def randomMV(self, n=1, **kwargs) -> MultiVector:
'''
Convenience method to create a random multivector.
see `clifford.randomMV` for details
'''
return cf.randomMV(layout=self, n=n, **kwargs)
def randomV(self, n=1, **kw):
'''
generate n random 1-vector s
'''
kw.update(dict(n=n, grades=[1]))
return cf.randomMV(layout=self, **kw)
def randomMV(self, n=1, **kw):
'''
Convenience method to create a random multivector.
see `clifford.randomMV` for details
'''
kw.update(dict(n=n))
return cf.randomMV(layout=self, **kw)
def test_inverse(self):
for layout, blades in self.algebras:
a = 1. + blades['e1']
self.assertRaises(ValueError, lambda x: 1/x, a)
for i in range(10):
a = randomMV(layout, grades=[0, 1])
denominator = float(a(1)**2-a(0)**2)
if abs(denominator) > 1.e-5:
a_inv = (-a(0)/denominator) + ((1./denominator) * a(1))
self.assert_(abs((a * a_inv)-1.) < 1.e-11)
self.assert_(abs((a_inv * a)-1.) < 1.e-11)
self.assert_(abs(a_inv - 1./a) < 1.e-11)
def test_inverse(self):
for layout, blades in self.algebras:
a = 1. + blades['e1']
self.assertRaises(ValueError, lambda x: 1 / x, a)
for i in range(10):
a = randomMV(layout, grades=[0, 1])
denominator = float(a(1)**2 - a(0)**2)
if abs(denominator) > 1.e-5:
a_inv = (-a(0) / denominator) + ((1. / denominator) * a(1))
self.assert_(abs((a * a_inv) - 1.) < 1.e-11)
self.assert_(abs((a_inv * a) - 1.) < 1.e-11)
self.assert_(abs(a_inv - 1. / a) < 1.e-11)
def test_inverse(self, algebra):
layout, blades = algebra, algebra.blades
a = 1. + blades['e1']
with pytest.raises(ValueError):
1 / a
for i in range(10):
a = randomMV(layout, grades=[0, 1])
denominator = float(a(1)**2 - a(0)**2)
if abs(denominator) > 1.e-5:
a_inv = (-a(0) / denominator) + ((1. / denominator) * a(1))
assert abs((a * a_inv) - 1.) < 1.e-11
assert abs((a_inv * a) - 1.) < 1.e-11
assert abs(a_inv - 1. / a) < 1.e-11
def randomV(self,*args, **kw):
'''
create a random MV within space of self
This is a wrapper for `Layout.randomMV`
See Also
---------
Layout.randomMV
'''
if not self.isBlade():
raise ValueError('I must be a blade')
kw.update(grades=[1])
return cf.randomMV(layout=self.layout, *args, **kw)(self)
def randomV(self, n=1, **kwargs) -> MultiVector:
'''
generate n random 1-vector s
'''
return cf.randomMV(layout=self, n=n, grades=[1], **kwargs)
