HaselgroveSequence¶
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class
HaselgroveSequence
(*args)¶ Haselgrove sequence.
- Available constructors:
HaselgroveSequence(dimension=1)
HaselgroveSequence(base)
Parameters: - dimension : positive int
Dimension of the points.
- base : sequence of positive float
Sequence of positive real values linearly independent over the integer ring, i.e. no linear combination with integer coefficients of these values can be zero excepted if all the coefficients are zero. The dimension of the sequence is given by the dimension of the base.
Examples
>>> import openturns as ot >>> sequence = ot.HaselgroveSequence(2) >>> print(sequence.generate(5)) 0 : [ 0.414214 0.732051 ] 1 : [ 0.828427 0.464102 ] 2 : [ 0.242641 0.196152 ] 3 : [ 0.656854 0.928203 ] 4 : [ 0.0710678 0.660254 ]
Methods
ComputeStarDiscrepancy
(sample)Compute the star discrepancy of a sample uniformly distributed over [0, 1). generate
(*args)Generate a sample of pseudo-random vectors of numbers uniformly distributed over [0, 1). getClassName
()Accessor to the object’s name. getDimension
()Accessor to the dimension of the points of the low discrepancy sequence. getId
()Accessor to the object’s id. getName
()Accessor to the object’s name. getShadowedId
()Accessor to the object’s shadowed id. getVisibility
()Accessor to the object’s visibility state. hasName
()Test if the object is named. hasVisibleName
()Test if the object has a distinguishable name. initialize
(dimension)Initialize the sequence. setName
(name)Accessor to the object’s name. setShadowedId
(id)Accessor to the object’s shadowed id. setVisibility
(visible)Accessor to the object’s visibility state. -
__init__
(*args)¶ Initialize self. See help(type(self)) for accurate signature.
-
static
ComputeStarDiscrepancy
(sample)¶ Compute the star discrepancy of a sample uniformly distributed over [0, 1).
Parameters: - sample : 2-d sequence of float
Returns: - starDiscrepancy : float
Star discrepancy of a sample uniformly distributed over [0, 1).
Examples
>>> import openturns as ot >>> # Create a sequence of 3 points of 2 dimensions >>> sequence = ot.LowDiscrepancySequence(ot.SobolSequence(2)) >>> sample = sequence.generate(16) >>> print(sequence.computeStarDiscrepancy(sample)) 0.12890625 >>> sample = sequence.generate(64) >>> print(sequence.computeStarDiscrepancy(sample)) 0.0537109375
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generate
(*args)¶ Generate a sample of pseudo-random vectors of numbers uniformly distributed over [0, 1).
Parameters: - size : int
Number of points to be generated. Default is 1.
Returns: - sample :
Sample
Sample of pseudo-random vectors of numbers uniformly distributed over [0, 1).
Examples
>>> import openturns as ot >>> # Create a sequence of 3 points of 2 dimensions >>> sequence = ot.LowDiscrepancySequence(ot.SobolSequence(2)) >>> print(sequence.generate(3)) 0 : [ 0.5 0.5 ] 1 : [ 0.75 0.25 ] 2 : [ 0.25 0.75 ]
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getClassName
()¶ Accessor to the object’s name.
Returns: - class_name : str
The object class name (object.__class__.__name__).
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getDimension
()¶ Accessor to the dimension of the points of the low discrepancy sequence.
Returns: - dimension : int
Dimension of the points of the low discrepancy sequence.
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getId
()¶ Accessor to the object’s id.
Returns: - id : int
Internal unique identifier.
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getName
()¶ Accessor to the object’s name.
Returns: - name : str
The name of the object.
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getShadowedId
()¶ Accessor to the object’s shadowed id.
Returns: - id : int
Internal unique identifier.
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getVisibility
()¶ Accessor to the object’s visibility state.
Returns: - visible : bool
Visibility flag.
-
hasName
()¶ Test if the object is named.
Returns: - hasName : bool
True if the name is not empty.
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hasVisibleName
()¶ Test if the object has a distinguishable name.
Returns: - hasVisibleName : bool
True if the name is not empty and not the default one.
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initialize
(dimension)¶ Initialize the sequence.
Parameters: - dimension : int
Dimension of the points of the low discrepancy sequence.
Examples
>>> import openturns as ot >>> # Create a sequence of 3 points of 2 dimensions >>> sequence = ot.LowDiscrepancySequence(ot.SobolSequence(2)) >>> print(sequence.generate(3)) 0 : [ 0.5 0.5 ] 1 : [ 0.75 0.25 ] 2 : [ 0.25 0.75 ] >>> print(sequence.generate(3)) 0 : [ 0.375 0.375 ] 1 : [ 0.875 0.875 ] 2 : [ 0.625 0.125 ] >>> sequence.initialize(2) >>> print(sequence.generate(3)) 0 : [ 0.5 0.5 ] 1 : [ 0.75 0.25 ] 2 : [ 0.25 0.75 ]
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setName
(name)¶ Accessor to the object’s name.
Parameters: - name : str
The name of the object.
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setShadowedId
(id)¶ Accessor to the object’s shadowed id.
Parameters: - id : int
Internal unique identifier.
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setVisibility
(visible)¶ Accessor to the object’s visibility state.
Parameters: - visible : bool
Visibility flag.