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java.lang.Objectedu.stanford.nlp.optimization.AbstractCachingDiffFloatFunction
public abstract class AbstractCachingDiffFloatFunction
| Field Summary | |
|---|---|
protected float[] |
derivative
|
protected float |
value
|
| Constructor Summary | |
|---|---|
AbstractCachingDiffFloatFunction()
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| Method Summary | |
|---|---|
protected abstract void |
calculate(float[] x)
Calculate the value at x and the derivative and save them in the respective fields |
protected void |
copy(float[] y,
float[] x)
|
float[] |
derivativeAt(float[] x)
Returns the first-derivative vector at the input location. |
abstract int |
domainDimension()
Returns the number of dimensions in the function's domain |
float[] |
initial()
Returns the intitial point in the domain (but not necessarily a feasible one). |
float |
valueAt(float[] x)
Returns the value of the function at a single point. |
| Methods inherited from class java.lang.Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Field Detail |
|---|
protected float[] derivative
protected float value
| Constructor Detail |
|---|
public AbstractCachingDiffFloatFunction()
| Method Detail |
|---|
public abstract int domainDimension()
FloatFunction
domainDimension in interface FloatFunctionprotected abstract void calculate(float[] x)
public float[] initial()
HasFloatInitial
initial in interface HasFloatInitial
protected void copy(float[] y,
float[] x)
public float valueAt(float[] x)
FloatFunction
valueAt in interface FloatFunctionx - a double[] input
public float[] derivativeAt(float[] x)
DiffFloatFunction
derivativeAt in interface DiffFloatFunctionx - a double[] input vector
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