Merge branch 'master' of github.com:rougier/from-python-to-numpy

Author: rougier

03-anatomy.rst

@@ -379,9 +379,9 @@ you don't need `X` nor `Y` afterwards, an alternate solution would be:
    >>> np.multiply(Y, 2, out=Y)
    >>> np.add(X, Y, out=X)
 
-Using this alternate solution, no temporary array has been created. Problem is
-that there are many other cases where such copies needs to be created and this
-impact the performance like demonstrated on the example below:
+Using this alternate solution, no temporary array has been created. The problem 
+is that there are many other cases where such copies need to be created and 
+this impacts the performance like demonstrated in the example below:
 
 .. code:: pycon
 

04-code-vectorization.rst

@@ -111,8 +111,8 @@ dead. Every cell interacts with its eight neighbours, which are the cells that
 are directly horizontally, vertically, or diagonally adjacent. At each step in
 time, the following transitions occur:
 
-1. Any live cell with fewer than two live neighbours dies, as if by needs
-   caused by underpopulation.
+1. Any live cell with fewer than two live neighbours dies, as if by 
+   underpopulation.
 2. Any live cell with more than three live neighbours dies, as if by
    overcrowding.
 3. Any live cell with two or three live neighbours lives, unchanged, to the

05-problem-vectorization.rst

@@ -104,9 +104,9 @@ compute it only once:
            result += X[i]*Ysum
        return result
 
-Not so bad, we have removed the inner loop, meaning with transform a
-:math:`O(n^2)` complexity into :math:`O(n)` complexity. Using the same
-approach, we can now write:
+Not so bad, we have removed the inner loop, transforming :math:`O(n^2)` 
+complexity into :math:`O(n)` complexity. Using the same approach, we can now 
+write:
 
 .. code:: python
 

06-custom-vectorization.rst

@@ -64,11 +64,11 @@ others) for the creation of a `TypedList` object.
            whose __array__ method returns an array, or any (nested) sequence.
 
        sizes:  int or 1-D array
-           If `itemsize is an integer, N, the array will be divided
+           If `itemsize` is an integer, N, the array will be divided
            into elements of size N. If such partition is not possible,
            an error is raised.
 
-           If `itemsize` is 1-D array, the array will be divided into
+           If `itemsize` is a 1-D array, the array will be divided into
            elements whose successive sizes will be picked from itemsize.
            If the sum of itemsize values is different from array size,
            an error is raised.

07-beyond-numpy.rst

@@ -39,7 +39,7 @@ surprising results. But let's start with the most obvious Python solution:
        return Z
 
 This solution is the slowest solution because it requires 4 loops, and more
-importantly, it tests all the different combinations (11641) of 4 integers
+importantly, it tests all the different combinations (14641) of 4 integers
 between 0 and 10 to retain only combinations whose sum is 10. We can of course
 get rid of the 4 loops using itertools, but the code remains slow:
 
@@ -380,8 +380,7 @@ Glumpy
 
 `Glumpy <http://glumpy.github.io>`_ is an OpenGL-based interactive
 visualization library in Python. Its goal is to make it easy to create fast,
-scalable, beautiful, interactive and dynamic visualizations. The main
-documentation for the site is organized into a couple of sections:
+scalable, beautiful, interactive and dynamic visualizations.
 
 
 Conclusion

code/array_list.py

@@ -55,7 +55,7 @@ def __init__(self, data=None, sizes=None, dtype=float, sizeable=True, writeable=
             an error is raised.
 
             If `itemsize` is 1-D array, the array will be divided into
-            elements whose succesive sizes will be picked from itemsize.
+            elements whose successive sizes will be picked from itemsize.
             If the sum of itemsize values is different from array size,
             an error is raised.
 
@@ -298,7 +298,7 @@ def insert(self, index, data, sizes=None):
             an error is raised.
 
             If `itemsize` is 1-D array, the array will be divided into
-            elements whose succesive sizes will be picked from itemsize.
+            elements whose successive sizes will be picked from itemsize.
             If the sum of itemsize values is different from array size,
             an error is raised.
         """
@@ -404,7 +404,7 @@ def append(self, data, sizes=None):
             an error is raised.
 
             If `itemsize` is 1-D array, the array will be divided into
-            elements whose succesive sizes will be picked from itemsize.
+            elements whose successive sizes will be picked from itemsize.
             If the sum of itemsize values is different from array size,
             an error is raised.
         """

code/find_index.py

@@ -7,7 +7,7 @@
 import matplotlib.pyplot as plt
 
 
-def find_view(base, view):
+def find_index(base, view):
     """
     Given an array that is a `view` of a `base`, find an index such that
     `base[index] is view`