def test_batch_apply(points_1):
c = Calibraxis(verbose=False)
c.add_points(points_1)
c.calibrate_accelerometer()
out = c.batch_apply(points_1)
normed = np.sqrt((np.array(out) ** 2).sum(axis=1))
np.testing.assert_array_almost_equal(normed, 1.0, 2)
def test_add_points_4(points_2):
c = Calibraxis(verbose=False)
points = points_2 / ((2 ** 15) / 8.)
c.add_points(points.tolist())
np.testing.assert_almost_equal(np.linalg.norm(np.array(c._calibration_points) - points), 0.0, 6)
c.calibrate_accelerometer()
np.testing.assert_almost_equal(c._calibration_errors[-1], 0.0, 2)
def test_batch_apply(points_1):
c = Calibraxis(verbose=False)
c.add_points(points_1)
c.calibrate_accelerometer()
out = c.batch_apply(points_1)
normed = np.sqrt((np.array(out)**2).sum(axis=1))
np.testing.assert_array_almost_equal(normed, 1.0, 2)
def test_verbose_prints_progress(points_2, capsys):
c = Calibraxis(verbose=True)
c.add_points(points_2)
c.calibrate_accelerometer()
out, err = capsys.readouterr()
for row in filter(None, out.split('\n')):
assert re.match('^([0-9]+):\s([0-9\-\.e]+)\s*(\([0-9\s\-\.e,]+\))$', row)
def test_verbose_prints_progress(points_2, capsys):
c = Calibraxis(verbose=True)
c.add_points(points_2)
c.calibrate_accelerometer()
out, err = capsys.readouterr()
for row in filter(None, out.split('\n')):
assert re.match('^([0-9]+):\s([0-9\-\.e]+)\s*(\([0-9\s\-\.e,]+\))$',
row)
def test_add_points_4(points_2):
c = Calibraxis(verbose=False)
points = points_2 / ((2**15) / 8.)
c.add_points(points.tolist())
np.testing.assert_almost_equal(
np.linalg.norm(np.array(c._calibration_points) - points), 0.0, 6)
c.calibrate_accelerometer()
np.testing.assert_almost_equal(c._calibration_errors[-1], 0.0, 2)
def test_add_points_3(points_1):
c = Calibraxis(verbose=False)
points = points_1 / ((2 ** 15) / 8.)
for p in points:
c.add_points(tuple(p))
np.testing.assert_almost_equal(np.linalg.norm(np.array(c._calibration_points) - points), 0.0, 6)
c.calibrate_accelerometer()
np.testing.assert_almost_equal(c._calibration_errors[-1], 0.0, 2)
def test_add_points_3(points_1):
c = Calibraxis(verbose=False)
points = points_1 / ((2**15) / 8.)
for p in points:
c.add_points(tuple(p))
np.testing.assert_almost_equal(
np.linalg.norm(np.array(c._calibration_points) - points), 0.0, 6)
c.calibrate_accelerometer()
np.testing.assert_almost_equal(c._calibration_errors[-1], 0.0, 2)
def test_recalibration_points_2(points_2):
c = Calibraxis(verbose=False)
points = points_2 / ((2 ** 15) / 16.)
for p in points[:-1, :]:
c.add_points(p)
c.calibrate_accelerometer()
np.testing.assert_almost_equal(c._calibration_errors[-1], 0.0, 2)
c.add_points(points[-1, :])
c.calibrate_accelerometer()
np.testing.assert_almost_equal(c._calibration_errors[-1], 0.0, 2)
def test_recalibration_points_2(points_2):
c = Calibraxis(verbose=False)
points = points_2 / ((2**15) / 16.)
for p in points[:-1, :]:
c.add_points(p)
c.calibrate_accelerometer()
np.testing.assert_almost_equal(c._calibration_errors[-1], 0.0, 2)
c.add_points(points[-1, :])
c.calibrate_accelerometer()
np.testing.assert_almost_equal(c._calibration_errors[-1], 0.0, 2)
import numpy as np
from calibraxis import Calibraxis
c = Calibraxis()
points = np.array([[-4772.38754098, 154.04459016, -204.39081967],
[3525.0346179, -68.64924886, -34.54604833],
[-658.17681729, -4137.60248854, -140.49377865],
[-564.18562092, 4200.29150327, -130.51895425],
[-543.18289474, 18.14736842, -4184.43026316],
[-696.62532808, 15.70209974, 3910.20734908],
[406.65271419, 18.46827992, -4064.61085677],
[559.45926413, -3989.69513798, -174.71879106],
[597.22629169, -3655.54153041, -1662.83257031],
[1519.02616089, -603.82472204, 3290.58469588]])
# Add points to calibration object's storage.
c.add_points(points)
# Run the calibration parameter optimization.
c.calibrate_accelerometer()
# Applying the calibration parameters to the calibration data.
c.apply(points[0:])
c.batch_apply(points)
def test_calibration_points_2_scaled(points_2):
c = Calibraxis(verbose=False)
c.add_points(points_2 / ((2 ** 15) / 16.))
c.calibrate_accelerometer()
np.testing.assert_almost_equal(c._calibration_errors[-1], 0.0, 2)
def test_calibration_points_1(points_1):
c = Calibraxis(verbose=False)
c.add_points(points_1)
c.calibrate_accelerometer()
np.testing.assert_almost_equal(c._calibration_errors[-1], 0.0, 2)
def test_apply(points_1):
c = Calibraxis(verbose=False)
c.add_points(points_1)
c.calibrate_accelerometer()
np.testing.assert_almost_equal(np.linalg.norm(c.apply(points_1[0, :])),
1.0, 2)
def test_error_to_few_points(points_2):
c = Calibraxis(verbose=False)
for p in points_2[:5, :]:
c.add_points(p)
with pytest.raises(ValueError):
c.calibrate_accelerometer()
def test_error_to_few_points(points_2):
c = Calibraxis(verbose=False)
for p in points_2[:5, :]:
c.add_points(p)
with pytest.raises(ValueError):
c.calibrate_accelerometer()
def test_apply(points_1):
c = Calibraxis(verbose=False)
c.add_points(points_1)
c.calibrate_accelerometer()
np.testing.assert_almost_equal(np.linalg.norm(c.apply(points_1[0, :])), 1.0, 2)
def test_calibration_points_1(points_1):
c = Calibraxis(verbose=False)
c.add_points(points_1)
c.calibrate_accelerometer()
np.testing.assert_almost_equal(c._calibration_errors[-1], 0.0, 2)
def test_calibration_points_2_scaled(points_2):
c = Calibraxis(verbose=False)
c.add_points(points_2 / ((2**15) / 16.))
c.calibrate_accelerometer()
np.testing.assert_almost_equal(c._calibration_errors[-1], 0.0, 2)