fix typos and unused imports in ex/event_handling

Author: ivanov

examples/event_handling/data_browser.py

@@ -5,7 +5,7 @@ class PointBrowser:
     """
     Click on a point to select and highlight it -- the data that
     generated the point will be shown in the lower axes.  Use the 'n'
-    and 'p' keys to browse through the next and pervious points
+    and 'p' keys to browse through the next and previous points
     """
     def __init__(self):
         self.lastind = 0

examples/event_handling/lasso_demo.py

@@ -8,7 +8,6 @@
 inside polygon detection routine.
 """
 from matplotlib.widgets import Lasso
-import matplotlib.mlab
 from matplotlib.nxutils import points_inside_poly
 from matplotlib.colors import colorConverter
 from matplotlib.collections import RegularPolyCollection

examples/event_handling/legend_picking.py

@@ -28,7 +28,7 @@
 
 def onpick(event):
     # on the pick event, find the orig line corresponding to the
-    # legend proxy line, and toggle the visibilit
+    # legend proxy line, and toggle the visibility
     legline = event.artist
     origline = lined[legline]
     vis = not origline.get_visible()

examples/event_handling/path_editor.py

@@ -2,7 +2,6 @@
 import matplotlib.path as mpath
 import matplotlib.patches as mpatches
 import matplotlib.pyplot as plt
-import matplotlib.mlab as mlab
 
 Path = mpath.Path
 

examples/event_handling/pick_event_demo.py

@@ -2,8 +2,8 @@
 
 """
 
-You can enable picking by setting the"picker" property of an artist
-(eg a matplotlib Line2D, Text, Patch, Polygon, AxesImage,
+You can enable picking by setting the "picker" property of an artist
+(for example, a matplotlib Line2D, Text, Patch, Polygon, AxesImage,
 etc...)
 
 There are a variety of meanings of the picker property
@@ -15,27 +15,27 @@
       the artist
 
     float - if picker is a number it is interpreted as an
-      epsilon tolerance in points and the the artist will fire
+      epsilon tolerance in points and the artist will fire
       off an event if it's data is within epsilon of the mouse
       event.  For some artists like lines and patch collections,
       the artist may provide additional data to the pick event
-      that is generated, eg the indices of the data within
+      that is generated, for example, the indices of the data within
       epsilon of the pick event
 
-     function - if picker is callable, it is a user supplied
+    function - if picker is callable, it is a user supplied
       function which determines whether the artist is hit by the
       mouse event.
 
          hit, props = picker(artist, mouseevent)
 
-      to determine the hit test.  if the mouse event is over the
+      to determine the hit test.  If the mouse event is over the
       artist, return hit=True and props is a dictionary of properties
       you want added to the PickEvent attributes
 
 
 After you have enabled an artist for picking by setting the "picker"
 property, you need to connect to the figure canvas pick_event to get
-pick callbacks on mouse press events.  Eg,
+pick callbacks on mouse press events.  For example,
 
   def pick_handler(event):
       mouseevent = event.mouseevent
@@ -47,9 +47,9 @@ def pick_handler(event):
 your callback is always fired with two attributes:
 
   mouseevent - the mouse event that generate the pick event.  The
-    mouse event in turn has attributes like x and y (the coords in
-    display space, eg pixels from left, bottom) and xdata, ydata (the
-    coords in data space).  Additionaly, you can get information about
+    mouse event in turn has attributes like x and y (the coordinates in
+    display space, such as pixels from left, bottom) and xdata, ydata (the
+    coords in data space).  Additionally, you can get information about
     which buttons were pressed, which keys were pressed, which Axes
     the mouse is over, etc.  See matplotlib.backend_bases.MouseEvent
     for details.
@@ -58,8 +58,8 @@ def pick_handler(event):
 
 Additionally, certain artists like Line2D and PatchCollection may
 attach additional meta data like the indices into the data that meet
-the picker criteria (eg all the points in the line that are within the
-specified epsilon tolerance)
+the picker criteria (for example, all the points in the line that are within
+the specified epsilon tolerance)
 
 The examples below illustrate each of these methods.
 """

examples/event_handling/pick_event_demo2.py

@@ -1,7 +1,7 @@
 """
-compute the mean and stddev of 100 data sets and plot mean vs stddev.
-When you click on one of the mu, sigma points, plot the raw data from
-the dataset that generated the mean and stddev
+compute the mean and standard deviation (stddev) of 100 data sets and plot
+mean vs stddev.  When you click on one of the mu, sigma points, plot the raw
+data from the dataset that generated the mean and stddev.
 """
 import numpy
 import matplotlib.pyplot as plt
@@ -31,7 +31,7 @@ def onpick(event):
         ax.plot(X[dataind])
         ax.text(0.05, 0.9, 'mu=%1.3f\nsigma=%1.3f'%(xs[dataind], ys[dataind]),
                 transform=ax.transAxes, va='top')
-        ax.set_ylim(-0.5, 1.5)        
+        ax.set_ylim(-0.5, 1.5)
     figi.show()
     return True
 

examples/event_handling/pipong.py

@@ -1,6 +1,6 @@
 #!/usr/bin/env python
 # A matplotlib based game of Pong illustrating one way to write interactive
-# animation which are easily ported to multiply backends
+# animation which are easily ported to multiple backends
 # pipong.py was written by Paul Ivanov <http://pirsquared.org>
 
 from __future__ import print_function

examples/event_handling/pong_gtk.py

@@ -12,10 +12,8 @@
 import matplotlib
 matplotlib.use('GTKAgg')
 
-import numpy as np
 import matplotlib.pyplot as plt
 import pipong
-from numpy.random import randn, randint
 
 
 fig = plt.figure()

examples/event_handling/pong_qt.py

@@ -3,7 +3,6 @@
 
 from __future__ import print_function
 
-import os, sys
 import matplotlib
 matplotlib.use('QtAgg') # qt3 example
 
@@ -16,12 +15,9 @@
 FALSE = 0
 ITERS = 1000
 
-import pylab as p
 import matplotlib.pyplot as plt
-import numpy as np
 import time
 import pipong
-from numpy.random import randn, randint
 
 class BlitQT(QObject):
     def __init__(self):

examples/event_handling/zoom_window.py

@@ -1,10 +1,10 @@
 """
-This example shows how to connect events in one window, eg a mouse
+This example shows how to connect events in one window, for example, a mouse
 press, to another figure window.
 
 If you click on a point in the first window, the z and y limits of the
 second will be adjusted so that the center of the zoom in the second
-window will be the x,y coords of the clicked point.
+window will be the x,y coordinates of the clicked point.
 
 Note the diameter of the circles in the scatter are defined in
 points**2, so their size is independent of the zoom