def test_physicaliam_scalar(): aoi = -45. iam = pvsystem.physicaliam(aoi, 1.526, 0.002, 4) expected = 0.98797788 assert_allclose(iam, expected, equal_nan=True) aoi = np.nan iam = pvsystem.physicaliam(aoi, 1.526, 0.002, 4) expected = np.nan assert_allclose(iam, expected, equal_nan=True)
def test_physicaliam(): aoi = np.array([-90. , -67.5, -45. , -22.5, 0. , 22.5, 45. , 67.5, 90. , np.nan]) iam = pvsystem.physicaliam(aoi, 1.526, 0.002, 4) expected = np.array([ 0, 0.8893998, 0.98797788, 0.99926198, 1, 0.99926198, 0.98797788, 0.8893998, 0, np.nan]) assert_allclose(iam, expected, equal_nan=True) # GitHub issue 397 aoi = pd.Series(aoi) iam = pvsystem.physicaliam(aoi, 1.526, 0.002, 4) expected = pd.Series(expected) assert_series_equal(iam, expected)
def test_physicaliam(): thetas = np.linspace(-90, 90, 9) iam = pvsystem.physicaliam(4, 0.002, 1.526, thetas) expected = np.array([ nan, 0.8893998, 0.98797788, 0.99926198, nan, 0.99926198, 0.98797788, 0.8893998, nan ]) assert np.isclose(iam, expected, equal_nan=True).all()
def test_physicaliam(): thetas = np.array( [-90., -67.5, -45., -22.5, 0., 22.5, 45., 67.5, 90., np.nan]) iam = pvsystem.physicaliam(thetas, 1.526, 0.002, 4) expected = np.array([ 0, 0.8893998, 0.98797788, 0.99926198, 1, 0.99926198, 0.98797788, 0.8893998, 0, np.nan ]) assert_allclose(iam, expected, equal_nan=True)
def test_physicaliam(): thetas = pd.Series(np.linspace(-180,180,361)) iam = pvsystem.physicaliam(4, 0.002, 1.526, thetas)
def test_physicaliam(): thetas = np.linspace(-90, 90, 9) iam = pvsystem.physicaliam(4, 0.002, 1.526, thetas) expected = np.array([ nan, 0.8893998 , 0.98797788, 0.99926198, nan, 0.99926198, 0.98797788, 0.8893998 , nan]) assert np.isclose(iam, expected, equal_nan=True).all()
def test_proper(): IAM=physicaliam(.05,.5,.2,pd.DataFrame(list(range(90)))) assert(np.size(IAM)==90)