def test__reordered_axes():
a = Axis('x', 0, None)
b = Axis('y', 1, None)
c = Axis('z', 2, None)
res = _reordered_axes([a, b, c], (1, 2, 0))
names_inds = [(ax.name, ax.index) for ax in res]
yield nt.assert_equal, set(names_inds), set([('y', 0), ('z', 1), ('x', 2)])
def test_axes_numeric_access(self):
for i, spec in enumerate(self.axes_spec):
try:
name, labels = spec
except ValueError:
name, labels = spec, None
nt.assert_true(self.A.axes[i] == Axis(
name=name, index=i, parent_arr=self.A, labels=labels))
def test_2d():
b = DataArray([[1, 2], [3, 4], [5, 6]], 'xy')
yield (nt.assert_equals, b.names, ('x', 'y'))
# Check row named slicing
rs = b.axes.x[0]
yield (npt.assert_equal, rs, [1, 2])
yield nt.assert_equal, rs.names, ('y', )
yield nt.assert_equal, tuple(rs.axes), (Axis('y', 0, rs), )
# Now, check that when slicing a row, we get the right names in the output
yield (nt.assert_equal, b.axes.x[1:].names, ('x', 'y'))
# Check column named slicing
cs = b.axes.y[1]
yield (npt.assert_equal, cs, [2, 4, 6])
yield nt.assert_equal, cs.names, ('x', )
yield nt.assert_equal, tuple(cs.axes), (Axis('x', 0, cs), )
# What happens if we do normal slicing?
rs = b[0]
yield (npt.assert_equal, rs, [1, 2])
yield nt.assert_equal, rs.names, ('y', )
yield nt.assert_equal, tuple(rs.axes), (Axis('y', 0, rs), )
def test_singleton_axis_prep():
b = DataArray(np.random.randn(5, 6), 'xz')
slicing = (None, )
shape, axes, key = _make_singleton_axes(b, slicing)
key_should_be = (slice(None), ) # should be trimmed
shape_should_be = (1, 5, 6)
ax_should_be = [Axis(l, i, b) for i, l in enumerate((None, 'x', 'z'))]
yield nt.assert_true, key_should_be == key, 'key translated poorly'
yield nt.assert_true, shape_should_be == shape, 'shape computed poorly'
yield nt.assert_true, all([a1==a2 for a1,a2 in zip(ax_should_be, axes)]), \
'axes computed poorly'
def test_singleton_axis_prep2():
# a little more complicated
b = DataArray(np.random.randn(5, 6), 'xz')
slicing = (0, None)
shape, axes, key = _make_singleton_axes(b, slicing)
key_should_be = (0, ) # should be trimmed
shape_should_be = (5, 1, 6)
ax_should_be = [Axis(l, i, b) for i, l in enumerate(('x', None, 'z'))]
nt.assert_true(key_should_be == key, 'key translated poorly')
nt.assert_true(shape_should_be == shape, 'shape computed poorly')
nt.assert_true(all([a1 == a2 for a1, a2 in zip(ax_should_be, axes)]),
'axes computed poorly')
def test__pull_axis():
a = Axis('x', 0, None)
b = Axis('y', 1, None)
c = Axis('z', 2, None)
t_pos = Axis('y', 1, None)
t_neg = Axis('x', 5, None)
axes = [a, b, c]
yield nt.assert_true, t_pos in axes
yield nt.assert_false, t_neg in axes
yield nt.assert_equal, axes, _pull_axis(axes, t_neg)
yield nt.assert_equal, axes[:-1], _pull_axis(axes, c)
new_axes = [a, Axis('z', 1, None)]
yield nt.assert_equal, new_axes, _pull_axis(axes, t_pos)
def test__pull_axis():
a = Axis('x', 0, None)
b = Axis('y', 1, None)
c = Axis('z', 2, None)
t_pos = Axis('y', 1, None)
t_neg = Axis('x', 5, None)
axes = [a, b, c]
nt.assert_true(t_pos in axes)
nt.assert_false(t_neg in axes)
nt.assert_equal(axes, _pull_axis(axes, t_neg))
nt.assert_equal(axes[:-1], _pull_axis(axes, c))
new_axes = [a, Axis('z', 1, None)]
nt.assert_equal(new_axes, _pull_axis(axes, t_pos))
def test_axis_equal():
ax1 = Axis('aname', 0, None)
ax2 = Axis('aname', 0, None)
yield nt.assert_equal, ax1, ax2
# The array to which the axis points does not matter in comparison
ax3 = Axis('aname', 0, np.arange(10))
yield nt.assert_equal, ax1, ax3
# but the index does
ax4 = Axis('aname', 1, None)
yield nt.assert_not_equal, ax1, ax4
# so does the name
ax5 = Axis('anothername', 0, None)
yield nt.assert_not_equal, ax1, ax5
# and obviously both
yield nt.assert_not_equal, ax4, ax5
# Try with labels
ax6 = Axis('same', 0, None, labels=['a', 'b'])
ax7 = Axis('same', 0, None, labels=['a', 'b'])
yield nt.assert_equal, ax6, ax7
ax8 = Axis('same', 0, None, labels=['a', 'xx'])
yield nt.assert_not_equal, ax6, ax8
'''Tests for DataArray and friend'''
import sys
PY3 = sys.version_info[0] >= 3
import numpy as np
from datarray.datarray import (Axis, DataArray, NamedAxisError, AxesManager,
_pull_axis, _reordered_axes)
import nose.tools as nt
import numpy.testing as npt
DA = DataArray(np.random.randn(4, 2, 6), 'xyz')
YZ = AxesManager(DA, (Axis('y', 0, None), Axis('z', 1, None)))
XZ = AxesManager(DA, (Axis('x', 0, None), Axis('z', 1, None)))
XY = AxesManager(DA, (Axis('x', 0, None), Axis('y', 1, None)))
AXES_REMOVED = dict(x=YZ, y=XZ, z=XY)
def test_axis_equal():
ax1 = Axis('aname', 0, None)
ax2 = Axis('aname', 0, None)
nt.assert_equal(ax1, ax2)
# The array to which the axis points does not matter in comparison
ax3 = Axis('aname', 0, np.arange(10))
nt.assert_equal(ax1, ax3)
# but the index does
ax4 = Axis('aname', 1, None)
nt.assert_not_equal(ax1, ax4)
# so does the name