def lap(k,data,style_data,dim,outfile):
''' 1. Construct your k nearest neighbors adjacency matrix
2. Use Heat Equation exp -{||x_i-x_j||^2/4t}
'''
adjacency = knn(data,data.shape[1])
heat = 1.0
print "--- Seeting Weights on Adjacency Matrix ---\n"
heat_matrix = set_weights(adjacency,k,heat)
print "--- Creating Laplacian Matrix ---\n"
laplacian, weight = get_laplacian(heat_matrix)
print "--- Eigendecomp -> Points ---\n"
points = eigen_decomp( laplacian,weight,dim)
print "--- Plotting Points ---\n"
plot_points(points,style_data, outfile)
def lle(k,data,style_data,src,outfile,dim):
'''1. Start with knn
'''
n = data.shape[1]
# k+1 because nearest neighbor includes self
matrix = knn(data,k+1)
print "--- Seeting Weights on Adjacency Matrix ---\n"
# weighted is a 500x500 matrix
weighted = set_weights(matrix,data,k,dim,src,n)
print "--- Embedding Coordinates ---\n"
# matrix is nxn
matrix = embedd_y(weighted,n)
print "--- Eigendecomp -> Points ---\n"
# return a 500x2 points
points = get_points(matrix,dim,src)
print "--- Plotting Points ---\n"
plot_points(np.transpose(points),style_data,outfile)
