## org.apache.commons.math3.analysis.polynomials Class PolynomialFunctionLagrangeForm

```java.lang.Object org.apache.commons.math3.analysis.polynomials.PolynomialFunctionLagrangeForm
```
All Implemented Interfaces:
UnivariateFunction

`public class PolynomialFunctionLagrangeFormextends Objectimplements UnivariateFunction`

Implements the representation of a real polynomial function in Lagrange Form. For reference, see Introduction to Numerical Analysis, ISBN 038795452X, chapter 2.

The approximated function should be smooth enough for Lagrange polynomial to work well. Otherwise, consider using splines instead.

Since:
1.2
Version:
\$Id: PolynomialFunctionLagrangeForm.java 1364387 2012-07-22 18:14:11Z tn \$

Constructor Summary
```PolynomialFunctionLagrangeForm(double[] x, double[] y)```
Construct a Lagrange polynomial with the given abscissas and function values.

Method Summary
`protected  void` `computeCoefficients()`
Calculate the coefficients of Lagrange polynomial from the interpolation data.
` int` `degree()`
Returns the degree of the polynomial.
`static double` ```evaluate(double[] x, double[] y, double z)```
Evaluate the Lagrange polynomial using Neville's Algorithm.
` double[]` `getCoefficients()`
Returns a copy of the coefficients array.
` double[]` `getInterpolatingPoints()`
Returns a copy of the interpolating points array.
` double[]` `getInterpolatingValues()`
Returns a copy of the interpolating values array.
` double` `value(double z)`
Calculate the function value at the given point.
`static boolean` ```verifyInterpolationArray(double[] x, double[] y, boolean abort)```
Check that the interpolation arrays are valid.

Methods inherited from class java.lang.Object
`clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Constructor Detail

### PolynomialFunctionLagrangeForm

```public PolynomialFunctionLagrangeForm(double[] x,
double[] y)```
Construct a Lagrange polynomial with the given abscissas and function values. The order of interpolating points are not important.

The constructor makes copy of the input arrays and assigns them.

Parameters:
`x` - interpolating points
`y` - function values at interpolating points
Throws:
`DimensionMismatchException` - if the array lengths are different.
`NumberIsTooSmallException` - if the number of points is less than 2.
`NonMonotonicSequenceException` - if two abscissae have the same value.
Method Detail

### value

`public double value(double z)`
Calculate the function value at the given point.

Specified by:
`value` in interface `UnivariateFunction`
Parameters:
`z` - Point at which the function value is to be computed.
Returns:
the function value.
Throws:
`DimensionMismatchException` - if `x` and `y` have different lengths.
`NonMonotonicSequenceException` - if `x` is not sorted in strictly increasing order.
`NumberIsTooSmallException` - if the size of `x` is less than 2.

### degree

`public int degree()`
Returns the degree of the polynomial.

Returns:
the degree of the polynomial

### getInterpolatingPoints

`public double[] getInterpolatingPoints()`
Returns a copy of the interpolating points array.

Changes made to the returned copy will not affect the polynomial.

Returns:
a fresh copy of the interpolating points array

### getInterpolatingValues

`public double[] getInterpolatingValues()`
Returns a copy of the interpolating values array.

Changes made to the returned copy will not affect the polynomial.

Returns:
a fresh copy of the interpolating values array

### getCoefficients

`public double[] getCoefficients()`
Returns a copy of the coefficients array.

Changes made to the returned copy will not affect the polynomial.

Note that coefficients computation can be ill-conditioned. Use with caution and only when it is necessary.

Returns:
a fresh copy of the coefficients array

### evaluate

```public static double evaluate(double[] x,
double[] y,
double z)```
Evaluate the Lagrange polynomial using Neville's Algorithm. It takes O(n^2) time.

Parameters:
`x` - Interpolating points array.
`y` - Interpolating values array.
`z` - Point at which the function value is to be computed.
Returns:
the function value.
Throws:
`DimensionMismatchException` - if `x` and `y` have different lengths.
`NonMonotonicSequenceException` - if `x` is not sorted in strictly increasing order.
`NumberIsTooSmallException` - if the size of `x` is less than 2.

### computeCoefficients

`protected void computeCoefficients()`
Calculate the coefficients of Lagrange polynomial from the interpolation data. It takes O(n^2) time. Note that this computation can be ill-conditioned: Use with caution and only when it is necessary.

### verifyInterpolationArray

```public static boolean verifyInterpolationArray(double[] x,
double[] y,
boolean abort)```
Check that the interpolation arrays are valid. The arrays features checked by this method are that both arrays have the same length and this length is at least 2.

Parameters:
`x` - Interpolating points array.
`y` - Interpolating values array.
`abort` - Whether to throw an exception if `x` is not sorted.
Returns:
`false` if the `x` is not sorted in increasing order, `true` otherwise.
Throws:
`DimensionMismatchException` - if the array lengths are different.
`NumberIsTooSmallException` - if the number of points is less than 2.
`NonMonotonicSequenceException` - if `x` is not sorted in strictly increasing order and `abort` is `true`.
See Also:
`evaluate(double[], double[], double)`, `computeCoefficients()`

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