adding pip caching and tests on 2.7

.travis.yml

@@ -1,5 +1,6 @@
 language: python
 python:
+  - "2.7"
   - "3.4"
   - "3.5"
   - "3.6"
@@ -16,8 +17,17 @@ install:
   - pip install .
   - pip install pytest-cov
 
+
+# Installing matplotlib is long processes. Using a cache allows
+# to fasten the tests by reducing drastically the install time.
+cache:
+    directories:
+        # Cache for pip, mostly to speed up matplotlib install
+        - $HOME/.cache/pip
+
 script:
   - pytest --cov ripser
 
+# Upload the code coverage report
 after_success:
   - bash <(curl -s https://codecov.io/bash)

ripser/ripser.py

@@ -84,7 +84,7 @@ def transform(self, X, distance_matrix=False, metric='euclidean'):
             distance matrix from X using the chosen metric.
 
         metric: string or callable
-            The metric to use when calculating distance between instances in a feature array. If metric is a string, it must be one of the options specified in PAIRED_DISTANCES, including “euclidean”, “manhattan”, or “cosine”. Alternatively, if metric is a callable function, it is called on each pair of instances (rows) and the resulting value recorded. The callable should take two arrays from X as input and return a value indicating the distance between them.
+            The metric to use when calculating distance between instances in a feature array. If metric is a string, it must be one of the options specified in PAIRED_DISTANCES, including "euclidean", "manhattan", or "cosine". Alternatively, if metric is a callable function, it is called on each pair of instances (rows) and the resulting value recorded. The callable should take two arrays from X as input and return a value indicating the distance between them.
 
         """
 
@@ -108,7 +108,7 @@ def fit_transform(self, X, distance_matrix=False, metric='euclidean'):
             distance matrix from X using the chosen metric.
 
         metric: string or callable
-            The metric to use when calculating distance between instances in a feature array. If metric is a string, it must be one of the options specified in PAIRED_DISTANCES, including “euclidean”, “manhattan”, or “cosine”. Alternatively, if metric is a callable function, it is called on each pair of instances (rows) and the resulting value recorded. The callable should take two arrays from X as input and return a value indicating the distance between them.
+            The metric to use when calculating distance between instances in a feature array. If metric is a string, it must be one of the options specified in PAIRED_DISTANCES, including "euclidean", "manhattan", or "cosine". Alternatively, if metric is a callable function, it is called on each pair of instances (rows) and the resulting value recorded. The callable should take two arrays from X as input and return a value indicating the distance between them.
 
         Return
         ------