def tst_five_d_cube():
hcube = sm.halton(5)
result = flex.double([0, 0, 0, 0, 0])
for ii in range(5000):
vec = flex.double(hcube.nth_all(ii))
result += vec
result = result / 5000.0
for ii in result:
assert approx_equal(ii, 0.5, 0.01)
def tst_five_d_cube():
hcube = sm.halton(5)
result = flex.double( [0,0,0,0,0] )
for ii in xrange(5000):
vec = flex.double(hcube.nth_all(ii))
result += vec
result = result/5000.0
for ii in result:
assert approx_equal(ii, 0.5, 0.01)
def test_halton_sequence_2(n_points, high_limit=5.0):
norm = math.pi * 2.0
h_gen = sm.halton(1)
result = 0.0
for ii in range(n_points):
x = (1.0 - 2.0 * h_gen.nth_given_base(5, ii)) * high_limit
y = (1.0 - 2.0 * h_gen.nth_given_base(7, ii)) * high_limit
result += math.exp(-(x * x + y * y) * 0.5) / norm
tmp = high_limit * high_limit * 4.0 * result / (float(n_points))
assert approx_equal(tmp, 1.0, eps=1e-2)
def test_halton_sequence_2(n_points, high_limit=5.0):
norm = math.pi*2.0
h_gen = sm.halton(1)
result = 0.0
for ii in xrange(n_points):
x = (1.0-2.0*h_gen.nth_given_base(5, ii))*high_limit
y = (1.0-2.0*h_gen.nth_given_base(7, ii))*high_limit
result += math.exp( -(x*x+y*y)*0.5 )/norm
tmp = high_limit*high_limit*4.0*result/(float(n_points))
assert approx_equal(tmp,1.0,eps=1e-2)
def test_halton_sequence_1(n_points, high_limit=1.0):
h_gen = sm.halton(1)
result = 0.0
for ii in range(n_points):
x = h_gen.nth_given_base(5, ii) * high_limit
y = h_gen.nth_given_base(7, ii) * high_limit
result += math.exp(float(-x - y))
tmp = (math.exp(-2.0 * high_limit)) * (math.exp(high_limit) - 1.0)**2.0
result /= float(n_points)
result *= high_limit * high_limit
tmp = (math.exp(-2.0 * high_limit)) * (math.exp(high_limit) - 1.0)**2.0
assert approx_equal(result / tmp, 1.0, eps=1e-2)
def test_halton_sequence_1(n_points, high_limit=1.0):
h_gen = sm.halton(1)
result = 0.0
for ii in xrange(n_points):
x = h_gen.nth_given_base(5, ii)*high_limit
y = h_gen.nth_given_base(7, ii)*high_limit
result += math.exp( float(-x - y) )
tmp = ( math.exp(-2.0*high_limit) )*( math.exp(high_limit)-1.0 )**2.0
result /= float(n_points)
result *= high_limit*high_limit
tmp = ( math.exp(-2.0*high_limit) )*( math.exp(high_limit)-1.0 )**2.0
assert approx_equal( result/tmp, 1.0 ,eps=1e-2)
