From e027936920d1421d0ab29b7e90350d28e1411500 Mon Sep 17 00:00:00 2001
From: Ines Montani <ines@ines.io>
Date: Wed, 11 Jan 2017 18:54:56 +0100
Subject: [PATCH] Modernise Doc noun chunks tests

---
 spacy/tests/tokens/test_noun_chunks.py | 38 ++++++++++++--------------
 1 file changed, 18 insertions(+), 20 deletions(-)

diff --git a/spacy/tests/tokens/test_noun_chunks.py b/spacy/tests/tokens/test_noun_chunks.py
index 642ce715b..659edbf57 100644
--- a/spacy/tests/tokens/test_noun_chunks.py
+++ b/spacy/tests/tokens/test_noun_chunks.py
@@ -1,27 +1,26 @@
-import numpy as np
+# coding: utf-8
+from __future__ import unicode_literals
 
-from spacy.attrs import HEAD, DEP
-from spacy.symbols import nsubj, dobj, punct, amod, nmod, conj, cc, root
-from spacy.en import English
-from spacy.syntax.iterators import english_noun_chunks
+from ...attrs import HEAD, DEP
+from ...symbols import nsubj, dobj, amod, nmod, conj, cc, root
+from ...syntax.iterators import english_noun_chunks
+from ..util import get_doc
+
+import numpy
 
 
-def test_not_nested():
-    nlp = English(parser=False, entity=False)
-    sent = u'''Peter has chronic command and control issues'''.strip()
-    tokens = nlp(sent)
+def test_noun_chunks_not_nested(en_tokenizer):
+    text = "Peter has chronic command and control issues"
+    heads = [1, 0, 4, 3, -1, -2, -5]
+    deps = ['nsubj', 'ROOT', 'amod', 'nmod', 'cc', 'conj', 'dobj']
+
+    tokens = en_tokenizer(text)
+    doc = get_doc(tokens.vocab, [t.text for t in tokens], heads=heads, deps=deps)
+
     tokens.from_array(
         [HEAD, DEP],
-        np.asarray(
-            [
-                [1, nsubj],
-                [0, root],
-                [4, amod],
-                [3, nmod],
-                [-1, cc],
-                [-2, conj],
-                [-5, dobj]
-            ], dtype='int32'))
+        numpy.asarray([[1, nsubj], [0, root], [4, amod], [3, nmod], [-1, cc],
+                       [-2, conj], [-5, dobj]], dtype='int32'))
     tokens.noun_chunks_iterator = english_noun_chunks
     word_occurred = {}
     for chunk in tokens.noun_chunks:
@@ -30,4 +29,3 @@ def test_not_nested():
             word_occurred[word.text] += 1
     for word, freq in word_occurred.items():
         assert freq == 1, (word, [chunk.text for chunk in tokens.noun_chunks])
-