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""" test_function.py
Tests the PieceWiseConst and PieceWiseLinear functions
Copyright 2014, Mario Mulansky <mario.mulansky@gmx.net>
Distributed under the BSD License
"""
from __future__ import print_function
import numpy as np
from copy import copy
from numpy.testing import assert_almost_equal, assert_array_almost_equal
import pyspike as spk
def test_pwc():
# some random data
x = [0.0, 1.0, 2.0, 2.5, 4.0]
y = [1.0, -0.5, 1.5, 0.75]
f = spk.PieceWiseConstFunc(x, y)
xp, yp = f.get_plottable_data()
xp_expected = [0.0, 1.0, 1.0, 2.0, 2.0, 2.5, 2.5, 4.0]
yp_expected = [1.0, 1.0, -0.5, -0.5, 1.5, 1.5, 0.75, 0.75]
assert_array_almost_equal(xp, xp_expected, decimal=16)
assert_array_almost_equal(yp, yp_expected, decimal=16)
assert_almost_equal(f.avrg(), (1.0-0.5+0.5*1.5+1.5*0.75)/4.0, decimal=16)
assert_almost_equal(f.abs_avrg(), (1.0+0.5+0.5*1.5+1.5*0.75)/4.0,
decimal=16)
def test_pwc_add():
# some random data
x = [0.0, 1.0, 2.0, 2.5, 4.0]
y = [1.0, -0.5, 1.5, 0.75]
f = spk.PieceWiseConstFunc(x, y)
f1 = copy(f)
x = [0.0, 0.75, 2.0, 2.5, 2.7, 4.0]
y = [0.5, 1.0, -0.25, 0.0, 1.5]
f2 = spk.PieceWiseConstFunc(x, y)
f1.add(f2)
x_expected = [0.0, 0.75, 1.0, 2.0, 2.5, 2.7, 4.0]
y_expected = [1.5, 2.0, 0.5, 1.25, 0.75, 2.25]
assert_array_almost_equal(f1.x, x_expected, decimal=16)
assert_array_almost_equal(f1.y, y_expected, decimal=16)
f2.add(f)
assert_array_almost_equal(f2.x, x_expected, decimal=16)
assert_array_almost_equal(f2.y, y_expected, decimal=16)
f1.add(f2)
# same x, but y doubled
assert_array_almost_equal(f1.x, f2.x, decimal=16)
assert_array_almost_equal(f1.y, 2*f2.y, decimal=16)
def test_pwc_mul():
x = [0.0, 1.0, 2.0, 2.5, 4.0]
y = [1.0, -0.5, 1.5, 0.75]
f = spk.PieceWiseConstFunc(x, y)
f.mul_scalar(1.5)
assert_array_almost_equal(f.x, x, decimal=16)
assert_array_almost_equal(f.y, 1.5*np.array(y), decimal=16)
f.mul_scalar(1.0/5.0)
assert_array_almost_equal(f.y, 1.5/5.0*np.array(y), decimal=16)
def test_pwl():
x = [0.0, 1.0, 2.0, 2.5, 4.0]
y1 = [1.0, -0.5, 1.5, 0.75]
y2 = [1.5, -0.4, 1.5, 0.25]
f = spk.PieceWiseLinFunc(x, y1, y2)
xp, yp = f.get_plottable_data()
xp_expected = [0.0, 1.0, 1.0, 2.0, 2.0, 2.5, 2.5, 4.0]
yp_expected = [1.0, 1.5, -0.5, -0.4, 1.5, 1.5, 0.75, 0.25]
assert_array_almost_equal(xp, xp_expected, decimal=16)
assert_array_almost_equal(yp, yp_expected, decimal=16)
avrg_expected = (1.25 - 0.45 + 0.75 + 1.5*0.5) / 4.0
assert_almost_equal(f.avrg(), avrg_expected, decimal=16)
abs_avrg_expected = (1.25 + 0.45 + 0.75 + 1.5*0.5) / 4.0
assert_almost_equal(f.abs_avrg(), abs_avrg_expected, decimal=16)
def test_pwl_add():
x = [0.0, 1.0, 2.0, 2.5, 4.0]
y1 = [1.0, -0.5, 1.5, 0.75]
y2 = [1.5, -0.4, 1.5, 0.25]
f = spk.PieceWiseLinFunc(x, y1, y2)
f1 = copy(f)
x = [0.0, 0.75, 2.0, 2.5, 2.7, 4.0]
y1 = [0.5, 1.0, -0.25, 0.0, 1.5]
y2 = [0.8, 0.2, -1.0, 0.0, 2.0]
f2 = spk.PieceWiseLinFunc(x, y1, y2)
f1.add(f2)
x_expected = [0.0, 0.75, 1.0, 2.0, 2.5, 2.7, 4.0]
y1_expected = [1.5, 1.0+1.0+0.5*0.75, -0.5+1.0-0.8*0.25/1.25, 1.5-0.25,
0.75, 1.5+0.75-0.5*0.2/1.5]
y2_expected = [0.8+1.0+0.5*0.75, 1.5+1.0-0.8*0.25/1.25, -0.4+0.2, 1.5-1.0,
0.75-0.5*0.2/1.5, 2.25]
assert_array_almost_equal(f1.x, x_expected, decimal=16)
assert_array_almost_equal(f1.y1, y1_expected, decimal=16)
assert_array_almost_equal(f1.y2, y2_expected, decimal=16)
f2.add(f)
assert_array_almost_equal(f2.x, x_expected, decimal=16)
assert_array_almost_equal(f2.y1, y1_expected, decimal=16)
assert_array_almost_equal(f2.y2, y2_expected, decimal=16)
f1.add(f2)
# same x, but y doubled
assert_array_almost_equal(f1.x, f2.x, decimal=16)
assert_array_almost_equal(f1.y1, 2*f2.y1, decimal=16)
assert_array_almost_equal(f1.y2, 2*f2.y2, decimal=16)
def test_pwl_mul():
x = [0.0, 1.0, 2.0, 2.5, 4.0]
y1 = [1.0, -0.5, 1.5, 0.75]
y2 = [1.5, -0.4, 1.5, 0.25]
f = spk.PieceWiseLinFunc(x, y1, y2)
f.mul_scalar(1.5)
assert_array_almost_equal(f.x, x, decimal=16)
assert_array_almost_equal(f.y1, 1.5*np.array(y1), decimal=16)
assert_array_almost_equal(f.y2, 1.5*np.array(y2), decimal=16)
f.mul_scalar(1.0/5.0)
assert_array_almost_equal(f.y1, 1.5/5.0*np.array(y1), decimal=16)
assert_array_almost_equal(f.y2, 1.5/5.0*np.array(y2), decimal=16)
if __name__ == "__main__":
test_pwc()
test_pwc_add()
test_pwc_mul()
test_pwl()
test_pwl_add()
test_pwl_mul()
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