx, gs(), auc_threshold=percentiles[0.01], num_workers=4)
+def test_aucell_w2(exp_matrix, gs):
+    percentiles = derive_auc_threshold(exp_matrix)
+    aucs_mtx = aucell(exp_matrix, gs, auc_threshold=percentiles[0.01], num_workers=4)
 
 
-def test_aucell_mismatch():
-    ex_mtx = exp_matrix()
-    percentiles = derive_auc_threshold(ex_mtx)
-    gss = [GeneSignature(name="test", gene2weight=list(map("FAKE{}".format, range(100))))] + gs()
-    aucs_mtx = aucell(ex_mtx, gss, auc_threshold=percentiles[0.01], num_workers=1)
+def test_aucell_mismatch(exp_matrix, gs):
+    percentiles = derive_auc_threshold(exp_matrix)
+    gss = [GeneSignature(name="test", gene2weight=list(map("FAKE{}".format, range(100))))] + gs
+    aucs_mtx = aucell(exp_matrix, gss, auc_threshold=percentiles[0.01], num_workers=1)
     print(aucs_mtx.head())
 
 

diff --git a/tests/test_recovery.py b/tests/test_recovery.py
@@ -25,8 +25,8 @@ def gs():
                                   gene_separator="\t", field_separator="\t", )[0]
 
 
-def test_enrichment():
-    df = enrichment(db(), gs())
+def test_enrichment(db, gs):
+    df = enrichment(db, gs)
 
 
 def test_auc1d_1():