def test_ipfp_no_values(self):
# 6, 12, 18
along_a = ndtest([(3, 'b')], start=1) * 6
# 6, 12, 18
along_b = ndtest([(3, 'a')], start=1) * 6
r = ipfp([along_a, along_b])
assert_array_equal(r,
[[1.0, 2.0, 3.0], [2.0, 4.0, 6.0], [3.0, 6.0, 9.0]])
along_a = LArray([2, 1], Axis(2, 'b'))
along_b = LArray([1, 2], Axis(2, 'a'))
r = ipfp([along_a, along_b])
assert_array_equal(r, [[2 / 3, 1 / 3], [4 / 3, 2 / 3]])
def test_ipfp(self):
a = Axis(2, 'a')
b = Axis(2, 'b')
initial = LArray([[2, 1], [1, 2]], [a, b])
# array sums already match target sums
# [3, 3], [3, 3]
r = ipfp([initial.sum(a), initial.sum(b)], initial)
assert_array_equal(r, [[2, 1], [1, 2]])
# array sums do not match target sums (ie the usual case)
along_a = LArray([2, 1], b)
along_b = LArray([1, 2], a)
r = ipfp([along_a, along_b], initial)
assert_array_equal(r, [[0.8, 0.2], [1.0, 1.0]])
# same as above but using a more precise threshold
r = ipfp([along_a, along_b], initial, threshold=0.01)
assert_array_equal(r, [[0.8450704225352113, 0.15492957746478875],
[1.1538461538461537, 0.8461538461538463]])
# inverted target sums
with self.assertRaisesRegexp(
ValueError,
"axes of target sum along axis 0 \(a\) do not match corresponding "
"array axes: got {a\*} but expected {b\*}. Are the target sums in the "
"correct order\?"):
ipfp([along_b, along_a], initial, threshold=0.01)
def test_create_model():
# data = None --> empty array with shape (0,0) is generated
model = ArrayModel()
assert model.get_data_2D().shape == (0, 0)
# data = scalar
model = ArrayModel(LArray(5))
assert model.get_data_2D().shape == (1, 1)
# data = 1D array --> reshaped to 2D array with dim (1, len(data))
model = ArrayModel(ndtest(5))
assert model.get_data_2D().shape == (1, 5)
# data = 3D array --> reshaped to 2D array with dim (axis1*axis2, axis3)
model = ArrayModel(ndtest((5, 5, 5)))
assert model.get_data_2D().shape == (5 * 5, 5)
def test_ipfp_no_name(self):
initial = LArray([[2, 1], [1, 2]])
# sums already correct
# [3, 3], [3, 3]
r = ipfp([initial.sum(axis=0), initial.sum(axis=1)], initial)
assert_array_equal(r, [[2, 1], [1, 2]])
# different sums (ie the usual case)
along_a = LArray([2, 1])
along_b = LArray([1, 2])
r = ipfp([along_a, along_b], initial)
assert_array_equal(r, [[0.8, 0.2], [1.0, 1.0]])
def test_ipfp(self):
a = Axis('a=a0,a1')
b = Axis('b=b0,b1')
initial = LArray([[2, 1], [1, 2]], [a, b])
# array sums already match target sums
# [3, 3], [3, 3]
r = ipfp([initial.sum(a), initial.sum(b)], initial)
assert_array_equal(r, initial)
# array sums do not match target sums (ie the usual case)
along_a = LArray([2, 1], b)
along_b = LArray([1, 2], a)
r = ipfp([along_a, along_b], initial)
assert_array_equal(r, [[0.8, 0.2], [1.0, 1.0]])
# same as above but using a more precise threshold
r = ipfp([along_a, along_b], initial, threshold=0.01)
assert_array_equal(r, [[0.8450704225352113, 0.15492957746478875],
[1.1538461538461537, 0.8461538461538463]])
# inverted target sums
with self.assertRaisesRegexp(
ValueError,
"axes of target sum along a \(axis 0\) do not match corresponding "
"array axes: got {a} but expected {b}. Are the target sums in the "
"correct order\?"):
ipfp([along_b, along_a], initial)
# different target sums totals
along_a = LArray([2, 1], b)
along_b = LArray([1, 3], a)
with self.assertRaisesRegexp(
ValueError,
"target sum along b \(axis 1\) is different than target sum along "
"a \(axis 0\): 4 vs 3"):
ipfp([along_a, along_b], initial)
# all zero values
initial = LArray([[0, 0], [1, 2]], [a, b])
along_a = LArray([2, 1], b)
along_b = LArray([1, 2], a)
with self.assertRaisesRegexp(
ValueError,
"found all zero values sum along b \(axis 1\) but non zero target "
"sum:\na0: 1"):
ipfp([along_a, along_b], initial)
# zero target sum
initial = LArray([[2, 1], [1, 2]], [a, b])
along_a = LArray([0, 1], b)
along_b = LArray([1, 0], a)
with self.assertRaisesRegexp(
ValueError,
"found Non Zero Values but Zero target Sum \(nzvzs\) along a "
"\(axis 0\), use nzvzs='warn' or 'fix' to set them to zero "
"automatically:\nb0: 3"):
ipfp([along_a, along_b], initial)
# negative initial values
initial = LArray([[2, -1], [1, 2]], [a, b])
with self.assertRaisesRegexp(ValueError,
"negative value\(s\) found:\na0_b1: -1"):
ipfp([along_a, along_b], initial)