def test_cartesian_apply(self):
from pyhrf.tools import cartesian_apply
def foo(a, b, c=1, d=2):
return a + b + c + d
varying_args = {'a': range(2),
'b' : range(2),
'c' : range(2)
}
fixed_args = {'d' : 10}
result = cartesian_apply(varying_args, foo,
fixed_args=fixed_args)
self.assertEqual(result, [10, 11, 11, 12, 11, 12, 12, 13])
def test_cartesian_apply_parallel(self):
from pyhrf.tools import cartesian_apply
from pyhrf.tools.backports import OrderedDict
# OrderDict to keep track of parameter orders in the result
# arg values must be hashable
varying_args = OrderedDict([('a', range(2)),
('b', range(2)),
('c', range(2))])
fixed_args = {'d': 10}
result_tree = cartesian_apply(varying_args, foo,
fixed_args=fixed_args,
nb_parallel_procs=4)
self.assertEqual(result_tree, {0: {0: {0: 10, 1: 11},
1: {0: 11, 1: 12}},
1: {0: {0: 11, 1: 12},
1: {0: 12, 1: 13}}})
def test_cartesian_apply_parallel(self):
from pyhrf.tools import cartesian_apply
from pyhrf.tools.backports import OrderedDict
# OrderDict to keep track of parameter orders in the result
# arg values must be hashable
varying_args = OrderedDict([('a', range(2)),
('b', range(2)),
('c', range(2))])
fixed_args = {'d': 10}
result_tree = cartesian_apply(varying_args, foo,
fixed_args=fixed_args,
nb_parallel_procs=4)
self.assertEqual(result_tree, {0: {0: {0: 10, 1: 11},
1: {0: 11, 1: 12}},
1: {0: {0: 11, 1: 12},
1: {0: 12, 1: 13}}})
def test_cartesian_eval(self):
"""
Test the multiple evaluations of a function that returns
a xndarray, over the cartesian products of given arguments.
"""
def foo(a, b, size, aname):
return xndarray(np.ones(size) * a + b, axes_names=[aname])
from pyhrf.tools import cartesian_apply
from pyhrf.tools.backports import OrderedDict
varying_args = OrderedDict([('a', [1, 2]), ('b', [.5, 1.5])])
fixed_args = {'size': 2, 'aname': 'my_axis'}
res = tree_to_xndarray(cartesian_apply(varying_args, foo, fixed_args))
self.assertEqual(res.data.shape, (2, 2, 2))
npt.assert_array_equal(
res.data,
np.array([[[1.5, 1.5], [2.5, 2.5]], [[2.5, 2.5], [3.5, 3.5]]]))
def test_cartesian_eval(self):
"""
Test the multiple evaluations of a function that returns
a xndarray, over the cartesian products of given arguments.
"""
def foo(a, b, size, aname):
return xndarray(np.ones(size) * a + b, axes_names=[aname])
from pyhrf.tools import cartesian_apply
from pyhrf.tools.backports import OrderedDict
varying_args = OrderedDict([('a', [1, 2]), ('b', [.5, 1.5])])
fixed_args = {'size': 2, 'aname': 'my_axis'}
res = tree_to_xndarray(cartesian_apply(varying_args, foo, fixed_args))
self.assertEqual(res.data.shape, (2, 2, 2))
npt.assert_array_equal(res.data, np.array([[[1.5, 1.5],
[2.5, 2.5]],
[[2.5, 2.5],
[3.5, 3.5]]]))
