Merge pull request #206 from vahtras/errorfix

Fix html build errors

Author: GaelVaroquaux

advanced/advanced_numpy/index.rst

@@ -481,7 +481,9 @@ Main point
 **The answer** (in Numpy)
 
   - **strides**: the number of bytes to jump to find the next element
-  - 1 stride per dimension::
+  - 1 stride per dimension
+
+.. code-block:: python
 
     >>> x.strides
     (3, 1)

advanced/mathematical_optimization/index.rst

@@ -881,13 +881,14 @@ Curve fitting
     :target: auto_examples/plot_curve_fit.html
     :align: right
 
+.. Comment to make doctest pass
+    >>> np.random.seed(0)
+
 Least square problems occur often when fitting a non-linear to data.
 While it is possible to construct our optimization problem ourselves,
 scipy provides a helper function for this purpose:
 :func:`scipy.optimize.curve_fit`::
 
-.. Comment to make doctest pass
-    >>> np.random.seed(0)
 
     >>> def f(t, omega, phi):
     ...     return np.cos(omega * t + phi)

guide/index.rst

@@ -90,7 +90,7 @@ This is the way to include your image and link it to the code:
 You can display the corresponding code using the ``literal-include``
 directive.
 
-.. literal-include:: examples/plot_simple.py
+.. literalinclude:: examples/plot_simple.py
 
 .. note::
 

intro/language/functions.rst

@@ -376,7 +376,9 @@ Exercises
 .. topic:: Exercise: Quicksort
     :class: green
 
-    Implement the quicksort algorithm, as defined by wikipedia::
+    Implement the quicksort algorithm, as defined by wikipedia
+
+.. parsed-literal::
 
     function quicksort(array)
         var list less, greater

intro/scipy.rst

@@ -446,11 +446,12 @@ our initial guess: ::
 
 **Curve fitting**
 
-Suppose we have data sampled from ``f`` with some noise: ::
-
 .. Comment to make doctest pass
     >>> np.random.seed(42)
 
+Suppose we have data sampled from ``f`` with some noise: ::
+
+
     >>> xdata = np.linspace(-10, 10, num=20)
     >>> ydata = f(xdata) + np.random.randn(xdata.size)