Raise the numpy version supported to 1.5.0 and scipy to 0.8

.travis.yml

@@ -11,7 +11,7 @@ before_install:
   - sudo apt-get install -qq libatlas3gf-base libatlas-dev
 install:
 #If we don't install numpy before SciPy 0.10.1, the SciPy installations fails.
-  - "pip install -q numpy==1.4.1 --use-mirrors"
+  - "pip install -q numpy==1.5 --use-mirrors"
 #We can't install SciPy as there is no BLAS installed.
   - "pip install . --no-deps --use-mirrors"
 # command to run tests

doc/install.txt

@@ -32,15 +32,16 @@ instructions below for detailed installation steps):
 	g++ >= 4.2 (for openmp that is currently always used)
         more recent version recommended!
 
-    `NumPy <http://numpy.scipy.org/>`_ >= 1.3.0
-        Earlier versions have memory leaks.
+    `NumPy <http://numpy.scipy.org/>`_ >= 1.5.0
+        Earlier versions could work, but we don't test it.
 
     `SciPy <http://scipy.org>`_
         Only currently required for sparse matrix and special functions
         support, but *highly* recommended. We recommend SciPy
-        >=0.7 if you are using sparse matrices, because ``scipy.sparse``
+        >=0.8 if you are using sparse matrices, because ``scipy.sparse``
         is buggy in 0.6 (the ``scipy.csc_matrix`` version of ``dot()`` has a
-        bug with singleton dimensions, there may be more bugs).
+        bug with singleton dimensions, there may be more bugs) and we do not
+	tests with 0.7*.
 
     A `BLAS`_ installation (with Level 3 functionality)
         Including the development headers (``-dev``, ``-devel``, depending on

doc/sandbox/sparse.txt

@@ -7,14 +7,16 @@ Sparse matrices
 scipy.sparse
 ------------
 
-Note that you want scipy >= 0.7.0.
+Note that you want SciPy >= 0.8.0.
 
 .. warning::
 
-    In scipy 0.6, ``scipy.csc_matrix.dot`` has a bug with singleton
+    In SciPy 0.6, ``scipy.csc_matrix.dot`` has a bug with singleton
     dimensions. There may be more bugs. It also has inconsistent
     implementation of sparse matrices.
 
+    We do not test again SciPy 0.7.*.
+
 We describe the details of the compressed sparse matrix types.
     ``scipy.sparse.csc_matrix``
         should be used if the columns are sparse.

setup.py

@@ -153,7 +153,7 @@ def do_setup():
           license=LICENSE,
           platforms=PLATFORMS,
           packages=find_packages(),
-          install_requires=['numpy>=1.3.0', 'scipy>=0.7.0'],
+          install_requires=['numpy>=1.5.0', 'scipy>=0.8.0'],
           package_data={
               '': ['*.txt', '*.rst', '*.cu', '*.cuh', '*.c', '*.sh',
                    'ChangeLog'],