def test__golden_sect_DataFrame_nans():
# nan in bounds
params = {'c': np.array([1., 2., 1.]), 'n': np.array([1., 1., 1.])}
lower = np.array([0., 0.001, np.nan])
upper = np.array([1.1, 1.2, 1.])
expected = np.array([0.5, 0.25, np.nan])
v, x = tools._golden_sect_DataFrame(params, lower, upper,
_obj_test_golden_sect)
assert np.allclose(x, expected, atol=1e-8, equal_nan=True)
# nan in function values
params = {'c': np.array([1., 2., np.nan]), 'n': np.array([1., 1., 1.])}
lower = np.array([0., 0.001, 0.])
upper = np.array([1.1, 1.2, 1.])
expected = np.array([0.5, 0.25, np.nan])
v, x = tools._golden_sect_DataFrame(params, lower, upper,
_obj_test_golden_sect)
assert np.allclose(x, expected, atol=1e-8, equal_nan=True)
# all nan in bounds
params = {'c': np.array([1., 2., 1.]), 'n': np.array([1., 1., 1.])}
lower = np.array([np.nan, np.nan, np.nan])
upper = np.array([1.1, 1.2, 1.])
expected = np.array([np.nan, np.nan, np.nan])
v, x = tools._golden_sect_DataFrame(params, lower, upper,
_obj_test_golden_sect)
assert np.allclose(x, expected, atol=1e-8, equal_nan=True)
def test__golden_sect_DataFrame_vector():
params = {'c': np.array([1., 2.]), 'n': np.array([1., 1.])}
lower = np.array([0., 0.001])
upper = np.array([1.1, 1.2])
expected = np.array([0.5, 0.25])
v, x = tools._golden_sect_DataFrame(params, lower, upper,
_obj_test_golden_sect)
assert np.allclose(x, expected, atol=1e-8)
def test__golden_sect_DataFrame_atol():
params = {'c': 0.2, 'n': 0.3}
expected = 89.14332727531685
v, x = tools._golden_sect_DataFrame(params,
0.,
100.,
_obj_test_golden_sect,
atol=1e-12)
assert np.isclose(x, expected, atol=1e-12)
def _lambertw(photocurrent,
saturation_current,
resistance_series,
resistance_shunt,
nNsVth,
ivcurve_pnts=None):
# Compute short circuit current
i_sc = _lambertw_i_from_v(resistance_shunt, resistance_series, nNsVth, 0.,
saturation_current, photocurrent)
# Compute open circuit voltage
v_oc = _lambertw_v_from_i(resistance_shunt, resistance_series, nNsVth, 0.,
saturation_current, photocurrent)
params = {
'r_sh': resistance_shunt,
'r_s': resistance_series,
'nNsVth': nNsVth,
'i_0': saturation_current,
'i_l': photocurrent
}
# Find the voltage, v_mp, where the power is maximized.
# Start the golden section search at v_oc * 1.14
p_mp, v_mp = _golden_sect_DataFrame(params, 0., v_oc * 1.14, _pwr_optfcn)
# Find Imp using Lambert W
i_mp = _lambertw_i_from_v(resistance_shunt, resistance_series, nNsVth,
v_mp, saturation_current, photocurrent)
# Find Ix and Ixx using Lambert W
i_x = _lambertw_i_from_v(resistance_shunt, resistance_series, nNsVth,
0.5 * v_oc, saturation_current, photocurrent)
i_xx = _lambertw_i_from_v(resistance_shunt, resistance_series, nNsVth,
0.5 * (v_oc + v_mp), saturation_current,
photocurrent)
out = (i_sc, v_oc, i_mp, v_mp, p_mp, i_x, i_xx)
# create ivcurve
if ivcurve_pnts:
ivcurve_v = (np.asarray(v_oc)[..., np.newaxis] *
np.linspace(0, 1, ivcurve_pnts))
ivcurve_i = _lambertw_i_from_v(resistance_shunt, resistance_series,
nNsVth, ivcurve_v.T, saturation_current,
photocurrent).T
out += (ivcurve_i, ivcurve_v)
return out
def test__golden_sect_DataFrame(params, lb, ub, expected, func):
v, x = tools._golden_sect_DataFrame(params, lb, ub, func)
assert np.isclose(x, expected, atol=1e-8)
