The purpose of this chapter is to introduce phcpy via some use cases.

In all cases, there are three stages:

  1. Given a problem, formulate the polynomial equations which describe the problem. This formulation results in a list of string representations for polynomials in several variables. This list is the input for the second stage.
  2. If the problem leads to a polynomial system for which only the isolated solution are of interest, then the blackbox solver as in the solve method of the solver method will do. Otherwise, for positive dimensional solution sets, cascades of homotopies and diagonal homotopies are needed.
  3. The solvers return their results as string representations for solutions. To process the solutions we convert the string representations into Python dictionaries.

In the first use cases, plots of the solutions are made with matplotlib. To formulate the polynomial equations we may use sympy, as illustrated in the design of 4-bar mechanisms. In the problem of the four lines, the intersection conditions are verified with numpy.

The python interpreter in Sage can be extended to include phcpy. In the problem of all lines tangent to four given lines, the polynomial system is formulated with Sage and the visualization of the solutions is also done within Sage.

In all use cases, we distinguish between general instances of a problem (where the numbers for the parameters are chosen at random), and specific instances of the problem. For these specific instances, singular solutions are likely to occur.