Compare `e2a46b0 ... +1 ... c9957f3`

functions with stochastic output.
"""

from . import kernels, mean_fns
from . import kernels
from ._gaussian_process import GaussianProcess
from ._random_process import RandomProcess


@@ -5,7 +5,7 @@

import numpy as np
import scipy.stats

from probnum import _function, randvars, utils
from probnum import functions, randvars, utils
from probnum.randprocs import _random_process, kernels
from probnum.randprocs.markov import _transition, continuous, discrete
from probnum.typing import ShapeLike

@@ -31,7 +31,7 @@

            input_shape=input_shape,
            output_shape=output_shape,
            dtype=np.dtype(np.float_),
            mean=_function.LambdaFunction(
            mean=functions.LambdaFunction(
                lambda x: self.__call__(args=x).mean,
                input_shape=input_shape,
                output_shape=output_shape,

@@ -0,0 +1,6 @@

1	+	"""Callables with in- and output shape information supporting algebraic operations."""
2	+
3	+	from . import _algebra
4	+	from ._algebra_fallbacks import ScaledFunction, SumFunction
5	+	from ._function import Function, LambdaFunction
6	+	from ._zero import Zero

@@ -3,12 +3,13 @@

from __future__ import annotations

import abc
import functools
from typing import Callable

import numpy as np

from . import utils
from .typing import ArrayLike, ShapeLike, ShapeType
from probnum import utils
from probnum.typing import ArrayLike, ShapeLike, ShapeType


class Function(abc.ABC):

@@ -17,6 +18,8 @@

    This class represents a, uni- or multivariate, scalar- or tensor-valued,
    mathematical function. Hence, the call method should not have any observable
    side-effects.
    Instances of this class can be added and multiplied by a scalar, which means that
    they are elements of a vector space.

    Parameters
    ----------

@@ -29,7 +32,7 @@

    See Also
    --------
    LambdaFunction : Define a :class:`Function` from an anonymous function.
    ~probnum.randprocs.mean_fns.Zero : Zero mean function of a random process.
    ~probnum.functions.Zero : Zero function.
    """

    def __init__(self, input_shape: ShapeLike, output_shape: ShapeLike = ()) -> None:

@@ -112,6 +115,39 @@

112	115		def _evaluate(self, x: np.ndarray) -> np.ndarray:
113	116		pass
114	117
	118	+	def __neg__(self):
	119	+	return -1.0 * self
	120	+
	121	+	@functools.singledispatchmethod
	122	+	def __add__(self, other):
	123	+	return NotImplemented
	124	+
	125	+	@functools.singledispatchmethod
	126	+	def __sub__(self, other):
	127	+	return NotImplemented
	128	+
	129	+	@functools.singledispatchmethod
	130	+	def __mul__(self, other):
	131	+	if np.ndim(other) == 0:
	132	+	from ._algebra_fallbacks import ( # pylint: disable=import-outside-toplevel
	133	+	ScaledFunction,
	134	+	)
	135	+
	136	+	return ScaledFunction(function=self, scalar=other)
	137	+
	138	+	return NotImplemented
	139	+
	140	+	@functools.singledispatchmethod
	141	+	def __rmul__(self, other):
	142	+	if np.ndim(other) == 0:
	143	+	from ._algebra_fallbacks import ( # pylint: disable=import-outside-toplevel
	144	+	ScaledFunction,
	145	+	)
	146	+
	147	+	return ScaledFunction(function=self, scalar=other)
	148	+
	149	+	return NotImplemented
	150	+
115	151
116	152		class LambdaFunction(Function):
117	153		"""Define a :class:`Function` from a given :class:`callable`.

@@ -131,7 +167,7 @@

    Examples
    --------
    >>> import numpy as np
    >>> from probnum import LambdaFunction
    >>> from probnum.functions import LambdaFunction
    >>> fn = LambdaFunction(fn=lambda x: 2 * x + 1, input_shape=(2,), output_shape=(2,))
    >>> fn(np.array([[1, 2], [4, 5]]))
    array([[ 3,  5],

@@ -7,7 +7,7 @@


import numpy as np

from probnum import _function, randvars, utils as _utils
from probnum import functions, randvars, utils as _utils
from probnum.randprocs import kernels
from probnum.typing import DTypeLike, ShapeLike, ShapeType


@@ -56,7 +56,7 @@

        input_shape: ShapeLike,
        output_shape: ShapeLike,
        dtype: DTypeLike,
        mean: Optional[_function.Function] = None,
        mean: Optional[functions.Function] = None,
        cov: Optional[kernels.Kernel] = None,
    ):
        self._input_shape = _utils.as_shape(input_shape)

@@ -75,7 +75,7 @@


        # Mean function
        if mean is not None:
            if not isinstance(mean, _function.Function):
            if not isinstance(mean, functions.Function):
                raise TypeError("The mean function must have type `probnum.Function`.")

            if mean.input_shape != self._input_shape:

@@ -177,7 +177,7 @@

        raise NotImplementedError

    @property
    def mean(self) -> _function.Function:
    def mean(self) -> functions.Function:
        r"""Mean function :math:`m(x) := \mathbb{E}[f(x)]` of the random process."""
        if self._mean is None:
            raise NotImplementedError

Click to load this diff.

Loading diff...

Click to load this diff.

Loading diff...

Click to load this diff.

Loading diff...

Click to load this diff.

Loading diff...

Click to load this diff.

Loading diff...

Learn more Showing 7 files with coverage changes found.

Changes in src/probnum/linops/_kronecker.py

-6

→

Loading file...

Changes in src/probnum/linops/_linear_operator.py

-1

→

Loading file...

New file src/probnum/functions/_algebra_fallbacks.py

New

Loading file...

New file src/probnum/functions/_algebra.py

New

Loading file...

New file src/probnum/functions/__init__.py

New

Loading file...

Changes in src/probnum/linops/_arithmetic.py

-3

→

Loading file...

Changes in src/probnum/randvars/_arithmetic.py

-2

→

Loading file...

90.28% 93.60% +0.15%

Algebraic Operations on `Functions` (#725)

marvinpfoertner

c9957f3

CI Passed

Hiding 1 contexual commits

+3 Files

+92

+94

-3

90.13% ø ø

Update sphinx requirement from <5.1,>=3.0 to >=3.0,<5.2 (#722)

Unknown

e2a46b0

CI Passed

Files		•	•	•	Coverage
src/probnum	+92	+94	-3	+1	^0.15% 90.28%
Project Totals (197 files)	7,445	6,721	237	487	90.28%

177	177		raise NotImplementedError
178	178
179	179		@property
180		-	def mean(self) -> _function.Function:
	180	+	def mean(self) -> functions.Function:
181	181		r"""Mean function :math:`m(x) := \mathbb{E}[f(x)]` of the random process."""
182	182		if self._mean is None:
183	183		raise NotImplementedError

Navigation	Overlay
`t` Navigate files	`h` Toggle hits
`y` Change url to tip of branch	`m` Toggle misses
`b / v` Jump to prev/next hit line	`p` Toggle partial
`z / x` Jump to prev/next missed or partial line	`1..9` Toggle flags
`shift + o` Open current page in GitHub	`a` Toggle all on
`/ or ?` Show keyboard shortcuts dialog	`c` Toggle context lines or commits

Compare `e2a46b0 ... +1 ... c9957f3`

No flags found

Show failed CI and contexual commits `c`

3 Commits

6	6		functions with stochastic output.
7	7		"""
8	8
9		-	from . import kernels, mean_fns
	9	+	from . import kernels
10	10		from ._gaussian_process import GaussianProcess
11	11		from ._random_process import RandomProcess
12	12

5	5		import numpy as np
6	6		import scipy.stats
7	7
8		-	from probnum import _function, randvars, utils
	8	+	from probnum import functions, randvars, utils
9	9		from probnum.randprocs import _random_process, kernels
10	10		from probnum.randprocs.markov import _transition, continuous, discrete
11	11		from probnum.typing import ShapeLike

31	31		input_shape=input_shape,
32	32		output_shape=output_shape,
33	33		dtype=np.dtype(np.float_),
34		-	mean=_function.LambdaFunction(
	34	+	mean=functions.LambdaFunction(
35	35		lambda x: self.__call__(args=x).mean,
36	36		input_shape=input_shape,
37	37		output_shape=output_shape,

3	3		from __future__ import annotations
4	4
5	5		import abc
	6	+	import functools
6	7		from typing import Callable
7	8
8	9		import numpy as np
9	10
10		-	from . import utils
11		-	from .typing import ArrayLike, ShapeLike, ShapeType
	11	+	from probnum import utils
	12	+	from probnum.typing import ArrayLike, ShapeLike, ShapeType
12	13
13	14
14	15		class Function(abc.ABC):

17	18		This class represents a, uni- or multivariate, scalar- or tensor-valued,
18	19		mathematical function. Hence, the call method should not have any observable
19	20		side-effects.
	21	+	Instances of this class can be added and multiplied by a scalar, which means that
	22	+	they are elements of a vector space.
20	23
21	24		Parameters
22	25		----------

29	32		See Also
30	33		--------
31	34		LambdaFunction : Define a :class:`Function` from an anonymous function.
32		-	~probnum.randprocs.mean_fns.Zero : Zero mean function of a random process.
	35	+	~probnum.functions.Zero : Zero function.
33	36		"""
34	37
35	38		def __init__(self, input_shape: ShapeLike, output_shape: ShapeLike = ()) -> None:

131	167		Examples
132	168		--------
133	169		>>> import numpy as np
134		-	>>> from probnum import LambdaFunction
	170	+	>>> from probnum.functions import LambdaFunction
135	171		>>> fn = LambdaFunction(fn=lambda x: 2 * x + 1, input_shape=(2,), output_shape=(2,))
136	172		>>> fn(np.array([[1, 2], [4, 5]]))
137	173		array([[ 3, 5],

56	56		input_shape: ShapeLike,
57	57		output_shape: ShapeLike,
58	58		dtype: DTypeLike,
59		-	mean: Optional[_function.Function] = None,
	59	+	mean: Optional[functions.Function] = None,
60	60		cov: Optional[kernels.Kernel] = None,
61	61		):
62	62		self._input_shape = _utils.as_shape(input_shape)

75	75
76	76		# Mean function
77	77		if mean is not None:
78		-	if not isinstance(mean, _function.Function):
	78	+	if not isinstance(mean, functions.Function):
79	79		raise TypeError("The mean function must have type `probnum.Function`.")
80	80
81	81		if mean.input_shape != self._input_shape:

Compare e2a46b0 ... +1 ... c9957f3

No flags found

Show failed CI and contexual commits c 3 Commits

Compare `e2a46b0 ... +1 ... c9957f3`

Show failed CI and contexual commits `c`

3 Commits