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import numpy as np
import pytest
from pvlib import pvsystem
from pvlib.ivtools import sde
@pytest.fixture
def get_test_iv_params():
return {'IL': 8.0, 'I0': 5e-10, 'Rs': 0.2, 'Rsh': 1000, 'nNsVth': 1.61864}
def test_fit_sandia_simple(get_test_iv_params, get_bad_iv_curves):
test_params = get_test_iv_params
test_params = dict(photocurrent=test_params['IL'],
saturation_current=test_params['I0'],
resistance_series=test_params['Rs'],
resistance_shunt=test_params['Rsh'],
nNsVth=test_params['nNsVth'])
testcurve = pvsystem.singlediode(**test_params)
v = np.linspace(0., testcurve['v_oc'], 300)
i = pvsystem.i_from_v(voltage=v, **test_params)
expected = tuple(test_params.values())
result = sde.fit_sandia_simple(voltage=v, current=i)
assert np.allclose(result, expected, rtol=5e-5)
result = sde.fit_sandia_simple(voltage=v, current=i,
v_oc=testcurve['v_oc'],
i_sc=testcurve['i_sc'])
assert np.allclose(result, expected, rtol=5e-5)
result = sde.fit_sandia_simple(voltage=v, current=i,
v_oc=testcurve['v_oc'],
i_sc=testcurve['i_sc'],
v_mp_i_mp=(testcurve['v_mp'],
testcurve['i_mp']))
assert np.allclose(result, expected, rtol=5e-5)
result = sde.fit_sandia_simple(voltage=v, current=i, vlim=0.1)
assert np.allclose(result, expected, rtol=5e-5)
def test_fit_sandia_simple_bad_iv(get_bad_iv_curves):
# bad IV curves for coverage of if/then in sde._sandia_simple_params
v1, i1, v2, i2 = get_bad_iv_curves
result = sde.fit_sandia_simple(voltage=v1, current=i1)
assert np.allclose(result, (-2.4322856072799985, 8.826830831727355,
111.18558915546389, -63.56227601452038,
-137.9965046659527))
result = sde.fit_sandia_simple(voltage=v2, current=i2)
assert np.allclose(result, (2.62405311949227, 5.075520636620032,
-65.652554411442, 110.35202827739991,
174.49362093001415))
@pytest.mark.parametrize('i,v,nsvth,expected', [
(np.array([3., 2.9, 2.8, 2.7, 2.6, 2.5, 2.4, 1.7, 0.8, 0.]),
np.array([0., 0.2, 0.4, 0.6, 0.8, 1., 1.2, 1.4, 1.45, 1.5]),
10.,
(2.3392, 11.6865, -.2596, -.232, -.7119)),
(np.array(
[5., 4.9, 4.8, 4.7, 4.6, 4.5, 4.4, 4.3, 4.2, 4.1, 4., 3.8, 3.5, 1.7,
0.]),
np.array(
[0., .1, .2, .3, .4, .5, .6, .7, .8, .9, 1., 1.1, 1.18, 1.2, 1.22]),
15.,
(-22.0795, 27.1196, -.0056, -4.2076, -.0498))])
def test__fit_sandia_cocontent(i, v, nsvth, expected):
# test confirms agreement with Matlab code. The returned parameters
# are nonsense
iph, io, rs, rsh, n = sde._fit_sandia_cocontent(v, i, nsvth)
np.testing.assert_allclose(iph, np.array(expected[0]), atol=.0001)
np.testing.assert_allclose(io, np.array([expected[1]]), atol=.0001)
np.testing.assert_allclose(rs, np.array([expected[2]]), atol=.0001)
np.testing.assert_allclose(rsh, np.array([expected[3]]), atol=.0001)
np.testing.assert_allclose(n, np.array([expected[4]]), atol=.0001)
def test__fit_sandia_cocontent_fail():
# tests for ValueError
exc_text = 'voltage and current should have the same length'
with pytest.raises(ValueError, match=exc_text):
sde._fit_sandia_cocontent(np.array([0., 1., 2.]), np.array([4., 3.]),
2.)
exc_text = 'at least 6 voltage points are required; ~50 are recommended'
with pytest.raises(ValueError, match=exc_text):
sde._fit_sandia_cocontent(np.array([0., 1., 2., 3., 4.]),
np.array([4., 3.9, 3.4, 2., 0.]),
2.)
@pytest.fixture
def get_bad_iv_curves():
# v1, i1 produces a bad value for I0_voc
v1 = np.array([0, 0.338798867469060, 0.677597734938121, 1.01639660240718,
1.35519546987624, 1.69399433734530, 2.03279320481436,
2.37159207228342, 2.71039093975248, 3.04918980722154,
3.38798867469060, 3.72678754215966, 4.06558640962873,
4.40438527709779, 4.74318414456685, 5.08198301203591,
5.42078187950497, 5.75958074697403, 6.09837961444309,
6.43717848191215, 6.77597734938121, 7.11477621685027,
7.45357508431933, 7.79237395178839, 8.13117281925745,
8.46997168672651, 8.80877055419557, 9.14756942166463,
9.48636828913369, 9.82516715660275, 10.1639660240718,
10.5027648915409, 10.8415637590099, 11.1803626264790,
11.5191614939481, 11.8579603614171, 12.1967592288862,
12.5355580963552, 12.8743569638243, 13.2131558312934,
13.5519546987624, 13.8907535662315, 14.2295524337005,
14.5683513011696, 14.9071501686387, 15.2459490361077,
15.5847479035768, 15.9235467710458, 16.2623456385149,
16.6011445059840, 16.9399433734530, 17.2787422409221,
17.6175411083911, 17.9563399758602, 18.2951388433293,
18.6339377107983, 18.9727365782674, 19.3115354457364,
19.6503343132055, 19.9891331806746, 20.3279320481436,
20.6667309156127, 21.0055297830817, 21.3443286505508,
21.6831275180199, 22.0219263854889, 22.3607252529580,
22.6995241204270, 23.0383229878961, 23.3771218553652,
23.7159207228342, 24.0547195903033, 24.3935184577724,
24.7323173252414, 25.0711161927105, 25.4099150601795,
25.7487139276486, 26.0875127951177, 26.4263116625867,
26.7651105300558, 27.1039093975248, 27.4427082649939,
27.7815071324630, 28.1203059999320, 28.4591048674011,
28.7979037348701, 29.1367026023392, 29.4755014698083,
29.8143003372773, 30.1530992047464, 30.4918980722154,
30.8306969396845, 31.1694958071536, 31.5082946746226,
31.8470935420917, 32.1858924095607, 32.5246912770298,
32.8634901444989, 33.2022890119679, 33.5410878794370])
i1 = np.array([3.39430882774470, 2.80864492110761, 3.28358165429196,
3.41191190551673, 3.11975662808148, 3.35436585834612,
3.23953272899809, 3.60307083325333, 2.80478101508277,
2.80505102853845, 3.16918996870373, 3.21088388439857,
3.46332865310431, 3.09224155015883, 3.17541550741062,
3.32470179290389, 3.33224664316240, 3.07709000050741,
2.89141245343405, 3.01365768561537, 3.23265176770231,
3.32253647634228, 2.97900657569736, 3.31959549243966,
3.03375461550111, 2.97579298978937, 3.25432831375159,
2.89178382564454, 3.00341909207567, 3.72637492250097,
3.28379856976360, 2.96516169245835, 3.25658381110230,
3.41655911533139, 3.02718097944604, 3.11458376760376,
3.24617304369762, 3.45935502367636, 3.21557333256913,
3.27611176482650, 2.86954135732485, 3.32416319254657,
3.15277467598732, 3.08272557013770, 3.15602202666259,
3.49432799877150, 3.53863997177632, 3.10602611478455,
3.05373911151821, 3.09876772570781, 2.97417228624287,
2.84573593699237, 3.16288578405195, 3.06533173612783,
3.02118336639575, 3.34374977225502, 2.97255164138821,
3.19286135682863, 3.10999753817133, 3.26925354620079,
3.11957809501529, 3.20155017481720, 3.31724984405837,
3.42879043512927, 3.17933067619240, 3.47777362613969,
3.20708912539777, 3.48205761174907, 3.16804363684327,
3.14055472378230, 3.13445657434470, 2.91152696252998,
3.10984113847427, 2.80443349399489, 3.23146278164875,
2.94521083406108, 3.17388903141715, 3.05930294897030,
3.18985234673287, 3.27946609274898, 3.33717523113602,
2.76394303462702, 3.19375132937510, 2.82628616689450,
2.85238527394143, 2.82975892599489, 2.79196912313914,
2.72860792049395, 2.75585977414140, 2.44280222448805,
2.36052347370628, 2.26785071765738, 2.10868255743462,
2.06165739407987, 1.90047259509385, 1.39925575828709,
1.24749015957606, 0.867823806536762, 0.432752457749993, 0])
# v2, i2 produces a bad value for I0_vmp
v2 = np.array([0, 0.365686097622586, 0.731372195245173, 1.09705829286776,
1.46274439049035, 1.82843048811293, 2.19411658573552,
2.55980268335810, 2.92548878098069, 3.29117487860328,
3.65686097622586, 4.02254707384845, 4.38823317147104,
4.75391926909362, 5.11960536671621, 5.48529146433880,
5.85097756196138, 6.21666365958397, 6.58234975720655,
6.94803585482914, 7.31372195245173, 7.67940805007431,
8.04509414769690, 8.41078024531949, 8.77646634294207,
9.14215244056466, 9.50783853818725, 9.87352463580983,
10.2392107334324, 10.6048968310550, 10.9705829286776,
11.3362690263002, 11.7019551239228, 12.0676412215454,
12.4333273191679, 12.7990134167905, 13.1646995144131,
13.5303856120357, 13.8960717096583, 14.2617578072809,
14.6274439049035, 14.9931300025260, 15.3588161001486,
15.7245021977712, 16.0901882953938, 16.4558743930164,
16.8215604906390, 17.1872465882616, 17.5529326858841,
17.9186187835067, 18.2843048811293, 18.6499909787519,
19.0156770763745, 19.3813631739971, 19.7470492716197,
20.1127353692422, 20.4784214668648, 20.8441075644874,
21.2097936621100, 21.5754797597326, 21.9411658573552,
22.3068519549778, 22.6725380526004, 23.0382241502229,
23.4039102478455, 23.7695963454681, 24.1352824430907,
24.5009685407133, 24.8666546383359, 25.2323407359585,
25.5980268335810, 25.9637129312036, 26.3293990288262,
26.6950851264488, 27.0607712240714, 27.4264573216940,
27.7921434193166, 28.1578295169392, 28.5235156145617,
28.8892017121843, 29.2548878098069, 29.6205739074295,
29.9862600050521, 30.3519461026747, 30.7176322002973,
31.0833182979198, 31.4490043955424, 31.8146904931650,
32.1803765907876, 32.5460626884102, 32.9117487860328,
33.2774348836554, 33.6431209812779, 34.0088070789005,
34.3744931765231, 34.7401792741457, 35.1058653717683,
35.4715514693909, 35.8372375670135, 36.2029236646360])
i2 = np.array([6.49218806928330, 6.49139336899548, 6.17810697175204,
6.75197816263663, 6.59529074137515, 6.18164578868300,
6.38709397931910, 6.30685422248427, 6.44640615548925,
6.88727230397772, 6.42074852785591, 6.46348580823746,
6.38642309763941, 5.66356277572311, 6.61010381702082,
6.33288284311125, 6.22475343933610, 6.30651399433833,
6.44435022944051, 6.43741711131908, 6.03536180208946,
6.23814639328170, 5.97229140403242, 6.20790000748341,
6.22933550182341, 6.22992127804882, 6.13400871899299,
6.83491312449950, 6.07952797245846, 6.35837746415450,
6.41972128662324, 6.85256717258275, 6.25807797296759,
6.25124948151766, 6.22229212812413, 6.72249444167406,
6.41085549981649, 6.75792874870056, 6.22096181559171,
6.47839564388996, 6.56010208597432, 6.63300966556949,
6.34617546039339, 6.79812221146153, 6.14486056194136,
6.14979256889311, 6.16883037644880, 6.57309183229605,
6.40064681038509, 6.18861448239873, 6.91340138179698,
5.94164388433788, 6.23638991745862, 6.31898940411710,
6.45247884556830, 6.58081455524297, 6.64915284801713,
6.07122119270245, 6.41398258148256, 6.62144271089614,
6.36377197712687, 6.51487678829345, 6.53418950147730,
6.18886469125371, 6.26341063475750, 6.83488211680259,
6.62699397226695, 6.41286837534735, 6.44060085001851,
6.48114130629288, 6.18607038456406, 6.16923370572396,
6.64223126283631, 6.07231852289266, 5.79043710204375,
6.48463886529882, 6.36263392044401, 6.11212476454494,
6.14573900812925, 6.12568047243240, 6.43836230231577,
6.02505694060219, 6.13819468942244, 6.22100593815064,
6.02394682666345, 5.89016573063789, 5.74448527739202,
5.50415294280017, 5.31883018164157, 4.87476769510305,
4.74386713755523, 4.60638346931628, 4.06177345572680,
3.73334482123538, 3.13848311672243, 2.71638862600768,
2.02963773590165, 1.49291145092070, 0.818343889647352, 0])
return v1, i1, v2, i2