image_slicer.ipynb

Kernel: Python 2 (SageMath)

#Code to take Julia set iteration data and produce sliced images

import numpy as np
import cPickle as pickle
from matplotlib import cm
import matplotlib.pyplot as plt
from PIL import Image
from math import sqrt

DATA = '../data/iterations_data.bin'
colormap = cm.viridis

with open(DATA) as f:
    iteration_data = np.fromfile( f.read(), dtype=np.uint8 )
    iteration_data = iteration_data.reshape( (1000, 1000) )

unique_values = np.unique(iteration_data) 
print(unique_values)
n = len(unique_values)//5
slices = [ unique_values[i:i+n] for i in range(0, len(unique_values), n)]

for slice_index, slice_values in enumerate( slices ):
    img = np.zeros( iteration_data.shape, dtype=np.int32)
    img.fill(0xFFFFFFFF)
    for index, slice_value in enumerate(slice_values):
        #raw_color = colormap(slice_value)
        #raw_color = RGB_tuples[ slice_index*n + index ]
        #color = sum( [int((0xFF*v))<<(8*i) for i,v in enumerate(raw_color)] )
        shift = 8*(slice_value//(255//3))
        color = (255//2 +slice_value%(255//3))
        color = color<<shift
        color += 0xFF000000
        img[ np.where( iterations_data == slice_value) ] = color
    pilImage = Image.frombuffer('RGBA', img.shape, img,'raw','RGBA',0,1)
    pilImage.save( "../Image_Slices/img_{0}.png".format(slice_index) )

[ 8*(i//(255//3)) for i in range(1,256) ]

import numpy as np
a = np.array([1,2,3,4,5,6,7,8,9])

a.reshape(np.array('3,3'.split(',')).astype(int))

b = a.reshape(np.array('3,3'.split(',')).astype(int))
b

a