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data-visualizationpythonself-organizing-maps

Visualizing class labels in self-organizing map plot or iris dataset

I am trying to produce a visualization of the SOM mapping for the Iris dataset ( https://archive.ics.uci.edu/ml/datasets/Iris).

My code so far:

from sklearn.datasets import load_iris
from mvpa2.suite import *
import pandas as pd
import numpy as np

df = pd.read_csv(filepath_or_buffer='data/iris.data', header=None, sep=',')
df.columns=['sepal_len', 'sepal_wid', 'petal_len', 'petal_wid', 'class']
df.dropna(how="all", inplace=True) # drops the empty line at file-end

# split the data table into feature data x and class labels y
x = df.ix[:,0:4].values # the first 4 columns are the features
y = df.ix[:,4].values   # the last column is the class label
t = np.zeros(len(y), dtype=int)
t[y == 'Iris-setosa'] = 0
t[y == 'Iris-versicolor'] = 1
t[y == 'Iris-virginica'] = 2

som = SimpleSOMMapper((240, 320), 100, learning_rate=0.05)
som.train(x)

pl.imshow(som.K, origin='lower')
mapped = som(x)

for i, m in enumerate(mapped):
    pl.text(m[1], m[0], t[i], ha='center', va='center',
           bbox=dict(facecolor='white', alpha=0.5, lw=0))
pl.show()

which produces this mapping:

enter image description here

Is there any way to customize the palette so it looks nicer like this one? (taken from https://github.com/JustGlowing/minisom)?

enter image description here

Basically I am trying to use a nicer palette (perhaps with fewer colors) and mark the class labels in a nicer way.

Thank you.

Solution

  • I will answer my own question: it turns out that I forgot to slice my data:

    pl.imshow(som.K[:,:,0], origin='lower')

    Everything looks fine now: enter image description here