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

# # Custom Display Logic Exercises

# In[1]:


from IPython.display import display
from IPython.display import (
    display_png, display_html, display_latex,
    display_javascript, display_svg
)


# ## Circle class with custom display methods

# Write a simple `MyCircle` Python class. Here is a skeleton to get you started:
# 
# ```python
# class MyCircle(object):
#     def __init__(self, center=(0.0,0.0), radius=1.0, color='blue'):
#         self.center = center
#         self.radius = radius
#         self.color = color
# ```
# 
# Now add special display methods to this class for the following representations (remember to wrap them in Python strings):
# 
# For HTML:
# 
#     ○
# 
# For LaTeX (wrap with `$` and use a raw Python string):
# 
#     \bigcirc
# 
# For JavaScript:
# 
#     alert('I am a circle!');
# 
# After you write the class, create an instance and then use `display_html`, `display_svg`, `display_latex` and `display_javascript` to display those representations.

# ### Solution

# Here is the solution to the simple `MyCircle` class:

# In[ ]:


get_ipython().run_line_magic('load', 'soln/mycircle.py')


# Now create an instance and use the display methods:

# In[ ]:


c = MyCircle()


# In[ ]:


display(c)


# In[ ]:


display_html(c)


# In[ ]:


display_latex(c)


# ## PNG formatter for `MyCircle`

# In[ ]:


get_ipython().run_line_magic('matplotlib', 'inline')
from matplotlib import pyplot as plt


# Now let's assume that the `MyCircle` class has already been defined and add a PNG representation using a formatter display function. Here is a function that converts a `MyCircle` instance to raw PNG data.

# In[ ]:


from IPython.core.pylabtools import print_figure

def circle_to_png(circle):
    """Render AnotherCircle to png data using matplotlib"""
    fig, ax = plt.subplots()
    patch = plt.Circle(circle.center,
                       radius=circle.radius,
                       fc=circle.color,
                       )
    ax.add_patch(patch)
    plt.axis('scaled')
    data = print_figure(fig, 'png')
    # We MUST close the figure, otherwise IPython's display machinery
    # will pick it up and send it as output, resulting in a double display
    plt.close(fig)
    return data


# Now use the IPython API to get the PNG formatter (`image/png`) and call the `for_type` method to register `circle_to_png` as the display function for `MyCircle`.

# In[ ]:


get_ipython().run_line_magic('load', 'soln/mycircle_png.py')


# In[ ]:


display_png(c)


# ## PNG formatter for NumPy arrays

# In this exercise, you will register a display formatter function that generates a PNG representation of a 2d NumPy array. Here is the function that uses the [Python Imaging Library (PIL)](http://www.pythonware.com/products/pil/) to generate the raw PNG data:

# In[ ]:


from PIL import Image
from io import BytesIO
import numpy as np

def ndarray_to_png(x):
    if len(x.shape) != 2: return
    x = np.asarray(Image.fromarray(x).resize((500, 500)))
    x = (x - x.min()) / (x.max() - x.min())
    img = Image.fromarray((x*256).astype('uint8'))
    img_buffer = BytesIO()
    img.save(img_buffer, format='png')
    return img_buffer.getvalue()


# Use the `for_type` method of the PNG formatter to register `ndarray_to_png` as the display function for `np.ndarray`.

# In[ ]:


get_ipython().run_line_magic('load', 'soln/ndarray_png.py')


# Now create a few NumPy arrays and display them. Notice that their default representation in the Notebook is PNG rather than text.

# In[ ]:


a = np.random.rand(100,100)


# In[ ]:


a


# You can still display the plain text representation using the `display_pretty` function.

# In[ ]:


from IPython.display import display_pretty


# In[ ]:


display_pretty(a)


# In[ ]:


b = np.linspace(0,100.0, 100**2).reshape((100,100))


# In[ ]:


b