In [41]:

    

class JuliaSet():
    import numpy as np
    
    def __init__(self, c, n=100): # This is the data for the class - 
        self.c = c     
        self.n = n
        self._d = 0.001
        self.set = [ ]
        self._complexplane = [ ]
    
    def juliamap(self, z) : # This is the method for the class 
        return (z**2 + self.c)
    

    def  iterate(self, z):  # This is the method for the class
        m = 0
        while True:
            z = self.juliamap(z)
            m = m+1
            if abs(z) > 2 :
                return(m)
            elif m >= self.n :
                return(0)

            
    def create_complexplane(self,d) :
        list1 = [ ]
        coun = np.arange(-2,2,d)
        list1=[complex(x,y) for x in coun for y in coun]
        return list1 
    

    def set_spacing(self, d) : # This is the method for the class 
        self._d = d
        self._complexplane = self.create_complexplane(self._d)
        #print self._complexplane  # to troubleshoot the code
   
    def generate(self) :
        self.set_spacing(self._d)
        for complex_number in self._complexplane:
             self.set.append(self.iterate(complex_number))
        return self.set


    

In [46]:

    

j = JuliaSet(0)
j.set_spacing(0.5)
print j._complexplane
print j.generate()


    

    




[(-2-2j), (-2-1.5j), (-2-1j), (-2-0.5j), (-2+0j), (-2+0.5j), (-2+1j), (-2+1.5j), (-1.5-2j), (-1.5-1.5j), (-1.5-1j), (-1.5-0.5j), (-1.5+0j), (-1.5+0.5j), (-1.5+1j), (-1.5+1.5j), (-1-2j), (-1-1.5j), (-1-1j), (-1-0.5j), (-1+0j), (-1+0.5j), (-1+1j), (-1+1.5j), (-0.5-2j), (-0.5-1.5j), (-0.5-1j), (-0.5-0.5j), (-0.5+0j), (-0.5+0.5j), (-0.5+1j), (-0.5+1.5j), -2j, -1.5j, -1j, -0.5j, 0j, 0.5j, 1j, 1.5j, (0.5-2j), (0.5-1.5j), (0.5-1j), (0.5-0.5j), (0.5+0j), (0.5+0.5j), (0.5+1j), (0.5+1.5j), (1-2j), (1-1.5j), (1-1j), (1-0.5j), (1+0j), (1+0.5j), (1+1j), (1+1.5j), (1.5-2j), (1.5-1.5j), (1.5-1j), (1.5-0.5j), (1.5+0j), (1.5+0.5j), (1.5+1j), (1.5+1.5j)]
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 0, 3, 2, 1, 1, 1, 3, 0, 0, 0, 3, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 3, 0, 0, 0, 3, 1, 1, 1, 2, 3, 0, 3, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1]

In [44]:

    

# from juliasets2 import JuliaSet
# Math libraries
import numpy as np
from math import sqrt

# Matplotlib plotting libraries
import matplotlib.pyplot as plt
%matplotlib inline

# Bokeh plotting libraries
import bokeh.plotting as blt
blt.output_notebook()

class JuliaSetPlot(JuliaSet):
    """Extend JuliaSet to add plotting functionality"""
    
    def __init__(self, *args, **kwargs):
        # Invoke constructor for JuliaSet first, unaltered
        JuliaSet.__init__(self, *args, **kwargs)
        # Add another attribute: a rendered image array
        self.img = np.array([])
    
    def get_dim(self):
        """Return linear number of points in axis"""
        return int(4.0 / self._d)
    
    def render(self):
        """Render image as square array of ints"""
        if not self.set: self.generate()
        # Convert inefficient list to efficient numpy array
        self.img = np.array(self.set)
        # Reshape array into a 2d complex plane
        dim = int(sqrt(len(self.img)))
        self.img = np.reshape(self.img, (dim,dim)).T
        
    def show(self):
        """Use matplotlib to plot image as an efficient mesh"""
        if not self.img.size: self.render()
        plt.figure(1, figsize=(12,9))
        dim = int(sqrt(len(self.img)))
        xy = np.linspace(-2,2,dim)
        plt.pcolormesh(xy, xy, self.img, cmap=plt.cm.hot)
        plt.colorbar()
        plt.show()
        
    def interact(self):
        """Use bokeh to plot an interactive image"""
        from matplotlib.colors import rgb2hex
        if not self.img.size: self.render()
        # Mimic matplotlib "hot" color palette
        colormap = plt.cm.get_cmap("hot")
        bokehpalette = [rgb2hex(m) for m in colormap(np.arange(colormap.N))]
        # Create bokeh figure
        f = blt.figure(x_range=(-2,2), y_range=(-2,2), plot_width=600, plot_height=600)
        f.image(image=[self.img], x=[-2], y=[-2], dw=[4], dh=[4], palette=bokehpalette, dilate=True)
        blt.show(f)
        
j = JuliaSetPlot(0.3)
%time j.set_spacing(0.006)
%time j.interact()


    

    





    
        
        
        
    

        
        BokehJS successfully loaded.
    






    




CPU times: user 316 ms, sys: 16 ms, total: 332 ms
Wall time: 787 ms






    















    




CPU times: user 2.7 s, sys: 20 ms, total: 2.72 s
Wall time: 2.91 s

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