Package | Description |
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de.erichseifert.gral.data.filters |
Classes for filtering data sources.
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Modifier and Type | Method and Description |
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Kernel |
Kernel.add(double v)
Returns a new Kernel, where the specified value was added to each of
the items.
|
Kernel |
Kernel.add(Kernel k)
Returns a new Kernel, where the specified kernel was added.
|
static Kernel |
KernelUtils.getBinomial(double variance)
Returns a Kernel of specified variance with binomial coefficients.
|
static Kernel |
KernelUtils.getBinomial(int size)
Returns a Kernel of specified size with binomial coefficients.
|
Kernel |
Convolution.getKernel()
Returns the kernel.
|
static Kernel |
KernelUtils.getUniform(int size,
int offset,
double value)
Returns a Kernel with the specified size and offset, filled with a
single value.
|
Kernel |
Kernel.mul(double v)
Returns a new Kernel, where the specified value was multiplied with
each of the items.
|
Kernel |
Kernel.mul(Kernel k)
Returns a new Kernel, where the specified kernel was multiplied.
|
Kernel |
Kernel.negate()
Returns a Kernel with all values being negated.
|
Kernel |
Kernel.normalize()
Returns a normalized Kernel so that the sum of all values equals 1.
|
Modifier and Type | Method and Description |
---|---|
Kernel |
Kernel.add(Kernel k)
Returns a new Kernel, where the specified kernel was added.
|
Kernel |
Kernel.mul(Kernel k)
Returns a new Kernel, where the specified kernel was multiplied.
|
Constructor and Description |
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Convolution(DataSource original,
Kernel kernel,
Filter.Mode mode,
int... cols)
Initialized a new instance with the specified data source, convolution
kernel, edge handling mode, and columns to be filtered.
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