model -- creates a new model for random objects with a given list of parameters and generating function

Synopsis

Usage:

model(L,f,name)
Inputs:
- L, a list, of parameter values chosen for the model
- f, a function closure, function that generates random elements in this model
- name, a string, of the model constructed
Outputs:
- an instance of the type Model, with those fixed parameter values

Description

To create your own model for random polynomials or other algebraic objects, use the model method as follows. Suppose you wish to construct a set of M random polynomials in 3 variables of degree 2. You may use Macaulay2's built-in random function:

i1 : f=(D,n,M)->(R=QQ[x_1..x_n];apply(M,i->random(D,R)))

o1 = f

o1 : FunctionClosure

To formalize the study of these random polynomials, embed this function into an object of type Model:

i2 : myModel = model({2,3,4},f,"rand(D,n,M): M random polynomials in n variables of degree D")

o2 = Model{Generate => FunctionClosure[/usr/local/share/Macaulay2/RandomMonomialIdeals.m2:116:20-116:40]}
           Name => rand(D,n,M): M random polynomials in n variables of degree D
           Parameters => {2, 3, 4}

o2 : Model

Now obtain the data about such random polynomials from the sample (that is, the actual sample in the statistical sense) as follows:

i3 : N=2;

i4 : mySample = sample(myModel,N);

i5 : peek mySample

o5 = Sample{ModelName => rand(D,n,M): M random polynomials in n variables of degree D                                                                                                                                                                                                                                                                             }
            Parameters => {2, 3, 4}
            SampleSize => 2
                      9 2   1       1 2   9              3 2  3 2   3       7 2   7        7       1 2   7 2   7       3 2           5       6 2  2 2            2           5       2 2      2    3       3 2                  10 2  1 2              2           3       4 2  7 2   5       2 2           5       7 2  2 2   6       5 2   5       5       5 2
            Data => {{-x  + -x x  + -x  + -x x  + x x  + -x , -x  + -x x  + -x  + -x x  + --x x  + -x , --x  + -x x  + -x  + 7x x  + -x x  + -x , -x  + x x  + 6x  + 2x x  + -x x  + -x }, {5x  + --x x  + -x  + x x  + 5x x  + --x , -x  + 10x x  + 3x  + 3x x  + -x x  + -x , -x  + -x x  + -x  + 5x x  + -x x  + -x , -x  + -x x  + -x  + -x x  + -x x  + -x }}
                      2 1   2 1 2   2 2   4 1 3    2 3   4 3  2 1   4 1 2   9 2   4 1 3   10 2 3   2 3  10 1   3 1 2   7 2     1 3   2 2 3   7 3  3 1    1 2     2     1 3   4 2 3   9 3      1   10 1 2   7 2    1 3     2 3    9 3  2 1      1 2     2     1 3   2 2 3   3 3  8 1   6 1 2   5 2     1 3   3 2 3   2 3  5 1   5 1 2   7 2   4 1 3   9 2 3   3 3

Ways to use model:

model(List,FunctionClosure,String)

For the programmer

The object model is a method function.

model -- creates a new model for random objects with a given list of parameters and generating function

Synopsis

Description

See also

Ways to use model:

For the programmer