MathGrapher is a graphical calculator for functions of the form F(x) and F(x,y)
containing up to 20 subfunctions and 150 numerical and 100 named constants. Cartesian as well as polar coordinates can be
chosen and functions can be represented in patametrized form (2D). F(x,y) can be represented in 2D and 3D
by Shaded surfaces, Contour plots and Cross-sections through Contourplots. In the 3D viewer you may rapidly vary the
viewing angle, distance and shading of the 3D surface using your mouse.
Edit and draw graphs of your 2D or 3D Data. 3D surfaces can be previewed in the 3D viewer (OpenGL). Shaded surfaces,
Contour plots and Cross-sections through Contour plots can be drawn in same way as 3D Functions.
A number of least squares curve fitting methods can be selected: e.g. linear regression, polynomials, trigonometric
polynomials and cubic splines. An important feature of this program is that you can use the
general and powerfull (non-linear) Levenberg-Marquardt method to fit your data to any continuous function you define.
Calculate algebraic series or study iterative multi-dimensional maps. Several mathematical tools are
available to analyse the results (zie ODE's below). Look at the examples to see how you may use Mathgrapher to
study the route to chaos via period doublings in the simple logistic map
The evolution of dynamical systems in physics, chemistry, electronics, economics and population dynamics can often
be described with a set of coupled ODE's. Mathgrapher uses an
accurate Adams-Bashforth variable order, variable step predictor-corrector algorithm to
integrate systems of up to 20 coupled ODE's. Several tools are available to analyse the
results of the integrations (and iterations) such as: Graph of the time evolution,
Projections in 2 or 3 dimensions, Surfaces of Section and Power spectrum analysis.
Edit and select Data from a grid and draw a
2D or 3D Graph.
You may view 3D data in the 3D viewer and make Contour plots and Cross-sections through Contour plots.
Some statistical properties of the data may be calculated. You may also draw
a histogram or the (cumulative, normalized) distribution function of selected data.
You may apply a Chi-square test or a
Kolmogorov-Smirnov test to compare two distributions
Graph of data selected from the grid (2D-mode)