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4 Implemented packages
 4.1 MPFR
 4.2 MPFI
 4.3 MPC
 4.4 CXSC
 4.5 FPLLL

4 Implemented packages

4.1 MPFR

4.1-1 IsMPFRFloat
‣ IsMPFRFloat( filter )
‣ TYPE_MPFR( global variable )

The category of floating-point numbers.

Note that they are treated as commutative and scalar, but are not necessarily associative.

4.2 MPFI

4.2-1 IsMPFIFloat
‣ IsMPFIFloat( filter )
‣ TYPE_MPFI( global variable )

The category of intervals of floating-point numbers.

Note that they are treated as commutative and scalar, but are not necessarily associative.

4.3 MPC

4.3-1 IsMPCFloat
‣ IsMPCFloat( filter )
‣ TYPE_MPC( global variable )

The category of intervals of floating-point numbers.

Note that they are treated as commutative and scalar, but are not necessarily associative.

4.4 CXSC

4.4-1 IsCXSCReal
‣ IsCXSCReal( filter )
‣ IsCXSCComplex( filter )
‣ IsCXSCInterval( filter )
‣ IsCXSCBox( filter )
‣ TYPE_CXSC_RP( global variable )
‣ TYPE_CXSC_CP( global variable )
‣ TYPE_CXSC_RI( global variable )
‣ TYPE_CXSC_CI( global variable )

The category of floating-point numbers.

Note that they are treated as commutative and scalar, but are not necessarily associative.

4.5 FPLLL

4.5-1 FPLLLReducedBasis
‣ FPLLLReducedBasis( m )( operation )

Returns: A matrix spanning the same lattice as m.

This function implements the LLL (Lenstra-Lenstra-Lovász) lattice reduction algorithm via the external library fplll.

The result is guaranteed to be optimal up to 1%.

4.5-2 FPLLLShortestVector
‣ FPLLLShortestVector( m )( operation )

Returns: A short vector in the lattice spanned by m.

This function implements the LLL (Lenstra-Lenstra-Lovász) lattice reduction algorithm via the external library fplll, and then computes a short vector in this lattice.

The result is guaranteed to be optimal up to 1%.

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