numeric library
Numeric algorithms and solutions.
Classes
- CurveFit
- Curve fitting is the process of constructing a curve, or mathematical function, that has the best fit to a series of data points, possibly subject to constraints.
- CurveFitResult
- Generic result of a curve fitting.
- LevenbergMarquardt
- The Levenberg–Marquardt algorithm, also known as the damped least-squares method, is used to solve non-linear least squares problems.
- LevenbergMarquardtResult
-
ParametrizedUnaryFunction<
T> -
Abstract factory of parametrized unary functions of type
UnaryFunction<T>
. - PolynomialRegression
-
Polynomial least-squares regression, in which the relationship between the
independent elements
xs
and the dependent elementsys
is modelled as a polynomial of a given degree. - PolynomialRegressionResult
Enums
- IntegrateWarning
- Integration warnings that can be triggered for badly behaving functions or ill defined parameters.
Functions
-
derivative(
UnaryFunction< double> function, double x, {int derivative = 1, int accuracy = 2, double epsilon = 1e-5}) → double -
Returns the numerical derivative of the provided function
function
atx
. -
fft(
List< Complex> values, {bool inverse = false}) → List<Complex> -
Performs an in-place Discrete Fast Fourier transformation on the provided
values
. If necessary, extends the size the provided list to a power of two. Returns the modified collection of transformed values. -
geometricSpaced(
double start, double stop, {int count = 10, bool includeEndpoint = true, DataType< double> ? dataType, VectorFormat? format}) → Vector<double> -
Generates a Vector with a sequence of
count
evenly spaced values on a log scale (a geometric progression) on the interval betweenstart
andstop
. -
integrate(
UnaryFunction< double> function, double a, double b, {int depth = 6, double epsilon = 1e-6, Iterable<double> poles = const [], void onWarning(IntegrateWarning type, double x)?}) → double -
Returns the numerical integration of the provided
function
froma
tob
, that is the result of int(f(x), dx=a..b). -
lagrangeInterpolation<
T> (DataType< T> dataType, {required Vector<T> xs, required Vector<T> ys}) → UnaryFunction<T> -
A function providing a Lagrange polynomial interpolation through the unique
sample points
xs
andys
. -
linearInterpolation<
T> (DataType< T> dataType, {required Vector<T> xs, required Vector<T> ys, T? left, T? right}) → UnaryFunction<T> -
A function providing linear interpolation of a discrete monotonically
increasing set of sample points
xs
andys
. Returnsleft
orright
, if the point is outside the data range, by default extrapolate linearly. -
linearSpaced(
double start, double stop, {int count = 10, bool includeEndpoint = true, DataType< double> ? dataType, VectorFormat? format}) → Vector<double> -
Generates a Vector with a sequence of
count
evenly spaced values over an interval betweenstart
andstop
. -
logarithmicSpaced(
double start, double stop, {int count = 10, double base = 10.0, bool includeEndpoint = true, DataType< double> ? dataType, VectorFormat? format}) → Vector<double> -
Generates a Vector with a sequence of
count
evenly spaced values on a log scale (a geometric progression) on the interval betweenbase ^ start
andbase ^ stop
. -
nearestInterpolation(
{required Vector< double> xs, required Vector<double> ys, bool preferLower = true}) → UnaryFunction<double> -
A function providing the nearest value of a discrete monotonically
increasing set of sample points
xs
andys
. -
nextInterpolation(
{required Vector< double> xs, required Vector<double> ys, double right = double.nan}) → UnaryFunction<double> -
A function providing the next value of a discrete monotonically
increasing set of sample points
xs
andys
. Returnsright
if there is no next sample point. -
previousInterpolation(
{required Vector< double> xs, required Vector<double> ys, double left = double.nan}) → UnaryFunction<double> -
A function providing the previous value of a discrete monotonically
increasing set of sample points
xs
andys
. Returnsleft
if there is no previous sample point. -
solve(
UnaryFunction< double> function, double a, double b, {double bracketEpsilon = 1e-10, double solutionEpsilon = 1e-50, int maxIterations = 50}) → double -
Returns the root of the provided
function
bracketed betweena
andb
, that is f(x) = 0 is solved for x in the range of [a, b].
Typedefs
-
UnaryFunction<
T> = T Function(T x) -
A function with a single argument and an identical return type. Typically
used for numerical functions like f(x) where x ∈
T
and f(x) ∈T
.
Exceptions / Errors
- IntegrateError
- Integration error that is thrown when warnings are not handled explicitly.