- All values are separated by either space or a line break.
- Commas generally aren't used.
- Decimal separator is a dot.
- Fraction are written as m/n
- File content after
@line is ignored (can be used to leave comments)
Solves a system of linear inequations, with RHS being <= 0.
Similar to previous mode, but instead of point coordinates specify variable coefficients.
Common limits are not used (since system of equations is singular)
Computes a minimal convex hull of given points and the lookup table (aka table of correspondence) for normal vectors, source points and polyhedron faces.
Input format, sequentially:
- Space dimension
- (Optional) Coefficients for common equations for all systems.
If used, line before and after should be a single
$ - (Optional) Solution basis.
If used, line before and after should be a single
# - Points description
Example 1:
2
1 0
0 1
0 0
Example 2:
3
#
1 0 0
0 1 0
0 0 1
#
1 1 1
4 0 0
0 4 0
0 0 4
2 0 2
Searches for intersections between normal cones for several polyhedrons. Polyhedrons should have the same dimension (n), and there shouldn't be less than n-1 of them (no less than 2 in 3D space, etc.)
Input format, sequentially:
- Space dimension
- Polyhedrons, separated by
%
Example:
3
9 0 0
0 8 0
0 0 7
3 2 1
%
3 0 0
0 4 0
0 0 5
1 2 2
Computes a determinant of a square matrix or its minor.
Input format, sequentially:
- Square matrix dimension
- Two numbers - 0-based indices of elements, for which minor is computed. -1 if determinant is computed
- Matrix description
Example:
4
-1 -1
1 0 0 0
1 2 0 0
0 0 3 0
0 0 0 4
@
This is a comment. This matrix determinant is 24
Computes an inverse matrix for a given square matrix.
Input format, sequentially:
- Square matrix dimension
- Matrix description
Example:
3
1 0 0
-3 1 0
0 0 1
@
This is a comment. Inverse matrix is
1 0 0
3 1 0
0 0 1
Computes the unimodular matrix ("Alpha") in the following way:
- Rows and columns matrices are created, initialized as identity matrices
- Given matrix is converted to diagonal form via linear transformations. All rows transformations are mirrored by row matrix, same for columns.
- Rows and columns matrices are inverted and multiplied together
Input format, sequentially:
- Square matrix dimension
- Matrix description. Last line may be missing, in this case it's treated as zero vector.
Example:
3
1 3 4
3 4 2
@
This is a comment. The result is as follows:
1 3 4
3 10 14
0 0 1
(NOTE: So far, only 3D case is supported)
Executes one step of power transformation (computation of approximation) for the selected members of the given power equations
Input format, sequentially:
- k, number of variables in polynomials
- k-1 polynomials, separated by
%line. Each polynomial is described as a sequence of monomials in form (coefficient, power_1 power_2 ... power_k), one per line #line- Space-separated 0-based indices of monomials selected for approximation for each polynomial. Number of lines is equal to number of polynomials
Example:
3
40, 1 1 1
25, 4 0 0
-25, 0 4 0
-1, 0 0 4
+16, 2 0 2
%
-1, 0 1 1
-1, 2 0 1
-1, 3 1 0
-1, 2 1 1
#
0 1 3 4
0 1