matplotlib · cubreto · Sep 27, 2014 · Sep 27, 2014 · tacaswell · Sep 27, 2014
diff --git a/examples/api/two_scales.py b/examples/api/two_scales.py
@@ -1,44 +1,86 @@
 #!/usr/bin/env python
-"""
 
-Demonstrate how to do two plots on the same axes with different left
-right scales.
+import numpy as np
+import matplotlib.pyplot as plt
 
 
-The trick is to use *2 different axes*.  Turn the axes rectangular
-frame off on the 2nd axes to keep it from obscuring the first.
-Manually set the tick locs and labels as desired.  You can use
-separate matplotlib.ticker formatters and locators as desired since
-the two axes are independent.
 
-This is achieved in the following example by calling the Axes.twinx()
-method, which performs this work. See the source of twinx() in
-axes.py for an example of how to do it for different x scales. (Hint:
-use the xaxis instance and call tick_bottom and tick_top in place of
-tick_left and tick_right.)
+def two_scales(ax1, ax2, time, data1, data2, param1_dic , param2_dic):
+    """
 
-The twinx and twiny methods are also exposed as pyplot functions.
 
-"""
+    Demonstrate how to do two plots on the same axes with different left
+    right scales.
+
+
+    The trick is to use *2 different axes*.  Turn the axes rectangular
+    frame off on the 2nd axes to keep it from obscuring the first.
+    Manually set the tick locs and labels as desired.  You can use
+    separate matplotlib.ticker formatters and locators as desired since
+    the two axes are independent.
+
+    This is achieved in the following example by calling the Axes.twinx()
+    method, which performs this work. See the source of twinx() in
+    axes.py for an example of how to do it for different x scales. (Hint:
+    use the xaxis instance and call tick_bottom and tick_top in place of
+    tick_left and tick_right.)
+
+    The twinx and twiny methods are also exposed as pyplot functions.
 
-import numpy as np
-import matplotlib.pyplot as plt
+    Parameters
+    ----------
+    ax : (type of axis)
+        A description of axis
+
+    data1: (first dataset)
+        A description of data1
+
+    data2 : (first dataset)
+        A description of data2
+
+    param_dic : This is a dictionary of the parameters of the style and color e.g. {line style: '-', text color = 'r'}
+    Returns
+    -------
+    Overlays
+    data1 : (Plot first data set)
+    data2 : (Plot second data set)
+
+     """
+    def color_y_axes(ax, color):
+        """Color your axes."""
+        for t in ax.get_yticklabels():
+            t.set_color(color)
+        return None  
+
+
+    ax1.plot(time, data1, param1_dic['color'] + param1_dic['style'])
+    ax1.set_xlabel('time (s)')
+    # Make the y-axis label and tick labels match the line color.
+    ax1.set_ylabel('exp', color=param1_dic['color'])
+    color_y_axes(ax1, param1_dic['color'])
+
+
+    ax2.plot(time, data2, param2_dic['color'] + param2_dic['style'])
+    ax2.set_ylabel('sin', color=param2_dic['color'])
+    color_y_axes(ax2, param2_dic['color'])
+    return plt.show()
 
-fig, ax1 = plt.subplots()
+#Create some mock data
 t = np.arange(0.01, 10.0, 0.01)
 s1 = np.exp(t)
-ax1.plot(t, s1, 'b-')
-ax1.set_xlabel('time (s)')
-# Make the y-axis label and tick labels match the line color.
-ax1.set_ylabel('exp', color='b')
-for tl in ax1.get_yticklabels():
-    tl.set_color('b')
+s2 = np.sin(2*np.pi*t)
+
+#Specify your parameter dictionary
+d1 = {'style': '-', 'color' : 'r'}
+d2 = {'style': '.', 'color' :'b'}
+
+#create your axes
+fig, ax = plt.subplots()
+ax2 = ax.twinx()
+
+#Call the function
+two_scales(ax, ax2, t, s1, s2, d1, d2)
+
+
 
 
-ax2 = ax1.twinx()
-s2 = np.sin(2*np.pi*t)
-ax2.plot(t, s2, 'r.')
-ax2.set_ylabel('sin', color='r')
-for tl in ax2.get_yticklabels():
-    tl.set_color('r')
-plt.show()