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#! /usr/bin/env python
# Last Change: Tue Jul 17 10:00 PM 2007 J
# Various utilities for examples
import numpy as N
from numpy.testing import set_package_path, restore_path
from scikits.learn.datasets import oldfaithful, pendigits, iris
def get_faithful():
"""Return faithful data as a nx2 array, first column being duration, second
being waiting time."""
# Load faithful data, convert waiting into integer, remove L, M and S data
data = oldfaithful.load()
tmp1 = []
tmp2 = []
for i in data['data']:
if not (i[0] == 'L' or i[0] == 'M' or i[0] == 'S'):
tmp1.append(i[0])
tmp2.append(i[1])
waiting = N.array([int(i) for i in tmp1], dtype = N.float)
duration = N.array([i for i in tmp2], dtype = N.float)
waiting = waiting[:, N.newaxis]
duration = duration[:, N.newaxis]
return N.concatenate((waiting, duration), 1)
def get_pendigits():
"""Return faithful data as a nx2 array, first column being duration, second
being waiting time."""
# Load faithful data, convert waiting into integer, remove L, M and S data
data = pendigits.load()
return data['training']['x'], data['training']['y']
def scale(data):
""" Scale data such as each col is in the range [0..1].
Note: inplace."""
n = N.min(data, 0)
m = N.max(data, 0)
data -= n
data /= (m-n)
return data
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