def test_interp(h, wd, ws, h_i, wd_l, ws_k):
ds = xr.Dataset({
'TI': 1,
'P': 1,
'XYHLK': (['x', 'y', 'h', 'wd', 'ws'], np.random.rand(10, 20, len(h), len(wd), len(ws))),
'XYHL': (['x', 'y', 'h', 'wd'], np.random.rand(10, 20, len(h), len(wd))),
'XYHK': (['x', 'y', 'h', 'ws'], np.random.rand(10, 20, len(h), len(ws))),
'K': (['ws'], np.random.rand(len(ws))),
'L': (['wd'], np.random.rand(len(wd))),
'KL': (['wd', 'ws'], np.random.rand(len(wd), len(ws))),
'XY': (['x', 'y'], np.random.rand(10, 20)),
'H': (['h'], np.random.rand(len(h))),
'XYH': (['x', 'y', 'h'], np.random.rand(10, 20, len(h))),
'XYL': (['x', 'y', 'wd'], np.random.rand(10, 20, len(wd))),
'XYK': (['x', 'y', 'ws'], np.random.rand(10, 20, len(ws))),
'I': (['i'], np.random.rand(2)),
'IL': (['i', 'wd'], np.random.rand(2, len(wd))),
'IK': (['i', 'ws'], np.random.rand(2, len(ws))),
'ILK': (['i', 'wd', 'ws'], np.random.rand(2, len(wd), len(ws))),
},
coords={'x': np.linspace(0, 100, 10),
'y': np.linspace(200, 300, 20),
'h': h,
'wd': wd,
'ws': ws,
'i': [0, 1]}
)
site = XRSite(ds)
lw = LocalWind(x_i=[25, 50], y_i=[225, 250], h_i=h_i, wd=wd_l, ws=ws_k, wd_bin_size=1)
for n in ['XYHLK', 'XYHL', 'XYHK', 'K', 'L', 'KL', 'XY', 'H', 'XYH', 'XYL', 'XYK', 'I', 'IL', 'IK', 'ILK']:
ip1 = site.interp(site.ds[n], lw.coords)
ip2 = ds[n].sel_interp_all(lw.coords)
npt.assert_array_equal(ip1.shape, ip2.shape)
npt.assert_array_almost_equal(ip1.data, ip2.data)
def test_interp_special_cases():
wd = np.arange(5)
ws = np.arange(10)
ds = xr.Dataset({
'TI': (['i', 'wd', 'ws'], np.random.rand(10, len(wd), len(ws))),
'P': 1
},
coords={'i': np.arange(10),
'wd': wd,
'ws': ws}
)
site = XRSite(ds)
with pytest.raises(ValueError, match=r"Number of points, i\(=10\), in site data variable, TI, must match "):
lw = LocalWind(x_i=[25, 50], y_i=[225, 250], h_i=110, wd=wd, ws=ws, wd_bin_size=1)
site.interp(site.ds.TI, lw.coords)
x = y = np.arange(10)
lw = LocalWind(x_i=x, y_i=y, h_i=110, wd=wd, ws=ws, wd_bin_size=1)
ip1 = site.interp(site.ds.TI, lw.coords)
ip2 = ds.TI.sel_interp_all(lw.coords)
npt.assert_array_equal(ip1.shape, ip2.shape)
npt.assert_array_almost_equal(ip1.data, ip2.data)
