verifies that two vectors are close (sup norm)

Returns the sum of {@code this} and {@code m}. @param m matrix to be added @return {@code this + m} @throws MatrixDimensionMismatchException if {@cod

Returns the result of postmultiplying {@code this} by {@code m}. @param m matrix to postmultiply by @return {@code this m} @throws DimensionMismatchE

Makes a {@link Dfp} with a value of 0. @return a new {@link Dfp} with a value of 0

Verifies that expected and actual are within delta, or are both NaN or infinities of the same sign.

Get the entry in the specified row and column. Row and column indices start at 0. @param row Row index of entry to be fetched. @param column Column i

@param x Number. @return abs(x). @see Math#abs(int)

Returns {@code this} minus {@code m}. @param m matrix to be subtracted @return {@code this - m} @throws MatrixDimensionMismatchException if {@code m}

Get the real value of the number. @return real value

Get the additive identity of the field. <p> The additive identity is the element e₀ of the field such that for all elements a of the field,

Returns a {@link RealMatrix} with specified dimensions. <p>The type of matrix returned depends on the dimension. Below 2¹² elements (i.e. 4

Gets the number of rows. @return the number of rows.

Compute this &divide; a. @param a element to divide by @return a new element representing this &divide; a @throws NullArgumentException if {@code a} i

Get a partial derivative. @param orders derivation orders with respect to each variable (if all orders are 0, the value is returned) @return partial d

Get the type of field elements of the vector. @return type of field elements of the vector

Gets the number of columns. @return the number of columns.

Get the final time. @return final time

Get the value of the entry. @return the value of the entry.

Returns the size of the vector. @return size

@param x Number. @return sqrt(x). @see Math#sqrt(double)

Get the number of elements stored in the map. @return number of elements stored in the map

Construct a vector by appending a vector to this vector. @param v vector to append to this one. @return a new vector

Compute the value for the function. @param x Abscissa for which the function value should be computed. @param y Ordinate for which the function value

Retrieves a copy of the simplex point stored at {@code index}. @param index Location. @return the point at location {@code index}.

Integrate the differential equations up to the given time. <p>This method solves an Initial Value Problem (IVP).</p> <p>Since this method stores some

Get time. @return time

Get the initial time. @return initial time

Set the entry in the specified row and column. Row and column indices start at 0. @param row Row index of entry to be set. @param column Column index

@param x Number. @param y Number. @return max(x, y). @see Math#max(int,int)

Compute this + a. @param a element to add @return a new element representing this + a @throws NullArgumentException if {@code a} is {@code null}.

Create a fraction. @param p numerator @param q denominator @return p/q computed in the instance field

Build an array of elements. <p> Arrays are filled with field.getZero() @param <T> the type of the field elements @param field field to which array el

Put a value associated with a key in the map. @param key key to which value is associated @param value value to put in the map @return previous value

Get the initial state vector. @return initial state vector

Converts a test string to a {@link LinearConstraint}. Ex: x0 + x1 + x2 + x3 - x12 = 0

Creates a simplex transformation. @param evaluationFunction Evaluation function. @param comparator Vertex fitness comparator. @param saAcceptance Sim

Returns the unique instance of this class. @return the unique instance of this class

Solve the linear equation A &times; X = B for matrices A. <p> The A matrix is implicit, it is provided by the underlying decomposition algorithm. @pa

@param x Number. @param y Number. @return min(x, y). @see Math#min(int,int)

absolute value. @return abs(this)

Convert the vector to a T array. <p>The array is independent from vector data, it's elements are copied.</p> @return array containing a copy of vector

Factory method creating an independent variable. @param idx index of the variable @param value value of the variable @return a new instance

Create an instance with a value of 0. Use this internally in preference to constructors to facilitate subclasses @return a new instance with a value o

Get the multiplicative identity of the field. <p> The multiplicative identity is the element e₁ of the field such that for all elements a o

Returns {@code true} if {@code this} double precision number is Not-a-Number ({@code NaN}), false otherwise. @return {@code true} if {@code this} is

Returns the additive inverse of {@code this} element. @return the opposite of {@code this}.

@param x Number. @param y Number. @return pow(x, y). @see Math#pow(double,double)

Retrieves the neuron with the given (unique) {@code id}. @param id Identifier. @return the neuron associated with the given {@code id}. @throws NoSuc

Add a step handler to this integrator. <p>The handler will be called by the integrator for each accepted step.</p> @param handler handler for the acce

Returns the <a href="https://mathworld.wolfram.com/MaximumAbsoluteRowSumNorm.html"> maximum absolute row sum norm</a> of the matrix. @return norm

Power function. Compute x^y. @param x a double @param y a double @return double

Check the value of a vector. @param tolerance the absolute tolerance of comparisons @param actual the vector to test @param expected the expected valu

Convert the instance into a double. @return a double approximating the instance @see #toSplitDouble()

This method calls {@link #format(Object,StringBuffer,FieldPosition)}. @param c Complex object to format. @return A formatted number in the form "Re(c

Sets all elements to the given value. @param value Value of the elements of the matrix. @return {@code this}.

Check if instance is not a number. @return true if instance is not a number

@param x Number. @return sin(x). @see Math#sin(double)

Creates a new instance of {@link RealVector}, with specified entries. The returned vector must be of the type currently tested. It should be noted tha

Gets the point. @return a copy of the stored point.

Square root. @return square root of the instance

Get the absolute accuracy of the solver. Solutions returned by the solver should be accurate to this tolerance, i.e., if &epsilon; is the absolute ac

Gets the n-dimensional point. @return the point array

Raises base to the power a by successive squaring. @param base number to raise @param a power @return base^a

Get the value part of the derivative structure. @return value part of the derivative structure @see #getPartialDerivative(int...)

Gets the number of elements contained in the range. @return the size of the range.

Start visiting a vector. This method is called once, before any entry of the vector is visited. @param dimension the size of the vector @param start

Solve the non-linear least squares problem. @param leastSquaresProblem the problem definition, including model function and

Checks that an object is not null. @param o Object to be checked. @param pattern Message pattern. @param args Arguments to replace the placeholders i

Get the number of evaluations of the differential equations function. <p> The number of evaluations corresponds to the last call to the <code>integrat

Get the derivative with respect to a particular index variable. @param index index to differentiate with. @return derivative with respect to a partic

{@inheritDoc}

Get the key. @return the key (first element of the pair).

Adds 1 to the frequency count for v. @param v the value to add.

@param x Number. @return cos(x). @see Math#cos(double)

Returns the result of evaluating the statistic over the input array, using the supplied weights. @param values input array @param weights array of we

Compute n &times; this. Multiplication by an integer number is defined as the following sum: <p>n &times; this = &sum;_i=1ⁿ this.

@param x Number. @return exp(x). @see Math#exp(double)

Generates a random value vector sampled from this distribution. @return a random value vector.

Get the value of the function. @return value of the function.

Returns the transpose of this matrix. @return transpose matrix

Get the state vector of the interpolated point. <p>The returned vector is a reference to a reused array, so it should not be modified and it should be

@param x Number. @return log(x). @see Math#log(double)

{@inheritDoc}

Get the name of the method. @return name of the method

Return the entry at the specified index. @param index Index location of entry to be fetched. @return the vector entry at {@code index}. @throws OutOf

Simple mathematical function. <p>{@link UnivariateDifferentiableFunction} classes compute both the value and the first derivative of the function.</p>