Since you’ve tagged this question with sympy, I will give such an example. From the documentation: http://docs.sympy.org/latest/modules/plotting.html. from sympy import var, plot_implicit var(‘x y’) plot_implicit(x*y**3 – y*x**3)
You can use determinant to calculate values of x y and z. Logic can be found out here http://www.intmath.com/Matrices-determinants/1_Determinants.php And then you need to implement it in java using 3 dimensional arrays.
You could make use of Java 1.6’s scripting capabilities: import javax.script.*; import java.util.*; public class Main { public static void main(String[] args) throws Exception { ScriptEngine engine = new ScriptEngineManager().getEngineByName(“JavaScript”); Map<String, Object> vars = new HashMap<String, Object>(); vars.put(“x”, 2); vars.put(“y”, 1); vars.put(“z”, 3); System.out.println(“result = “+engine.eval(“x + y + z”, new SimpleBindings(vars))); } } which … Read more
Don’t laugh, but the easiest would be to use the rectangle function, indeed 😉 %// radius r = 2; %// center c = [3 3]; pos = [c-r 2*r 2*r]; rectangle(‘Position’,pos,’Curvature’,[1 1]) axis equal but set the curvature of the rectangle to 1! The position vector defines the rectangle, the first two values x and … Read more
Try mathjax http://www.mathjax.org/ . I personally find it very good.
How about SymPy? Their solver looks like what you need. Have a look at their source code if you want to build the library yourself…
One way would be to use numexpr. It’s mostly a module for optimizing (and multithreading) numpy operations but it can also handle mathematical python expressions: >>> import numexpr >>> numexpr.evaluate(‘2 + 4.1 * 3′) array(14.299999999999999) You can call .item on the result to get a python-like type: >>> numexpr.evaluate(’17 / 3′).item() 5.666666666666667 It’s a 3rd … Read more
By using masked arrays you can avoid plotting selected regions of a curve. To remove the singularity at x=2: import matplotlib.numerix.ma as M # for older versions, prior to .98 #import numpy.ma as M # for newer versions of matplotlib from pylab import * figure() xx = np.arange(-0.5,5.5,0.01) vals = 1/(xx-2) vals = M.array(vals) mvals … Read more
I don’t believe there’s very good support for this, but you could try something like import matplotlib.pyplot from numpy import arange from numpy import meshgrid delta = 0.025 xrange = arange(-5.0, 20.0, delta) yrange = arange(-5.0, 20.0, delta) X, Y = meshgrid(xrange,yrange) # F is one side of the equation, G is the other F … Read more
Python’s own internal compiler can parse this, if you use Python notation. If your change the notation slightly, you’ll be happier. import compiler eq= “sin(x)*x**2” ast= compiler.parse( eq ) You get an abstract syntax tree that you can work with.