"""
Motivation and help seeked from http://scikit-learn.org/stable/auto_examples/manifold/plot_swissroll.html
The code for the plotting 2D manifold has been modified from http://scikit-learn.org/stable/auto_examples/manifold/plot_lle_digits.html#example-manifold-plot-lle-digits-py
Proper documentation in R wasnt available
"""
from sklearn import manifold
import numpy as np
from scipy import linalg as LA
import pylab
import numpy
from pylab import imread,subplot,imshow,title,gray,figure,show,NullLocator
from numpy import linalg,size
from sklearn import decomposition
import os, glob
import pickle
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from matplotlib.ticker import NullFormatter
from matplotlib import offsetbox
from PIL import Image
from sklearn.metrics.pairwise import euclidean_distances
from sklearn.decomposition import KernelPCA

def plot_embedding(result, imList,list_length,title):
    x_min, x_max = np.min(result, 0)-np.min(result, 0)*0.25, np.max(result, 0)+np.max(result, 0)*0.25
    plt.figure()
    ax = plt.subplot(111)
    if hasattr(offsetbox, 'AnnotationBbox'):
        large_images = np.array([[1., 1]])  
        for i in range(len(list_length)):
            plt.plot(result[i][0], result[i][1], 'bo')
            large_images = np.r_[large_images, [result[i]]]
            img=Image.open(imList[list_length[i]])
            imagebox = offsetbox.AnnotationBbox(offsetbox.OffsetImage(img, cmap=plt.cm.gray_r,zoom=0.04),
            result[i],xybox=(-30, 50),xycoords='data',boxcoords="offset points",arrowprops=dict(arrowstyle="->"),pad=0)
            ax.add_artist(imagebox)
    plt.xticks([]), plt.yticks([])
    plt.axis()
    if title is not None:
        plt.title(title)

def main():

        imlist=[]
        imlist=np.array([j for j in glob.glob('jpg/*')]) 
        x = np.array([np.array(Image.open(counter)).flatten() for counter in glob.glob('jpg/*')],'f')
        kpca = KernelPCA(kernel="linear",  n_components=2)
        kpca_reusult = kpca.fit_transform(x)
        plot_embedding(kpca_reusult,imlist,range(143),'2D Manifold, RBF Kernel with images')
        plt.savefig('2drbfimg.png', bbox_inches='tight')
        plt.close
                
main()