Michael Thomas Flanagan's Java Scientific Library Class List

This page contains a list of, short descriptions of, and links to, Michael Thomas Flanagan's Java Scientific Library classes.

A to Z index of topics covered by these classes.

Home Page of this Java scientific and numerical library.

• INPUT AND OUTPUT
  • Db   This class contains easy to use methods for entering, from the keyboard via an input dialog box, numbers and characters, of the following types:
    double,  float,  BigDecimal,   int,  long,  BigInteger,  short,  byte,  char,  boolean,  Complex number,  Phasor number and a line of text (String) plus a yes/no and a multiple choice dialog box;
    and methods for displaying, in an message dialog box, numbers and characters, of the following types:
    double,  float,  BigDecimal,  int,  long,  BigInteger,  short,  byte,  char,  String,  boolean,  Complex number,  Phasor number,  ErrorProp number and ComplexErrorProp number.
  • KeyboardInput   This class contains easy to use methods for entering, from the keyboard via the standard console window, numbers and characters, of the following types:
    double,  float,  BigDecimal,  int , long,  BigInteger,  short,  byte,  Complex number,  Phasor number,  boolean,  char and a line of text.
  • PrintToScreen    This class supplements the System.out.print and System.out.println statements allowing easy printing of one-dimesional and two-dimensional arrays to the screen. The type of the elements in a single array must be identical but may be of type:
    double,  Double,  float,  Float,  long,  Long,  int,  Integer,  short,  Short,   byte,  Byte,  char,  Character,  String,  BigDecimal,  BigInteger,  Complex   or  Phasor.
  • FileInput   This class contains easy to use methods for reading, from a text file, numbers and characters, of the following types:
    double,  float,  BigDecimal,  int,  long,  BigInteger,  short,  byte,  char,   boolean,  Complex,  Phasor,  a word of text  and  a line of text.
  • FileManipulate   This class contains easy to use methods for reading a text file character by character including the non-print characters, e.g. line return. It also contains methods for returning a file with the original contents organised to lines of a given length or as a single line.
  • FileChooser   This class contains methods for selecting a file via an Open File dialog window and the easy to use methods for reading numbers and characters, of the following types:
    double,  float,  BigDecimal,  int,  long,  BigInteger,  short,  byte,  char,   boolean,  Complex,  Phasor,  a word of text  and  a line of text.
  • MultipleFilesChooser   This class contains methods for selecting several files via an Open File dialog window and the easy to use methods for reading, from the selected files, numbers and characters, of the following types:
    double,  float,  BigDecimal,  int,  long,  BigInteger,  short,  byte),  char,  boolean,  Complex,  Phasor,  a word of text  and  a line of text.
  • FileNameSelector   This class contains methods for selecting a file name via an Open File dialog window. This class does NOT open the selected file for reading.
  • FileOutput   This class contains easy to use methods for writing, to a text file, numbers, characters and text of the following types:,br /> double,  float,  BigDecimal,  int,  long,  BigInteger,  short,  byte,  boolean,  char,  String,  Complex,  Phasor,  ErrorProp,  ComplexErrorProp,  arrays of the previous listed types  and  the date and time.
  • DigiGraph   This class contains the methods for digitising the points on a graph presented as a JPEG, GIF or PNG file.
  • Graphical Output   See Graph Plotting below.
• MATHEMATICAL FUNCTIONS
  • Fmath   This class supplements the java.lang.math class. It contains:
    • Trigonometric functions absent from the java math class:
      cot,  sec,  cosec,  sinh,  cosh,  tanh,  coth,  sech,  csch,  exsec,  vers,  covers,  hav,  sinc
      acot,  acot2,  asec,  acsc,  asinh,  acosh,  atanh,  acoth,  asech,  acsch,  aexesc,  avers,  acovers,  ahav.
      Angles of a triangle given apices or side lengths.
    • Common physical and mathematical constants:
      Avagadro,  Boltzmann,  Planck,  reduced Plank,  Faraday,  Molar Gas,  speed of light,  absolute zero,  charge on the electron,  electron mass,  proton mass,  neutron mass,  epsilon0,  mu0,  Euler's constant (gamma).
    • Additional mathematical functions:
      factorials,  log to a given base b (log_b(x)),  log₂(x),  log₁₀(x),  square,  sign,  truncate.
    • Logical tests:
      is equal within limits,  is equal within a percentage of the mean,  is an integer,  is even,  is odd,  is positive infinity,  is negative infinity,  is Not-a-Number,   is a leap year.
  • ArrayMaths   This one-dimensional array class contains methods for:
    • the inter-conversion (recasting) of one dimensional arrays of the following data types:
      double[],  Double[],  float[],  Float[],  long[],  Long[],  int[],  Integer[],  short[],  Short[],  byte[],  Byte[],  BigDecimal[],  BigInteger[],  Complex[],  Phasor[],  char[],  Character[],  String[ ],  Vector<Object> or ArrayList<Object>.
    • mathematical operations on such arrays:
      return a sub-array,  array maximum,  array minimum,  array sort,  sum of all elements,  product of all elements,  negate all elements of an array,  invert all elements of an array
      array element absolutes,  array element exponentials,  array element square roots,  inverse of the square roots of all array element,  raise elements to a power
      truncate array elements, round up array elements, round down array elements, reverse array elements, randomise array elements
      array element natural logs,  array element log2s,  array element log10s,  antilog10,
      array element x.loge(x)s,  array element x.log2(x)s,  array element x.log10(x)s,  array element -x.loge(x)s,  array element -x.log2(x)s,  array element -x.log10(x)s
      add a constant to all elements,  subtract a constant from all elements,   multiply all elements by a constant,  divide all elements by a constant
      add the elements of a second array to the corresponding elements,  subtract the elements of a second array to the corresponding elements
      indices of a value within an array,  value of and index of nearest element to a given value,  minimum difference between elements (range of the array),  minimum difference between elements
    • print array to screen,  plot the array,  concatenate two arrays .
  ArrayMaths is a superclass for the Stat class.
  • Conv   This class contains methods for:
    • the inter-conversion (recasting) the following data types:
      double,  Double,  float,  Float,  long,  Long,  int,  Integer,  short,  Short,  byte,  Byte,  BigDecimal,  BigInteger,  Complex  or  Phasor.
      These methods differ from the standard Java conversions in that, where possible, they throw an exception if a numerically meaningful recast cannot be made in contrast to the standard conventional narrowing primitive conversions
    • Conversion of physical units:
      electron volts to corresponding photon wavelength,  molar to %w/v,  calories to Joules,  Celsius to Fahrenheit,  Celsius to Kelvin,  Imperial to metric,  Imperial to American,  date to computer time,  height & weight to BMI and the reverse conversions.
  • DataType   This class contains methods for:
    • returning the name of an Object, e.g. double[][] is returned for a two dimensional array of doubles
    • returning the dimension of an Object, e.g. 3 is returned for a three dimensional array of Floats
    • if the entered Object is an ArrayList, an ArrayDeque, a LinkedList, an Object[] or a Vector:
      • returning the names of all elements of the entered Object
      • returning the dimensions of all elements of the entered Object
      • returning the name of the highest precision element of the entered Object
      • returning an array of all the elements of the entered Object converted to the type of highest precision present
      • returning an array of all the elements of the entered Object converted to the type double
      • returning an array of all the elements of the entered Object converted to the type BigDecimal
      • returning an array of all the elements of the entered Object converted to the type String
  • DeepCopy   This class contains methods for:
    • Deep coping of one-, two, three- and four-dimensional arrays of double, Double, float, Float, long, Long, int, Integer, short, Short, byte, Byte, char, Character, String, BigDecimal, BigInteger, Complex, Phasor, Point, VectorMaths, ArrayMaths, Matrix, ComplexMatrix, ErrorProp and ComplexErrorProp, Polynomial and ComplexPoly
    • Deep copying of a serialisable Object
  • FourierTransform   Fourier Transform procedures: This class contains the method for performing a Fast Fourier Transform (FFT) and associated methods, e.g.
    
    • for obtaining a power spectrum
    • for windowing data
    • for obtaining a time-frequency representation (short-time Fourier Transform)
    • correlation
  • Gradient   Gradient procedures: This class contains methods for the calculation of the gradients within 1-dimensional and 2-dimensional data arrays.
    Two options are offered in the calculation of the gradients:
    
    • Cubic and Bicubic spline interpolation of the first derivatives
    • Numerical difference calculation of the first derivatives
  • Matrix- This class defines an object representing a two dimensional array of real (double) numbers, i.e. a real matrix. It contains the methods for:

    Matrix arithmetic, e.g. matrix multiplication The solution of a linear set of equations Elementary statistics

    Matrix transformations, e.g. transpose Eigenvalues and eigenvectors

  See ComplexMatrix for matrix operations in complex arithmetic.
  See PhasorMatrix for matrix operations in phasor arithmetic.
  See RankAnalysis for matrix rank analysis.
• Minimisation (or Minimization)   Minimisation procedures: This class contains a Nelder and Mead simplex method for obtaining the value of a function, f(a[0], a[1],a[2] ... ), at its minimum and the values of its parameters, a[0], a[1],a[2] ... , at the minimum. Several constraint options available.
• Maximisation (or Maximization)   Maximisation procedures: This class contains a Nelder and Mead simplex method for obtaining the value of a function, f(a[0], a[1],a[2] ... ), at its maximum and the values of its parameters, a[0], a[1],a[2] ... , at the maximum. Several constraint options available.
• Point - a point in n-dimesional space
• Polynomial - Polynomials
  This class defines an object representing a polynomial
  
  It contains the methods for:
  • The addition, subtraction and multiplication of polynomials.
  • The evaluation of polynomials.
  • The evaluation of the derivatives of polynomials.
  • Finding the roots of polynomials.
See ComplexPoly for complex polynomial procedures.

• PsRandom   This class supplements java.util.Random. It contains methods for generating single random and arrays of random:

  Uniform deviates (floating point (double) numbers) Binary numbers (bits) Gaussian (normal) and correlated Gaussian deviates Beta distribution deviates Binomial deviates Chi-square distribution deviates Erlang distribution deviates Exponential distribution deviates F-distribution deviates Fréchet (Type 2 Extreme Value) deviates

  Gamma distribution deviates Gumbel (Type 1 Extreme Value) deviates Logistic (sech squared) deviates Log-normal deviates Lorentzian (Cauchy) deviates Pareto deviates Rayleigh deviates Poissonian deviates Student's t-deviates Weibull (Type 3 Extreme Value) deviates

• TimeAndDate   This class contains methods for:

  TIME Returning the time Returning the 'computer time' Calculating the 'computer time' Timing the running of time-intensive blocks of code Introducing a waiting period

  DATE Returning the date Checking for a leap year British Summer Time Clock Changes Returning the day of a date Returning dates of feast days, e.g. Easter, Christmas

• VetorMaths - Mathematical Vectors
  This class defines an object representing a a mathematical vector
  It contains the methods for:
  • The addition, subtraction and scalar multiplication of vectors.
  • Dot product.
  • Cross product.
  • plus other miscellaneous methods.
• DATA REDUCTION, DATA ANALYSIS AND ERROR ANALYSIS
  • Stat   Statistical analyses: this class contains:
    • Arithmetic, geometric, harmonic, generalised and interquartile means, root mean square, median, standard deviation, standard error, volatlity, coefficient of variation, variance, skewness, kurtosis, standardisation and scaling of data to a new mean and standard deviation
    • Normal (Gaussian) distribution, Log-normal distribution, Logistic (sech squared) distribution, Lorentzian (Cauchy) distribution, Poisson distribution, Type 1 extreme value distribution (Gumbel), Type 2 extreme value distributions (Fréchet), Type 3 extreme value distributions (Weibull, Exponential, Rayleigh), Pareto distribution, Binomial distribution, Student's t-distribution, Beta distribution and beta functions, Gamma distribution and gamma functions, Erlang distribution and Erlang B and C equations, Engset Equation, Chi-square distribution and chi-square statistic, F-distribution
    • Linear correlation coefficient, covariance
    • Error functions, factorials
    • Shannon Entropy (Information Entropy), Binary Shannon Entropy, Rényi Entropy, Tsallis Entropy and a Generalised Entropy
    • Histograms
    Stat is a subclass of the ArrayMaths class.
  • ANOVA   Class for performing an analysis of variance (ANOVA).
  • Outliers   Class for detecting data outliers.
  • Grubbs’ Test
  • Teitjen-Moore Test
  • Generalised ESD (Extreme Studentised Deviate) Test
  • Dixon’s Test
  • Scores   Class for entering and analysing item-response data matrices. It is the superclass for Cronbach and PCA.
  • PCA   Principal Component Analysis: This class contains methods for performing a basic principal component analysis with:
    
    • a covariance matrix or a correlation matrix option
    • a Monte Carlo parallel analysis
    • a varimax rotation
  • Cronbach   Cronbach's alpha consistency analysis: this class contains:
    • Calculation of Cronbach's raw data alpha consistency coefficient
    • Calculation of Cronbach's standardised data alpha consistency coefficient
    • Calculation of the inter-item correlation coefficients
    • Display of inter-item scatter plots
    • Analysis of deleting each item in turn
    • Data input from a text file or as a 2D array (String, double, float, int, char, boolean or Matrix)
      Responses may be entered as integer numbers, e.g. 1, 2, 3, 4 . . ., floating point numbers, e.g. 2.34, 5.8, -8.91, 0.635 . . ., single words, e.g. true or false,    Yes or No
    • 'No response' handling options: deletion, replacement (mean of the item, mean of the persons responses, total mean, zero, user supplied value)
    • Full range of methods returning item or person statistics, e.g. means, standard deviations, ranges of the items, item-item correlation coefficients
    • Full analysis written to a text file or Excel readable file
  • BoxCox   Box-Cox transformation: this class contains the methods for performing a Box-Cox transformation and for analysing the efficacy of the transformation.
  • RankAnalysis   Matrix rank analysis: this class contains the methods for performing a Matrix rank analysis for experimental data.
  • Normality   Matrix rank analysis: this class contains the methods for examining deviations from normality, e.g. Shapiro-Wilk W Test, Normal Probability Plot.
  • ProbabilityPlot   Probability plots: this class contains the methods for drawing and analysing Probability Plots for data drawn from a:
    

    Gaussian distribution [Normal distribution] Exponential distribution F-distribution Fréchet distribution Gumbel (minimum order statistic) distribution Gumbel (maximum order statistic) distribution

    Logistic distribution Lorentzian distribution Normal distribution [Gaussian distribution] Pareto distribution Rayleigh distribution Weibull distribution

  • Regression   Regression procedures: this class contains:

    General linear regression Linear regression with intercept Polynomial fitting Non linear regression - Nelder and Mead Simplex - unconstrained and constrained Fitting data to a Rectangular Hyperbola Fitting data to a Sigmoid threshold function Fitting data to a Hill/Sips Sigmoid Fitting data to a 5 Parameter Logistic curve Fitting data to a 4 Parameter Logistic [EC50 dose response] curve Fitting data to a Scaled Heaviside Step Function Fitting data to a Gaussian Distribution [Normal Distribution] Fitting data to a Log-normal Distribution Fitting data to a Logistic Distribution [sech squared Distribution] Fitting data to a Lorentzian Distribution [Cauchy Distribution] Fitting data to a Poisson Distribution See ImmunoAssay (below) for fitting immunoassay data to standard assay equations. See Impedance Spectroscopy (below) for fitting impedance data to circuit models

    Fitting data to a Beta Distribution Fitting data to a Gamma Distribution Fitting data to an Erlang Distribution Fitting data to a Type 1 Extreme Value Distribution (Gumbel Distribution) Fitting data to a Type 2 Extreme Value Distribution (Fréchet Distribution) Fitting data to a Type 3 Extreme Value Distribution (Weibull Distribution) Fitting data to a Type 3 Extreme Value Distribution (Exponential Distribution) Fitting data to a Type 3 Extreme Value Distribution (Rayleigh Distribution) Fitting data to a Pareto Distribution

  • ImpedSpecRegression - Regression procedures for fitting impedance spectroscopy and electrochemical impedance spectroscopy (EIS) data to circuit models. This is a subclass of Regression (immediately above)
    
  • ErrorProp   Error Propagation: The constructor defines a variable and its associated error (double variables named value and sd) and the class includes the methods for propagating the error in standard arithmetic operations for both correlated and uncorrelated errors. The error should be the standard deviation, or an estimate of the standard deviation, of the variable. See ComplexErrorProp for error propagation in complex arithmetic.
  • CurveSmooth   This class contains the following methods:
    • Savitzky-Golay smoothing filter for smoothing a data curve and also providing smoothed nth derivative curves;
    • Moving average smoothing window for smoothing a data curve;
    • Interpolation of the smoothed data
    • Finding all minima and maxima in a data curve.
  • SurfaceSmooth   This class contains the following methods:
    • Savitzky-Golay smoothing filter for smoothing two dimensional data, i.e. a surface, and also providing the smoothed derivative;
    • Moving average smoothing window for smoothing two dimensional data, i.e. a surface;
    • Interpolation of the two dimensional smoothed data
  • ThreeDimensionalSmooth   This class contains the following methods:
    • Savitzky-Golay smoothing filter for smoothing thre dimensional data and also providing the smoothed derivative;
    • Moving average smoothing window for smoothing three dimensional data
    • Interpolation of the three dimensional smoothed data
  NUMERICAL INTEGRATION
  • Integration   This class contains the following numerical integration procedures and associated methods:
    • Gauss-Legendre Quadrature and the generation of the Gauss-Legendre weights;
    • Trapezoidal Rule;
    • Backward and Foreward Rectangular Rule.
  • RungeKutta   This class contains the following procedures and associated methods for solving a single or a set of ordinary differential equations:
    • Fourth order Runge-Kutta (fixed step size);
    • Runge-Kutta-Fehlberg (adaptive step size);
    • Runge-Kutta-Cash-Karp (adaptive step size).
• INTERPOLATION
  • LinearInterpolation - Interpolation within a one dimensional array of data points.. Also calculates the interpolated first derivatives.
  • CubicInterpolation - Interpolation within a one dimensional array of data points.. Also calculates the interpolated first derivatives.
  • CubicSpline - Spline interpolation within a one dimension array of data points using a cubic spline. Also calculates the interpolated first derivative.
  • CubicSplineFast - Fast spline interpolation within a one dimensional array of data points using a natural cubic spline [no data checking]
  • BiCubicInterpolation - Spline interpolation within a two dimensional array of data points. Uses grid point gradients including the cross gradients. Also calculates the interpolated first and cross derivatives.
  • BiCubicSpline - Interpolation within a two dimensional array of data points using a natural bicubic spline
  • BiCubicSplineFast - Fast interpolation within a two dimensional array of data points using a natural bicubic spline [no data checking]
  • BiCubicSplineFirstDerivative - Interpolation within a two dimensional array of data points using a natural bicubic spline. Also calculates the interpolated first derivatives.
  • TriCubicInterpolation - Interpolation within a three dimensional array of data points. Uses grid point gradients including the cross gradients. Also calculates the interpolated first and cross derivatives.
  • TriCubicSpline - Interpolation within a three dimensional array of data points using a natural tricubic spline
  • QuadriCubicSpline - Interpolation within a four dimensional array of data points using a natural quadricubic spline
  • PolyCubicSpline - Interpolation within a multidimensional array of data points using natural cubic splines
  • PolyCubicSplineFast - Fast interpolation within a multidimensional array of data points using a natural cubic splines [no data checking]
  • PolylineSimplification Douglas-Peucker Polyline Simplification
• ROOT SEARCHING
  • RealRoot - Real root searching methods: Combined Bisection and Newton-Raphson method, Combined Bisection and Inverse Quadratic Interpolation [Brent] method, Newton-Raphson method, Bisection method, False position method.
  • ComplexPoly - Contains methods for finding the roots of Complex polynomials (see below for a fuller description of ComplexPoly).
• COMPLEX NUMBERS
  • Complex - Basic complex class.
    This class defines an object representing a complex number and contains:
    • The methods for basic complex arithmetic, e.g. complex multiplication.
    • The standard complex mathematical functions, e.g. complex sqrt.
    • The complex trigonometric functions, e.g. complex sine.
    • The methods for the creation of one and two dimensional arrays of complex numbers.
  • ComplexMatrix - Complex Matrices
    This class defines an object representing a two dimensional array of complex numbers, i.e. a complex matrix. It contains the methods for:
    • Complex matrix arithmetic, e.g. matrix multiplication.
    • Complex matrix transformations, e.g. transpose, adjoin.
    • The solution of a complex linear set of equations.
  • ComplexPoly - Complex Polynomials
    This class defines an object representing a complex polynomial
    
    It contains the methods for:
    • The addition, subtraction and multiplication of complex polynomials.
    • The evaluation of complex polynomials.
    • The evaluation of the derivatives of complex polynomials.
    • Finding the roots of complex polynomials.
  • ComplexErrorProp - Error propagation in complex arithmetic
  • Phasor - This class defines an object that represents a Phasor; magnitudephase = magnitude.exp(j.phase). It includes an extensive range of the methods needed in Phasor arithmetic and methods for converting the impedances of standard circuit components into phasors.
    
  • PhasorMatrix - This class defines an object representing a two dimensional array of Phasors. It contains the methods for:
    • Phasor matrix arithmetic, e.g. matrix multiplication.
    • Phasor matrix transformations, e.g. transpose, adjoin.
    • The solution of a linear set of phasor equations.
• POLYNOMIALS
  • Polynomial - Polynomials
    This class defines an object representing a polynomial
    
    It contains the methods for:
    • The addition, subtraction and multiplication of polynomials.
    • The evaluation of polynomials.
    • The evaluation of the derivatives of polynomials.
    • Finding the roots of polynomials.
  • ComplexPoly - Complex Polynomials
    This class defines an object representing a complex polynomial
    It contains the methods for:
    • The addition, subtraction and multiplication of complex polynomials.
    • The evaluation of complex polynomials.
    • The evaluation of the derivatives of complex polynomials.
    • Finding the roots of complex polynomials.
• CIRCUITS
  • Impedance - This class contains the basic method for calculating the complex impedance of circuits containing:
    

    Resistors. Inductors. 'Infinite' Warburg impedances

    Capacitors. Constant phase elements 'Infinite' Warburg impedances

    and for calculating the resistances of wires and plates made from a range of metals and alloys.
  • TransmissionLine - This class provides, for a generalised transmission line, the methods for obtaining:
    

    Characteristic impedance, Zo Input impedance, Zi Shorted line impedance, Zload = 0 Open line impedance, Zload = ∞ Quater-wave line impedance Half-wave line impedance Wavelength, λ Transmission matrix (ABCD matrix)

    Distributed impedance, R + jωL Distributed admittance, G + jωC Reflection coefficient, ρ Standing-wave ratio Attenuation constant, α Phase constant, β Propagation constant, γ = α + jβ Phase velocity, vp

    This is the superclass for SurfaceStripLine, CoaxialLine, ParallelPlateLine and TwoWireLine.
  • SurfaceStripLine - This is a subclass of TransmissionLine (above) modelling a surface strip transmission line.
    
  • CoaxialLine - This is a subclass of TransmissionLine (above) modelling a coaxial cable transmission line.
    
  • ParallelPlateLine - This is a subclass of TransmissionLine (above) modelling a parallel plate cable transmission line.
    
  • TwoWireLine - This is a subclass of TransmissionLine (above) modelling a two wire transmission line.
    
  • Phasor - This class defines an object that represents a Phasor; magnitudephase = magnitude.exp(j.phase). It includes an extensive range of the methods needed in Phasor arithmetic and methods for converting the impedances of standard circuit components into phasors.
    
  • PhasorMatrix - This class defines an object representing a two dimensional array of Phasors. It contains the methods for:
    • Phasor matrix arithmetic, e.g. matrix multiplication.
    • Phasor matrix transformations, e.g. transpose, adjoin.
    • The solution of a linear set of phasor equations.
• IMPEDANCE SPECTROSCOPY
  • ImpedSpecRegression - Regression procedures for fitting impedance spectroscopy and electrochemical impedance spectroscopy (EIS) data to circuit models.
    
  • ImpedSpecSimulation - provides methods for simulating impedance spectroscopy and electrochemical impedance spectroscopy (EIS) scans.
    
• GRAPH PLOTTING
  • PlotGraph   This class contains methods for plotting several curves on one set of x-y axes and displaying the graph in a window. For adding a graph plotting procedure to an application.
  • Plotter   This class contains methods and an application for taking data from a text file and plotting several curves on one set of x-y axes and displaying the graph in a window. A free standing graph plotting application.
  • PlotPoleZero   This class calculates the poles and zeros of a transfer function, of the form, polynomial/polynomial, plots them on an s- or z-plane graph and writes the results to a text file.
  • DigiGraph   This class contains the methods for digitising the points on a graph presented as a JPEG, GIF or PNG file.
• BIOLOGICAL APPLICATIONS
  • ImmunoAssay -   This class contains the methods for fitting assay data to the following equations
    
    • five parameter logistic function:      r = top + (bottom - top)/((1 + (a/C50)^HillSlope)^asymm).
    • four parameter logistic function (EC₅₀ dose response curve):      r = top + (bottom - top)/(1 + (a/C50)^HillSlope).
    • the best fit polynomial as determined by comparing the extra sum of squares F-ratio probabilities of successive pairs of polynomials of increasing degree.
    • a polynomial of user chosen degree, n:      r = c₀ + c₁.a + c₂.a² + . . . + c_n.aⁿ
    • the non-integer polynomial:      r = c₀ + c₁.a + c₂.a^c₃.
    • the sigmoid threshold function:      r = A_o/(1 + exp(-α(a - θ))).
    • Sips sigmoid function:      r = A_oaⁿ/(θⁿ + aⁿ)
    • rectangular hyperbola:      r = A_oa/(θ + a)
    • ‘Amersham’ model:     
    • cubic spline interpolation
    for obtaining the analyte concentration for a given resonse and for comparing the goodness of fit of the above equations.
  • ChapmanGouyStern -   This class contains the methods for calculating surface potentials using the Chapman-Gouy-Stern equations.
  • Donnan -   This class contains the methods for calculating, for a Donnan Equilibrium of ions distributed between two phases with an ionophore in one phase, the interfacial potential and the ionic concentrations in both phases.
• OPTICS
  • Reflectivity   This class contains the methods for calculating, for the reflection of light from the surface of a dielectric and/or metal multilayer:
    • Reflectivity
    • Transmissivity
    • Angle of the transmitted beam θ_r
    • TE mode reflection coefficient
    • TM mode reflection coefficient
    • TE mode transmission coefficient
    • TM mode transmission coefficient
    • Evanescent field intensity (for total internal reflection)
    • Evanescent field penetration depth (for total internal reflection)
    • Wave vector k_o
    • Wave vectors k_i
    • Wave vectors k_x,i
    • Wave vector k_z
  • PrismCoupler   This class contains the methods for:
    • calculating the refractive index of the core thin film of an asymmetric slab planar waveguide from the core thicknesses and coupling angles at a prism coupler on the waveguide;
    • displaying a normalised propagation vector against core thickness dispersion curve.
    This class is a subclass of superclass PlanarWaveguide.
  • GratingCoupler   This class contains the methods for:
    • calculating the refractive index of the core thin film of an asymmetric slab planar waveguide from the core thicknesses and coupling angles at a grating coupler on the waveguide;
    • displaying a normalised propagation vector against core thickness dispersion curve.
    This class is a subclass of superclass PlanarWaveguide.
  • PlanarWaveguide   This class contains the methods for:
    • calculating the refractive index of the core thin film of an asymmetric slab planar waveguide from the core thicknesses and the normalised propagation vectors, i.e. effective refractive indices;
    • displaying a normalised propagation vector against core thickness dispersion curve.
    This class is the superclass for the subclasses PrismCoupler and GratingCoupler.
  • RefractiveIndex -  Refractive Indices [Replaces RefrIndex]
    This class contains the methods for:
    • Returning, for a given wavelength, the complex refractive index of:
      • Gold;
      • Silver.
    • Returning, for a given wavelength, the real refractive index of:
      • Fused Quartz;
      • LAF78847 Crown glass;
      • Pilkington Permabloc Float Glass;
      • Chance Popper Microscope Slide Glass;
      • Polymethacrylate;
      • Air.
    • Returning, for a given wavelength and temperature, the real refractive index of:
      • Water.
    • Returning, for a given concentration, wavelength and temperature, the real refractive index of:
      • Aqueous NaCl solutions (saline solutions);
      • Aqueous polyvinylalcohol (pva) solutions.
    • Returning, for a given concentration and temperature, the real refractive index of:
      • Aqueous sucrose solutions.
    • Calculating the refractive index of mixtures (Lorenz-Lorentz equation).
    • Interconverting absorption coefficients and the imaginary part of the refractive index.
• IONIC RADII
  • IonicRadii -   This class contains the methods for returning the ionic radii of a range bare and hydrated anions and cations
• PROPERTIES OF WATER
  • Water -   This class contains the methods for returning the following physical properties of water:
    • Density as a function of temperature.
    • Viscosity as a function of temperature.
    • Static Relative Electrical Permittivity (dielectric constant) as a function of temperature.
    • Refractive Index as a function of wavelength and temperature.
    • Molecular Weight.
• PROPERTIES OF AQUEOUS NaCl SOLUTIONS
  • Saline -   This class contains the methods for returning the following physical properties of aqueous NaCl solutions:
    • Density as a function of NaCl concentration.
    • Viscosity as a function of NaCl concentration and temperature.
    • Refractive Index as a function of NaCl concentration, wavelength and temperature.
    • Mole Fraction of NaCl in an aqueous NaCl solution.
    • Molecular Weight of NaCl.
    • and concentration interconversion (Molar - grams per litre).
• PROPERTIES OF AQUEOUS SUCROSE SOLUTIONS
  • Sucrose -   This class contains the methods for returning the following physical properties of aqueous sucrose solutions:
    • Density as a function of sucrose concentration and temperature.
    • Viscosity as a function of sucrose concentration and temperature.
    • Refractive Index as a function of sucrose concentration and temperature at 589.3 nm.
    • Solubility as a function of temperature.
    • Specific Volume as a function of concentration of sucrose.
    • Diffusion coefficient as a function of temperature and concentration of sucrose.
    • Mole fraction of sucrose in an aqueous sucrose solution.
    • Molecular Weight of sucrose.
    • and concentration interconversion (Molar - grams per litre - percent weight by weight).
• PROPERTIES OF AQUEOUS POLYVINYLALCOHOL (PVA) SOLUTIONS
  • Pva -   This class contains the methods for returning the following physical properties of aqueous polyvinylalcohol (pva) solutions:
    • Density as a function of pva concentration and pva molecular weight.
    • Viscosity as a function of pva concentration, pva molecular weight and temperature.
    • Refractive Index as a function of pva concentration, wavelength and temperature.
    • Specific Volume.
    • Diffusion coefficient as a function of the pva concentration, pva molecular weight and temperature.
• UTILITIES
  • Chars - This class contains some simple manipulations and tests of characters:
    • HTML code
    • ASCII decimal number
    • ASCII hexadecimal number
    • Position in alphabet
    • Remove an accent
    • Change case
    • Check case
    • check for quotation mark
    • check for dash
    • Check if alphabetic, alphanumeric
    • Check if a digit
  • Strings - This class contains some simple manipulations and tests of String:
    • Tokenisation
    • Concatenation
    • Conversions
      
      • to upper case
      • to lower case
      • to title case
      • to sentence case
      • remove accents
      • reverse character order
• CONTROL & SYSTEMS ENGINEERING
  • BlackBox - This class contains the constructor to create an instance of a generalised BlackBox with a single input, single output, a dead (transportation) time and a gain that in the s-domain may be representede by a ratio of two complex polynomials. It contains the methods, amongst others, for: setting the s-domain transfer function; obtaining the s-domain poles and zeros; setting, or mapping from the s-domain, the z-domain transfer function; obtaining the z-domain poles and zeros; plotting the poles and zeros; plotting the transient response for impulse, step and ramp inputs; plotting the Bode plots; setting the variables needed for handling sampled data.
    This class is the superclass for the following sub-classes:
  • OpenLoop - This class supports the creation of an open path of Black Boxes, i.e. of instances of BlackBox and of any of its subclasses, e.g. PropIntDeriv, FirstOrder, and the methods to combine these into a single instance of BlackBox and a Vector of analogue segments, digital segments and converters.
  • ClosedLoop - This class supports the creation of a closed loop of Black Boxes, i.e. of instances of BlackBox and of any of its subclasses, e.g. PropIntDeriv, FirstOrder, and the methods to combine these into a single instance of BlackBox and a Vector of analogue segments, digital segments and converters.
  • Compensator - This class contains the constructor to create an instance of a Generalised Compensator and the methods to use this in both continuous time and discrete control simulations.
    This is a subclass of the superclass BlackBox.
  • LowPassPassive - This class contains the constructor to create an instance of a simple passive Low Pass Filter and the methods to use this in control simulations.
    This is a subclass of the superclass BlackBox.
  • HighPassPassive - This class contains the constructor to create an instance of a simple passive High Pass Filter and the methods to use this in control simulations.
    This is a subclass of the superclass BlackBox.
  • AtoD - This class contains the constructor to create an instance of a Analogue to Digital Converter and the methods to use this in control simulations.
  • DtoA - This class contains the constructor to create an instance of a Digital to Analogue Converter and the methods to use this in control simulations.
  This is a subclass of the superclass BlackBox.
  • PropIntDeriv - A PID Controller class. This class contains the constructor to create an instance of a Proportional, Integral and Derivative (PID) controller and the methods to use this in both continuous time and discrete control simulations.
    This is a subclass of the superclass BlackBox.
  • PropInt - A PI Controller class. This class contains the constructor to create an instance of a Proportional and Integral (PI) controller and the methods to use this in both continuous time and discrete control simulations.
    This is a subclass of the superclass BlackBox.
  • PropDeriv - A PD Controller class. This class contains the constructor to create an instance of a Proportional and Derivative (PD) controller and the methods to use this in both continuous time and discrete control simulations.
    This is a subclass of the superclass BlackBox.
  • Prop - A Proportional Gain Controller class. This class contains the constructor to create an instance of a Proportional Gain (P) controller and the methods to use this in both continuous time and discrete control simulations.
    This is a subclass of the superclass BlackBox.
  • FirstOrder - This class contains the constructor to create an instance of a First Order Process and the methods to use this in both continuous time and discrete control simulations.
    This is a subclass of the superclass BlackBox.
  • SecondOrder - This class contains the constructor to create an instance of a Second Order Process and the methods to use this in both continuous time and discrete control simulations.
    This is a subclass of the superclass BlackBox.
  • DelayLine - This class contains the constructor to create an instance of a Delay Line and the methods to use this in both continuous time and discrete control simulations.
    This is a subclass of the superclass BlackBox.
  • ZeroOrderHold - This class contains the constructor to create an instance of a Zero Order Hold and the methods to use this in both continuous time and discrete control simulations.
    This is a subclass of the superclass BlackBox.
  • Transducer - This class contains the constructor to create an instance of a Transducer and the methods to use this in both continuous time and discrete control simulations.
    This is a subclass of the superclass BlackBox.

---

This page was prepared by Dr Michael Thomas Flanagan

---