import copy
import operator as op
import unittest
from unittest.mock import patch
from pint import DimensionalityError, OffsetUnitCalculusError, UnitStrippedWarning
from pint.compat import np
from pint.testsuite import QuantityTestCase, helpers
from pint.testsuite.test_umath import TestUFuncs
[docs]@helpers.requires_numpy()
class TestNumpyMethods(QuantityTestCase):
FORCE_NDARRAY = True
[docs] @classmethod
def setUpClass(cls):
from pint import _DEFAULT_REGISTRY
cls.ureg = _DEFAULT_REGISTRY
cls.Q_ = cls.ureg.Quantity
@property
def q(self):
return [[1, 2], [3, 4]] * self.ureg.m
@property
def q_nan(self):
return [[1, 2], [3, np.nan]] * self.ureg.m
@property
def q_temperature(self):
return self.Q_([[1, 2], [3, 4]], self.ureg.degC)
def assertNDArrayEqual(self, actual, desired):
# Assert that the given arrays are equal, and are not Quantities
np.testing.assert_array_equal(actual, desired)
self.assertFalse(isinstance(actual, self.Q_))
self.assertFalse(isinstance(desired, self.Q_))
[docs]class TestNumpyArrayCreation(TestNumpyMethods):
# https://docs.scipy.org/doc/numpy/reference/routines.array-creation.html
@helpers.requires_array_function_protocol()
def test_ones_like(self):
self.assertNDArrayEqual(np.ones_like(self.q), np.array([[1, 1], [1, 1]]))
@helpers.requires_array_function_protocol()
def test_zeros_like(self):
self.assertNDArrayEqual(np.zeros_like(self.q), np.array([[0, 0], [0, 0]]))
@helpers.requires_array_function_protocol()
def test_empty_like(self):
ret = np.empty_like(self.q)
self.assertEqual(ret.shape, (2, 2))
self.assertTrue(isinstance(ret, np.ndarray))
@helpers.requires_array_function_protocol()
def test_full_like(self):
self.assertQuantityEqual(
np.full_like(self.q, self.Q_(0, self.ureg.degC)),
self.Q_([[0, 0], [0, 0]], self.ureg.degC),
)
self.assertNDArrayEqual(np.full_like(self.q, 2), np.array([[2, 2], [2, 2]]))
[docs]class TestNumpyArrayManipulation(TestNumpyMethods):
# TODO
# https://www.numpy.org/devdocs/reference/routines.array-manipulation.html
# copyto
# broadcast , broadcast_arrays
# asarray asanyarray asmatrix asfarray asfortranarray ascontiguousarray asarray_chkfinite asscalar require
# Changing array shape
def test_flatten(self):
self.assertQuantityEqual(self.q.flatten(), [1, 2, 3, 4] * self.ureg.m)
def test_flat(self):
for q, v in zip(self.q.flat, [1, 2, 3, 4]):
self.assertEqual(q, v * self.ureg.m)
def test_reshape(self):
self.assertQuantityEqual(self.q.reshape([1, 4]), [[1, 2, 3, 4]] * self.ureg.m)
def test_ravel(self):
self.assertQuantityEqual(self.q.ravel(), [1, 2, 3, 4] * self.ureg.m)
@helpers.requires_array_function_protocol()
def test_ravel_numpy_func(self):
self.assertQuantityEqual(np.ravel(self.q), [1, 2, 3, 4] * self.ureg.m)
# Transpose-like operations
@helpers.requires_array_function_protocol()
def test_moveaxis(self):
self.assertQuantityEqual(
np.moveaxis(self.q, 1, 0), np.array([[1, 2], [3, 4]]).T * self.ureg.m
)
@helpers.requires_array_function_protocol()
def test_rollaxis(self):
self.assertQuantityEqual(
np.rollaxis(self.q, 1), np.array([[1, 2], [3, 4]]).T * self.ureg.m
)
@helpers.requires_array_function_protocol()
def test_swapaxes(self):
self.assertQuantityEqual(
np.swapaxes(self.q, 1, 0), np.array([[1, 2], [3, 4]]).T * self.ureg.m
)
def test_transpose(self):
self.assertQuantityEqual(self.q.transpose(), [[1, 3], [2, 4]] * self.ureg.m)
@helpers.requires_array_function_protocol()
def test_transpose_numpy_func(self):
self.assertQuantityEqual(np.transpose(self.q), [[1, 3], [2, 4]] * self.ureg.m)
@helpers.requires_array_function_protocol()
def test_flip_numpy_func(self):
self.assertQuantityEqual(
np.flip(self.q, axis=0), [[3, 4], [1, 2]] * self.ureg.m
)
# Changing number of dimensions
@helpers.requires_array_function_protocol()
def test_atleast_1d(self):
actual = np.atleast_1d(self.Q_(0, self.ureg.degC), self.q.flatten())
expected = (self.Q_(np.array([0]), self.ureg.degC), self.q.flatten())
for ind_actual, ind_expected in zip(actual, expected):
self.assertQuantityEqual(ind_actual, ind_expected)
self.assertQuantityEqual(np.atleast_1d(self.q), self.q)
@helpers.requires_array_function_protocol()
def test_atleast_2d(self):
actual = np.atleast_2d(self.Q_(0, self.ureg.degC), self.q.flatten())
expected = (
self.Q_(np.array([[0]]), self.ureg.degC),
np.array([[1, 2, 3, 4]]) * self.ureg.m,
)
for ind_actual, ind_expected in zip(actual, expected):
self.assertQuantityEqual(ind_actual, ind_expected)
self.assertQuantityEqual(np.atleast_2d(self.q), self.q)
@helpers.requires_array_function_protocol()
def test_atleast_3d(self):
actual = np.atleast_3d(self.Q_(0, self.ureg.degC), self.q.flatten())
expected = (
self.Q_(np.array([[[0]]]), self.ureg.degC),
np.array([[[1], [2], [3], [4]]]) * self.ureg.m,
)
for ind_actual, ind_expected in zip(actual, expected):
self.assertQuantityEqual(ind_actual, ind_expected)
self.assertQuantityEqual(
np.atleast_3d(self.q), np.array([[[1], [2]], [[3], [4]]]) * self.ureg.m
)
@helpers.requires_array_function_protocol()
def test_broadcast_to(self):
self.assertQuantityEqual(
np.broadcast_to(self.q[:, 1], (2, 2)),
np.array([[2, 4], [2, 4]]) * self.ureg.m,
)
@helpers.requires_array_function_protocol()
def test_expand_dims(self):
self.assertQuantityEqual(
np.expand_dims(self.q, 0), np.array([[[1, 2], [3, 4]]]) * self.ureg.m
)
@helpers.requires_array_function_protocol()
def test_squeeze(self):
self.assertQuantityEqual(np.squeeze(self.q), self.q)
self.assertQuantityEqual(
self.q.reshape([1, 4]).squeeze(), [1, 2, 3, 4] * self.ureg.m
)
# Changing number of dimensions
# Joining arrays
@helpers.requires_array_function_protocol()
def test_concatentate(self):
self.assertQuantityEqual(
np.concatenate([self.q] * 2),
self.Q_(np.concatenate([self.q.m] * 2), self.ureg.m),
)
@helpers.requires_array_function_protocol()
def test_stack(self):
self.assertQuantityEqual(
np.stack([self.q] * 2), self.Q_(np.stack([self.q.m] * 2), self.ureg.m)
)
@helpers.requires_array_function_protocol()
def test_column_stack(self):
self.assertQuantityEqual(np.column_stack([self.q[:, 0], self.q[:, 1]]), self.q)
@helpers.requires_array_function_protocol()
def test_dstack(self):
self.assertQuantityEqual(
np.dstack([self.q] * 2), self.Q_(np.dstack([self.q.m] * 2), self.ureg.m)
)
@helpers.requires_array_function_protocol()
def test_hstack(self):
self.assertQuantityEqual(
np.hstack([self.q] * 2), self.Q_(np.hstack([self.q.m] * 2), self.ureg.m)
)
@helpers.requires_array_function_protocol()
def test_vstack(self):
self.assertQuantityEqual(
np.vstack([self.q] * 2), self.Q_(np.vstack([self.q.m] * 2), self.ureg.m)
)
@helpers.requires_array_function_protocol()
def test_block(self):
self.assertQuantityEqual(
np.block([self.q[0, :], self.q[1, :]]), self.Q_([1, 2, 3, 4], self.ureg.m)
)
@helpers.requires_array_function_protocol()
def test_append(self):
self.assertQuantityEqual(
np.append(self.q, [[0, 0]] * self.ureg.m, axis=0),
[[1, 2], [3, 4], [0, 0]] * self.ureg.m,
)
def test_astype(self):
actual = self.q.astype(np.float32)
expected = self.Q_(np.array([[1.0, 2.0], [3.0, 4.0]], dtype=np.float32), "m")
self.assertQuantityEqual(actual, expected)
self.assertEqual(actual.m.dtype, expected.m.dtype)
def test_item(self):
self.assertQuantityEqual(self.Q_([[0]], "m").item(), 0 * self.ureg.m)
[docs]class TestNumpyMathematicalFunctions(TestNumpyMethods):
# https://www.numpy.org/devdocs/reference/routines.math.html
# Trigonometric functions
@helpers.requires_array_function_protocol()
def test_unwrap(self):
self.assertQuantityEqual(
np.unwrap([0, 3 * np.pi] * self.ureg.radians), [0, np.pi]
)
self.assertQuantityEqual(
np.unwrap([0, 540] * self.ureg.deg), [0, 180] * self.ureg.deg
)
# Rounding
@helpers.requires_array_function_protocol()
def test_fix(self):
self.assertQuantityEqual(np.fix(3.14 * self.ureg.m), 3.0 * self.ureg.m)
self.assertQuantityEqual(np.fix(3.0 * self.ureg.m), 3.0 * self.ureg.m)
self.assertQuantityEqual(
np.fix([2.1, 2.9, -2.1, -2.9] * self.ureg.m),
[2.0, 2.0, -2.0, -2.0] * self.ureg.m,
)
# Sums, products, differences
def test_prod(self):
self.assertEqual(self.q.prod(), 24 * self.ureg.m ** 4)
def test_sum(self):
self.assertEqual(self.q.sum(), 10 * self.ureg.m)
self.assertQuantityEqual(self.q.sum(0), [4, 6] * self.ureg.m)
self.assertQuantityEqual(self.q.sum(1), [3, 7] * self.ureg.m)
@helpers.requires_array_function_protocol()
def test_sum_numpy_func(self):
self.assertQuantityEqual(np.sum(self.q, axis=0), [4, 6] * self.ureg.m)
self.assertRaises(OffsetUnitCalculusError, np.sum, self.q_temperature)
@helpers.requires_array_function_protocol()
def test_nansum_numpy_func(self):
self.assertQuantityEqual(np.nansum(self.q_nan, axis=0), [4, 2] * self.ureg.m)
def test_cumprod(self):
self.assertRaises(DimensionalityError, self.q.cumprod)
self.assertQuantityEqual((self.q / self.ureg.m).cumprod(), [1, 2, 6, 24])
@helpers.requires_array_function_protocol()
def test_cumprod_numpy_func(self):
self.assertRaises(DimensionalityError, np.cumprod, self.q)
self.assertRaises(DimensionalityError, np.cumproduct, self.q)
self.assertQuantityEqual(np.cumprod(self.q / self.ureg.m), [1, 2, 6, 24])
self.assertQuantityEqual(np.cumproduct(self.q / self.ureg.m), [1, 2, 6, 24])
self.assertQuantityEqual(
np.cumprod(self.q / self.ureg.m, axis=1), [[1, 2], [3, 12]]
)
@helpers.requires_array_function_protocol()
def test_nancumprod_numpy_func(self):
self.assertRaises(DimensionalityError, np.nancumprod, self.q_nan)
self.assertQuantityEqual(np.nancumprod(self.q_nan / self.ureg.m), [1, 2, 6, 6])
@helpers.requires_array_function_protocol()
def test_diff(self):
self.assertQuantityEqual(np.diff(self.q, 1), [[1], [1]] * self.ureg.m)
self.assertQuantityEqual(
np.diff(self.q_temperature, 1), [[1], [1]] * self.ureg.delta_degC
)
@helpers.requires_array_function_protocol()
def test_ediff1d(self):
self.assertQuantityEqual(np.ediff1d(self.q), [1, 1, 1] * self.ureg.m)
self.assertQuantityEqual(
np.ediff1d(self.q_temperature), [1, 1, 1] * self.ureg.delta_degC
)
@helpers.requires_array_function_protocol()
def test_gradient(self):
grad = np.gradient([[1, 1], [3, 4]] * self.ureg.m, 1 * self.ureg.J)
self.assertQuantityEqual(
grad[0], [[2.0, 3.0], [2.0, 3.0]] * self.ureg.m / self.ureg.J
)
self.assertQuantityEqual(
grad[1], [[0.0, 0.0], [1.0, 1.0]] * self.ureg.m / self.ureg.J
)
grad = np.gradient(self.Q_([[1, 1], [3, 4]], self.ureg.degC), 1 * self.ureg.J)
self.assertQuantityEqual(
grad[0], [[2.0, 3.0], [2.0, 3.0]] * self.ureg.delta_degC / self.ureg.J
)
self.assertQuantityEqual(
grad[1], [[0.0, 0.0], [1.0, 1.0]] * self.ureg.delta_degC / self.ureg.J
)
@helpers.requires_array_function_protocol()
def test_cross(self):
a = [[3, -3, 1]] * self.ureg.kPa
b = [[4, 9, 2]] * self.ureg.m ** 2
self.assertQuantityEqual(
np.cross(a, b), [[-15, -2, 39]] * self.ureg.kPa * self.ureg.m ** 2
)
@helpers.requires_array_function_protocol()
def test_trapz(self):
self.assertQuantityEqual(
np.trapz([1.0, 2.0, 3.0, 4.0] * self.ureg.J, dx=1 * self.ureg.m),
7.5 * self.ureg.J * self.ureg.m,
)
@helpers.requires_array_function_protocol()
def test_dot(self):
self.assertQuantityEqual(
self.q.ravel().dot(np.array([1, 0, 0, 1])), 5 * self.ureg.m
)
@helpers.requires_array_function_protocol()
def test_dot_numpy_func(self):
self.assertQuantityEqual(
np.dot(self.q.ravel(), [0, 0, 1, 0] * self.ureg.dimensionless),
3 * self.ureg.m,
)
@helpers.requires_array_function_protocol()
def test_einsum(self):
a = np.arange(25).reshape(5, 5) * self.ureg.m
b = np.arange(5) * self.ureg.m
self.assertQuantityEqual(np.einsum("ii", a), 60 * self.ureg.m)
self.assertQuantityEqual(
np.einsum("ii->i", a), np.array([0, 6, 12, 18, 24]) * self.ureg.m
)
self.assertQuantityEqual(np.einsum("i,i", b, b), 30 * self.ureg.m ** 2)
self.assertQuantityEqual(
np.einsum("ij,j", a, b),
np.array([30, 80, 130, 180, 230]) * self.ureg.m ** 2,
)
@helpers.requires_array_function_protocol()
def test_solve(self):
self.assertQuantityAlmostEqual(
np.linalg.solve(self.q, [[3], [7]] * self.ureg.s),
self.Q_([[1], [1]], "m / s"),
)
# Arithmetic operations
def test_addition_with_scalar(self):
a = np.array([0, 1, 2])
b = 10.0 * self.ureg("gram/kilogram")
self.assertQuantityAlmostEqual(
a + b, self.Q_([0.01, 1.01, 2.01], self.ureg.dimensionless)
)
self.assertQuantityAlmostEqual(
b + a, self.Q_([0.01, 1.01, 2.01], self.ureg.dimensionless)
)
def test_addition_with_incompatible_scalar(self):
a = np.array([0, 1, 2])
b = 1.0 * self.ureg.m
self.assertRaises(DimensionalityError, op.add, a, b)
self.assertRaises(DimensionalityError, op.add, b, a)
def test_power(self):
arr = np.array(range(3), dtype=np.float)
q = self.Q_(arr, "meter")
for op_ in [op.pow, op.ipow, np.power]:
q_cp = copy.copy(q)
self.assertRaises(DimensionalityError, op_, 2.0, q_cp)
arr_cp = copy.copy(arr)
arr_cp = copy.copy(arr)
q_cp = copy.copy(q)
self.assertRaises(DimensionalityError, op_, q_cp, arr_cp)
q_cp = copy.copy(q)
q2_cp = copy.copy(q)
self.assertRaises(DimensionalityError, op_, q_cp, q2_cp)
self.assertQuantityEqual(
np.power(self.q, self.Q_(2)), self.Q_([[1, 4], [9, 16]], "m**2")
)
self.assertQuantityEqual(
self.q ** self.Q_(2), self.Q_([[1, 4], [9, 16]], "m**2")
)
self.assertNDArrayEqual(arr ** self.Q_(2), np.array([0, 1, 4]))
def test_sqrt(self):
q = self.Q_(100, "m**2")
self.assertQuantityEqual(np.sqrt(q), self.Q_(10, "m"))
def test_cbrt(self):
q = self.Q_(1000, "m**3")
self.assertQuantityEqual(np.cbrt(q), self.Q_(10, "m"))
@unittest.expectedFailure
@helpers.requires_numpy()
def test_exponentiation_array_exp_2(self):
arr = np.array(range(3), dtype=np.float)
# q = self.Q_(copy.copy(arr), None)
q = self.Q_(copy.copy(arr), "meter")
arr_cp = copy.copy(arr)
q_cp = copy.copy(q)
# this fails as expected since numpy 1.8.0 but...
self.assertRaises(DimensionalityError, op.pow, arr_cp, q_cp)
# ..not for op.ipow !
# q_cp is treated as if it is an array. The units are ignored.
# Quantity.__ipow__ is never called
arr_cp = copy.copy(arr)
q_cp = copy.copy(q)
self.assertRaises(DimensionalityError, op.ipow, arr_cp, q_cp)
[docs]class TestNumpyUnclassified(TestNumpyMethods):
def test_tolist(self):
self.assertEqual(
self.q.tolist(),
[[1 * self.ureg.m, 2 * self.ureg.m], [3 * self.ureg.m, 4 * self.ureg.m]],
)
def test_fill(self):
tmp = self.q
tmp.fill(6 * self.ureg.ft)
self.assertQuantityEqual(tmp, [[6, 6], [6, 6]] * self.ureg.ft)
tmp.fill(5 * self.ureg.m)
self.assertQuantityEqual(tmp, [[5, 5], [5, 5]] * self.ureg.m)
def test_take(self):
self.assertQuantityEqual(self.q.take([0, 1, 2, 3]), self.q.flatten())
def test_put(self):
q = [1.0, 2.0, 3.0, 4.0] * self.ureg.m
q.put([0, 2], [10.0, 20.0] * self.ureg.m)
self.assertQuantityEqual(q, [10.0, 2.0, 20.0, 4.0] * self.ureg.m)
q = [1.0, 2.0, 3.0, 4.0] * self.ureg.m
q.put([0, 2], [1.0, 2.0] * self.ureg.mm)
self.assertQuantityEqual(q, [0.001, 2.0, 0.002, 4.0] * self.ureg.m)
q = [1.0, 2.0, 3.0, 4.0] * self.ureg.m / self.ureg.mm
q.put([0, 2], [1.0, 2.0])
self.assertQuantityEqual(
q, [0.001, 2.0, 0.002, 4.0] * self.ureg.m / self.ureg.mm
)
q = [1.0, 2.0, 3.0, 4.0] * self.ureg.m
with self.assertRaises(DimensionalityError):
q.put([0, 2], [4.0, 6.0] * self.ureg.J)
with self.assertRaises(DimensionalityError):
q.put([0, 2], [4.0, 6.0])
def test_repeat(self):
self.assertQuantityEqual(
self.q.repeat(2), [1, 1, 2, 2, 3, 3, 4, 4] * self.ureg.m
)
def test_sort(self):
q = [4, 5, 2, 3, 1, 6] * self.ureg.m
q.sort()
self.assertQuantityEqual(q, [1, 2, 3, 4, 5, 6] * self.ureg.m)
@helpers.requires_array_function_protocol()
def test_sort_numpy_func(self):
q = [4, 5, 2, 3, 1, 6] * self.ureg.m
self.assertQuantityEqual(np.sort(q), [1, 2, 3, 4, 5, 6] * self.ureg.m)
def test_argsort(self):
q = [1, 4, 5, 6, 2, 9] * self.ureg.MeV
self.assertNDArrayEqual(q.argsort(), [0, 4, 1, 2, 3, 5])
@helpers.requires_array_function_protocol()
def test_argsort_numpy_func(self):
self.assertNDArrayEqual(np.argsort(self.q, axis=0), np.array([[0, 0], [1, 1]]))
def test_diagonal(self):
q = [[1, 2, 3], [1, 2, 3], [1, 2, 3]] * self.ureg.m
self.assertQuantityEqual(q.diagonal(offset=1), [2, 3] * self.ureg.m)
@helpers.requires_array_function_protocol()
def test_diagonal_numpy_func(self):
q = [[1, 2, 3], [1, 2, 3], [1, 2, 3]] * self.ureg.m
self.assertQuantityEqual(np.diagonal(q, offset=-1), [1, 2] * self.ureg.m)
def test_compress(self):
self.assertQuantityEqual(
self.q.compress([False, True], axis=0), [[3, 4]] * self.ureg.m
)
self.assertQuantityEqual(
self.q.compress([False, True], axis=1), [[2], [4]] * self.ureg.m
)
@helpers.requires_array_function_protocol()
def test_compress_nep18(self):
self.assertQuantityEqual(
np.compress([False, True], self.q, axis=1), [[2], [4]] * self.ureg.m
)
def test_searchsorted(self):
q = self.q.flatten()
self.assertNDArrayEqual(q.searchsorted([1.5, 2.5] * self.ureg.m), [1, 2])
q = self.q.flatten()
self.assertRaises(DimensionalityError, q.searchsorted, [1.5, 2.5])
[docs] @helpers.requires_array_function_protocol()
def test_searchsorted_numpy_func(self):
"""Test searchsorted as numpy function."""
q = self.q.flatten()
self.assertNDArrayEqual(np.searchsorted(q, [1.5, 2.5] * self.ureg.m), [1, 2])
def test_nonzero(self):
q = [1, 0, 5, 6, 0, 9] * self.ureg.m
self.assertNDArrayEqual(q.nonzero()[0], [0, 2, 3, 5])
@helpers.requires_array_function_protocol()
def test_nonzero_numpy_func(self):
q = [1, 0, 5, 6, 0, 9] * self.ureg.m
self.assertNDArrayEqual(np.nonzero(q)[0], [0, 2, 3, 5])
@helpers.requires_array_function_protocol()
def test_any_numpy_func(self):
q = [0, 1] * self.ureg.m
self.assertTrue(np.any(q))
self.assertRaises(ValueError, np.any, self.q_temperature)
@helpers.requires_array_function_protocol()
def test_all_numpy_func(self):
q = [0, 1] * self.ureg.m
self.assertFalse(np.all(q))
self.assertRaises(ValueError, np.all, self.q_temperature)
@helpers.requires_array_function_protocol()
def test_count_nonzero_numpy_func(self):
q = [1, 0, 5, 6, 0, 9] * self.ureg.m
self.assertEqual(np.count_nonzero(q), 4)
def test_max(self):
self.assertEqual(self.q.max(), 4 * self.ureg.m)
def test_max_numpy_func(self):
self.assertEqual(np.max(self.q), 4 * self.ureg.m)
@helpers.requires_array_function_protocol()
def test_max_with_axis_arg(self):
self.assertQuantityEqual(np.max(self.q, axis=1), [2, 4] * self.ureg.m)
@helpers.requires_array_function_protocol()
def test_max_with_initial_arg(self):
self.assertQuantityEqual(
np.max(self.q[..., None], axis=2, initial=3 * self.ureg.m),
[[3, 3], [3, 4]] * self.ureg.m,
)
@helpers.requires_array_function_protocol()
def test_nanmax(self):
self.assertEqual(np.nanmax(self.q_nan), 3 * self.ureg.m)
def test_argmax(self):
self.assertEqual(self.q.argmax(), 3)
@helpers.requires_array_function_protocol()
def test_argmax_numpy_func(self):
self.assertNDArrayEqual(np.argmax(self.q, axis=0), np.array([1, 1]))
@helpers.requires_array_function_protocol()
def test_nanargmax_numpy_func(self):
self.assertNDArrayEqual(np.nanargmax(self.q_nan, axis=0), np.array([1, 0]))
def test_maximum(self):
self.assertQuantityEqual(
np.maximum(self.q, self.Q_([0, 5], "m")), self.Q_([[1, 5], [3, 5]], "m")
)
def test_min(self):
self.assertEqual(self.q.min(), 1 * self.ureg.m)
@helpers.requires_array_function_protocol()
def test_min_numpy_func(self):
self.assertEqual(np.min(self.q), 1 * self.ureg.m)
@helpers.requires_array_function_protocol()
def test_min_with_axis_arg(self):
self.assertQuantityEqual(np.min(self.q, axis=1), [1, 3] * self.ureg.m)
@helpers.requires_array_function_protocol()
def test_min_with_initial_arg(self):
self.assertQuantityEqual(
np.min(self.q[..., None], axis=2, initial=3 * self.ureg.m),
[[1, 2], [3, 3]] * self.ureg.m,
)
@helpers.requires_array_function_protocol()
def test_nanmin(self):
self.assertEqual(np.nanmin(self.q_nan), 1 * self.ureg.m)
def test_argmin(self):
self.assertEqual(self.q.argmin(), 0)
@helpers.requires_array_function_protocol()
def test_argmin_numpy_func(self):
self.assertNDArrayEqual(np.argmin(self.q, axis=0), np.array([0, 0]))
@helpers.requires_array_function_protocol()
def test_nanargmin_numpy_func(self):
self.assertNDArrayEqual(np.nanargmin(self.q_nan, axis=0), np.array([0, 0]))
def test_minimum(self):
self.assertQuantityEqual(
np.minimum(self.q, self.Q_([0, 5], "m")), self.Q_([[0, 2], [0, 4]], "m")
)
def test_ptp(self):
self.assertEqual(self.q.ptp(), 3 * self.ureg.m)
@helpers.requires_array_function_protocol()
def test_ptp_numpy_func(self):
self.assertQuantityEqual(np.ptp(self.q, axis=0), [2, 2] * self.ureg.m)
def test_clip(self):
self.assertQuantityEqual(
self.q.clip(max=2 * self.ureg.m), [[1, 2], [2, 2]] * self.ureg.m
)
self.assertQuantityEqual(
self.q.clip(min=3 * self.ureg.m), [[3, 3], [3, 4]] * self.ureg.m
)
self.assertQuantityEqual(
self.q.clip(min=2 * self.ureg.m, max=3 * self.ureg.m),
[[2, 2], [3, 3]] * self.ureg.m,
)
self.assertRaises(DimensionalityError, self.q.clip, self.ureg.J)
self.assertRaises(DimensionalityError, self.q.clip, 1)
@helpers.requires_array_function_protocol()
def test_clip_numpy_func(self):
self.assertQuantityEqual(
np.clip(self.q, 150 * self.ureg.cm, None), [[1.5, 2], [3, 4]] * self.ureg.m
)
def test_round(self):
q = [1, 1.33, 5.67, 22] * self.ureg.m
self.assertQuantityEqual(q.round(0), [1, 1, 6, 22] * self.ureg.m)
self.assertQuantityEqual(q.round(-1), [0, 0, 10, 20] * self.ureg.m)
self.assertQuantityEqual(q.round(1), [1, 1.3, 5.7, 22] * self.ureg.m)
@helpers.requires_array_function_protocol()
def test_round_numpy_func(self):
self.assertQuantityEqual(
np.around(1.0275 * self.ureg.m, decimals=2), 1.03 * self.ureg.m
)
self.assertQuantityEqual(
np.round_(1.0275 * self.ureg.m, decimals=2), 1.03 * self.ureg.m
)
def test_trace(self):
self.assertEqual(self.q.trace(), (1 + 4) * self.ureg.m)
def test_cumsum(self):
self.assertQuantityEqual(self.q.cumsum(), [1, 3, 6, 10] * self.ureg.m)
@helpers.requires_array_function_protocol()
def test_cumsum_numpy_func(self):
self.assertQuantityEqual(
np.cumsum(self.q, axis=0), [[1, 2], [4, 6]] * self.ureg.m
)
@helpers.requires_array_function_protocol()
def test_nancumsum_numpy_func(self):
self.assertQuantityEqual(
np.nancumsum(self.q_nan, axis=0), [[1, 2], [4, 2]] * self.ureg.m
)
def test_mean(self):
self.assertEqual(self.q.mean(), 2.5 * self.ureg.m)
@helpers.requires_array_function_protocol()
def test_mean_numpy_func(self):
self.assertEqual(np.mean(self.q), 2.5 * self.ureg.m)
self.assertEqual(np.mean(self.q_temperature), self.Q_(2.5, self.ureg.degC))
@helpers.requires_array_function_protocol()
def test_nanmean_numpy_func(self):
self.assertEqual(np.nanmean(self.q_nan), 2 * self.ureg.m)
@helpers.requires_array_function_protocol()
def test_average_numpy_func(self):
self.assertQuantityAlmostEqual(
np.average(self.q, axis=0, weights=[1, 2]),
[2.33333, 3.33333] * self.ureg.m,
rtol=1e-5,
)
@helpers.requires_array_function_protocol()
def test_median_numpy_func(self):
self.assertEqual(np.median(self.q), 2.5 * self.ureg.m)
@helpers.requires_array_function_protocol()
def test_nanmedian_numpy_func(self):
self.assertEqual(np.nanmedian(self.q_nan), 2 * self.ureg.m)
def test_var(self):
self.assertEqual(self.q.var(), 1.25 * self.ureg.m ** 2)
@helpers.requires_array_function_protocol()
def test_var_numpy_func(self):
self.assertEqual(np.var(self.q), 1.25 * self.ureg.m ** 2)
@helpers.requires_array_function_protocol()
def test_nanvar_numpy_func(self):
self.assertQuantityAlmostEqual(
np.nanvar(self.q_nan), 0.66667 * self.ureg.m ** 2, rtol=1e-5
)
def test_std(self):
self.assertQuantityAlmostEqual(self.q.std(), 1.11803 * self.ureg.m, rtol=1e-5)
@helpers.requires_array_function_protocol()
def test_std_numpy_func(self):
self.assertQuantityAlmostEqual(np.std(self.q), 1.11803 * self.ureg.m, rtol=1e-5)
self.assertRaises(OffsetUnitCalculusError, np.std, self.q_temperature)
def test_prod(self):
self.assertEqual(self.q.prod(), 24 * self.ureg.m ** 4)
def test_cumprod(self):
self.assertRaises(DimensionalityError, self.q.cumprod)
self.assertQuantityEqual((self.q / self.ureg.m).cumprod(), [1, 2, 6, 24])
@helpers.requires_array_function_protocol()
def test_nanstd_numpy_func(self):
self.assertQuantityAlmostEqual(
np.nanstd(self.q_nan), 0.81650 * self.ureg.m, rtol=1e-5
)
@helpers.requires_numpy_previous_than("1.10")
def test_integer_div(self):
a = [1] * self.ureg.m
b = [2] * self.ureg.m
c = a / b # Should be float division
self.assertEqual(c.magnitude[0], 0.5)
a /= b # Should be integer division
self.assertEqual(a.magnitude[0], 0)
def test_conj(self):
self.assertQuantityEqual((self.q * (1 + 1j)).conj(), self.q * (1 - 1j))
self.assertQuantityEqual((self.q * (1 + 1j)).conjugate(), self.q * (1 - 1j))
def test_getitem(self):
self.assertRaises(IndexError, self.q.__getitem__, (0, 10))
self.assertQuantityEqual(self.q[0], [1, 2] * self.ureg.m)
self.assertEqual(self.q[1, 1], 4 * self.ureg.m)
def test_setitem(self):
with self.assertRaises(TypeError):
self.q[0, 0] = 1
with self.assertRaises(DimensionalityError):
self.q[0, 0] = 1 * self.ureg.J
with self.assertRaises(DimensionalityError):
self.q[0] = 1
with self.assertRaises(DimensionalityError):
self.q[0] = np.ndarray([1, 2])
with self.assertRaises(DimensionalityError):
self.q[0] = 1 * self.ureg.J
q = self.q.copy()
q[0] = 1 * self.ureg.m
self.assertQuantityEqual(q, [[1, 1], [3, 4]] * self.ureg.m)
q = self.q.copy()
q[...] = 1 * self.ureg.m
self.assertQuantityEqual(q, [[1, 1], [1, 1]] * self.ureg.m)
q = self.q.copy()
q[:] = 1 * self.ureg.m
self.assertQuantityEqual(q, [[1, 1], [1, 1]] * self.ureg.m)
# check and see that dimensionless num bers work correctly
q = [0, 1, 2, 3] * self.ureg.dimensionless
q[0] = 1
self.assertQuantityEqual(q, np.asarray([1, 1, 2, 3]))
q[0] = self.ureg.m / self.ureg.mm
self.assertQuantityEqual(q, np.asarray([1000, 1, 2, 3]))
q = [0.0, 1.0, 2.0, 3.0] * self.ureg.m / self.ureg.mm
q[0] = 1.0
self.assertQuantityEqual(q, [0.001, 1, 2, 3] * self.ureg.m / self.ureg.mm)
def test_iterator(self):
for q, v in zip(self.q.flatten(), [1, 2, 3, 4]):
self.assertEqual(q, v * self.ureg.m)
def test_iterable(self):
self.assertTrue(np.iterable(self.q))
self.assertFalse(np.iterable(1 * self.ureg.m))
[docs] def test_reversible_op(self):
""" """
x = self.q.magnitude
u = self.Q_(np.ones(x.shape))
self.assertQuantityEqual(x / self.q, u * x / self.q)
self.assertQuantityEqual(x * self.q, u * x * self.q)
self.assertQuantityEqual(x + u, u + x)
self.assertQuantityEqual(x - u, -(u - x))
def test_pickle(self):
import pickle
def pickle_test(q):
pq = pickle.loads(pickle.dumps(q))
self.assertNDArrayEqual(q.magnitude, pq.magnitude)
self.assertEqual(q.units, pq.units)
pickle_test([10, 20] * self.ureg.m)
def test_equal(self):
x = self.q.magnitude
u = self.Q_(np.ones(x.shape))
self.assertQuantityEqual(u, u)
self.assertQuantityEqual(u == u, u.magnitude == u.magnitude)
self.assertQuantityEqual(u == 1, u.magnitude == 1)
def test_shape(self):
u = self.Q_(np.arange(12))
u.shape = 4, 3
self.assertEqual(u.magnitude.shape, (4, 3))
@helpers.requires_array_function_protocol()
def test_shape_numpy_func(self):
self.assertEqual(np.shape(self.q), (2, 2))
@helpers.requires_array_function_protocol()
def test_alen_numpy_func(self):
self.assertEqual(np.alen(self.q), 2)
@helpers.requires_array_function_protocol()
def test_ndim_numpy_func(self):
self.assertEqual(np.ndim(self.q), 2)
@helpers.requires_array_function_protocol()
def test_copy_numpy_func(self):
q_copy = np.copy(self.q)
self.assertQuantityEqual(self.q, q_copy)
self.assertIsNot(self.q, q_copy)
@helpers.requires_array_function_protocol()
def test_trim_zeros_numpy_func(self):
q = [0, 4, 3, 0, 2, 2, 0, 0, 0] * self.ureg.m
self.assertQuantityEqual(np.trim_zeros(q), [4, 3, 0, 2, 2] * self.ureg.m)
@helpers.requires_array_function_protocol()
def test_result_type_numpy_func(self):
self.assertEqual(np.result_type(self.q), np.dtype("int64"))
@helpers.requires_array_function_protocol()
def test_nan_to_num_numpy_func(self):
self.assertQuantityEqual(
np.nan_to_num(self.q_nan, nan=-999 * self.ureg.mm),
[[1, 2], [3, -0.999]] * self.ureg.m,
)
@helpers.requires_array_function_protocol()
def test_meshgrid_numpy_func(self):
x = [1, 2] * self.ureg.m
y = [0, 50, 100] * self.ureg.mm
xx, yy = np.meshgrid(x, y)
self.assertQuantityEqual(xx, [[1, 2], [1, 2], [1, 2]] * self.ureg.m)
self.assertQuantityEqual(yy, [[0, 0], [50, 50], [100, 100]] * self.ureg.mm)
@helpers.requires_array_function_protocol()
def test_isclose_numpy_func(self):
q2 = [[1000.05, 2000], [3000.00007, 4001]] * self.ureg.mm
self.assertNDArrayEqual(
np.isclose(self.q, q2), np.array([[False, True], [True, False]])
)
@helpers.requires_array_function_protocol()
def test_interp_numpy_func(self):
x = [1, 4] * self.ureg.m
xp = np.linspace(0, 3, 5) * self.ureg.m
fp = self.Q_([0, 5, 10, 15, 20], self.ureg.degC)
self.assertQuantityAlmostEqual(
np.interp(x, xp, fp), self.Q_([6.66667, 20.0], self.ureg.degC), rtol=1e-5
)
def test_comparisons(self):
self.assertNDArrayEqual(
self.q > 2 * self.ureg.m, np.array([[False, False], [True, True]])
)
self.assertNDArrayEqual(
self.q < 2 * self.ureg.m, np.array([[True, False], [False, False]])
)
@helpers.requires_array_function_protocol()
def test_where(self):
self.assertQuantityEqual(
np.where(self.q >= 2 * self.ureg.m, self.q, 20 * self.ureg.m),
[[20, 2], [3, 4]] * self.ureg.m,
)
self.assertQuantityEqual(
np.where(self.q >= 2 * self.ureg.m, self.q, 0),
[[0, 2], [3, 4]] * self.ureg.m,
)
self.assertQuantityEqual(
np.where(self.q >= 2 * self.ureg.m, self.q, np.nan),
[[np.nan, 2], [3, 4]] * self.ureg.m,
)
self.assertQuantityEqual(
np.where(self.q >= 3 * self.ureg.m, 0, self.q),
[[1, 2], [0, 0]] * self.ureg.m,
)
self.assertQuantityEqual(
np.where(self.q >= 3 * self.ureg.m, np.nan, self.q),
[[1, 2], [np.nan, np.nan]] * self.ureg.m,
)
self.assertQuantityEqual(
np.where(self.q >= 2 * self.ureg.m, self.q, np.array(np.nan)),
[[np.nan, 2], [3, 4]] * self.ureg.m,
)
self.assertQuantityEqual(
np.where(self.q >= 3 * self.ureg.m, np.array(np.nan), self.q),
[[1, 2], [np.nan, np.nan]] * self.ureg.m,
)
self.assertRaises(
DimensionalityError,
np.where,
self.q < 2 * self.ureg.m,
self.q,
0 * self.ureg.J,
)
@helpers.requires_array_function_protocol()
def test_fabs(self):
self.assertQuantityEqual(
np.fabs(self.q - 2 * self.ureg.m), self.Q_([[1, 0], [1, 2]], "m")
)
@helpers.requires_array_function_protocol()
def test_isin(self):
self.assertNDArrayEqual(
np.isin(self.q, self.Q_([0, 2, 4], "m")),
np.array([[False, True], [False, True]]),
)
self.assertNDArrayEqual(
np.isin(self.q, self.Q_([0, 2, 4], "J")),
np.array([[False, False], [False, False]]),
)
self.assertNDArrayEqual(
np.isin(self.q, [self.Q_(2, "m"), self.Q_(4, "J")]),
np.array([[False, True], [False, False]]),
)
self.assertNDArrayEqual(
np.isin(self.q, self.q.m), np.array([[False, False], [False, False]])
)
self.assertNDArrayEqual(
np.isin(self.q / self.ureg.cm, [1, 3]),
np.array([[True, False], [True, False]]),
)
self.assertRaises(ValueError, np.isin, self.q.m, self.q)
@helpers.requires_array_function_protocol()
def test_percentile(self):
self.assertQuantityEqual(np.percentile(self.q, 25), self.Q_(1.75, "m"))
@helpers.requires_array_function_protocol()
def test_nanpercentile(self):
self.assertQuantityEqual(np.nanpercentile(self.q_nan, 25), self.Q_(1.5, "m"))
@helpers.requires_array_function_protocol()
def test_copyto(self):
a = self.q.m
q = copy.copy(self.q)
np.copyto(q, 2 * q, where=[True, False])
self.assertQuantityEqual(q, self.Q_([[2, 2], [6, 4]], "m"))
np.copyto(q, 0, where=[[False, False], [True, False]])
self.assertQuantityEqual(q, self.Q_([[2, 2], [0, 4]], "m"))
np.copyto(a, q)
self.assertNDArrayEqual(a, np.array([[2, 2], [0, 4]]))
@helpers.requires_array_function_protocol()
def test_tile(self):
self.assertQuantityEqual(
np.tile(self.q, 2), np.array([[1, 2, 1, 2], [3, 4, 3, 4]]) * self.ureg.m
)
@helpers.requires_array_function_protocol()
def test_rot90(self):
self.assertQuantityEqual(
np.rot90(self.q), np.array([[2, 4], [1, 3]]) * self.ureg.m
)
@helpers.requires_array_function_protocol()
def test_insert(self):
self.assertQuantityEqual(
np.insert(self.q, 1, 0 * self.ureg.m, axis=1),
np.array([[1, 0, 2], [3, 0, 4]]) * self.ureg.m,
)
@patch("pint.quantity.ARRAY_FALLBACK", False)
def test_ndarray_downcast(self):
with self.assertWarns(UnitStrippedWarning):
np.asarray(self.q)
@patch("pint.quantity.ARRAY_FALLBACK", False)
def test_ndarray_downcast_with_dtype(self):
with self.assertWarns(UnitStrippedWarning):
qarr = np.asarray(self.q, dtype=np.float64)
self.assertEqual(qarr.dtype, np.float64)
def test_array_protocol_fallback(self):
with self.assertWarns(DeprecationWarning) as cm:
for attr in ("__array_struct__", "__array_interface__"):
getattr(self.q, attr)
warning_text = str(cm.warnings[0].message)
self.assertTrue(
f"unit of the Quantity being stripped" in warning_text
and "will become unavailable" in warning_text
)
@patch("pint.quantity.ARRAY_FALLBACK", False)
def test_array_protocol_unavailable(self):
for attr in ("__array_struct__", "__array_interface__"):
self.assertRaises(AttributeError, getattr, self.q, attr)
@helpers.requires_array_function_protocol()
def test_resize(self):
self.assertQuantityEqual(
np.resize(self.q, (2, 4)), [[1, 2, 3, 4], [1, 2, 3, 4]] * self.ureg.m
)
@helpers.requires_array_function_protocol()
def test_pad(self):
# Tests reproduced with modification from NumPy documentation
a = [1, 2, 3, 4, 5] * self.ureg.m
self.assertQuantityEqual(
np.pad(a, (2, 3), "constant", constant_values=(4, 600 * self.ureg.cm)),
[4, 4, 1, 2, 3, 4, 5, 6, 6, 6] * self.ureg.m,
)
self.assertQuantityEqual(
np.pad(a, (2, 3), "edge"), [1, 1, 1, 2, 3, 4, 5, 5, 5, 5] * self.ureg.m
)
self.assertQuantityEqual(
np.pad(a, (2, 3), "linear_ramp", end_values=(5, -4) * self.ureg.m),
[5, 3, 1, 2, 3, 4, 5, 2, -1, -4] * self.ureg.m,
)
self.assertQuantityEqual(
np.pad(a, (2,), "maximum"), [5, 5, 1, 2, 3, 4, 5, 5, 5] * self.ureg.m
)
self.assertQuantityEqual(
np.pad(a, (2,), "mean"), [3, 3, 1, 2, 3, 4, 5, 3, 3] * self.ureg.m
)
self.assertQuantityEqual(
np.pad(a, (2,), "median"), [3, 3, 1, 2, 3, 4, 5, 3, 3] * self.ureg.m
)
self.assertQuantityEqual(
np.pad(self.q, ((3, 2), (2, 3)), "minimum"),
[
[1, 1, 1, 2, 1, 1, 1],
[1, 1, 1, 2, 1, 1, 1],
[1, 1, 1, 2, 1, 1, 1],
[1, 1, 1, 2, 1, 1, 1],
[3, 3, 3, 4, 3, 3, 3],
[1, 1, 1, 2, 1, 1, 1],
[1, 1, 1, 2, 1, 1, 1],
]
* self.ureg.m,
)
self.assertQuantityEqual(
np.pad(a, (2, 3), "reflect"), [3, 2, 1, 2, 3, 4, 5, 4, 3, 2] * self.ureg.m
)
self.assertQuantityEqual(
np.pad(a, (2, 3), "reflect", reflect_type="odd"),
[-1, 0, 1, 2, 3, 4, 5, 6, 7, 8] * self.ureg.m,
)
self.assertQuantityEqual(
np.pad(a, (2, 3), "symmetric"), [2, 1, 1, 2, 3, 4, 5, 5, 4, 3] * self.ureg.m
)
self.assertQuantityEqual(
np.pad(a, (2, 3), "symmetric", reflect_type="odd"),
[0, 1, 1, 2, 3, 4, 5, 5, 6, 7] * self.ureg.m,
)
self.assertQuantityEqual(
np.pad(a, (2, 3), "wrap"), [4, 5, 1, 2, 3, 4, 5, 1, 2, 3] * self.ureg.m
)
def pad_with(vector, pad_width, iaxis, kwargs):
pad_value = kwargs.get("padder", 10)
vector[: pad_width[0]] = pad_value
vector[-pad_width[1] :] = pad_value
b = self.Q_(np.arange(6).reshape((2, 3)), "degC")
self.assertQuantityEqual(
np.pad(b, 2, pad_with),
self.Q_(
[
[10, 10, 10, 10, 10, 10, 10],
[10, 10, 10, 10, 10, 10, 10],
[10, 10, 0, 1, 2, 10, 10],
[10, 10, 3, 4, 5, 10, 10],
[10, 10, 10, 10, 10, 10, 10],
[10, 10, 10, 10, 10, 10, 10],
],
"degC",
),
)
self.assertQuantityEqual(
np.pad(b, 2, pad_with, padder=100),
self.Q_(
[
[100, 100, 100, 100, 100, 100, 100],
[100, 100, 100, 100, 100, 100, 100],
[100, 100, 0, 1, 2, 100, 100],
[100, 100, 3, 4, 5, 100, 100],
[100, 100, 100, 100, 100, 100, 100],
[100, 100, 100, 100, 100, 100, 100],
],
"degC",
),
) # Note: Does not support Quantity pad_with vectorized callable use
@unittest.skip
class TestBitTwiddlingUfuncs(TestUFuncs):
"""Universal functions (ufuncs) > Bittwiddling functions
http://docs.scipy.org/doc/numpy/reference/ufuncs.html#bittwiddlingfunctions
bitwise_and(x1, x2[, out]) Compute the bitwise AND of two arrays elementwise.
bitwise_or(x1, x2[, out]) Compute the bitwise OR of two arrays elementwise.
bitwise_xor(x1, x2[, out]) Compute the bitwise XOR of two arrays elementwise.
invert(x[, out]) Compute bitwise inversion, or bitwise NOT, elementwise.
left_shift(x1, x2[, out]) Shift the bits of an integer to the left.
right_shift(x1, x2[, out]) Shift the bits of an integer to the right.
Parameters
----------
Returns
-------
"""
@property
def qless(self):
return np.asarray([1, 2, 3, 4], dtype=np.uint8) * self.ureg.dimensionless
@property
def qs(self):
return 8 * self.ureg.J
@property
def q1(self):
return np.asarray([1, 2, 3, 4], dtype=np.uint8) * self.ureg.J
@property
def q2(self):
return 2 * self.q1
@property
def qm(self):
return np.asarray([1, 2, 3, 4], dtype=np.uint8) * self.ureg.m
def test_bitwise_and(self):
self._test2(np.bitwise_and, self.q1, (self.q2, self.qs), (self.qm,), "same")
def test_bitwise_or(self):
self._test2(
np.bitwise_or, self.q1, (self.q1, self.q2, self.qs), (self.qm,), "same"
)
def test_bitwise_xor(self):
self._test2(
np.bitwise_xor, self.q1, (self.q1, self.q2, self.qs), (self.qm,), "same"
)
def test_invert(self):
self._test1(np.invert, (self.q1, self.q2, self.qs), (), "same")
def test_left_shift(self):
self._test2(
np.left_shift, self.q1, (self.qless, 2), (self.q1, self.q2, self.qs), "same"
)
def test_right_shift(self):
self._test2(
np.right_shift,
self.q1,
(self.qless, 2),
(self.q1, self.q2, self.qs),
"same",
)
