Interface Convolution
- All Superinterfaces:
ArrayProcessor
,ArrayProcessorWithContextSwitching
- All Known Implementing Classes:
AbstractConvolution
,BasicConvolution
,ContinuedConvolution
,TiledConvolution
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Method Summary
Modifier and TypeMethodDescriptionasConvolution
(Class<? extends T> requiredType, Matrix<? extends PArray> src, WeightedPattern pattern) Returns an immutable view of the passed source matrix, such that any reading data from it calculates and returns the convolution of the source matrix by the specified pattern.asConvolution
(Matrix<? extends PArray> src, WeightedPattern pattern) Equivalent toasConvolution
(src.type
(PArray.class), src, pattern).context
(ArrayContext newContext) Switches the context: returns an instance, identical to this one excepting that it uses the specified newContext for all operations.convolution
(Class<? extends T> requiredType, Matrix<? extends PArray> src, WeightedPattern pattern) Matrix<? extends UpdatablePArray>
convolution
(Matrix<? extends PArray> src, WeightedPattern pattern) Returns a new updatable matrix, containing the convolution of the source matrix by the specified pattern.void
convolution
(Matrix<? extends UpdatablePArray> dest, Matrix<? extends PArray> src, WeightedPattern pattern) double
boolean
Returns true, if this class works in the defaultpseudo-cyclic continuation mode
.Methods inherited from interface net.algart.arrays.ArrayProcessor
context
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Method Details
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context
Description copied from interface:ArrayProcessorWithContextSwitching
Switches the context: returns an instance, identical to this one excepting that it uses the specified newContext for all operations. The returned instance is usually a clone of this one, but there is no guarantees that it is a deep clone. Usually, the returned instance is used only for performing asubtask
of the full task.- Specified by:
context
in interfaceArrayProcessorWithContextSwitching
- Parameters:
newContext
- another context, used by the returned instance; may be null.- Returns:
- new instance with another context.
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isPseudoCyclic
boolean isPseudoCyclic()Returns true, if this class works in the defaultpseudo-cyclic continuation mode
.More precisely, it means that when the value in some element of the processed matrix, returned by a method of this class, depends on elements of the source matrix, lying outside its bounds, then it is supposed that the values outside the source matrix are calculated as described in
Matrix.ContinuationMode.PSEUDO_CYCLIC
. Exactly such behaviour is specified in the comments to theconvolution(Matrix, WeightedPattern)
method as the default definition of convolution.This method returns true in
BasicConvolution
implementation. However, it usually returns false inContinuedConvolution
class — excepting the only degenerated case when the usedcontinuation mode
isPSEUDO_CYCLIC
.- Returns:
- whether this class works in the pseudo-cyclic continuation mode.
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increment
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asConvolution
Equivalent toasConvolution
(src.type
(PArray.class), src, pattern). In other words, the element type of the returned matrix is chosen the same as in src matrix.- Parameters:
src
- the source matrix.pattern
- the pattern.- Returns:
- the "lazy" matrix containing the convolution of the source matrix with the given pattern.
- Throws:
NullPointerException
- if one of the arguments is null.
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asConvolution
<T extends PArray> Matrix<T> asConvolution(Class<? extends T> requiredType, Matrix<? extends PArray> src, WeightedPattern pattern) Returns an immutable view of the passed source matrix, such that any reading data from it calculates and returns the convolution of the source matrix by the specified pattern. Seeconvolution(Class, Matrix, WeightedPattern)
method about the "convolution" term.The matrix, returned by this method, is immutable, and the class of its built-in array implements one of the basic interfaces
BitArray
,CharArray
,ByteArray
,ShortArray
,IntArray
,LongArray
,FloatArray
orDoubleArray
. The class of desired interface (one of 8 possible classes) must be passed as requiredType argument. So, it defines the element type of the returned matrix. For example, if requiredType=ByteArray
.class, the returned matrix consists of byte elements. The rules of casting the real numbers, results of the convolution, to the desired element type are the same as inArrays.asFuncArray(boolean, net.algart.math.functions.Func, Class, PArray...)
method with the argument truncateOverflows=true.The result is usually "lazy", that means that this method finishes immediately and all actual calculations are performed while getting elements of the returned matrix. It is true for all implementations provided by this package. However, some implementations may not support lazy dilation; then this method will be equivalent to
convolution(Class, Matrix, WeightedPattern)
.Please note: this method does not require time, but the resulting matrix can work slowly! for example, reading all its content than work much slower than
convolution(Class, Matrix, WeightedPattern)
method for some complex patterns. Usually you should use it only for very little patterns, or if you know that the implementation of this interface does not provide better algorithm for non-"lazy"convolution(Class, Matrix, WeightedPattern)
method.- Parameters:
requiredType
- desired type of the built-in array in the returned matrix.src
- the source matrix.pattern
- the pattern.- Returns:
- the "lazy" matrix containing the convolution of the source matrix with the given pattern.
- Throws:
NullPointerException
- if one of the arguments is null.
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convolution
Matrix<? extends UpdatablePArray> convolution(Matrix<? extends PArray> src, WeightedPattern pattern) Returns a new updatable matrix, containing the convolution of the source matrix by the specified pattern.Usually convolution means the weighted sum of the set of matrices, obtained by pseudo-cyclic shifting the source matrix by the vectors, equal to all pattern points, with weights, equal to
weights
of the pattern points. More precisely, let mi=Matrices.asShifted
(src,ip.coordinates()
), where ip is the point #i from all points contained in the pattern, and let wi=pattern.weight
(ip). Then the every element of the returned matrix is the weighted sum of all corresponding elements of all mi matrices:∑ wimi
Theelement type
of the created matrix is the same as the element type of the source one. The byte and short elements are considered to be unsigned. If the element type if integer, the precise is rounded to the nearest integer.The
BasicConvolution
class strictly complies this definition. However, other implementations of this interface may use alternate definitions of the convolution term. For example, elements outside the matrix may be supposed to be filled according some non-trivial rules instead of pseudo-cyclic continuation (as inContinuedConvolution
objects), or only some region of the matrix may be processed, etc.- Parameters:
src
- the source matrix.pattern
- the pattern.- Returns:
- the result of convolution of the source matrix with the given pattern.
- Throws:
NullPointerException
- if one of the arguments is null.- See Also:
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convolution
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convolution
void convolution(Matrix<? extends UpdatablePArray> dest, Matrix<? extends PArray> src, WeightedPattern pattern)
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