nyanshell/mandelbrot.py

## mandelbrot.py
from __future__ import division

import numpy as np
from bokeh.plotting import *

from bokeh.resources import CDN
from bokeh.embed import components

from bottle import run, template, route, jinja2_view

# NOTE: if you do not have numba installed, comment out this import,
# and the 'autojit' lines below (the example will run more slowly).
# from numba import autojit

# These functions generate the Mandelbrot set image. Don't worry if
# you are not familiar with them. The import thing is just to know
# that they create a 2D array of numbers that we can colormap.

# @autojit
def mandel(x, y, max_iters):
    """
    Given the real and imaginary parts of a complex number,
    determine if it is a candidate for membership in the Mandelbrot
    set given a fixed number of iterations.
    """
    c = complex(x, y)
    z = 0.0j
    for i in range(max_iters):
        z = z*z + c
        if (z.real*z.real + z.imag*z.imag) >= 4:
            return i
    return max_iters

# @autojit
def create_fractal(min_x, max_x, min_y, max_y, image, iters):
    height = image.shape[0]
    width = image.shape[1]

    pixel_size_x = (max_x - min_x) / width
    pixel_size_y = (max_y - min_y) / height

    for x in range(width):
        real = min_x + x * pixel_size_x
        for y in range(height):
            imag = min_y + y * pixel_size_y
            color = mandel(real, imag, iters)
            image[y, x] = color

# Define the bounding coordinates to generate the Mandelbrot image in. You
# can play around with these.
min_x = -2.0
max_x = 1.0
min_y = -1.0
max_y = 1.0

# Use the functions above to create a scalar image (2D array of numbers)
img = np.zeros((1024, 1536), dtype = np.uint8)
create_fractal(min_x, max_x, min_y, max_y, img, 20)

# EXERCISE: Fill in the missing parameters to use the `image` renderer to
# display the Mandelbrot image 'img' with the title 'Mandelbrot', colormapped
# with the palette 'Spectral-11', and a fixed range given by (min_x, max_x)
# and (min_y, max_y).
#
# NOTE: the `image` renderer can display many images at once, so it takes
# **lists** of images, coordinates, and palettes. Remember to supply sequences
# for these parameters, even if you are just supply one.

min_x = -2.0
max_x = 1.0
min_y = -1.0
max_y = 1.0

image = image(image=[img],
      x=[min_x],
      y=[min_y],
      dw=[max_x-min_x],
      dh=[max_y-min_y],
      palette=["Spectral-11"],
      x_range = [min_x, max_x],
      y_range = [min_y, max_y],
      title="Mandelbrot",
      tools="pan,wheel_zoom,box_zoom,reset,previewsave",
      plot_width=900,
      plot_height=600
)

# EXERCISE: use `image_rgba` to display the image above. Use the following
# cordinates: (x0,y0) = (0,0)  and (x1,y1) = (10,10). Remember to set the
# x_range and y_range explicitly as above.

script, div = components(image, CDN)

render_template = """<!DOCTYPE html>
<html lang="zh-cn">
<head>
  <meta charset="UTF-8">
  <title>Bosondata Analyzer Portal</title>
  <script type="text/javascript" src="https://code.jquery.com/jquery-2.1.1.min.js"></script>
  <script type="text/javascript" src="http://cdn.pydata.org/bokeh-0.6.1.min.js"></script>
  <link href="http://cdn.pydata.org/bokeh-0.6.1.min.css" rel="stylesheet", type="text/css">
  {{script|safe}}
</head>
<body>
========hello==============
  {{div}}
========hello!!!===========
</body>
</html>"""

@route('/hello')
@jinja2_view(render_template)
def hello():
    return {"div": div, "script": script}

run(host='0.0.0.0', port=8080, debug=True)
	from __future__ import division

	import numpy as np
	from bokeh.plotting import *

	from bokeh.resources import CDN
	from bokeh.embed import components

	from bottle import run, template, route, jinja2_view

	# NOTE: if you do not have numba installed, comment out this import,
	# and the 'autojit' lines below (the example will run more slowly).
	# from numba import autojit

	# These functions generate the Mandelbrot set image. Don't worry if
	# you are not familiar with them. The import thing is just to know
	# that they create a 2D array of numbers that we can colormap.

	# @autojit
	def mandel(x, y, max_iters):
	"""
	Given the real and imaginary parts of a complex number,
	determine if it is a candidate for membership in the Mandelbrot
	set given a fixed number of iterations.
	"""
	c = complex(x, y)
	z = 0.0j
	for i in range(max_iters):
	z = z*z + c
	if (z.realz.real + z.imagz.imag) >= 4:
	return i
	return max_iters

	# @autojit
	def create_fractal(min_x, max_x, min_y, max_y, image, iters):
	height = image.shape[0]
	width = image.shape[1]

	pixel_size_x = (max_x - min_x) / width
	pixel_size_y = (max_y - min_y) / height

	for x in range(width):
	real = min_x + x * pixel_size_x
	for y in range(height):
	imag = min_y + y * pixel_size_y
	color = mandel(real, imag, iters)
	image[y, x] = color

	# Define the bounding coordinates to generate the Mandelbrot image in. You
	# can play around with these.
	min_x = -2.0
	max_x = 1.0
	min_y = -1.0
	max_y = 1.0

	# Use the functions above to create a scalar image (2D array of numbers)
	img = np.zeros((1024, 1536), dtype = np.uint8)
	create_fractal(min_x, max_x, min_y, max_y, img, 20)

	# EXERCISE: Fill in the missing parameters to use the `image` renderer to
	# display the Mandelbrot image 'img' with the title 'Mandelbrot', colormapped
	# with the palette 'Spectral-11', and a fixed range given by (min_x, max_x)
	# and (min_y, max_y).
	#
	# NOTE: the `image` renderer can display many images at once, so it takes
	# lists of images, coordinates, and palettes. Remember to supply sequences
	# for these parameters, even if you are just supply one.

	min_x = -2.0
	max_x = 1.0
	min_y = -1.0
	max_y = 1.0

	image = image(image=[img],
	x=[min_x],
	y=[min_y],
	dw=[max_x-min_x],
	dh=[max_y-min_y],
	palette=["Spectral-11"],
	x_range = [min_x, max_x],
	y_range = [min_y, max_y],
	title="Mandelbrot",
	tools="pan,wheel_zoom,box_zoom,reset,previewsave",
	plot_width=900,
	plot_height=600
	)

	# EXERCISE: use `image_rgba` to display the image above. Use the following
	# cordinates: (x0,y0) = (0,0) and (x1,y1) = (10,10). Remember to set the
	# x_range and y_range explicitly as above.

	script, div = components(image, CDN)

	render_template = """<!DOCTYPE html>
	<html lang="zh-cn">
	<head>
	<meta charset="UTF-8">
	<title>Bosondata Analyzer Portal</title>
	<script type="text/javascript" src="https://code.jquery.com/jquery-2.1.1.min.js"></script>
	<script type="text/javascript" src="http://cdn.pydata.org/bokeh-0.6.1.min.js"></script>
	<link href="http://cdn.pydata.org/bokeh-0.6.1.min.css" rel="stylesheet", type="text/css">
	{{script\|safe}}
	</head>
	<body>
	========hello==============
	{{div}}
	========hello!!!===========
	</body>
	</html>"""

	@route('/hello')
	@jinja2_view(render_template)
	def hello():
	return {"div": div, "script": script}

	run(host='0.0.0.0', port=8080, debug=True)