Re-black the code

lmcinnes · Sep 6, 2019 · bc6106c · bc6106c
1 parent fc0af08
commit bc6106c
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Showing 4 changed files with 29 additions and 34 deletions.
diff --git a/pynndescent/distances.py b/pynndescent/distances.py
@@ -366,7 +366,6 @@ def hellinger(x, y):
         return np.sqrt(1 - result / np.sqrt(l1_norm_x * l1_norm_y))
 
 
-
 named_distances = {
     # general minkowski distances
     "euclidean": euclidean,

diff --git a/pynndescent/pynndescent_.py b/pynndescent/pynndescent_.py
@@ -156,7 +156,6 @@ def init_rp_tree(data, dist, dist_args, current_graph, leaf_array, tried=None):
                     tried.add((q, p))
 
 
-
 @numba.njit(fastmath=True)
 def nn_descent_internal_low_memory(
     current_graph,

diff --git a/pynndescent/sparse.py b/pynndescent/sparse.py
@@ -403,7 +403,6 @@ def sparse_hellinger(ind1, data1, ind2, data2):
         return np.sqrt(1.0 - (result / sqrt_norm_prod))
 
 
-
 sparse_named_distances = {
     # general minkowski distances
     "euclidean": sparse_euclidean,

diff --git a/pynndescent/sparse_nndescent.py b/pynndescent/sparse_nndescent.py
@@ -56,23 +56,22 @@ def sparse_init_rp_tree(
                     tried.add((q, p))
 
 
-
 @numba.njit(fastmath=True)
 def sparse_nn_descent_internal_low_memory(
-        current_graph,
-        inds,
-        indptr,
-        data,
-        n_vertices,
-        n_neighbors,
-        rng_state,
-        max_candidates=50,
-        sparse_dist=sparse_euclidean,
-        dist_args=(),
-        n_iters=10,
-        delta=0.001,
-        rho=0.5,
-        verbose=False,
+    current_graph,
+    inds,
+    indptr,
+    data,
+    n_vertices,
+    n_neighbors,
+    rng_state,
+    max_candidates=50,
+    sparse_dist=sparse_euclidean,
+    dist_args=(),
+    n_iters=10,
+    delta=0.001,
+    rho=0.5,
+    verbose=False,
 ):
     for n in range(n_iters):
         if verbose:
@@ -134,21 +133,21 @@ def sparse_nn_descent_internal_low_memory(
 
 @numba.njit(fastmath=True)
 def sparse_nn_descent_internal_high_memory(
-        current_graph,
-        inds,
-        indptr,
-        data,
-        n_vertices,
-        n_neighbors,
-        rng_state,
-        max_candidates=50,
-        sparse_dist=sparse_euclidean,
-        dist_args=(),
-        n_iters=10,
-        delta=0.001,
-        rho=0.5,
-        tried=set([(-1, -1)]),
-        verbose=False,
+    current_graph,
+    inds,
+    indptr,
+    data,
+    n_vertices,
+    n_neighbors,
+    rng_state,
+    max_candidates=50,
+    sparse_dist=sparse_euclidean,
+    dist_args=(),
+    n_iters=10,
+    delta=0.001,
+    rho=0.5,
+    tried=set([(-1, -1)]),
+    verbose=False,
 ):
     for n in range(n_iters):
         if verbose:
@@ -300,7 +299,6 @@ def sparse_nn_descent(
             verbose=verbose,
         )
 
-
     return deheap_sort(current_graph)