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Make check_build run through. #146

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Make check_build run through. #146

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2 changes: 1 addition & 1 deletion mlens/externals/sklearn/type_of_target.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,7 @@
# License: BSD 3 clause

from __future__ import division
from collections import Sequence
from collections.abc import Sequence


from scipy.sparse import issparse
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2 changes: 1 addition & 1 deletion mlens/index/base.py
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Expand Up @@ -80,7 +80,7 @@ def partition(n, p):
>>> _partition(8, 3)
array([3, 3, 2])
"""
sizes = (n // p) * np.ones(p, dtype=np.int)
sizes = (n // p) * np.ones(p, dtype=np.int32)
sizes[:n % p] += 1
return sizes

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4 changes: 2 additions & 2 deletions mlens/testing/dummy.py
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Expand Up @@ -356,7 +356,7 @@ def _folded_ests(self, X, y, subsets=1):
t.sort()

weights = []
F = np.zeros((len(t), n_ests * subsets * labels), dtype=np.float)
F = np.zeros((len(t), n_ests * subsets * labels), dtype=np.float32)

col_id = {}
col_ass = 0
Expand Down Expand Up @@ -417,7 +417,7 @@ def _full_ests(self, X, y, subsets=1):
indexer = self.indexer
indexer.fit(X)

P = np.zeros((X.shape[0], n_ests * subsets * labels), dtype=np.float)
P = np.zeros((X.shape[0], n_ests * subsets * labels), dtype=np.float32)

weights = list()
col_id = {}
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4 changes: 2 additions & 2 deletions mlens/visualization/var_analysis.py
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Expand Up @@ -79,7 +79,7 @@ def pca_comp_plot(X, y=None, figsize=(10, 8),

for dim, frame in [(2, 221), (3, 223)]:

if dim is 3:
if dim == 3:
# Need to specify projection
subplot_kwarg = {'projection': '3d'}

Expand All @@ -94,7 +94,7 @@ def pca_comp_plot(X, y=None, figsize=(10, 8),
ax[-1].set_title('%s kernel, %i dims' % (kernel, dim))

# Whiten background if dim is 3
if dim is 3:
if dim == 3:
ax[-1].set_facecolor((1, 1, 1))

if show:
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