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

# # Image Format vs Fossil Repository Size
# 
# ## Prerequisites
# 
# This notebook was originally developed with standalone [JupyterLab] and Python 2 but was later moved to JupyterLab under [Anaconda] with Python 3. Backporting to Python 2 may require manual adjustment. Getting it running under stock JupyterLab or plain-old-Jupyter should be straightforward for one familiar with the tools. We will assume you're following in my footsteps, using Anaconda.
# 
# One of the reasons we switched to Anaconda is that it comes with all but one of this notebook's prerequisites, that last remaining one of which you install so:
# 
#     $ pip install wand
# 
# That should be done in a shell where "`pip`" is the version that came with Anaconda. Otherwise, the package will likely end up in some *other* Python package tree, which Anaconda's Python kernel may not be smart enough to find on its own.
# 
# Note that you do *not* use `conda` for this: as of this writing, [Wand] is not available in a form that installs via `conda`.
# 
# This notebook was written and tested on a macOS system where `/tmp` exists. Other platforms may require adjustments to the scripts below.
# 
# [Anaconda]:   https://www.anaconda.com/distribution/
# [JupyterLab]: https://github.com/jupyterlab/
# [Wand]:       http://wand-py.org/
# 
# 
# ## Running
# 
# The next cell generates the test repositories. This takes about 3 seconds to run on my machine. If you have to uncomment the "`sleep`" call in the inner loop, this will go up to about 45 seconds.
# 
# The next cell produces the bar chart from the collected data, all but instantaneously.
# 
# This split allows you to generate the expensive experimental data in a single pass, then play as many games as you like with the generated data.
# 
# 
# ## Discussion
# 
# That is kept in [a separate document](image-format-vs-repo-size.md) so we can share that document with Fossil's Markdown renderer.

# In[1]:


import os
import random
import subprocess
import time

from wand.color import Color
from wand.drawing import Drawing
from wand.image import Image

import pandas as pd

size = 256
iterations = 10
start = time.time()
repo_sizes = []
fossil = '/usr/local/bin/fossil'

if not os.path.isfile(fossil): raise RuntimeError("No such executable " + fossil)
if not os.access(fossil, os.X_OK): raise RuntimeError("Cannot execute " + fossil)

tdir = os.path.join('/tmp', 'image-format-vs-repo-size')
if not os.path.isdir(tdir): os.mkdir(tdir, 0o700)
print("Created test directory " + tdir)
    
formats = ['JPEG', 'BMP', 'TIFF', 'PNG']
for f in formats:
    ext = f.lower()
    wdir = os.path.join(tdir, 'work-' + ext)
    if not os.path.isdir(wdir): os.mkdir(wdir, 0o700)
    os.chdir(wdir)
    repo = '../test-' + ext + '.fossil'
    ifn = 'test.' + ext
    ipath = os.path.join(wdir, ifn)
    rs = []
    
    def add_repo_size():
        rs.append(os.path.getsize(repo) / 1024.0 / 1024.0)
        
    def set_repo_page_size(n):
        subprocess.run([
            fossil,
            'rebuild',
            '--compress',
            '--pagesize',
            str(n),
            '--vacuum'
        ])

    try:
        # Create test repo
        subprocess.run([fossil, 'init', repo])
        subprocess.run([fossil, 'open', repo])
        subprocess.run([fossil, 'set', 'binary-glob', "*.{0}".format(ext)])
        set_repo_page_size(512)    # minimum
        add_repo_size()
        set_repo_page_size(8192)   # default
        print("Created " + repo + " for format " + f + ".")

        # Create test image and add it to the repo
        img = Image(width = size, height = size, depth = 8,
                    background = 'white')
        img.alpha_channel = 'remove'
        img.evaluate('gaussiannoise', 1.0)
        img.save(filename = ipath)
        subprocess.run([fossil, 'add', ifn])
        subprocess.run([fossil, 'ci', '-m', 'initial'])
        #print("Added initial " + f + " image.")
        add_repo_size()

        # Change a random pixel to a random RGB value and check it in
        # $iterations times.
        for i in range(iterations - 1):
            with Drawing() as draw:
                x = random.randint(0, size - 1)
                y = random.randint(0, size - 1)

                r = random.randint(0, 255)
                g = random.randint(0, 255)
                b = random.randint(0, 255)
                
                draw.fill_color = Color('rgb({0},{1},{2})'.format(
                    r, g, b
                ))
                draw.color(x, y, 'point')
                draw(img)
                img.save(filename = ipath)
                
                # You might need to uncomment the next line if you find that
                # the repo size doesn't change as expected.  In some versions
                # of Wand (or is it the ImageMagick underneath?) we have seen
                # what appear to be asynchronous saves, with a zero-length file
                # here if you don't wait for the save to complete.
                #time.sleep(1.0)
  
                subprocess.run([fossil, 'ci', '-m', '"change {0} step {1}'.format(
                    f, i
                )])
                add_repo_size()
                
        # Repo complete for this format
        repo_sizes.append(pd.Series(rs, name=f))

    finally:
        if os.path.exists(ipath): os.remove(ipath)
        if os.path.exists(tdir):
            if os.path.isfile(repo):
                subprocess.run([fossil, 'close', '-f'])
                os.unlink(repo)
            os.chdir(tdir);
            os.rmdir(wdir)
        if os.path.exists(repo): os.remove(repo)
            
print("Experiment completed in " + str(time.time() - start) + " seconds.")


# In[1]:


get_ipython().run_line_magic('config', "InlineBackend.figure_formats = ['svg']")

import matplotlib as mpl
import matplotlib.pyplot as plt
import pandas as pd

os.chdir(tdir)

# Merge per-format test data into a single DataFrame without the first
# first row, being the boring initial empty repo state.
data = pd.concat(repo_sizes, axis=1).drop(range(1))

mpl.rcParams['figure.figsize'] = (6, 4)
ax = data.plot(kind = 'bar', colormap = 'coolwarm',
          grid = False, width = 0.8,
          edgecolor = 'white', linewidth = 2)
ax.axes.set_xlabel('Checkin index')
ax.axes.set_ylabel('Repo size (MiB)')
plt.savefig('image-format-vs-repo-size.svg', transparent=True)
plt.show()


# In[ ]: