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Packages that use Kernel | |
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de.erichseifert.gral.data.filters | Classes for filtering data sources. |
Uses of Kernel in de.erichseifert.gral.data.filters |
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Methods in de.erichseifert.gral.data.filters that return Kernel | |
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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. |
Methods in de.erichseifert.gral.data.filters with parameters of type Kernel | |
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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. |
Constructors in de.erichseifert.gral.data.filters with parameters of type Kernel | |
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Convolution(DataSource original,
Kernel kernel,
Filter.Mode mode,
int... cols)
Creates a new Convolution object with the specified DataSource, Kernel, Mode and columns. |
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