ie (without a comma) to i.e.,

yuvallanger · yuvallanger · commit 2213ac87829b · 2014-11-01T19:42:27.000+02:00
Used:

```bash
find * -type f -exec sed -i 's/\bie\b/i.e.,/g' {} \;
```

Restructuring &gt;80 character docstring
diff --git a/doc/api/api_changes.rst b/doc/api/api_changes.rst
@@ -2078,7 +2078,7 @@ Transformations
   implementations, matplotlib.transforms.SeparableTransformation and
   matplotlib.transforms.Affine.  The SeparableTransformation is
   constructed with the bounding box of the input (this determines the
-  rectangular coordinate system of the input, ie the x and y view
+  rectangular coordinate system of the input, i.e., the x and y view
   limits), the bounding box of the display, and possibly nonlinear
   transformations of x and y.  The 2 most frequently used
   transformations, data coordinates -> display and axes coordinates ->
diff --git a/doc/faq/usage_faq.rst b/doc/faq/usage_faq.rst
@@ -295,7 +295,7 @@ others in web application servers to dynamically serve up graphs.
 
 To support all of these use cases, matplotlib can target different
 outputs, and each of these capabilities is called a backend; the
-"frontend" is the user facing code, ie the plotting code, whereas the
+"frontend" is the user facing code, i.e., the plotting code, whereas the
 "backend" does all the hard work behind-the-scenes to make the figure.
 There are two types of backends: user interface backends (for use in
 pygtk, wxpython, tkinter, qt4, or macosx; also referred to as
diff --git a/examples/pylab_examples/broken_barh.py b/examples/pylab_examples/broken_barh.py
@@ -1,5 +1,5 @@
 """
-Make a "broken" horizontal bar plot, ie one with gaps
+Make a "broken" horizontal bar plot, i.e., one with gaps
 """
 import matplotlib.pyplot as plt
 
diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py
@@ -2213,11 +2213,11 @@ def broken_barh(self, xranges, yrange, **kwargs):
 
         %(BrokenBarHCollection)s
 
-        these can either be a single argument, ie::
+        these can either be a single argument, i.e.,::
 
           facecolors = 'black'
 
-        or a sequence of arguments for the various bars, ie::
+        or a sequence of arguments for the various bars, i.e.,::
 
           facecolors = ('black', 'red', 'green')
 
@@ -5420,8 +5420,8 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
         normed : boolean, optional, default: False
             If `True`, the first element of the return tuple will
             be the counts normalized to form a probability density, i.e.,
-            ``n/(len(x)`dbin)``, ie the integral of the histogram will sum to
-            1. If *stacked* is also *True*, the sum of the histograms is
+            ``n/(len(x)`dbin)``, i.e., the integral of the histogram will sum
+            to 1. If *stacked* is also *True*, the sum of the histograms is
             normalized to 1.
 
         weights : array_like, shape (n, ), optional, default: None
diff --git a/lib/matplotlib/collections.py b/lib/matplotlib/collections.py
@@ -70,7 +70,7 @@ class Collection(artist.Artist, cm.ScalarMappable):
 
     The use of :class:`~matplotlib.cm.ScalarMappable` is optional.  If
     the :class:`~matplotlib.cm.ScalarMappable` matrix _A is not None
-    (ie a call to set_array has been made), at draw time a call to
+    (i.e., a call to set_array has been made), at draw time a call to
     scalar mappable will be made to set the face colors.
     """
     _offsets = np.array([], np.float_)
@@ -1030,7 +1030,7 @@ def __init__(self, segments,     # Can be None.
 
         The use of :class:`~matplotlib.cm.ScalarMappable` is optional.
         If the :class:`~matplotlib.cm.ScalarMappable` array
-        :attr:`~matplotlib.cm.ScalarMappable._A` is not None (ie a call to
+        :attr:`~matplotlib.cm.ScalarMappable._A` is not None (i.e., a call to
         :meth:`~matplotlib.cm.ScalarMappable.set_array` has been made), at
         draw time a call to scalar mappable will be made to set the colors.
         """
@@ -1190,7 +1190,7 @@ def __init__(self,
 
         The use of :class:`~matplotlib.cm.ScalarMappable` is optional.
         If the :class:`~matplotlib.cm.ScalarMappable` array
-        :attr:`~matplotlib.cm.ScalarMappable._A` is not None (ie a call to
+        :attr:`~matplotlib.cm.ScalarMappable._A` is not None (i.e., a call to
         :meth:`~matplotlib.cm.ScalarMappable.set_array` has been made), at
         draw time a call to scalar mappable will be made to set the colors.
 
@@ -1517,7 +1517,7 @@ def __init__(self, patches, match_original=False, **kwargs):
 
         The use of :class:`~matplotlib.cm.ScalarMappable` is optional.
         If the :class:`~matplotlib.cm.ScalarMappable` matrix _A is not
-        None (ie a call to set_array has been made), at draw time a
+        None (i.e., a call to set_array has been made), at draw time a
         call to scalar mappable will be made to set the face colors.
         """
 
diff --git a/lib/matplotlib/mlab.py b/lib/matplotlib/mlab.py
@@ -1677,7 +1677,7 @@ def __init__(self, a, standardize=True):
           *Y* : a projected into PCA space
 
 
-        The factor loadings are in the Wt factor, ie the factor
+        The factor loadings are in the Wt factor, i.e., the factor
         loadings for the 1st principal component are given by Wt[0].
         This row is also the 1st eigenvector.
 
diff --git a/lib/matplotlib/quiver.py b/lib/matplotlib/quiver.py
@@ -915,7 +915,7 @@ def _find_tails(self, mag, rounding=True, half=5, full=10, flag=50):
         '''
         Find how many of each of the tail pieces is necessary.  Flag
         specifies the increment for a flag, barb for a full barb, and half for
-        half a barb. Mag should be the magnitude of a vector (ie. >= 0).
+        half a barb. Mag should be the magnitude of a vector (i.e., >= 0).
 
         This returns a tuple of:
 
diff --git a/lib/matplotlib/ticker.py b/lib/matplotlib/ticker.py
@@ -993,7 +993,7 @@ class IndexLocator(Locator):
     """
     Place a tick on every multiple of some base number of points
     plotted, e.g., on every 5th point.  It is assumed that you are doing
-    index plotting; ie the axis is 0, len(data).  This is mainly
+    index plotting; i.e., the axis is 0, len(data).  This is mainly
     useful for x ticks.
     """
     def __init__(self, base, offset):
diff --git a/lib/mpl_toolkits/axes_grid1/axes_divider.py b/lib/mpl_toolkits/axes_grid1/axes_divider.py
@@ -390,7 +390,7 @@ def __init__(self, fig, *args, **kwargs):
 
         # total = rows*cols
         # num -= 1    # convert from matlab to python indexing
-        #             # ie num in range(0,total)
+        #             # i.e., num in range(0,total)
         # if num >= total:
         #     raise ValueError( 'Subplot number exceeds total subplots')
         # self._rows = rows
