#!/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')


# # Special plots in matplotlib

# # Sections

# - [Basic pie chart](#Basic-pie-chart)
# - [Basic triangulation](#Basic-triangulation)
# - [xkcd-style plots](#xkcd-style-plots)

# <br>
# <br>

# # Basic pie chart

# [[back to top](#Sections)]

# In[5]:


from matplotlib import pyplot as plt
import numpy as np

plt.pie(
    (10,5),
    labels=('spam','ham'),
    shadow=True,
    colors=('yellowgreen', 'lightskyblue'),
    explode=(0,0.15), # space between slices 
    startangle=90,    # rotate conter-clockwise by 90 degrees
    autopct='%1.1f%%',# display fraction as percentage
    )
plt.legend(fancybox=True)
plt.axis('equal')     # plot pyplot as circle
plt.tight_layout()
plt.show()


# <br>
# <br>

# # Basic triangulation

# [[back to top](#Sections)]

# In[5]:


from matplotlib import pyplot as plt
import matplotlib.tri as tri
import numpy as np

rand_data = np.random.randn(50, 2)

triangulation = tri.Triangulation(rand_data[:,0], rand_data[:,1])

plt.triplot(triangulation)

plt.show()


# <br>
# <br>

# # xkcd-style plots

# [[back to top](#Sections)]

# In[7]:


import matplotlib.pyplot as plt

x = [1, 2, 3]

y_1 = [50, 60, 70]
y_2 = [20, 30, 40]

with plt.xkcd():

    plt.plot(x, y_1, marker='x')
    plt.plot(x, y_2, marker='^')

    plt.xlim([0, len(x)+1])
    plt.ylim([0, max(y_1+y_2) + 10])
    plt.xlabel('x-axis label')
    plt.ylabel('y-axis label')
    plt.title('Simple line plot')
    plt.legend(['sample 1', 'sample2'], loc='upper left')

    plt.show()


# In[8]:


import numpy as np
import random
from matplotlib import pyplot as plt

data = np.random.normal(0, 20, 1000) 
bins = np.arange(-100, 100, 5) # fixed bin size

with plt.xkcd():
    plt.xlim([min(data)-5, max(data)+5])

    plt.hist(data, bins=bins, alpha=0.5)
    plt.title('Random Gaussian data (fixed bin size)')
    plt.xlabel('variable X (bin size = 5)')
    plt.ylabel('count')

    plt.show()


# In[9]:


from matplotlib import pyplot as plt
import numpy as np

with plt.xkcd():
    X = np.random.random_integers(1,5,5) # 5 random integers within 1-5
    cols = ['b', 'g', 'r', 'y', 'm']
    plt.pie(X, colors=cols)
    plt.legend(X)

    plt.show()


# <br>
# <br>