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[WIP] Kd tree, ball tree error #17400

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[WIP] Kd tree, ball tree error #17400

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3b79637
Merge pull request #1 from scikit-learn/master
arka204 Apr 11, 2020
464dc37
Merge pull request #2 from scikit-learn/master
arka204 May 10, 2020
02224ea
Fixing error when input has different dimensions.
arka204 May 31, 2020
ef6b1e5
Changing solution
arka204 Jun 8, 2020
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18 changes: 17 additions & 1 deletion sklearn/neighbors/_binary_tree.pxi
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Expand Up @@ -1053,9 +1053,25 @@ cdef class BinaryTree:
if leaf_size < 1:
raise ValueError("leaf_size must be greater than or equal to 1")

longest_data = max(len(item) for item in data)
padded_data = []
padding = False

for item in data:
if len(item) < longest_data:
item = np.asarray(item)
padded_item = np.zeros(longest_data)
padded_item[:item.shape[0]] = item
padded_data.append(padded_item)
padding = True
else:
padded_data.append(np.asarray(item))
if padding:
warnings.warn("Not all elements had the same number of dimensions"
" - proceeding after extending those with zeros")
data = np.asarray(padded_data)
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n_samples = data.shape[0]
n_features = data.shape[1]

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dont delete it line...

self.data_arr = np.asarray(data, dtype=DTYPE, order='C')
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I think you should rather just use sklearn.utils.check_array:

        self.data_arr = check_array(data, dtype=DTYPE, order='C')

It should display a ValueError with the message setting an array element with a sequence. which is good enough to me.

self.leaf_size = leaf_size
self.dist_metric = DistanceMetric.get_metric(metric, **kwargs)
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9 changes: 9 additions & 0 deletions sklearn/neighbors/tests/test_ball_tree.py
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Expand Up @@ -65,3 +65,12 @@ def test_query_haversine():

assert_array_almost_equal(dist1, dist2)
assert_array_almost_equal(ind1, ind2)


def test_different_dimension_size():
X = [(1, 2, 3), (2, 5), (5, 5, 1, 2)]
Y = np.array(X)
msg = ("Not all elements had the same number of dimensions"
" - proceeding after extending those with zeros")
with pytest.warns(UserWarning, match=msg):
BallTree(Y)
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it need change if u do raise error