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

# # Matplotlib styles examples
# 
# The matplotlib documentation is pretty incomplete, and all you really want to know about its style sheets is what they look like - but they're not shown in an easily comparable way. So here they are!

# In[49]:


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

from matplotlib import pyplot as plt
import numpy as np

sorted(plt.style.available)


# ## And what do they look like?
# 
# To globally change the style, use `plt.style.use(<name>)`. Here, we're going to temporarily switch between them using the context manager form: `with plt.style.context((<name>))`. But first let's set up the plots we want to show.

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def make_title(s):
    return s.replace('-', ' ').replace('_', ' ').title()


def make_plots(style_str=None):
    fig, axes_array = plt.subplots(2, 2)
    ((ax1, ax2), (ax3, ax4)) = axes_array
    
    # sine and cosine line plots
    x = np.arange(10)
    y_sin = np.sin(x)
    y_cos = np.cos(x)
    ax1.plot(x, y_sin)
    ax1.plot(x, y_cos)
    ax1.set_title('sine and cosine line plots')
    
    # a random scatter plot
    points1 = np.random.rand(20,2)
    points2 = np.random.rand(20,2)
    ax2.scatter(points1[:, 0], points1[:, 1])
    ax2.scatter(points2[:, 0], points1[:, 1])
    ax2.set_title('a random scatter plot')
    
    # a random bar graph
    width = 0.4
    middles = np.arange(1, 6)
    heights1 = np.random.rand(5)
    heights2 = np.random.rand(5)
    ax3.bar(middles - width, heights1, width)
    ax3.bar(middles, heights2, width)
    ax3.set_title('a random bar graph')
    
    # a random pie chart
    values = np.random.rand(5)
    frac_values = values/values.sum()
    labels = ['A', 'B', 'C', 'D', 'E']
    ax4.pie(frac_values, labels=labels)
    ax4.set_title('a random pie chart')
    
    # draw them!
    fig.suptitle('{} ({})'.format(make_title(style_str), style_str) if style_str else 'Default Settings', fontsize=20)
    fig.subplots_adjust(hspace=0.3)
    fig.set_size_inches(10, 10)
    plt.show()


# ## Things you'll note
# 
# - Pie charts don't play nice with style sheet colours
# - Seaborn styles are generally quite nice (note: your matplotlib starts using a seaborn style if you simply `import seaborn`!) 
# - Matlab-like styles make horrible graphs for horrible people
# - None of these plots are really ready for presenting without more tinkering! 

# ### Default settings

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make_plots()


# ### Seaborn Darkgrid (`'seaborn-darkgrid'`)

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with plt.style.context(('seaborn-darkgrid')):
    make_plots('seaborn-darkgrid')        


# ### Seaborn Whitegrid (`'seaborn-whitegrid'`)

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with plt.style.context(('seaborn-whitegrid')):
    make_plots('seaborn-whitegrid')        


# ### Seaborn Dark Palette (`'seaborn-dark-palette'`)

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with plt.style.context(('seaborn-dark-palette')):
    make_plots('seaborn-dark-palette')        


# ### Seaborn Paper (`'seaborn-paper'`)

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with plt.style.context(('seaborn-paper')):
    make_plots('seaborn-paper')        


# ### Seaborn Talk (`'seaborn-talk'`)

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with plt.style.context(('seaborn-talk')):
    make_plots('seaborn-talk')        


# ### Seaborn Dark (`'seaborn-dark'`)

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with plt.style.context(('seaborn-dark')):
    make_plots('seaborn-dark')        


# ### Seaborn Bright (`'seaborn-bright'`)

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with plt.style.context(('seaborn-bright')):
    make_plots('seaborn-bright')        


# ### Ggplot (`'ggplot'`)

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with plt.style.context(('ggplot')):
    make_plots('ggplot')        


# ### Grayscale (`'grayscale'`)

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with plt.style.context(('grayscale')):
    make_plots('grayscale')        


# ### Seaborn Pastel (`'seaborn-pastel'`)

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with plt.style.context(('seaborn-pastel')):
    make_plots('seaborn-pastel')        


# ### Bmh (`'bmh'`)

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with plt.style.context(('bmh')):
    make_plots('bmh')        


# ### Seaborn Colorblind (`'seaborn-colorblind'`)

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with plt.style.context(('seaborn-colorblind')):
    make_plots('seaborn-colorblind')        


# ### Seaborn Ticks (`'seaborn-ticks'`)

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with plt.style.context(('seaborn-ticks')):
    make_plots('seaborn-ticks')        


# ### Fivethirtyeight (`'fivethirtyeight'`)

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with plt.style.context(('fivethirtyeight')):
    make_plots('fivethirtyeight')        


# ### Dark Background (`'dark_background'`)

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with plt.style.context(('dark_background')):
    make_plots('dark_background')        


# ### Seaborn White (`'seaborn-white'`)

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with plt.style.context(('seaborn-white')):
    make_plots('seaborn-white')        


# ### Classic (`'classic'`)

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with plt.style.context(('classic')):
    make_plots('classic')        


# ### Seaborn Notebook (`'seaborn-notebook'`)

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with plt.style.context(('seaborn-notebook')):
    make_plots('seaborn-notebook')        


# ### Seaborn Muted (`'seaborn-muted'`)

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with plt.style.context(('seaborn-muted')):
    make_plots('seaborn-muted')        


# ### Seaborn Deep (`'seaborn-deep'`)

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with plt.style.context(('seaborn-deep')):
    make_plots('seaborn-deep')        


# ### Seaborn Poster (`'seaborn-poster'`)

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with plt.style.context(('seaborn-poster')):
    make_plots('seaborn-poster')