protect all numpy imports with a try-except block; so that NLTK can be imported…

protect all numpy imports with a try-except block; so that NLTK can be imported when numpy is not installed (i.e. missing numpy should only generate errors at runtime

nltk/classify/maxent.py

@@ -53,7 +53,11 @@ interface.
 """
 __docformat__ = 'epytext en'
 
-import numpy
+try:
+    import numpy
+except ImportError:
+    pass
+
 import time
 import tempfile
 import os

nltk/classify/scikitlearn.py

@@ -35,10 +35,12 @@ chi-square feature selection:
 
 from nltk.classify.api import ClassifierI
 from nltk.probability import DictionaryProbDist
-
-import numpy as np
 from scipy.sparse import coo_matrix
 
+try:
+    import numpy as np
+except ImportError:
+    pass
 
 class SklearnClassifier(ClassifierI):
     """Wrapper for scikit-learn classifiers."""

nltk/cluster/em.py

@@ -5,7 +5,10 @@
 # URL: <http://www.nltk.org/>
 # For license information, see LICENSE.TXT
 
-import numpy
+try:
+    import numpy
+except ImportError:
+    pass
 
 from util import VectorSpaceClusterer
 

nltk/cluster/gaac.py

@@ -5,9 +5,13 @@
 # URL: <http://www.nltk.org/>
 # For license information, see LICENSE.TXT
 
-import numpy
 import copy
 
+try:
+    import numpy
+except ImportError:
+    pass
+
 from nltk.cluster.util import VectorSpaceClusterer, Dendrogram
 
 class GAAClusterer(VectorSpaceClusterer):

nltk/cluster/kmeans.py

@@ -6,10 +6,15 @@
 # For license information, see LICENSE.TXT
 
 import copy
-import numpy
 import random
 import sys
 
+try:
+    import numpy
+except ImportError:
+    pass
+
+
 from nltk.cluster.util import VectorSpaceClusterer
 
 class KMeansClusterer(VectorSpaceClusterer):

nltk/cluster/util.py

@@ -6,10 +6,14 @@
 # For license information, see LICENSE.TXT
 
 import copy
-import numpy
 from sys import stdout
 from math import sqrt
 
+try:
+    import numpy
+except ImportError:
+    pass
+
 from nltk.cluster.api import ClusterI
 
 class VectorSpaceClusterer(ClusterI):

nltk/metrics/segmentation.py

@@ -41,7 +41,10 @@ Statistical Models for Text Segmentation
 Machine Learning, 34, 177-210
 """
 
-import numpy
+try:
+    import numpy
+except ImportError:
+    pass
 
 def windowdiff(seg1, seg2, k, boundary="1"):
     """

nltk/tokenize/texttiling.py

@@ -8,7 +8,11 @@
 
 import re
 import math
-import numpy
+
+try:
+    import numpy
+except ImportError:
+    pass
 
 from nltk.tokenize.api import TokenizerI