def log10(cube, in_place=False):
"""
Calculate the base-10 logarithm of the cube.
Args:
* cube:
An instance of :class:`iris.cube.Cube`.
Kwargs:
* in_place:
Whether to create a new Cube, or alter the given "cube".
Returns:
An instance of :class:`iris.cube.Cube`.
"""
_assert_is_cube(cube)
new_dtype = _output_dtype(np.log10, cube.dtype, in_place=in_place)
op = da.log10 if cube.has_lazy_data() else np.log10
return _math_op_common(cube,
op,
cube.units.log(10),
new_dtype,
in_place=in_place)
def test_lazy_concatenate_masked_array_mixed_deferred(self):
c1 = self.build_lazy_cube([1, 2])
c2 = self.build_lazy_cube([3, 4, 5])
c2.data = np.ma.masked_greater(c2.data, 3)
cube, = concatenate([c1, c2])
self.assertTrue(cube.has_lazy_data())
self.assertTrue(ma.isMaskedArray(cube.data))
def exp(cube, in_place=False):
"""
Calculate the exponential (exp(x)) of the cube.
Args:
* cube:
An instance of :class:`iris.cube.Cube`.
.. note::
Taking an exponential will return a cube with dimensionless units.
Kwargs:
* in_place:
Whether to create a new Cube, or alter the given "cube".
Returns:
An instance of :class:`iris.cube.Cube`.
"""
_assert_is_cube(cube)
new_dtype = _output_dtype(np.exp, cube.dtype, in_place=in_place)
op = da.exp if cube.has_lazy_data() else np.exp
return _math_op_common(cube, op, cf_units.Unit('1'), new_dtype,
in_place=in_place)
def log2(cube, in_place=False):
"""
Calculate the base-2 logarithm of the cube.
Args:
* cube:
An instance of :class:`iris.cube.Cube`.
Kwargs:lib/iris/tests/unit/analysis/maths/test_subtract.py
* in_place:
Whether to create a new Cube, or alter the given "cube".
Returns:
An instance of :class:`iris.cube.Cube`.
"""
_assert_is_cube(cube)
new_dtype = _output_dtype(np.log2, cube.dtype, in_place=in_place)
op = da.log2 if cube.has_lazy_data() else np.log2
return _math_op_common(cube,
op,
cube.units.log(2),
new_dtype,
in_place=in_place)
def abs(cube, in_place=False):
"""
Calculate the absolute values of the data in the Cube provided.
Args:
* cube:
An instance of :class:`iris.cube.Cube`.
Kwargs:
* in_place:
Whether to create a new Cube, or alter the given "cube".
Returns:
An instance of :class:`iris.cube.Cube`.
"""
_assert_is_cube(cube)
new_dtype = _output_dtype(np.abs, cube.dtype, in_place=in_place)
op = da.absolute if cube.has_lazy_data() else np.abs
return _math_op_common(cube,
op,
cube.units,
new_dtype=new_dtype,
in_place=in_place)
def _math_op_common(cube, operation_function, new_unit, new_dtype=None,
in_place=False):
_assert_is_cube(cube)
if in_place:
new_cube = cube
if cube.has_lazy_data():
new_cube.data = operation_function(cube.lazy_data())
else:
try:
operation_function(cube.data, out=cube.data)
except TypeError:
# Non ufunc function
operation_function(cube.data)
else:
new_cube = cube.copy(data=operation_function(cube.core_data()))
# If the result of the operation is scalar and masked, we need to fix up
# the dtype
if new_dtype is not None \
and not new_cube.has_lazy_data() \
and new_cube.data.shape == () \
and ma.is_masked(new_cube.data):
new_cube.data = ma.masked_array(0, 1, dtype=new_dtype)
iris.analysis.clear_phenomenon_identity(new_cube)
new_cube.units = new_unit
return new_cube
def test_lazy_concatenate_masked_array_mixed_deferred(self):
c1 = self.build_lazy_cube([1, 2])
c2 = self.build_lazy_cube([3, 4, 5])
c2.data = np.ma.masked_greater(c2.data, 3)
(cube, ) = concatenate([c1, c2])
self.assertTrue(cube.has_lazy_data())
self.assertTrue(ma.isMaskedArray(cube.data))
def exp(cube, in_place=False):
"""
Calculate the exponential (exp(x)) of the cube.
Args:
* cube:
An instance of :class:`iris.cube.Cube`.
.. note::
Taking an exponential will return a cube with dimensionless units.
Kwargs:
* in_place:
Whether to create a new Cube, or alter the given "cube".
Returns:
An instance of :class:`iris.cube.Cube`.
"""
_assert_is_cube(cube)
new_dtype = _output_dtype(np.exp, cube.dtype, in_place=in_place)
op = da.exp if cube.has_lazy_data() else np.exp
return _math_op_common(cube, op, cf_units.Unit('1'), new_dtype,
in_place=in_place)
def _math_op_common(cube, operation_function, new_unit, new_dtype=None,
in_place=False):
_assert_is_cube(cube)
if in_place:
new_cube = cube
if cube.has_lazy_data():
new_cube.data = operation_function(cube.lazy_data())
else:
try:
operation_function(cube.data, out=cube.data)
except TypeError:
# Non ufunc function
operation_function(cube.data)
else:
new_cube = cube.copy(data=operation_function(cube.core_data()))
# If the result of the operation is scalar and masked, we need to fix up
# the dtype
if new_dtype is not None \
and not new_cube.has_lazy_data() \
and new_cube.data.shape == () \
and ma.is_masked(new_cube.data):
new_cube.data = ma.masked_array(0, 1, dtype=new_dtype)
iris.analysis.clear_phenomenon_identity(new_cube)
new_cube.units = new_unit
return new_cube
def test_lazy_biggus_concatenate_masked_array_mixed_deffered(self):
c1 = self.build_lazy_cube([1, 2])
c2 = self.build_lazy_cube([3, 4, 5])
c2.data = np.ma.masked_greater(c2.data, 3)
self.assertFalse(c2.has_lazy_data())
cube, = concatenate([c1, c2])
self.assertTrue(cube.has_lazy_data())
self.assertIsInstance(cube.data, np.ma.MaskedArray)
def test_lazy_biggus_concatenate_masked_array_mixed_deffered(self):
c1 = self.build_lazy_cube([1, 2])
c2 = self.build_lazy_cube([3, 4, 5])
c2.data = np.ma.masked_greater(c2.data, 3)
self.assertFalse(c2.has_lazy_data())
cube, = concatenate([c1, c2])
self.assertTrue(cube.has_lazy_data())
self.assertIsInstance(cube.data, np.ma.MaskedArray)
def exponentiate(cube, exponent, in_place=False):
"""
Returns the result of the given cube to the power of a scalar.
Args:
* cube:
An instance of :class:`iris.cube.Cube`.
* exponent:
The integer or floating point exponent.
.. note:: When applied to the cube's unit, the exponent must
result in a unit that can be described using only integer
powers of the basic units.
e.g. Unit('meter^-2 kilogram second^-1')
Kwargs:
* in_place:
Whether to create a new Cube, or alter the given "cube".
Returns:
An instance of :class:`iris.cube.Cube`.
"""
_assert_is_cube(cube)
new_dtype = _output_dtype(
operator.pow,
cube.dtype,
second_dtype=_get_dtype(exponent),
in_place=in_place,
)
if cube.has_lazy_data():
def power(data):
return operator.pow(data, exponent)
else:
def power(data, out=None):
return np.power(data, exponent, out)
return _math_op_common(
cube,
power,
cube.units**exponent,
new_dtype=new_dtype,
in_place=in_place,
)
def abs(cube, in_place=False):
"""
Calculate the absolute values of the data in the Cube provided.
Args:
* cube:
An instance of :class:`iris.cube.Cube`.
Kwargs:
* in_place:
Whether to create a new Cube, or alter the given "cube".
Returns:
An instance of :class:`iris.cube.Cube`.
"""
_assert_is_cube(cube)
new_dtype = _output_dtype(np.abs, cube.dtype, in_place=in_place)
op = da.absolute if cube.has_lazy_data() else np.abs
return _math_op_common(cube, op, cube.units, new_dtype, in_place=in_place)
def exponentiate(cube, exponent, in_place=False):
"""
Returns the result of the given cube to the power of a scalar.
Args:
* cube:
An instance of :class:`iris.cube.Cube`.
* exponent:
The integer or floating point exponent.
.. note:: When applied to the cube's unit, the exponent must
result in a unit that can be described using only integer
powers of the basic units.
e.g. Unit('meter^-2 kilogram second^-1')
Kwargs:
* in_place:
Whether to create a new Cube, or alter the given "cube".
Returns:
An instance of :class:`iris.cube.Cube`.
"""
_assert_is_cube(cube)
new_dtype = _output_dtype(operator.pow, cube.dtype, _get_dtype(exponent),
in_place=in_place)
if cube.has_lazy_data():
def power(data):
return operator.pow(data, exponent)
else:
def power(data, out=None):
return np.power(data, exponent, out)
return _math_op_common(cube, power, cube.units ** exponent, new_dtype,
in_place=in_place)
def log2(cube, in_place=False):
"""
Calculate the base-2 logarithm of the cube.
Args:
* cube:
An instance of :class:`iris.cube.Cube`.
Kwargs:lib/iris/tests/unit/analysis/maths/test_subtract.py
* in_place:
Whether to create a new Cube, or alter the given "cube".
Returns:
An instance of :class:`iris.cube.Cube`.
"""
_assert_is_cube(cube)
new_dtype = _output_dtype(np.log2, cube.dtype, in_place=in_place)
op = da.log2 if cube.has_lazy_data() else np.log2
return _math_op_common(cube, op, cube.units.log(2), new_dtype,
in_place=in_place)
def log10(cube, in_place=False):
"""
Calculate the base-10 logarithm of the cube.
Args:
* cube:
An instance of :class:`iris.cube.Cube`.
Kwargs:
* in_place:
Whether to create a new Cube, or alter the given "cube".
Returns:
An instance of :class:`iris.cube.Cube`.
"""
_assert_is_cube(cube)
new_dtype = _output_dtype(np.log10, cube.dtype, in_place=in_place)
op = da.log10 if cube.has_lazy_data() else np.log10
return _math_op_common(cube, op, cube.units.log(10), new_dtype,
in_place=in_place)
def _math_op_common(
cube,
operation_function,
new_unit,
new_dtype=None,
in_place=False,
skeleton_cube=False,
):
_assert_is_cube(cube)
if in_place and not skeleton_cube:
if cube.has_lazy_data():
cube.data = operation_function(cube.lazy_data())
else:
try:
operation_function(cube.data, out=cube.data)
except TypeError:
# Non-ufunc function
operation_function(cube.data)
new_cube = cube
else:
data = operation_function(cube.core_data())
if skeleton_cube:
# Simply wrap the resultant data in a cube, as no
# cube metadata is required by the caller.
new_cube = iris.cube.Cube(data)
else:
new_cube = cube.copy(data)
# If the result of the operation is scalar and masked, we need to fix-up the dtype.
if (new_dtype is not None and not new_cube.has_lazy_data()
and new_cube.data.shape == () and ma.is_masked(new_cube.data)):
new_cube.data = ma.masked_array(0, 1, dtype=new_dtype)
_sanitise_metadata(new_cube, new_unit)
return new_cube
def test_lazy_concatenate(self):
c1 = self.build_lazy_cube([1, 2])
c2 = self.build_lazy_cube([3, 4, 5])
cube, = concatenate([c1, c2])
self.assertTrue(cube.has_lazy_data())
self.assertFalse(ma.isMaskedArray(cube.data))
def assert_is_not_lazy(self, cube):
self.assertFalse(cube.has_lazy_data())
def test_lazy_biggus_concatenate(self):
c1 = self.build_lazy_cube([1, 2])
c2 = self.build_lazy_cube([3, 4, 5])
cube, = concatenate([c1, c2])
self.assertTrue(cube.has_lazy_data())
self.assertNotIsInstance(cube.data, np.ma.MaskedArray)
def assert_is_not_lazy(self, cube):
self.assertFalse(cube.has_lazy_data())
def assert_is_lazy(self, cube):
self.assertTrue(cube.has_lazy_data())
def assert_is_lazy(self, cube):
self.assertTrue(cube.has_lazy_data())
def _is_concrete(self, cube):
self.assertFalse(cube.has_lazy_data())
def test_lazy_concatenate(self):
c1 = self.build_lazy_cube([1, 2])
c2 = self.build_lazy_cube([3, 4, 5])
(cube, ) = concatenate([c1, c2])
self.assertTrue(cube.has_lazy_data())
self.assertFalse(ma.isMaskedArray(cube.data))
def test_lazy_biggus_concatenate(self):
c1 = self.build_lazy_cube([1, 2])
c2 = self.build_lazy_cube([3, 4, 5])
cube, = concatenate([c1, c2])
self.assertTrue(cube.has_lazy_data())
self.assertNotIsInstance(cube.data, np.ma.MaskedArray)
def _is_concrete(self, cube):
self.assertFalse(cube.has_lazy_data())
