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dask: Data.allclose #413

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Jun 22, 2022
Merged

dask: Data.allclose #413

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67cf169
allclose
davidhassell Mar 31, 2022
dca2a6f
allclose
davidhassell Mar 31, 2022
ee0f74f
upstream merge conflicts
davidhassell Apr 5, 2022
c11fcaa
upstream merge
davidhassell May 9, 2022
cc27186
Data.allclose
davidhassell Jun 22, 2022
36baa69
Typo
davidhassell Jun 22, 2022
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38 changes: 17 additions & 21 deletions cf/data/data.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -5337,55 +5337,51 @@ def all(self, axis=None, keepdims=True, split_every=None):
d.override_units(_units_None, inplace=True)
return d

@daskified(_DASKIFIED_VERBOSE)
def allclose(self, y, rtol=None, atol=None):
"""Returns True if two broadcastable arrays have equal values,
False otherwise.
"""Whether an array is element-wise equal within a tolerance.

Return True if the data is broadcastable to array *y* and
element-wise equal within a tolerance.

Two real numbers ``x`` and ``y`` are considered equal if
``|x-y|<=atol+rtol|y|``, where ``atol`` (the tolerance on absolute
differences) and ``rtol`` (the tolerance on relative differences)
are positive, typically very small numbers. See the *atol* and
*rtol* parameters.
{{equals tolerance}}

.. seealso:: `all`, `any`, `isclose`

:Parameters:

y: data_like
The data to compare.

atol: `float`, optional
The absolute tolerance for all numerical comparisons. By
default the value returned by the `atol` function is used.
{{rtol: number, optional}}

rtol: `float`, optional
The relative tolerance for all numerical comparisons. By
default the value returned by the `rtol` function is used.
{{atol: number, optional}}

:Returns:

`bool`
`Data`
A scalar boolean array that is `True` if the two arrays
are equal within the given tolerance, or `False`
otherwise.

**Examples**

>>> d = cf.Data([1000, 2500], 'metre')
>>> e = cf.Data([1, 2.5], 'km')
>>> d.allclose(e)
>>> bool(d.allclose(e))
True

>>> d = cf.Data(['ab', 'cdef'])
>>> d.allclose([[['ab', 'cdef']]])
True

>>> d.allclose(e)
>>> bool(d.allclose([[['ab', 'cdef']]]))
True

>>> d = cf.Data([[1000, 2500], [1000, 2500]], 'metre')
>>> e = cf.Data([1, 2.5], 'km')
>>> d.allclose(e)
>>> bool(d.allclose(e))
True

>>> d = cf.Data([1, 1, 1], 's')
>>> d.allclose(1)
>>> bool(d.allclose(1))
True

"""
Expand Down
62 changes: 50 additions & 12 deletions cf/test/test_Data.py
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -2042,12 +2042,12 @@ def test_Data_BINARY_AND_UNARY_OPERATORS(self):
)

try:
d ** x
d**x
except Exception:
pass
else:
message = "Failed in {!r}**{!r}".format(d, x)
self.assertTrue((d ** x).all(), message)
self.assertTrue((d**x).all(), message)
# --- End: for

for a0 in arrays:
Expand Down Expand Up @@ -2121,12 +2121,12 @@ def test_Data_BINARY_AND_UNARY_OPERATORS(self):
)

try:
x ** d
x**d
except Exception:
pass
else:
message = "Failed in {}**{!r}".format(x, d)
self.assertTrue((x ** d).all(), message)
self.assertTrue((x**d).all(), message)

a = a0.copy()
try:
Expand Down Expand Up @@ -2241,12 +2241,12 @@ def test_Data_BINARY_AND_UNARY_OPERATORS(self):
)

try:
d ** x
d**x
except Exception:
pass
else:
self.assertTrue(
(x ** d).all(), "{}**{}".format(x, repr(d))
(x**d).all(), "{}**{}".format(x, repr(d))
)

self.assertTrue(
Expand Down Expand Up @@ -2529,7 +2529,7 @@ def test_Data_func(self):
if self.test_only and inspect.stack()[0][3] not in self.test_only:
return

a = np.array([[np.e, np.e ** 2, np.e ** 3.5], [0, 1, np.e ** -1]])
a = np.array([[np.e, np.e**2, np.e**3.5], [0, 1, np.e**-1]])

# Using sine as an example function to apply
b = np.sin(a)
Expand Down Expand Up @@ -2577,7 +2577,7 @@ def test_Data_log(self):
return

# Test natural log, base e
a = np.array([[np.e, np.e ** 2, np.e ** 3.5], [0, 1, np.e ** -1]])
a = np.array([[np.e, np.e**2, np.e**3.5], [0, 1, np.e**-1]])
b = np.log(a)
c = cf.Data(a, "s")
d = c.log()
Expand All @@ -2591,15 +2591,15 @@ def test_Data_log(self):
self.assertEqual(c.shape, b.shape)

# Test another base, using 10 as an example (special managed case)
a = np.array([[10, 100, 10 ** 3.5], [0, 1, 0.1]])
a = np.array([[10, 100, 10**3.5], [0, 1, 0.1]])
b = np.log10(a)
c = cf.Data(a, "s")
d = c.log(base=10)
self.assertTrue((d.array == b).all())
self.assertEqual(d.shape, b.shape)

# Test an arbitrary base, using 4 (not a special managed case like 10)
a = np.array([[4, 16, 4 ** 3.5], [0, 1, 0.25]])
a = np.array([[4, 16, 4**3.5], [0, 1, 0.25]])
b = np.log(a) / np.log(4) # the numpy way, using log rules from school
c = cf.Data(a, "s")
d = c.log(base=4)
Expand Down Expand Up @@ -3626,7 +3626,7 @@ def test_Data_collapse_units(self):
self.assertEqual(func().Units, d.Units)

for func in (d.sum_of_squares, d.var):
self.assertEqual(func().Units, d.Units ** 2)
self.assertEqual(func().Units, d.Units**2)

for func in (d.sum_of_weights, d.sum_of_weights2):
self.assertEqual(func().Units, cf.Units())
Expand All @@ -3635,7 +3635,7 @@ def test_Data_collapse_units(self):
w = cf.Data(1, "m")
self.assertEqual(d.integral(weights=w).Units, d.Units * w.Units)
self.assertEqual(d.sum_of_weights(weights=w).Units, w.Units)
self.assertEqual(d.sum_of_weights2(weights=w).Units, w.Units ** 2)
self.assertEqual(d.sum_of_weights2(weights=w).Units, w.Units**2)

# Dimensionless data
d = cf.Data([1, 2])
Expand Down Expand Up @@ -3775,6 +3775,44 @@ def test_Data_set_units(self):
with self.assertRaises(ValueError):
d.set_units("km")

def test_Data_allclose(self):
d = cf.Data(1, "m")
for x in (1, [1], np.array([[1]]), da.from_array(1), cf.Data(1)):
self.assertTrue(d.allclose(x).array)

d = cf.Data([1000, 2500], "metre")
e = cf.Data([1, 2.5], "km")
self.assertTrue(d.allclose(e))

e = cf.Data([1, 999], "km")
self.assertFalse(d.allclose(e))

d = cf.Data([[1000, 2500], [1000, 2500]], "metre")
e = cf.Data([1, 2.5], "km")
self.assertTrue(d.allclose(e))

d = cf.Data(["ab", "cdef"])
e = [[["ab", "cdef"]]]
self.assertTrue(d.allclose(e))

d = cf.Data([1, 1, 1], "s")
e = 1
self.assertTrue(d.allclose(e))

# Incompatible units
with self.assertRaises(ValueError):
d.allclose(cf.Data([1, 1, 1], "m"))

# Not broadcastable
with self.assertRaises(ValueError):
d.allclose([1, 2])

# Incompatible units
d = cf.Data([[1000, 2500]], "m")
e = cf.Data([1, 2.5], "s")
with self.assertRaises(ValueError):
d.allclose(e)

def test_Data_isclose(self):
d = cf.Data(1, "m")
for x in (1, [1], np.array([[1]]), da.from_array(1), cf.Data(1)):
Expand Down