parameter_sweep.sampling_types

Module Contents

Classes

SamplingType	Available sampling types.
SetMode	Available set modes.
RandomSample	Base class for random sampling.
FixedSample	Base class for fixed sampling.
LinearSample	Class for linear sampling using numpy.linspace().
GeomSample	Class for geometric sampling using numpy.geomspace().
ReverseGeomSample	Class for reverse geometric sampling using numpy.geomspace().
PredeterminedFixedSample	Similar to other fixed sampling types except the setup function arguments.
UniformSample	Class for random sampling from a uniform distribution using numpy.random.uniform().
NormalSample	Class for random sampling from a normal distribution using numpy.random.normal().
PredeterminedRandomSample	Similar to other fixed sampling types except the setup function arguments.
LatinHypercubeSample	Class for Latin Hypercube sampling.

class parameter_sweep.sampling_types.SamplingType

Available sampling types.

FIXED

RANDOM

RANDOM_LHS

class parameter_sweep.sampling_types.SetMode

Available set modes.

FIX_VALUE

SET_LB

SET_UB

SET_FIXED_STATE

class parameter_sweep.sampling_types.RandomSample(pyomo_object, *args, **kwargs)

Base class for random sampling.

sampling_type

class parameter_sweep.sampling_types.FixedSample(pyomo_object, *args, **kwargs)

Base class for fixed sampling.

sampling_type

class parameter_sweep.sampling_types.LinearSample(pyomo_object, *args, **kwargs)

Class for linear sampling using numpy.linspace().

sample()

setup(lower_limit, upper_limit, num_samples)

class parameter_sweep.sampling_types.GeomSample(pyomo_object, *args, **kwargs)

Class for geometric sampling using numpy.geomspace().

sample()

setup(lower_limit, upper_limit, num_samples)

class parameter_sweep.sampling_types.ReverseGeomSample(pyomo_object, *args, **kwargs)

Class for reverse geometric sampling using numpy.geomspace().

sample()

setup(lower_limit, upper_limit, num_samples)

class parameter_sweep.sampling_types.PredeterminedFixedSample(pyomo_object, *args, **kwargs)

Similar to other fixed sampling types except the setup function arguments. In this case a user needs to specify a numpy array (or a list) of predetermined values. For example:

sample_obj = PredeterminedFixedSample(np.array([1,2,3,4]))

sample()

setup(values)

class parameter_sweep.sampling_types.UniformSample(pyomo_object, *args, **kwargs)

Class for random sampling from a uniform distribution using numpy.random.uniform().

sample()

setup(lower_limit, upper_limit, num_samples)

class parameter_sweep.sampling_types.NormalSample(pyomo_object, *args, **kwargs)

Class for random sampling from a normal distribution using numpy.random.normal().

sample()

setup(mean, sd, num_samples)

class parameter_sweep.sampling_types.PredeterminedRandomSample(pyomo_object, *args, **kwargs)

Similar to other fixed sampling types except the setup function arguments. In this case a user needs to specify a numpy array (or a list) of predetermined values. For example:

sample_obj = PredeterminedRandomSample(np.array([1,2,3,4]))

sample()

setup(values)

class parameter_sweep.sampling_types.LatinHypercubeSample(pyomo_object, *args, **kwargs)

Class for Latin Hypercube sampling.

sampling_type

sample()

setup(lower_limit, upper_limit, num_samples)