#!/usr/bin/env python
# coding: utf-8

# [Sebastian Raschka](http://www.sebastianraschka.com)
# 
# [back](https://github.com/rasbt/matplotlib-gallery) to the `matplotlib-gallery` at [https://github.com/rasbt/matplotlib-gallery](https://github.com/rasbt/matplotlib-gallery)

# In[1]:


get_ipython().run_line_magic('load_ext', 'watermark')


# In[2]:


get_ipython().run_line_magic('watermark', '-u -v -d -p matplotlib,numpy')


# <font size="1.5em">[More info](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/ipython_magic/watermark.ipynb) about the `%watermark` extension</font>

# In[3]:


get_ipython().run_line_magic('matplotlib', 'inline')


# <br>
# <br>

# # Matplotlib Formatting IV: Style Sheets

# One of the coolest features added to matlotlib 1.5 is the support for "styles"! The "styles" functionality allows us to create beautiful plots rather painlessly -- a great feature for everyone who though that matplotlib's default layout looks a bit dated!

# <br>
# <br>

# # Sections

# The styles that are currently included can be listed via `print(plt.style.available)`:

# In[8]:


import matplotlib.pyplot as plt

print(plt.style.available)


# Now, there are two ways to apply the styling to our plots. First, we can set the style for our coding environment globally via the `plt.style.use` function:

# In[6]:


import numpy as np

plt.style.use('ggplot')

x = np.arange(10)
for i in range(1, 4):
    plt.plot(x, i * x**2, label='Group %d' % i)
plt.legend(loc='best')
plt.show()


# Another way to use styles is via the `with` context manager, which applies the styling to a specific code block only:

# In[7]:


with plt.style.context('fivethirtyeight'):
    for i in range(1, 4):
        plt.plot(x, i * x**2, label='Group %d' % i)
    plt.legend(loc='best')
    plt.show()


# Finally, here's an overview of how the different styles look like:

# In[56]:


import math

n = len(plt.style.available)
num_rows = math.ceil(n/4)

fig = plt.figure(figsize=(15, 15))

for i, s in enumerate(plt.style.available):
    with plt.style.context(s):
        ax = fig.add_subplot(num_rows, 4, i+1)
        for i in range(1, 4):
            ax.plot(x, i * x**2, label='Group %d' % i)
            ax.set_xlabel(s, color='black')
            ax.legend(loc='best')
    
fig.tight_layout()
plt.show()


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