def check0(self, ch, w, debug=False):
env = Env(w, [])
visitor = Projection()
visitor.execute(ch, env, debug)
chor = visitor.choreography
vectorize(chor, w)
checker = CompatibilityCheck(chor, w)
checker.localChoiceChecks()
checker.generateTotalGuardsChecks()
checker.computePreds(debug)
checker.generateCompatibilityChecks(debug)
for i in range(0, len(checker.vcs)):
vc = checker.vcs[i]
if not vc.discharge(debug=debug):
print(i, "inFP", vc.title)
if vc.hasModel():
print(vc.modelStr())
return False
return True
def check(self, P1, P2):
w = World()
p1 = P1(w, 0)
p2 = P2(w, 1)
env = Env(w, [])
ch = choreo()
visitor = Projection()
visitor.execute(ch, env)
chor = visitor.choreography
vectorize(chor, w)
checker = CompatibilityCheck(chor, w)
checker.localChoiceChecks()
checker.generateTotalGuardsChecks()
checker.computePreds()
checker.generateCompatibilityChecks()
for i in range(0, len(checker.vcs)):
vc = checker.vcs[i]
if not vc.discharge():
print(i, "inFP", vc.title)
if vc.hasModel():
print(vc.modelStr())
return False
return True
ks = np.empty_like(xs)
lams = np.empty_like(xs)
dnetas = np.empty_like(xs)
dks = np.empty_like(xs)
dfs = np.empty_like(xs)
print('Number of points: %d' % len(xs))
xnew = sym.initial(la.fem.density.copy())
for i, p in enumerate(xs):
xnew[index] = p
x1 = sym.execute(xnew)
x2 = density_filter.execute(x1)
x3 = projection.execute(x2)
dens = x3
la.execute_analysis(dens)
ddn = la.dneta1 @ projection.sensitivity(
x2) @ density_filter.sensitivity() @ sym.sensitivity()
ddk = la.dk1 @ projection.sensitivity(
x2) @ density_filter.sensitivity() @ sym.sensitivity()
ddf = la.df1 @ projection.sensitivity(
x2) @ density_filter.sensitivity() @ sym.sensitivity()
lams[i] = la.f1
netas[i] = la.neta1
ks[i] = la.k1
dnetas[i] = ddn[index]
