Created
January 30, 2014 09:15
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plot matrix with dendogram
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| import numpy as np | |
| import copy | |
| import random | |
| import pylab | |
| import scipy.cluster.hierarchy as sch | |
| def create_linkage_matrix(num_tasks): | |
| """ | |
| create stack of matrices for | |
| each inner node of binary tree | |
| """ | |
| num_levels = int(np.log2(num_tasks)) | |
| stack = [] | |
| cumulative = 0 | |
| for i in range(num_levels): | |
| block_size = 2 ** i | |
| num_blocks = int(num_tasks / block_size) | |
| for j in range(0, num_blocks, 2): | |
| row = [cumulative+j, cumulative+j+1, i+1, block_size*2] | |
| print row | |
| stack.append(row) | |
| cumulative += num_blocks | |
| stack = np.array(stack, dtype=np.float64) | |
| return stack | |
| def plot_dendrogram(data, Y): | |
| """ | |
| http://stackoverflow.com/questions/2982929/plotting-results-of-hierarchical-clustering-ontop-of-a-matrix-of-data-in-python | |
| """ | |
| D = copy.copy(data) | |
| D /= D[0,0] | |
| # Compute and plot first dendrogram. | |
| fig = pylab.figure(figsize=(8,8)) | |
| ax1 = fig.add_axes([0.09,0.1,0.2,0.6]) | |
| ax1.set_axis_off() | |
| Z1 = sch.dendrogram(Y, orientation='right', link_color_func=lambda k: "black") | |
| ax1.set_xticks([]) | |
| ax1.set_yticks([]) | |
| # Compute and plot second dendrogram. | |
| ax2 = fig.add_axes([0.3,0.71,0.6,0.2]) | |
| ax2.set_axis_off() | |
| Z2 = sch.dendrogram(Y, link_color_func=lambda k: "black") | |
| ax2.set_xticks([]) | |
| ax2.set_yticks([]) | |
| # Plot distance matrix. | |
| axmatrix = fig.add_axes([0.3,0.1,0.6,0.6]) | |
| idx1 = Z1['leaves'] | |
| idx2 = Z2['leaves'] | |
| D = D[idx1,:] | |
| D = D[:,idx2] | |
| im = axmatrix.matshow(D, aspect='auto', origin='lower') #, cmap=pylab.cm.YlGnBu) | |
| axmatrix.set_xticks([]) | |
| axmatrix.set_yticks([]) | |
| # Plot colorbar. | |
| axcolor = fig.add_axes([0.91,0.1,0.02,0.6]) | |
| pylab.colorbar(im, cax=axcolor) | |
| fig.show() | |
| pylab.show() | |
| def main(): | |
| Y = create_linkage_matrix(32) | |
| plot_dendrogram(sim, Y) | |
| pylab.figure() | |
| Z1 = sch.dendrogram(Y, orientation='right') | |
| pylab.imshow(sim, interpolation="nearest") | |
| pylab.show() |
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