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WIP real-valued functional #1333

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WIP real-valued functional #1333

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d4e5498
Tried to make functional possible to map to real numbers istead of sp…
miallo Apr 26, 2018
7a278f0
Merge branch 'master' of https://github.com/miallo/odl
miallo Apr 26, 2018
09b1e94
Continued implementation of functionals mapping to RealNumbers
miallo Apr 26, 2018
89652b1
Added range to functional operations
miallo Apr 27, 2018
69521ba
Continued to implement range in default_functionals
miallo Apr 27, 2018
85650f7
Mostly continued default_fuctionals
miallo Apr 27, 2018
7382635
fixed mistake where renaming proximal_l* function inputs to `domain`
miallo Apr 27, 2018
246a31b
fixed range of QuadraticForm-Functional
miallo Apr 27, 2018
5a55e75
Implemented most comments from @kohr-h and @aringh
miallo Apr 27, 2018
d1c4d68
Is there a reason for ufunc_ops to pass the explicit keyword `domain=…
miallo Apr 27, 2018
9003572
Added docstrings for `range` parameter
miallo Apr 27, 2018
77842df
Fields can now be added to the "highest" one
miallo Apr 29, 2018
c7a6127
Removed addition of fields again, Reverted `__repr__` not to include …
miallo Apr 29, 2018
3fa93d9
Changed the order to (domain, range, ...) in __init__ calls and fixed
miallo May 31, 2018
0951041
fixed typo in forward-backward documentation
miallo Jun 5, 2018
0ddd06c
Merged from odl main branch
miallo Jun 13, 2018
cb6df08
CallbackShowConvergence now supports saveto
miallo Jun 14, 2018
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7 changes: 5 additions & 2 deletions odl/operator/default_ops.py
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Original file line number Diff line number Diff line change
Expand Up @@ -182,7 +182,7 @@ class LinCombOperator(Operator):
LinCombOperator(a, b)([x, y]) == a * x + b * y
"""

def __init__(self, space, a, b):
def __init__(self, space, a, b, rangeType=None):
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Oh, that wasn't meant to be pushed... I used it for a mapping-oparator from R2 to C...

"""Initialize a new instance.

Parameters
Expand All @@ -204,8 +204,11 @@ def __init__(self, space, a, b):
>>> z
rn(3).element([ 2., 4., 6.])
"""
if rangeType is None:
rangeType = space.dtype
domain = ProductSpace(space, space)
super(LinCombOperator, self).__init__(domain, space, linear=True)
super(LinCombOperator, self).__init__(domain, space.astype(rangeType),
linear=True)
self.a = a
self.b = b

Expand Down
90 changes: 43 additions & 47 deletions odl/solvers/functional/default_functionals.py
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Expand Up @@ -76,7 +76,7 @@ def __init__(self, domain, exponent, range=None):
range = RealNumbers()
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How about

def __init__(self, domain, exponent, range=RealNumbers()):
    ...

? I feel that the current variant is unnecessarily indirect. None is usually a proxy for some_value_that_depends_on_other_stuff_or_must_be_computed

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This only works if we want RealNumbers to be forever immutable. Are we sure about that? (Id be fine with it)

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Yeah, we can make that clearer by adding __slots__ to RealNumbers and ComplexNumbers.


super(LpNorm, self).__init__(
domain=domain, linear=False, grad_lipschitz=np.nan, range=range)
domain=domain, range=range, linear=False, grad_lipschitz=np.nan)
self.exponent = float(exponent)

# TODO: update when integration operator is in place: issue #440
Expand Down Expand Up @@ -141,7 +141,8 @@ class L1Gradient(Operator):
def __init__(self):
"""Initialize a new instance."""
super(L1Gradient, self).__init__(
functional.domain, functional.domain, linear=False)
functional.domain, range=functional.domain,
linear=False)

def _call(self, x):
"""Apply the gradient operator to the given point."""
Expand All @@ -161,7 +162,8 @@ class L2Gradient(Operator):
def __init__(self):
"""Initialize a new instance."""
super(L2Gradient, self).__init__(
functional.domain, functional.domain, linear=False)
functional.domain, range=functional.domain,
linear=False)

def _call(self, x):
"""Apply the gradient operator to the given point.
Expand Down Expand Up @@ -251,7 +253,7 @@ def __init__(self, vfspace, exponent=None, range=None):
raise TypeError('`space.is_power_space` must be `True`')

super(GroupL1Norm, self).__init__(
domain=vfspace, linear=False, grad_lipschitz=np.nan, range=range)
domain=vfspace, range=range, linear=False, grad_lipschitz=np.nan)
self.pointwise_norm = PointwiseNorm(vfspace, exponent)

def _call(self, x):
Expand Down Expand Up @@ -294,7 +296,7 @@ class GroupL1Gradient(Operator):
def __init__(self):
"""Initialize a new instance."""
super(GroupL1Gradient, self).__init__(
functional.domain, functional.domain, linear=False)
functional.domain, range=functional.domain, linear=False)

def _call(self, x, out):
"""Return ``self(x)``."""
Expand Down Expand Up @@ -382,7 +384,7 @@ def __init__(self, vfspace, exponent=None, range=None):
raise TypeError('`space.is_power_space` must be `True`')

super(IndicatorGroupL1UnitBall, self).__init__(
domain=vfspace, linear=False, grad_lipschitz=np.nan, range=range)
domain=vfspace, range=range, linear=False, grad_lipschitz=np.nan)
self.pointwise_norm = PointwiseNorm(vfspace, exponent)

def _call(self, x):
Expand Down Expand Up @@ -474,8 +476,8 @@ def __init__(self, domain, exponent, range=None):
range : `Field`, optional
Range of the functional. Default: ``domain.field``.
"""
super(IndicatorLpUnitBall, self).__init__(domain=domain, linear=False,
range=range)
super(IndicatorLpUnitBall, self).__init__(domain=domain, range=range,
linear=False)

self.__norm = LpNorm(domain, exponent, range=RealNumbers())
self.__exponent = float(exponent)
Expand Down Expand Up @@ -585,7 +587,7 @@ def __init__(self, domain, range=None):
range : `Field`, optional
Range of the functional. Default: `RealNumbers`.
"""
super(L1Norm, self).__init__(domain=domain, exponent=1, range=range)
super(L1Norm, self).__init__(domain=domain, range=range, exponent=1)

def __repr__(self):
"""Return ``repr(self)``."""
Expand Down Expand Up @@ -624,7 +626,7 @@ def __init__(self, domain, range=None):
range : `Field`, optional
Range of the functional. Default: `RealNumbers`.
"""
super(L2Norm, self).__init__(domain=domain, exponent=2, range=range)
super(L2Norm, self).__init__(domain=domain, range=range, exponent=2)

def __repr__(self):
"""Return ``repr(self)``."""
Expand Down Expand Up @@ -672,7 +674,7 @@ def __init__(self, domain, range=None):
Range of the functional. Default: `RealNumbers`.
"""
super(L2NormSquared, self).__init__(
domain=domain, linear=False, grad_lipschitz=2, range=range)
domain=domain, range=range, linear=False, grad_lipschitz=2)

# TODO: update when integration operator is in place: issue #440
def _call(self, x):
Expand Down Expand Up @@ -731,8 +733,8 @@ def __init__(self, domain, constant, range=None):
Range of the functional. Default: ``domain.field``.
"""
super(ConstantFunctional, self).__init__(
domain=domain, linear=(constant == 0), grad_lipschitz=0,
range=range)
domain=domain, range=range, linear=(constant == 0),
grad_lipschitz=0)
self.__constant = self.range.element(constant)

@property
Expand Down Expand Up @@ -790,8 +792,8 @@ def __init__(self, domain, range=None):
range : `Field`, optional
Range of the functional. Default: ``domain.field``.
"""
super(ZeroFunctional, self).__init__(domain=domain, constant=0,
range=range)
super(ZeroFunctional, self).__init__(domain=domain, range=range,
constant=0)

def __repr__(self):
"""Return ``repr(self)``."""
Expand Down Expand Up @@ -823,9 +825,9 @@ def __init__(self, field, scale):
>>> func(5)
15.0
"""
Functional.__init__(self, domain=field, linear=True, grad_lipschitz=0,
range=field)
ScalingOperator.__init__(self, field, scale)
Functional.__init__(self, domain=field, range=field, linear=True,
grad_lipschitz=0)
ScalingOperator.__init__(self, domain=field, scalar=scale)

@property
def gradient(self):
Expand Down Expand Up @@ -894,7 +896,7 @@ def __init__(self, domain, lower=None, upper=None, range=None):
>>> func([0, 1, 3]) # one point outside
inf
"""
super(IndicatorBox, self).__init__(domain, linear=False, range=range)
super(IndicatorBox, self).__init__(domain, range=range, linear=False)
self.lower = lower
self.upper = upper

Expand Down Expand Up @@ -952,7 +954,7 @@ def __init__(self, domain, range=None):
inf
"""
super(IndicatorNonnegativity, self).__init__(
domain, lower=0, upper=None, range=range)
domain, range=range, lower=0, upper=None)

def __repr__(self):
"""Return ``repr(self)``."""
Expand Down Expand Up @@ -991,7 +993,7 @@ def __init__(self, domain, constant=0, range=None):
>>> func([0, 0, 0])
2
"""
super(IndicatorZero, self).__init__(domain, linear=False, range=range)
super(IndicatorZero, self).__init__(domain, range=range, linear=False)
self.__constant = constant

@property
Expand Down Expand Up @@ -1176,7 +1178,7 @@ class KLGradient(Operator):
def __init__(self):
"""Initialize a new instance."""
super(KLGradient, self).__init__(
functional.domain, functional.domain, linear=False)
functional.domain, range=functional.domain, linear=False)

def _call(self, x):
"""Apply the gradient operator to the given point.
Expand Down Expand Up @@ -1302,7 +1304,7 @@ class KLCCGradient(Operator):
def __init__(self):
"""Initialize a new instance."""
super(KLCCGradient, self).__init__(
functional.domain, functional.domain, linear=False)
functional.domain, range=functional.domain, linear=False)

def _call(self, x):
"""Apply the gradient operator to the given point.
Expand Down Expand Up @@ -1447,7 +1449,7 @@ class KLCrossEntropyGradient(Operator):
def __init__(self):
"""Initialize a new instance."""
super(KLCrossEntropyGradient, self).__init__(
functional.domain, functional.domain, linear=False)
functional.domain, range=functional.domain, linear=False)

def _call(self, x):
"""Apply the gradient operator to the given point.
Expand Down Expand Up @@ -1560,7 +1562,7 @@ class KLCrossEntCCGradient(Operator):
def __init__(self):
"""Initialize a new instance."""
super(KLCrossEntCCGradient, self).__init__(
functional.domain, functional.domain, linear=False)
functional.domain, range=functional.domain, linear=False)

def _call(self, x):
"""Apply the gradient operator to the given point."""
Expand Down Expand Up @@ -1680,21 +1682,17 @@ def __init__(self, *functionals):
# Make a power space if the second argument is an integer
if (len(functionals) == 2 and isinstance(functionals[1], Integral)):
functionals = [functionals[0]] * functionals[1]
for func1 in functionals:
if all(func1.range.contains_set(func2.range)
for func2 in functionals):
range = func1.range
break
else:
raise ValueError('No functional range contained all other ranges '
'in SeparableSum of {!r}'.format(functionals))

range = RealNumbers()
for func in functionals:
range = (func.range if func.range.contains_set(range) else range)

domains = [func.domain for func in functionals]
domain = ProductSpace(*domains)
linear = all(func.is_linear for func in functionals)

super(SeparableSum, self).__init__(domain=domain, linear=linear,
range=range)
super(SeparableSum, self).__init__(domain=domain, range=range,
linear=linear)
self.__functionals = tuple(functionals)

def _call(self, x):
Expand Down Expand Up @@ -1821,8 +1819,8 @@ def __init__(self, operator=None, vector=None, constant=0):
'to match')

super(QuadraticForm, self).__init__(
domain=domain, linear=(operator is None and constant == 0),
range=range)
domain=domain, range=range,
linear=(operator is None and constant == 0))

self.__operator = operator
self.__vector = vector
Expand Down Expand Up @@ -1998,7 +1996,7 @@ def __init__(self, domain, outer_exp=1, singular_vector_exp=2, range=None):
if range is None:
range = RealNumbers()
super(NuclearNorm, self).__init__(
domain=domain, linear=False, grad_lipschitz=np.nan, range=range)
domain=domain, range=range, linear=False, grad_lipschitz=np.nan)

self.outernorm = LpNorm(self.domain[0, 0], exponent=outer_exp,
range=range)
Expand Down Expand Up @@ -2078,7 +2076,7 @@ class NuclearNormProximal(Operator):
def __init__(self, sigma):
self.sigma = float(sigma)
super(NuclearNormProximal, self).__init__(
func.domain, func.domain, linear=False)
func.domain, range=func.domain, linear=False)

def _call(self, x):
"""Return ``self(x)``."""
Expand Down Expand Up @@ -2205,9 +2203,8 @@ def __init__(self, domain, outer_exp=1, singular_vector_exp=2, range=None):
if range is None:
range = getattr(domain, 'field', RealNumbers())
super(IndicatorNuclearNormUnitBall, self).__init__(
domain=domain, linear=False, grad_lipschitz=np.nan, range=range)
self.__norm = NuclearNorm(domain, outer_exp, singular_vector_exp,
range=RealNumbers())
domain=domain, range=range, linear=False, grad_lipschitz=np.nan)
self.__norm = NuclearNorm(domain, outer_exp, singular_vector_exp)

def _call(self, x):
"""Return ``self(x)``."""
Expand Down Expand Up @@ -2318,7 +2315,7 @@ def __init__(self, functional, sigma=1.0, range=None):
range = RealNumbers()

super(MoreauEnvelope, self).__init__(
domain=functional.domain, linear=False, range=range)
domain=functional.domain, range=range, linear=False)
self.__functional = functional
self.__sigma = sigma
self.__range = range
Expand Down Expand Up @@ -2436,9 +2433,8 @@ def __init__(self, domain, gamma, range=None):
if range is None:
range = RealNumbers()

super(Huber, self).__init__(
domain=domain, linear=False, grad_lipschitz=grad_lipschitz,
range=range)
super(Huber, self).__init__(domain=domain, range=range, linear=False,
grad_lipschitz=grad_lipschitz)

@property
def gamma(self):
Expand Down Expand Up @@ -2532,7 +2528,7 @@ class HuberGradient(Operator):
def __init__(self):
"""Initialize a new instance."""
super(HuberGradient, self).__init__(
functional.domain, functional.domain, linear=False)
functional.domain, range=functional.domain, linear=False)

def _call(self, x):
"""Apply the gradient operator to the given point."""
Expand Down
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