def test_flatten_unflatten():
# build three sets (x,y,z)
sx = set([point(1.0, 1.0), point(2.0, 1.0), point(3.0, 2.0)])
sy = set([point(0.0, 1.0), point(3.0, 2.0)])
sz = set([point(1.0, 1.0), point(2.0, 3.0)])
# build a collection
c = collection([sx, sy, sz])
# flatten and unflatten
from mystic.math.discrete import flatten, unflatten
d = unflatten(flatten(c), c.pts)
# check if the same
assert c.npts == d.npts
assert c.weights == d.weights
assert c.positions == d.positions
# flatten() and load(...)
e = collection().load(c.flatten(), c.pts)
# check if the same
assert c.npts == e.npts
assert c.weights == e.weights
assert c.positions == e.positions
# decompose and compose
from mystic.math.discrete import decompose, compose
b = compose(*decompose(c))
# check if the same
assert c.npts == b.npts
assert c.weights == b.weights
assert c.positions == b.positions
return
def test_flatten_unflatten(): # build three sets (x,y,z) sx = set([point(1.0,1.0), point(2.0,1.0), point(3.0,2.0)]) sy = set([point(0.0,1.0), point(3.0,2.0)]) sz = set([point(1.0,1.0), point(2.0,3.0)]) # build a collection c = collection([sx,sy,sz]) # flatten and unflatten from mystic.math.discrete import flatten, unflatten d = unflatten(flatten(c), c.pts) # check if the same assert c.npts == d.npts assert c.weights == d.weights assert c.positions == d.positions # flatten() and load(...) e = collection().load(c.flatten(), c.pts) # check if the same assert c.npts == e.npts assert c.weights == e.weights assert c.positions == e.positions # decompose and compose from mystic.math.discrete import decompose, compose b = compose(*decompose(c)) # check if the same assert c.npts == b.npts assert c.weights == b.weights assert c.positions == b.positions return
def constraints(x, w):
from mystic.math.discrete import compose, decompose
c = compose(x,w)
E = float(c[0].mean)
if not (E <= float(h_mean+h_error)) or not (float(h_mean-h_error) <= E):
c[0].mean = h_mean
E = float(c[2].mean)
if not (E <= float(v_mean+v_error)) or not (float(v_mean-v_error) <= E):
c[2].mean = v_mean
return decompose(c)[0]
def constraints(x, w):
from mystic.math.discrete import compose, decompose
c = compose(x,w)
E = float(c[0].mean)
if not (E <= float(h_mean+h_error)) or not (float(h_mean-h_error) <= E):
c[0].mean = h_mean
E = float(c[2].mean)
if not (E <= float(v_mean+v_error)) or not (float(v_mean-v_error) <= E):
c[2].mean = v_mean
return decompose(c)[0]