print matrix
# #Names col1 col2 col3 col4 col5 col6 col7
# A -1.23 -0.81 1.79 0.78 -0.42 -0.69 0.58
# B -1.76 -0.94 1.16 0.36 0.41 -0.35 1.12
# C -2.19 0.13 0.65 -0.51 0.52 1.04 0.36
# D -1.22 -0.98 0.79 -0.76 -0.29 1.54 0.93
# E -1.47 -0.83 0.85 0.07 -0.81 1.53 0.65
# F -1.04 -1.11 0.87 -0.14 -0.80 1.74 0.48
# G -1.57 -1.17 1.29 0.23 -0.20 1.17 0.26
# H -1.53 -1.25 0.59 -0.30 0.32 1.41 0.77
#
#
# We load a tree structure whose leaf nodes correspond to rows in the
# numerical matrix. We use the text_array argument to link the tree
# with numerical matrix.
t = ClusterTree("(((A,B),(C,(D,E))),(F,(G,H)));", text_array=matrix)
print "Example tree", t
# /-A
# /--------|
# | \-B
# /--------|
# | | /-C
# | \--------|
# | | /-D
#---------| \--------|
# | \-E
# |
# | /-F
# \--------|
# | /-G
# \--------|
from ete_dev import ClusterTree, TreeStyle, AttrFace, ProfileFace, TextFace
from ete_dev.treeview.faces import add_face_to_node
# To operate with numbers efficiently
import numpy
PATH = "./"
# Loads tree and array
t = ClusterTree(PATH+"diauxic.nw", PATH+"diauxic.array")
# nodes are linked to the array table
array = t.arraytable
# Calculates some stats on the matrix. Needed to establish the color
# gradients.
matrix_dist = [i for r in xrange(len(array.matrix))\
for i in array.matrix[r] if numpy.isfinite(i)]
matrix_max = numpy.max(matrix_dist)
matrix_min = numpy.min(matrix_dist)
matrix_avg = matrix_min+((matrix_max-matrix_min)/2)
# Creates a profile face that will represent node's profile as a
# heatmap
profileFace = ProfileFace(matrix_max, matrix_min, matrix_avg, \
200, 14, "heatmap")
cbarsFace = ProfileFace(matrix_max,matrix_min,matrix_avg,200,70,"cbars")
nameFace = AttrFace("name", fsize=8)
# Creates my own layout function that uses previous faces
def mylayout(node):
# If node is a leaf
if node.is_leaf():
