def test_constructor(self):
mat = np.arange(20).reshape(4, 5)
dat = RegularDataArray(mat, delta=[3, 5], coord_min=[6, 1], dims=('mydim_x', 'mydim_y'))
assert dat.dims == ('mydim_x', 'mydim_y')
dat_cr = dat.sel({'mydim_x': slice(8, 13), 'mydim_y': slice(5, 17)})
dat = RegularDataArray(dat_cr)
assert np.all(dat_cr.values == dat.values)
def test_numpy_1d(self):
# 1D Tests
x = np.arange(9)
y = RegularDataArray(x)
assert len(y.delta) == 1
assert y.delta[0] == 1
assert y.coord_min[0] == 0
y = RegularDataArray(x, axes=[3*np.arange(9) + 3])
assert y.delta[0] == 3
assert y.offset[0] == 3
def test_numpy_2d(self):
# 2D Tests
mat = np.arange(20).reshape(4, 5)
dat = RegularDataArray(mat, delta=[3, 5], coord_min=[6, 1])
assert dat.dims == ('x', 'y')
dat_cr = dat.sel({'x': slice(8, 13), 'y': slice(5, 17)})
assert np.all(dat_cr.values == np.array([[6, 7, 8], [11, 12, 13]]))
assert dat_cr.offset[0] == 9
assert dat_cr.delta[0] == 3
dat_cr = dat.isel({'x': slice(0, 3), 'y': slice(0, 2)})
assert np.all(dat_cr.values == np.array([[0, 1], [5, 6], [10, 11]]))
def test_sel(self):
mat = np.arange(20).reshape(4, 5)
dat = RegularDataArray(mat, delta=[3, 5], coord_min=[6, 1])
dat_cr = dat.sel(slice(8, 13), slice(5, 17))
assert np.allclose(dat_cr.values, mat[1:3, 1:4])
assert dat_cr.coord_min[0] == pytest.approx(9)
assert dat_cr.coord_min[1] == pytest.approx(6)
assert dat_cr.coord_max[0] == pytest.approx(12)
assert dat_cr.coord_max[1] == pytest.approx(16)
assert np.allclose(dat_cr.axes[0], np.arange(2) * 3 + 9)
assert np.allclose(dat_cr.axes[1], np.arange(3) * 5 + 6)
dat_cr = dat.sel(slice(-5, 7), slice(24, 100))
assert np.allclose(dat_cr.values, mat[0, -1].reshape(1, 1))
def test_numpy_1d(self):
# 1D Tests
x = np.arange(9)
y = RegularDataArray(x)
assert len(y.delta) == 1
assert y.delta[0] == 1
assert y.coord_min[0] == 0
y = RegularDataArray(x, delta=[3], coord_min=[3])
assert y.delta[0] == 3
assert y.offset[0] == 3
assert np.allclose(y.axes[0], np.arange(9) * 3 + 3)
y = RegularDataArray(x, coord_min=10, delta=-5)
assert y.delta[0] == pytest.approx(5)
assert y.coord_min[0] == pytest.approx(-30)
assert np.allclose(y.axes[0], np.arange(9) * 5 - 30)
assert np.allclose(y.values, x[::-1])
def make_regular_data():
# Generate data
mat = np.array([[[9, 1], [2, 3]], [[5, 5], [1, 1]], [[1, 1], [0, 0]],
[[3, 2], [1, 8]]])
delta = [2, 5, 7]
coord_min = [0, 1, 2]
return RegularDataArray(mat,
dims=('x4', 'y2', 'z2'),
delta=delta,
coord_min=coord_min)
def test_isel(self):
mat = np.arange(20).reshape(4, 5)
dat = RegularDataArray(mat, delta=[3, 5], coord_min=[6, 1])
dat_cr = dat.isel(slice(1, 3), slice(1, 4))
assert np.allclose(dat_cr.values, mat[1:3, 1:4])
assert dat_cr.coord_min[0] == pytest.approx(9)
assert dat_cr.coord_min[1] == pytest.approx(6)
assert dat_cr.coord_max[0] == pytest.approx(12)
assert dat_cr.coord_max[1] == pytest.approx(16)
assert np.allclose(dat_cr.axes[0], np.arange(2) * 3 + 9)
assert np.allclose(dat_cr.axes[1], np.arange(3) * 5 + 6)
dat_cr = dat.isel(0, None)
assert np.allclose(dat_cr.values, mat[0, :].reshape(1, -1))
dat_cr = dat.isel(-1, slice(None))
assert np.allclose(dat_cr.values, mat[-1, :].reshape(1, -1))
dat_cr = dat.isel(slice(None), 0)
assert np.allclose(dat_cr.values, mat[:, 0].reshape(-1, 1))
dat_cr = dat.isel(slice(None), -1)
assert np.allclose(dat_cr.values, mat[:, -1].reshape(-1, 1))
dat_cr = dat.isel(slice(-2, -1), slice(None))
assert np.allclose(dat_cr.values, mat[-2:-1, :].reshape(1, -1))
def from_file():
import h5py
f = h5py.File(r'Mn1610_02_00034.h5', 'r')
counts = np.array(f['data']['counts'])
exposure = np.array(f['data']['exposure'])
counts[exposure <= 0] = 0
dat_mat = counts
dat_mat[exposure > 0] /= exposure[exposure > 0]
dat_mat[np.isnan(dat_mat)] = 0
delta = [
f['data'][axis].attrs['delta'] for axis in ['axis0', 'axis1', 'axis2']
]
coord_min = [
f['data'][axis].attrs['offset']
for axis in ['axis0', 'axis1', 'axis2']
]
f.close()
mydata = RegularDataArray(dat_mat, delta=delta, coord_min=coord_min)
return mydata
def test_numpy_2d(self):
# 2D Tests
mat = np.arange(20).reshape(4, 5)
dat = RegularDataArray(mat, delta=[3, 5], coord_min=[6, 1])
assert dat.dims == ('x', 'y')
assert np.allclose(dat.axes[0], np.arange(4) * 3 + 6)
assert np.allclose(dat.axes[1], np.arange(5) * 5 + 1)
dat_cr = dat.sel(slice(8, 13), slice(5, 17))
assert np.allclose(dat_cr.values, np.array([[6, 7, 8], [11, 12, 13]]))
assert dat_cr.offset[0] == 9
assert dat_cr.delta[0] == 3
dat_cr = dat.isel(slice(0, 3), slice(0, 2))
assert np.allclose(dat_cr.values, np.array([[0, 1], [5, 6], [10, 11]]))
dat = RegularDataArray(mat, delta=[-3, 5], coord_min=[12, 1])
assert np.allclose(dat.axes[0], np.arange(4) * 3 + 3)
assert np.allclose(dat.values, mat[::-1, :])
def gen_data():
# Generate data
mat = np.array([[[0, 1], [2, 3]], [[0, 0], [1, 1]], [[1, 1], [0, 0]],
[[3, 2], [1, 0]]])
axes = None
return RegularDataArray.from_numpy_array(mat, axes=axes)
def make_5d():
mat = np.arange(3*4*5*6*7*8).reshape((3, 4, 5, 6, 7, 8))
dat = RegularDataArray(mat, delta=[2, 3, 4, 5, 6, 7], coord_min=[-1, -2, -3, -4, -5, -6])
return dat
def make_2d():
mat = np.arange(20).reshape(4, 5)
dat = RegularDataArray(mat, delta=[3, 5], coord_min=[6, 1])
return dat