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test_plot_semivariogram.py
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test_plot_semivariogram.py
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#!/usr/bin/env python
__author__ = "Antonio Gonzalez Pena"
__copyright__ = "Copyright 2011, The QIIME Project"
__credits__ = ["Antonio Gonzalez Pena"]
__license__ = "GPL"
__version__ = "1.9.1-dev"
__maintainer__ = "Antonio Gonzalez Pena"
__email__ = "antgonza@gmail.com"
from qiime.plot_semivariogram import hist_bins, fit_semivariogram
from unittest import TestCase, main
from numpy.testing import assert_almost_equal
from numpy import asarray
class FunctionTests(TestCase):
"""Tests of top-level functions"""
def test_hist_bins(self):
""" test hist_bins """
x = asarray(
[3.,
4.12310563,
4.24264069,
4.47213595,
5.,
5.,
5.,
5.,
5.38516481,
5.65685425,
6.40312424,
6.40312424,
6.70820393,
7.,
7.07106781,
7.07106781,
7.28010989,
7.81024968,
8.,
8.06225775,
8.06225775,
8.24621125,
9.,
9.48683298,
9.48683298,
9.89949494,
9.89949494,
10.,
10.04987562,
10.04987562])
bins = [2.0, 5.0, 7.5, 10.0, 11.0]
hist_res = [0., 8., 9., 11., 2.]
vals, hist = hist_bins(bins, x)
assert_almost_equal(vals, bins)
assert_almost_equal(hist, hist_res)
def test_reorder_samples(self):
""" test that regural and irregular order give the same results """
model = "linear"
# Test normal order
x_lbl = ['s1', 's2', 's3', 's4', 's5', 's6']
x = asarray(
[[0.0,
1.0,
2.0,
3.0,
4.0,
5.0],
[0.0,
0.0,
6.0,
7.0,
8.0,
9.0],
[0.0,
0.0,
0.0,
10.0,
11.0,
12.0],
[0.0,
0.0,
0.0,
0.0,
13.0,
14.0],
[0.0,
0.0,
0.0,
0.0,
0.0,
15.0]])
y_lbl = ['s1', 's2', 's3', 's4', 's5', 's6']
y = asarray(
[[0.0,
1.0,
2.0,
3.0,
4.0,
5.0],
[0.0,
0.0,
6.0,
7.0,
8.0,
9.0],
[0.0,
0.0,
0.0,
10.0,
11.0,
12.0],
[0.0,
0.0,
0.0,
0.0,
13.0,
14.0],
[0.0,
0.0,
0.0,
0.0,
0.0,
15.0]])
vals_exp = [0.0, 0.0, 0.0, 0.0, 1.0, 2.0, 3.0, 4.0, 6.0, 7.0]
x_vals, y_vals, x_fit, y_fit, func_text = fit_semivariogram(
(x_lbl, x), (x_lbl, x), model, [])
assert_almost_equal(x_vals, vals_exp)
assert_almost_equal(y_vals, vals_exp)
assert_almost_equal(x_fit, vals_exp)
assert_almost_equal(y_fit, vals_exp)
# Test altered
model = "linear"
# order = [5, 1, 3, 4, 0, 2]
x_lbl = ['s6', 's2', 's4', 's5', 's1', 's3']
x = asarray(
[[0.0,
0.0,
0.0,
0.0,
0.0,
0.0],
[9.0,
0.0,
7.0,
8.0,
0.0,
6.0],
[14.0,
0.0,
0.0,
13.0,
0.0,
0.0],
[15.0,
0.0,
0.0,
0.0,
0.0,
0.0],
[5.0,
1.0,
3.0,
4.0,
0.0,
2.0],
[12.0,
0.0,
10.0,
11.0,
0.0,
0.0]])
y_lbl = ['s1', 's2', 's3', 's4', 's5', 's6']
y = asarray(
[[0.0,
1.0,
2.0,
3.0,
4.0,
5.0],
[0.0,
0.0,
6.0,
7.0,
8.0,
9.0],
[0.0,
0.0,
0.0,
10.0,
11.0,
12.0],
[0.0,
0.0,
0.0,
0.0,
13.0,
14.0],
[0.0,
0.0,
0.0,
0.0,
0.0,
15.0],
[0.0,
0.0,
0.0,
0.0,
0.0,
0.0]])
vals_exp = [
1.,
2.,
3.,
4.,
5.,
6.,
7.,
8.,
9.,
10.,
11.,
12.,
13.,
14.,
15.]
x_vals, y_vals, x_fit, y_fit, func_text = fit_semivariogram(
(x_lbl, x), (y_lbl, y), model, [])
assert_almost_equal(x_vals, vals_exp)
assert_almost_equal(y_vals, vals_exp)
assert_almost_equal(x_fit, vals_exp)
assert_almost_equal(y_fit, vals_exp)
def test_models_semivariograms(self):
""" test the semivariogram fitting models """
# All models should return the same x_vals, y_vals, x_fit
# because we are using the same x
x_lbl = ['s1', 's2', 's3', 's4', 's5', 's6']
x = asarray(
[[0.0,
1.0,
2.0,
3.0,
4.0,
5.0],
[0.0,
0.0,
6.0,
7.0,
8.0,
9.0],
[0.0,
0.0,
0.0,
10.0,
11.0,
12.0],
[0.0,
0.0,
0.0,
0.0,
13.0,
14.0],
[0.0,
0.0,
0.0,
0.0,
0.0,
15.0]])
vals_exp = [0.0, 0.0, 0.0, 0.0, 1.0, 2.0, 3.0, 4.0, 6.0, 7.0]
model = "nugget"
y_lbl = ['s1', 's2', 's3', 's4', 's5', 's6']
y = asarray(
[[0.0,
5.0,
5.0,
5.0,
5.0,
5.0],
[0.0,
0.0,
5.0,
5.0,
5.0,
5.0],
[0.0,
0.0,
0.0,
5.0,
5.0,
5.0],
[0.0,
0.0,
0.0,
0.0,
5.0,
5.0],
[0.0,
0.0,
0.0,
0.0,
0.0,
5.0]])
y_vals_exp = [2.3000000143667378] * (len(x) * 2)
x_vals, y_vals, x_fit, y_fit, func_text = fit_semivariogram(
(x_lbl, x), (x_lbl, x), model, [])
assert_almost_equal(x_vals, vals_exp)
assert_almost_equal(y_vals, vals_exp)
assert_almost_equal(x_fit, vals_exp)
assert_almost_equal(y_fit, y_vals_exp)
model = "exponential"
y_lbl = ['s1', 's2', 's3', 's4', 's5', 's6']
y = asarray(
[[0.0,
1.0,
22.0,
33.0,
44.0,
55.0],
[0.0,
0.0,
66.0,
77.0,
88.0,
99.0],
[0.0,
0.0,
0.0,
1010.0,
1111.0,
1212.0],
[0.0,
0.0,
0.0,
0.0,
1313.0,
1414.0],
[0.0,
0.0,
0.0,
0.0,
0.0,
1515.0]])
x_vals_exp = [0.0, 0.0, 0.0, 0.0, 1.0, 2.0, 3.0, 4.0, 6.0, 7.0]
y_vals_exp = [0.0, 0.0, 0.0, 0.0, 1.0, 22.0, 33.0, 44.0, 66.0, 77.0]
x_fit_exp = [0.0, 0.0, 0.0, 0.0, 1.0, 2.0, 3.0, 4.0, 6.0, 7.0]
y_fit_exp = [-1.481486808707005, -1.481486808707005, -1.481486808707005,
-1.481486808707005, 9.72783464904061, 20.937152199747878,
32.14646584698613, 43.355775583612704, 65.7743833464588,
76.983681369107]
x_vals, y_vals, x_fit, y_fit, func_text = fit_semivariogram(
(x_lbl, x), (y_lbl, y), model, [])
assert_almost_equal(x_vals, x_vals_exp)
assert_almost_equal(y_vals, y_vals_exp)
assert_almost_equal(x_fit, x_fit_exp)
assert_almost_equal(y_fit, y_fit_exp, decimal=2)
model = "gaussian"
y_lbl = ['s1', 's2', 's3', 's4', 's5', 's6']
y = asarray(
[[0.0,
1.0,
22.0,
33.0,
44.0,
55.0],
[0.0,
0.0,
66.0,
77.0,
88.0,
99.0],
[0.0,
0.0,
0.0,
1010.0,
1111.0,
1212.0],
[0.0,
0.0,
0.0,
0.0,
1313.0,
1414.0],
[0.0,
0.0,
0.0,
0.0,
0.0,
1515.0]])
y_vals_exp = [0.17373844, 0.17373844, 0.17373844, 0.17373844,
0.54915099, 1.5597716 , 2.91606171, 4.2880578 ,
6.24509872, 6.74690541]
x_vals, y_vals, x_fit, y_fit, func_text = fit_semivariogram(
(x_lbl, x), (x_lbl, x), model, [])
assert_almost_equal(x_vals, vals_exp)
assert_almost_equal(y_vals, vals_exp)
assert_almost_equal(x_fit, vals_exp)
assert_almost_equal(y_fit, y_vals_exp, decimal=2)
model = "periodic"
y_lbl = ['s1', 's2', 's3', 's4', 's5', 's6']
y = asarray(
[[0.0,
1.0,
22.0,
33.0,
44.0,
55.0],
[0.0,
0.0,
66.0,
77.0,
88.0,
99.0],
[0.0,
0.0,
0.0,
1010.0,
1111.0,
1212.0],
[0.0,
0.0,
0.0,
0.0,
1313.0,
1414.0],
[0.0,
0.0,
0.0,
0.0,
0.0,
1515.0]])
y_vals_exp = [0.2324873886681871, 0.2324873886681871,
0.2324873886681871, 0.2324873886681871,
0.5528698895985695, 1.4508010363573784,
2.7491053124879112, 4.191607473962063,
6.39840364731269, 6.727263101495738]
x_vals, y_vals, x_fit, y_fit, func_text = fit_semivariogram(
(x_lbl, x), (x_lbl, x), model, [])
assert_almost_equal(x_vals, vals_exp)
assert_almost_equal(y_vals, vals_exp)
assert_almost_equal(x_fit, vals_exp)
assert_almost_equal(y_fit, y_vals_exp, decimal=2)
model = "linear"
y_lbl = x_lbl
y = x
x_vals, y_vals, x_fit, y_fit, func_text = fit_semivariogram(
(x_lbl, x), (x_lbl, x), model, [])
assert_almost_equal(x_vals, vals_exp)
assert_almost_equal(y_vals, vals_exp)
assert_almost_equal(x_fit, vals_exp)
assert_almost_equal(y_fit, vals_exp, decimal=2)
# run tests if called from command line
if __name__ == '__main__':
main()