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# The purpose of these tests are to ensure that calling quantities using
# array methods returns quantities with the right units, or raises exceptions.
import numpy as np
from ... import units as u
from ...tests.helper import pytest
from ...utils.compat import (NUMPY_LT_1_8, NUMPY_LT_1_9_1,
NUMPY_LT_1_10, NUMPY_LT_1_10_4)
class TestQuantityArrayCopy(object):
"""
Test whether arrays are properly copied/used in place
"""
def test_copy_on_creation(self):
v = np.arange(1000.)
q_nocopy = u.Quantity(v, "km/s", copy=False)
q_copy = u.Quantity(v, "km/s", copy=True)
v[0] = -1.
assert q_nocopy[0].value == v[0]
assert q_copy[0].value != v[0]
def test_to_copies(self):
q = u.Quantity(np.arange(1.,100.), "km/s")
q2 = q.to(u.m/u.s)
assert np.all(q.value != q2.value)
q3 = q.to(u.km/u.s)
assert np.all(q.value == q3.value)
q[0] = -1.*u.km/u.s
assert q[0].value != q3[0].value
def test_si_copies(self):
q = u.Quantity(np.arange(100.), "m/s")
q2 = q.si
assert np.all(q.value == q2.value)
q[0] = -1.*u.m/u.s
assert q[0].value != q2[0].value
def test_getitem_is_view(self):
"""Check that [keys] work, and that, like ndarray, it returns
a view, so that changing one changes the other.
Also test that one can add axes (closes #1422)
"""
q = u.Quantity(np.arange(100.), "m/s")
q_sel = q[10:20]
q_sel[0] = -1.*u.m/u.s
assert q_sel[0] == q[10]
# also check that getitem can do new axes
q2 = q[:, np.newaxis]
q2[10,0] = -9*u.m/u.s
assert np.all(q2.flatten() == q)
def test_flat(self):
q = u.Quantity(np.arange(9.).reshape(3, 3), "m/s")
q_flat = q.flat
# check that a single item is a quantity (with the right value)
assert q_flat[8] == 8. * u.m / u.s
# and that getting a range works as well
assert np.all(q_flat[0:2] == np.arange(2.) * u.m / u.s)
# as well as getting items via iteration
q_flat_list = [_q for _q in q.flat]
assert np.all(u.Quantity(q_flat_list) ==
u.Quantity([_a for _a in q.value.flat], q.unit))
# check that flat works like a view of the real array
q_flat[8] = -1. * u.km / u.s
assert q_flat[8] == -1. * u.km / u.s
assert q[2,2] == -1. * u.km / u.s
# while if one goes by an iterated item, a copy is made
q_flat_list[8] = -2 * u.km / u.s
assert q_flat_list[8] == -2. * u.km / u.s
assert q_flat[8] == -1. * u.km / u.s
assert q[2,2] == -1. * u.km / u.s
class TestQuantityReshapeFuncs(object):
"""Test different ndarray methods that alter the array shape
tests: reshape, squeeze, ravel, flatten, transpose, swapaxes
"""
def test_reshape(self):
q = np.arange(6.) * u.m
q_reshape = q.reshape(3, 2)
assert isinstance(q_reshape, u.Quantity)
assert q_reshape.unit == q.unit
assert np.all(q_reshape.value == q.value.reshape(3, 2))
def test_squeeze(self):
q = np.arange(6.).reshape(6, 1) * u.m
q_squeeze = q.squeeze()
assert isinstance(q_squeeze, u.Quantity)
assert q_squeeze.unit == q.unit
assert np.all(q_squeeze.value == q.value.squeeze())
def test_ravel(self):
q = np.arange(6.).reshape(3, 2) * u.m
q_ravel = q.ravel()
assert isinstance(q_ravel, u.Quantity)
assert q_ravel.unit == q.unit
assert np.all(q_ravel.value == q.value.ravel())
def test_flatten(self):
q = np.arange(6.).reshape(3, 2) * u.m
q_flatten = q.flatten()
assert isinstance(q_flatten, u.Quantity)
assert q_flatten.unit == q.unit
assert np.all(q_flatten.value == q.value.flatten())
def test_transpose(self):
q = np.arange(6.).reshape(3, 2) * u.m
q_transpose = q.transpose()
assert isinstance(q_transpose, u.Quantity)
assert q_transpose.unit == q.unit
assert np.all(q_transpose.value == q.value.transpose())
def test_swapaxes(self):
q = np.arange(6.).reshape(3, 1, 2) * u.m
q_swapaxes = q.swapaxes(0, 2)
assert isinstance(q_swapaxes, u.Quantity)
assert q_swapaxes.unit == q.unit
assert np.all(q_swapaxes.value == q.value.swapaxes(0, 2))
class TestQuantityStatsFuncs(object):
"""
Test statistical functions
"""
def test_mean(self):
q1 = np.array([1., 2., 4., 5., 6.]) * u.m
assert np.mean(q1) == 3.6 * u.m
def test_mean_inplace(self):
q1 = np.array([1., 2., 4., 5., 6.]) * u.m
qi = 1.5 * u.s
qi2 = np.mean(q1, out=qi)
assert qi2 is qi
assert qi == 3.6 * u.m
def test_std(self):
q1 = np.array([1., 2.]) * u.m
assert np.std(q1) == 0.5 * u.m
# For 1.7 <= Numpy < 1.9.1, inplace causes the variance to be stored instead
# of the standard deviation; https://github.com/numpy/numpy/issues/5240
@pytest.mark.xfail(NUMPY_LT_1_9_1, reason="Numpy 1.9.1 or later is required")
def test_std_inplace(self):
q1 = np.array([1., 2.]) * u.m
qi = 1.5 * u.s
np.std(q1, out=qi)
assert qi == 0.5 * u.m
def test_var(self):
q1 = np.array([1., 2.]) * u.m
assert np.var(q1) == 0.25 * u.m ** 2
def test_var_inplace(self):
q1 = np.array([1., 2.]) * u.m
qi = 1.5 * u.s
np.var(q1, out=qi)
assert qi == 0.25 * u.m ** 2
def test_median(self):
q1 = np.array([1., 2., 4., 5., 6.]) * u.m
assert np.median(q1) == 4. * u.m
def test_median_inplace(self):
q1 = np.array([1., 2., 4., 5., 6.]) * u.m
qi = 1.5 * u.s
np.median(q1, out=qi)
assert qi == 4 * u.m
def test_min(self):
q1 = np.array([1., 2., 4., 5., 6.]) * u.m
assert np.min(q1) == 1. * u.m
def test_min_inplace(self):
q1 = np.array([1., 2., 4., 5., 6.]) * u.m
qi = 1.5 * u.s
np.min(q1, out=qi)
assert qi == 1. * u.m
def test_argmin(self):
q1 = np.array([6., 2., 4., 5., 6.]) * u.m
assert np.argmin(q1) == 1
def test_max(self):
q1 = np.array([1., 2., 4., 5., 6.]) * u.m
assert np.max(q1) == 6. * u.m
def test_max_inplace(self):
q1 = np.array([1., 2., 4., 5., 6.]) * u.m
qi = 1.5 * u.s
np.max(q1, out=qi)
assert qi == 6. * u.m
def test_argmax(self):
q1 = np.array([5., 2., 4., 5., 6.]) * u.m
assert np.argmax(q1) == 4
def test_clip(self):
q1 = np.array([1., 2., 4., 5., 6.]) * u.km / u.m
c1 = q1.clip(1500, 5.5 * u.Mm / u.km)
assert np.all(c1 == np.array([1.5, 2., 4., 5., 5.5]) * u.km / u.m)
def test_clip_inplace(self):
q1 = np.array([1., 2., 4., 5., 6.]) * u.km / u.m
c1 = q1.clip(1500, 5.5 * u.Mm / u.km, out=q1)
assert np.all(q1 == np.array([1.5, 2., 4., 5., 5.5]) * u.km / u.m)
c1[0] = 10 * u.Mm/u.mm
assert np.all(c1.value == q1.value)
def test_conj(self):
q1 = np.array([1., 2., 4., 5., 6.]) * u.km / u.m
assert np.all(q1.conj() == q1)
def test_ptp(self):
q1 = np.array([1., 2., 4., 5., 6.]) * u.m
assert np.ptp(q1) == 5. * u.m
def test_ptp_inplace(self):
q1 = np.array([1., 2., 4., 5., 6.]) * u.m
qi = 1.5 * u.s
np.ptp(q1, out=qi)
assert qi == 5. * u.m
def test_round(self):
q1 = np.array([1.253, 2.253, 3.253]) * u.kg
assert np.all(np.round(q1) == np.array([1, 2, 3]) * u.kg)
assert np.all(np.round(q1, decimals=2) ==
np.round(q1.value, decimals=2) * u.kg)
assert np.all(q1.round(decimals=2) ==
q1.value.round(decimals=2) * u.kg)
def test_round_inplace(self):
q1 = np.array([1.253, 2.253, 3.253]) * u.kg
qi = np.zeros(3) * u.s
a = q1.round(decimals=2, out=qi)
assert a is qi
assert np.all(q1.round(decimals=2) == qi)
def test_sum(self):
q1 = np.array([1., 2., 6.]) * u.m
assert np.all(q1.sum() == 9. * u.m)
assert np.all(np.sum(q1) == 9. * u.m)
q2 = np.array([[4., 5., 9.], [1., 1., 1.]]) * u.s
assert np.all(q2.sum(0) == np.array([5., 6., 10.]) * u.s)
assert np.all(np.sum(q2, 0) == np.array([5., 6., 10.]) * u.s)
def test_sum_inplace(self):
q1 = np.array([1., 2., 6.]) * u.m
qi = 1.5 * u.s
np.sum(q1, out=qi)
assert qi == 9. * u.m
def test_cumsum(self):
q1 = np.array([1, 2, 6]) * u.m
assert np.all(q1.cumsum() == np.array([1, 3, 9]) * u.m)
assert np.all(np.cumsum(q1) == np.array([1, 3, 9]) * u.m)
q2 = np.array([4, 5, 9]) * u.s
assert np.all(q2.cumsum() == np.array([4, 9, 18]) * u.s)
assert np.all(np.cumsum(q2) == np.array([4, 9, 18]) * u.s)
def test_cumsum_inplace(self):
q1 = np.array([1, 2, 6]) * u.m
qi = np.ones(3) * u.s
np.cumsum(q1, out=qi)
assert np.all(qi == np.array([1, 3, 9]) * u.m)
q2 = q1
q1.cumsum(out=q1)
assert np.all(q2 == qi)
def test_nansum(self):
q1 = np.array([1., 2., np.nan]) * u.m
assert np.all(q1.nansum() == 3. * u.m)
assert np.all(np.nansum(q1) == 3. * u.m)
q2 = np.array([[np.nan, 5., 9.], [1., np.nan, 1.]]) * u.s
assert np.all(q2.nansum(0) == np.array([1., 5., 10.]) * u.s)
assert np.all(np.nansum(q2, 0) == np.array([1., 5., 10.]) * u.s)
@pytest.mark.xfail(NUMPY_LT_1_8, reason="Numpy 1.8 or later is required")
def test_nansum_inplace(self):
q1 = np.array([1., 2., np.nan]) * u.m
qi = 1.5 * u.s
qout = q1.nansum(out=qi)
assert qout is qi
assert qi == np.nansum(q1.value) * q1.unit
qi2 = 1.5 * u.s
qout2 = np.nansum(q1, out=qi2)
assert qout2 is qi2
assert qi2 == np.nansum(q1.value) * q1.unit
def test_prod(self):
q1 = np.array([1, 2, 6]) * u.m
with pytest.raises(ValueError) as exc:
q1.prod()
assert 'cannot use prod' in exc.value.args[0]
with pytest.raises(ValueError) as exc:
np.prod(q1)
assert 'cannot use prod' in exc.value.args[0]
q2 = np.array([3., 4., 5.]) * u.Unit(1)
assert q2.prod() == 60. * u.Unit(1)
assert np.prod(q2) == 60. * u.Unit(1)
def test_cumprod(self):
q1 = np.array([1, 2, 6]) * u.m
with pytest.raises(ValueError) as exc:
q1.cumprod()
assert 'cannot use cumprod' in exc.value.args[0]
with pytest.raises(ValueError) as exc:
np.cumprod(q1)
assert 'cannot use cumprod' in exc.value.args[0]
q2 = np.array([3, 4, 5]) * u.Unit(1)
assert np.all(q2.cumprod() == np.array([3, 12, 60]) * u.Unit(1))
assert np.all(np.cumprod(q2) == np.array([3, 12, 60]) * u.Unit(1))
def test_diff(self):
q1 = np.array([1., 2., 4., 10.]) * u.m
assert np.all(q1.diff() == np.array([1., 2., 6.]) * u.m)
assert np.all(np.diff(q1) == np.array([1., 2., 6.]) * u.m)
def test_ediff1d(self):
q1 = np.array([1., 2., 4., 10.]) * u.m
assert np.all(q1.ediff1d() == np.array([1., 2., 6.]) * u.m)
assert np.all(np.ediff1d(q1) == np.array([1., 2., 6.]) * u.m)
@pytest.mark.xfail
def test_dot_func(self):
q1 = np.array([1., 2., 4., 10.]) * u.m
q2 = np.array([3., 4., 5., 6.]) * u.s
q3 = np.dot(q1, q2)
assert q3.value == np.dot(q1.value, q2.value)
assert q3.unit == u.m * u.s
def test_dot_meth(self):
q1 = np.array([1., 2., 4., 10.]) * u.m
q2 = np.array([3., 4., 5., 6.]) * u.s
q3 = q1.dot(q2)
assert q3.value == np.dot(q1.value, q2.value)
assert q3.unit == u.m * u.s
@pytest.mark.xfail(NUMPY_LT_1_10_4,
reason="Numpy 1.10.4 or later is required")
def test_trace_func(self):
q = np.array([[1.,2.],[3.,4.]]) * u.m
assert np.trace(q) == 5. * u.m
def test_trace_meth(self):
q1 = np.array([[1.,2.],[3.,4.]]) * u.m
assert q1.trace() == 5. * u.m
cont = u.Quantity(4., u.s)
q2 = np.array([[3.,4.],[5.,6.]]) * u.m
q2.trace(out=cont)
assert cont == 9. * u.m
def test_clip_func(self):
q = np.arange(10) * u.m
assert np.all(np.clip(q, 3 * u.m, 6 * u.m) == np.array([3., 3.,3.,3.,4.,5.,6.,6.,6.,6.]) * u.m)
def test_clip_meth(self):
expected = np.array([3.,3.,3.,3.,4.,5.,6.,6.,6.,6.]) * u.m
q1 = np.arange(10) * u.m
q3 = q1.clip(3 * u.m, 6 * u.m)
assert np.all(q1.clip(3 * u.m, 6 * u.m) == expected)
cont = np.zeros(10) * u.s
q1.clip(3 * u.m, 6 * u.m, out=cont)
assert np.all(cont == expected)
class TestArrayConversion(object):
"""
Test array conversion methods
"""
def test_item(self):
q1 = u.Quantity(np.array([1, 2, 3]), u.m / u.km, dtype=int)
assert q1.item(1) == 2 * q1.unit
q1.itemset(1, 1)
assert q1.item(1) == 1000 * u.m / u.km
q1.itemset(1, 100 * u.cm / u.km)
assert q1.item(1) == 1 * u.m / u.km
with pytest.raises(TypeError):
q1.itemset(1, 1.5 * u.m / u.km)
with pytest.raises(ValueError):
q1.itemset()
q1[1] = 1
assert q1[1] == 1000 * u.m / u.km
q1[1] = 100 * u.cm / u.km
assert q1[1] == 1 * u.m / u.km
with pytest.raises(TypeError):
q1[1] = 1.5 * u.m / u.km
q1 = np.array([1, 2, 3]) * u.m / u.km
assert all(q1.take((0, 2)) == np.array([1, 3]) * u.m / u.km)
q1.put((1, 2), (3, 4))
assert np.all(q1.take((1, 2)) == np.array([3000, 4000]) * q1.unit)
q1.put(0, 500 * u.cm / u.km)
assert q1.item(0) == 5 * u.m / u.km
def test_slice(self):
"""Test that setitem changes the unit if needed (or ignores it for
values where that is allowed; viz., #2695)"""
q2 = np.array([[1., 2., 3.], [4., 5., 6.]]) * u.km / u.m
q1 = q2.copy()
q2[0, 0] = 10000.
assert q2.unit == q1.unit
assert q2[0, 0].value == 10.
q2[0] = 9. * u.Mm / u.km
assert all(q2.flatten()[:3].value == np.array([9., 9., 9.]))
q2[0, :-1] = 8000.
assert all(q2.flatten()[:3].value == np.array([8., 8., 9.]))
with pytest.raises(u.UnitsError):
q2[1, 1] = 10 * u.s
# just to be sure, repeat with a dimensionfull unit
q3 = u.Quantity(np.arange(10.), "m/s")
q3[5] = 100. * u.cm / u.s
assert q3[5].value == 1.
# and check unit is ignored for 0, inf, nan, where that is reasonable
q3[5] = 0.
assert q3[5] == 0.
q3[5] = np.inf
assert np.isinf(q3[5])
q3[5] = np.nan
assert np.isnan(q3[5])
def test_fill(self):
q1 = np.array([1, 2, 3]) * u.m / u.km
q1.fill(2)
assert np.all(q1 == 2000 * u.m / u.km)
def test_repeat_compress_diagonal(self):
q1 = np.array([1, 2, 3]) * u.m / u.km
q2 = q1.repeat(2)
assert q2.unit == q1.unit
assert all(q2.value == q1.value.repeat(2))
q2.sort()
assert q2.unit == q1.unit
q2 = q1.compress(np.array([True, True, False, False]))
assert q2.unit == q1.unit
assert all(q2.value == q1.value.compress(np.array([True, True,
False, False])))
q1 = np.array([[1, 2], [3, 4]]) * u.m / u.km
q2 = q1.diagonal()
assert q2.unit == q1.unit
assert all(q2.value == q1.value.diagonal())
def test_view(self):
q1 = np.array([1, 2, 3], dtype=np.int64) * u.m / u.km
q2 = q1.view(np.ndarray)
assert not hasattr(q2, 'unit')
q3 = q2.view(u.Quantity)
assert q3._unit is None
# MaskedArray copies and properties assigned in __dict__
q4 = np.ma.MaskedArray(q1)
assert q4._unit is q1._unit
q5 = q4.view(u.Quantity)
assert q5.unit is q1.unit
def test_slice_to_quantity(self):
"""
Regression test for https://github.com/astropy/astropy/issues/2003
"""
a = np.random.uniform(size=(10, 8))
x, y, z = a[:,1:4].T * u.km/u.s
total = np.sum(a[:, 1] * u.km / u.s - x)
assert isinstance(total, u.Quantity)
assert total == (0.0 * u.km / u.s)
def test_byte_type_view_field_changes(self):
q1 = np.array([1, 2, 3], dtype=np.int64) * u.m / u.km
q2 = q1.byteswap()
assert q2.unit == q1.unit
assert all(q2.value == q1.value.byteswap())
q2 = q1.astype(np.float64)
assert all(q2 == q1)
assert q2.dtype == np.float64
q2a = q1.getfield(np.int32, offset=0)
q2b = q1.byteswap().getfield(np.int32, offset=4)
assert q2a.unit == q1.unit
assert all(q2b.byteswap() == q2a)
def test_sort(self):
q1 = np.array([1., 5., 2., 4.]) * u.km / u.m
i = q1.argsort()
assert not hasattr(i, 'unit')
q1.sort()
i = q1.searchsorted([1500, 2500])
assert not hasattr(i, 'unit')
assert all(i == q1.to(
u.dimensionless_unscaled).value.searchsorted([1500, 2500]))
def test_not_implemented(self):
q1 = np.array([1, 2, 3]) * u.m / u.km
with pytest.raises(NotImplementedError):
q1.choose([0, 0, 1])
with pytest.raises(NotImplementedError):
q1.tolist()
with pytest.raises(NotImplementedError):
q1.tostring()
with pytest.raises(NotImplementedError):
q1.tofile(0)
with pytest.raises(NotImplementedError):
q1.dump('a.a')
with pytest.raises(NotImplementedError):
q1.dumps()
class TestRecArray(object):
"""Record arrays are not specifically supported, but we should not
prevent their use unnecessarily"""
def test_creation(self):
ra = (np.array(np.arange(12.).reshape(4,3))
.view(dtype=('f8,f8,f8')).squeeze())
qra = u.Quantity(ra, u.m)
assert np.all(qra[:2].value == ra[:2])
qra[1] = qra[2]
assert qra[1] == qra[2]
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