import pandas as pd
import numpy as np

%load_ext rmagic

%%R -o x,y
set.seed(1234); par(mar=c(0,0,0,0))
x <- rnorm(12,mean=rep(1:3,each=4),sd=0.2)
y <- rnorm(12,mean=rep(c(1,2,1),each=4),sd=0.2)
plot(x,y,col='blue',pch=19,cex=2)
text(x+0.05,y+0.05,labels=as.character(0:11))

dataFrame = pd.DataFrame(zip(x, y), columns=['x', 'y'])

# compute distance matrix
from scipy.spatial.distance import pdist, squareform

# not printed as pretty, but the values are correct
distxy = squareform(pdist(dataFrame, metric='euclidean'))
print distxy

# perform clustering and plot the dendrogram
from scipy.cluster.hierarchy import linkage, dendrogram

R = dendrogram(linkage(distxy, method='complete'))

xlabel('points')
ylabel('Height')
suptitle('Cluster Dendrogram', fontweight='bold', fontsize=14);

%%R -i x,y -o dataMatrix
dataFrame <- data.frame(x=x,y=y)
set.seed(143)
dataMatrix <- as.matrix(dataFrame)[sample(1:12),]

# a simple function to compute hierarchical cluster on both rows and columns, and plot heatmaps
def heatmap(dm):
    from scipy.cluster.hierarchy import linkage, dendrogram
    from scipy.spatial.distance import pdist, squareform
    
    D1 = squareform(pdist(dm, metric='euclidean'))
    D2 = squareform(pdist(dm.T, metric='euclidean'))
    
    f = figure(figsize=(8, 8))

    # add first dendrogram
    ax1 = f.add_axes([0.09, 0.1, 0.2, 0.6])
    Y = linkage(D1, method='complete')
    Z1 = dendrogram(Y, orientation='right')
    ax1.set_xticks([])
    ax1.set_yticks([])

    # add second dendrogram
    ax2 = f.add_axes([0.3, 0.71, 0.6, 0.2])
    Y = linkage(D2, method='complete')
    Z2 = dendrogram(Y)
    ax2.set_xticks([])
    ax2.set_yticks([])

    # add matrix plot
    axmatrix = f.add_axes([0.3, 0.1, 0.6, 0.6])
    idx1 = Z1['leaves']
    idx2 = Z2['leaves']
    D = D1[idx1, :]
    D = D[:, idx2]
    im = axmatrix.matshow(D, aspect='auto', origin='lower', cmap='hot')
    axmatrix.set_xticks([])
    axmatrix.set_yticks([])
    
    return {'ordered' : D, 'rorder' : Z1['leaves'], 'corder' : Z2['leaves']}

heatmap(dataMatrix)