Add some small patches to Text Intro Guide.

bingyao · bingyao · commit f6a742788206 · 2019-07-07T00:09:52.000+08:00
diff --git a/tutorials/text/text_intro.py b/tutorials/text/text_intro.py
@@ -69,15 +69,19 @@
 import matplotlib.pyplot as plt
 
 fig = plt.figure()
-fig.suptitle('bold figure suptitle', fontsize=14, fontweight='bold')
-
 ax = fig.add_subplot(111)
 fig.subplots_adjust(top=0.85)
+
+# Set titles for the figure and the subplot respectively
+fig.suptitle('bold figure suptitle', fontsize=14, fontweight='bold')
 ax.set_title('axes title')
 
 ax.set_xlabel('xlabel')
 ax.set_ylabel('ylabel')
 
+# Set both x- and y-axis limits to [0, 10] instead of default [0, 1]
+ax.axis([0, 10, 0, 10])
+
 ax.text(3, 8, 'boxed italics text in data coords', style='italic',
         bbox={'facecolor': 'red', 'alpha': 0.5, 'pad': 10})
 
@@ -90,13 +94,10 @@
         transform=ax.transAxes,
         color='green', fontsize=15)
 
-
 ax.plot([2], [1], 'o')
 ax.annotate('annotate', xy=(2, 1), xytext=(3, 4),
             arrowprops=dict(facecolor='black', shrink=0.05))
 
-ax.axis([0, 10, 0, 10])
-
 plt.show()
 
 ###############################################################################
@@ -157,8 +158,7 @@
 fig, ax = plt.subplots(figsize=(5, 3))
 fig.subplots_adjust(bottom=0.15, left=0.2)
 ax.plot(x1, y1)
-ax.set_xlabel('time [s]', position=(0., 1e6),
-                      horizontalalignment='left')
+ax.set_xlabel('time [s]', position=(0., 1e6), horizontalalignment='left')
 ax.set_ylabel('Damped oscillation [V]')
 
 plt.show()
@@ -226,34 +226,33 @@
 # ====================
 #
 # Placing ticks and ticklabels is a very tricky aspect of making a figure.
-# Matplotlib does the best it can automatically, but it also offers a very
-# flexible framework for determining the choices for tick locations, and
-# how they are labelled.
+# Matplotlib does its best to accomplish the task automatically, but it also
+# offers a very flexible framework for determining the choices for tick
+# locations, and how they are labelled.
 #
 # Terminology
 # ~~~~~~~~~~~
 #
-# *Axes* have an `matplotlib.axis` object for the ``ax.xaxis``
-# and ``ax.yaxis`` that
-# contain the information about how the labels in the axis are laid out.
+# *Axes* have a `matplotlib.axis` object for the ``ax.xaxis`` and ``ax.yaxis``
+# that contain the information about how the labels in the axis are laid out.
 #
 # The axis API is explained in detail in the documentation to
 # `~matplotlib.axis`.
 #
-# An Axis object has major and minor ticks.  The Axis has a
+# An Axis object has major and minor ticks.  The Axis has
 # `matplotlib.xaxis.set_major_locator` and
 # `matplotlib.xaxis.set_minor_locator` methods that use the data being plotted
 # to determine
 # the location of major and minor ticks.  There are also
 # `matplotlib.xaxis.set_major_formatter` and
-# `matplotlib.xaxis.set_minor_formatters` methods that format the tick labels.
+# `matplotlib.xaxis.set_minor_formatter` methods that format the tick labels.
 #
 # Simple ticks
 # ~~~~~~~~~~~~
 #
 # It often is convenient to simply define the
 # tick values, and sometimes the tick labels, overriding the default
-# locators and formatters.  This is discouraged because it breaks itneractive
+# locators and formatters.  This is discouraged because it breaks interactive
 # navigation of the plot.  It also can reset the axis limits: note that
 # the second plot has the ticks we asked for, including ones that are
 # well outside the automatic view limits.
@@ -285,8 +284,9 @@
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 #
 # Instead of making a list of all the tickalbels, we could have
-# used a `matplotlib.ticker.FormatStrFormatter` and passed it to the
-# ``ax.xaxis``
+# used `matplotlib.ticker.StrMethodFormatter` (new-style ``str.format()``
+# format string) or `matplotlib.ticker.FormatStrFormatter` (old-style '%'
+# format string) and passed it to the ``ax.xaxis``.
 
 fig, axs = plt.subplots(2, 1, figsize=(5, 3), tight_layout=True)
 axs[0].plot(x1, y1)
@@ -362,6 +362,7 @@ def formatoddticks(x, pos):
     else:
         return ''
 
+
 fig, ax = plt.subplots(figsize=(5, 3), tight_layout=True)
 ax.plot(x1, y1)
 formatter = matplotlib.ticker.FuncFormatter(formatoddticks)
@@ -383,17 +384,17 @@ def formatoddticks(x, pos):
 #
 # A simple example is as follows.  Note how we have to rotate the
 # tick labels so that they don't over-run each other.
+
 import datetime
 
 fig, ax = plt.subplots(figsize=(5, 3), tight_layout=True)
 base = datetime.datetime(2017, 1, 1, 0, 0, 1)
-time = [base + datetime.timedelta(days=x) for x in range(len(y1))]
+time = [base + datetime.timedelta(days=x) for x in range(len(x1))]
 
 ax.plot(time, y1)
 ax.tick_params(axis='x', rotation=70)
 plt.show()
 
-
 ##############################################################################
 # We can pass a format
 # to `matplotlib.dates.DateFormatter`.  Also note that the 29th and the
