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import numpy as np |
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import pandas as pd |
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import calculations |
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View Code Duplication |
def test_peak_values(): |
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"""This function tests peak_values() function.""" |
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potentials = [0.500, 0.499, 0.498, 0.497] |
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currents = [7.040, 6.998, 8.256, 8.286] |
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potentials_d = pd.DataFrame(potentials) |
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currents_d = pd.DataFrame(currents) |
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assert type(calculations.peak_values(potentials_d, currents_d)) == np.ndarray, "output is not an array" |
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assert calculations.peak_values(potentials_d, currents_d)[0] == 0.498, "array value incorrect for data" |
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assert calculations.peak_values(potentials_d, currents_d)[2] == 0.499, "array value incorrect for data" |
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assert calculations.peak_values(potentials_d, currents_d)[1] == 8.256, "array value incorrect for data" |
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assert calculations.peak_values(potentials_d, currents_d)[3] == 6.998, "array value incorrect for data" |
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return |
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View Code Duplication |
def test_del_potential(): |
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"""This function tests the del_potential function.""" |
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potentials = [0.500, 0.498, 0.499, 0.497] |
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currents = [7.040, 6.998, 8.256, 8.286] |
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potentials_d = pd.DataFrame(potentials) |
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currents_d = pd.DataFrame(currents) |
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assert type(calculations.del_potential(potentials_d, currents_d)) == np.ndarray, "output is not an array" |
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assert calculations.del_potential(potentials_d, currents_d).shape == (1,), "output shape incorrect" |
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assert calculations.del_potential(potentials_d, currents_d).size == 1, "array size incorrect" |
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np.testing.assert_almost_equal(calculations.del_potential(potentials_d, currents_d), 0.001, decimal=3), "value incorrect for data" |
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return |
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View Code Duplication |
def test_half_wave_potential(): |
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"""This function tests half_wave_potential() function.""" |
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potentials = [0.500, 0.498, 0.499, 0.497] |
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currents = [7.040, 6.998, 8.256, 8.286] |
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potentials_d = pd.DataFrame(potentials) |
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currents_d = pd.DataFrame(currents) |
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assert type(calculations.half_wave_potential(potentials_d, currents_d)) == np.ndarray, "output is not an array" |
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assert calculations.half_wave_potential(potentials_d, currents_d).size == 1, "out not correct size" |
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np.testing.assert_almost_equal(calculations.half_wave_potential(potentials_d, currents_d), 0.0005, decimal=4), "value incorrect for data" |
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return |
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def test_peak_heights(): |
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"""This function tests peak_heights() function.""" |
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potentials = [0.500, 0.498, 0.499, 0.497] |
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currents = [7.040, 6.998, 8.256, 8.286] |
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potentials_d = pd.DataFrame(potentials) |
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currents_d = pd.DataFrame(currents) |
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assert type(calculations.peak_heights(potentials_d, currents_d)) == list, "output is not a list" |
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assert len(calculations.peak_heights(potentials_d, currents_d)) == 2, "output list is not the correct length" |
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np.testing.assert_almost_equal(calculations.peak_heights(potentials_d, currents_d)[0], 7.256, decimal=3), "max peak height incorrect for data" |
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np.testing.assert_almost_equal(calculations.peak_heights(potentials_d, currents_d)[1], 4.998, decimal=3), "min peak height incorrect for data" |
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return |
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View Code Duplication |
def test_peak_ratio(): |
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"""This function tests peak_ratio() function.""" |
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potentials = [0.500, 0.498, 0.499, 0.497] |
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currents = [7.040, 6.998, 8.256, 8.286] |
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potentials_d = pd.DataFrame(potentials) |
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currents_d = pd.DataFrame(currents) |
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assert type(calculations.peak_ratio(potentials_d, currents_d)) == np.ndarray, "output is not an array" |
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assert len(calculations.peak_ratio(potentials_d, currents_d)) == 1, "output list is not the correct length" |
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np.testing.assert_almost_equal(calculations.peak_ratio(potentials_d, currents_d), 1.451, decimal=3), "max peak height incorrect for data" |
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return |
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sabiharustam /
voltcycle
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