def testRandom(self): l = Matrix(5) l.randomLowerTriangular(5) u = Matrix(5) u.randomUpperTriangular(5) m = l*u (x,y) = m.lu() self.assertTrue(m.isAlmostEqual(x*y))
def testRandom(self):
l = Matrix(self.size)
u = Matrix(self.size)
l.randomLowerTriangular(5)
u.randomUpperTriangular(5)
m = l * u
one = Matrix(self.size)
one.one()
self.assertTrue(one.isAlmostEqual(m * m.invertLU()))
def testUpperTriangularInversion(self):
a = Matrix(15)
a.randomUpperTriangular(87)
b = a.invertUpperTriangular()
c = Matrix(15)
c.one()
print (c - a * b).frobeniusNorm()
self.assertTrue(c.isAlmostEqual(a * b))
self.assertTrue(c.isAlmostEqual(b * a))
def genMatrix(size, kind):
m = Matrix(size)
if kind == "random":
m.random(seed())
elif kind == "triangular":
m.randomUpperTriangular(seed())
elif kind == "hilbert":
m.hilbert()
elif kind == "diagonal_dominant":
m.randomDiagonalDominant(seed())
elif kind == "almost_singular":
m.randomAlmostSingular(seed())
elif kind == "zero_minor":
m.randomZeroMinor(seed())
elif kind == "tridiagonal":
m.randomTridiagonal(seed())
else:
return None
return m