def test_distribute_products_k(self):
print 'distribute'
k = ff.SqExpKernel(dimension=0, lengthscale=0, sf=1)
k1 = k.copy()
k2 = k.copy()
k = ff.SqExpKernel(dimension=1, lengthscale=2, sf=2)
k3 = k.copy()
k4 = k.copy()
k5 = ff.NoiseKernel(sf=-1)
k6 = ff.ConstKernel(sf=1)
k = (k1 + k2 + k3) * (k4 + k5)
print '\n', k.pretty_print(), '\n'
components = k.distribute_products().simplified()
print components
print components.collapse_additive_idempotency()
for k in components.operands:
print '\n', k.pretty_print(), '\n'
k = ff.SqExpKernel(dimension=0, lengthscale=0, sf=1)
k1 = k.copy()
k2 = k.copy()
k = ff.SqExpKernel(dimension=1, lengthscale=2, sf=2)
k3 = k.copy()
k4 = k.copy()
k5 = ff.NoiseKernel(sf=-1)
k6 = ff.ConstKernel(sf=1)
k = (k1 * (k2 + k3)) + (k4 * k5)
print '\n', k.pretty_print(), '\n'
components = k.distribute_products().simplified()
print components
print components.collapse_additive_idempotency()
for k in components.operands:
print '\n', k.pretty_print(), '\n'
def test_simplify(self):
m = ff.GPModel(mean=ff.MeanZero(),
kernel=ff.SumKernel(operands=[
ff.ProductKernel(operands=[
ff.ConstKernel(sf=0.170186999131),
ff.SqExpKernel(dimension=0,
lengthscale=1.02215322228,
sf=5.9042619611)
]),
ff.ProductKernel(operands=[
ff.NoiseKernel(sf=2.43188502201),
ff.ConstKernel(sf=-0.368638271154)
]),
ff.ProductKernel(operands=[
ff.NoiseKernel(sf=1.47110516981),
ff.PeriodicKernel(dimension=0,
lengthscale=-1.19651800365,
period=0.550394248167,
sf=0.131044872864)
]),
ff.ProductKernel(operands=[
ff.SqExpKernel(dimension=0,
lengthscale=3.33346140605,
sf=3.7579461353),
ff.PeriodicKernel(dimension=0,
lengthscale=0.669624964607,
period=0.00216264543496,
sf=2.41995024965)
])
]),
likelihood=ff.LikGauss(sf=-np.inf),
nll=599.59757993,
ndata=144)
assert not m.simplified() == m
m = ff.GPModel(mean=ff.MeanZero(),
kernel=ff.SumKernel(operands=[
ff.ProductKernel(operands=[
ff.ConstKernel(sf=0.170186999131),
ff.SqExpKernel(dimension=0,
lengthscale=1.02215322228,
sf=5.9042619611)
]),
ff.ProductKernel(operands=[
ff.NoiseKernel(sf=2.43188502201),
ff.ConstKernel(sf=-0.368638271154)
])
]),
likelihood=ff.LikGauss(sf=-np.inf),
nll=599.59757993,
ndata=144)
assert not m.simplified() == m
def test_collapse_mult_idempotent(self):
k = ff.SqExpKernel(dimension=0, lengthscale=0, sf=1)
k1 = k.copy()
k2 = k.copy()
k = k1 * k2
print '\n', k.pretty_print(), '\n'
k = k.collapse_multiplicative_idempotency()
assert (isinstance(k, ff.SqExpKernel)) and (k.dimension == 0)
print '\n', k.pretty_print(), '\n'
k = ff.SqExpKernel(dimension=0, lengthscale=0, sf=1)
k1 = k.copy()
k2 = k.copy()
k = ff.SqExpKernel(dimension=1, lengthscale=2, sf=2)
k3 = k.copy()
k4 = k.copy()
k5 = ff.NoiseKernel(sf=-1)
k6 = ff.ConstKernel(sf=1)
k = k1 * k2 * k3 * k4 * k5 * k5.copy() + k6 + k6.copy()
print '\n', k.pretty_print(), '\n'
k = k.collapse_multiplicative_idempotency()
print '\n', k.pretty_print(), '\n'
k = k1 * k2 * k3 * k4 * k5 * k5.copy() * k6 * k6.copy()
print '\n', k.pretty_print(), '\n'
k = k.collapse_multiplicative_idempotency()
print '\n', k.pretty_print(), '\n'
def test_noise_kernel(self):
k = ff.NoiseKernel()
print '\n', k.pretty_print(), '\n'
print '\n', k.syntax, '\n'
print '\n', k, '\n'
print '\n', k.get_gpml_expression(dimensions=3), '\n'
k.initialise_params(data_shape={'y_sd': 0})
print '\n', k, '\n'
k = k.copy()
print '\n', k, '\n'
assert k == k.copy()
k.load_param_vector(k.param_vector)
print '\n', k, '\n'
def test_canonical_k(self):
print 'canonical_k form'
k = ff.SqExpKernel(dimension=0, lengthscale=0, sf=1)
k1 = k.copy()
k2 = k.copy()
k = ff.SqExpKernel(dimension=1, lengthscale=2, sf=2)
k3 = k.copy()
k4 = k.copy()
k5 = ff.NoiseKernel(sf=-1)
k6 = ff.ConstKernel(sf=1)
k = k1 * k2 * k3 * k4 * k5 * k5.copy() + k6 + k6.copy(
) + k1.copy() * k1.copy() * k3.copy()
print '\n', k.pretty_print(), '\n'
print '\n', k.canonical().pretty_print(), '\n'
def test_collapse_add_idempotent(self):
k = ff.SqExpKernel()
k1 = k.copy()
k2 = k.copy()
k = ff.NoiseKernel(sf=-1)
k3 = k.copy()
k4 = k.copy()
k = ff.ConstKernel(sf=1)
k5 = k.copy()
k6 = k.copy()
k = k1 + k2 + k3 + k4 + k5 + k6
print '\n', k.pretty_print(), '\n'
k = k.collapse_additive_idempotency()
print '\n', k.pretty_print(), '\n'
def test_additive_form_k(self):
print 'additive form'
k = ff.SqExpKernel(dimension=0, lengthscale=0, sf=1)
k1 = k.copy()
k2 = k.copy()
k = ff.SqExpKernel(dimension=1, lengthscale=2, sf=2)
k3 = k.copy()
k4 = k.copy()
k5 = ff.NoiseKernel(sf=-1)
k6 = ff.ConstKernel(sf=1)
k = (k1 * (k2 + k3)) + (k4 * k5)
print '\n', k.pretty_print(), '\n'
components = k.additive_form().simplified()
print components
for k in components.operands:
print '\n', k.pretty_print(), '\n'
def test_collapse_zero(self):
k1 = ff.SqExpKernel(dimension=0, lengthscale=0, sf=1)
k2 = ff.NoiseKernel(sf=-1)
k = k1 * k2
print '\n', k.pretty_print(), '\n'
k = k.collapse_multiplicative_zero()
assert isinstance(k, ff.NoiseKernel)
print '\n', k.pretty_print(), '\n'
k = (k1 + k1.copy() + k1.copy() * k2.copy()) * k2
print(k1 + k1.copy()).sf
print(k1.copy() * k2.copy()).sf
print(k1 + k1.copy() + k1.copy() * k2.copy()).sf
print k.sf
print '\n', k.pretty_print(), '\n'
k = k.collapse_multiplicative_zero()
assert isinstance(k, ff.NoiseKernel)
print '\n', k.pretty_print(), '\n'
def test_simplified_k(self):
print 'simplified_k'
k = ff.SqExpKernel(dimension=0, lengthscale=0, sf=1)
k1 = k.copy()
k2 = k.copy()
k = k1 * k2
k = ff.SqExpKernel(dimension=0, lengthscale=0, sf=1)
k1 = k.copy()
k2 = k.copy()
k = ff.SqExpKernel(dimension=1, lengthscale=2, sf=2)
k3 = k.copy()
k4 = k.copy()
k5 = ff.NoiseKernel(sf=-1)
k6 = ff.ConstKernel(sf=1)
k = k1 * k2 * k3 * k4 * k5 * k5.copy() + k6 + k6.copy(
) + k1.copy() * k1.copy() * k3.copy()
print '\n', k.pretty_print(), '\n'
k = k.simplified()
print '\n', k.pretty_print(), '\n'