def test_unsat(self):
result = CheckSatisfiability(f_unsat, 0.001)
self.assertEqual(result, None)
b = Box([x, y, z])
b_copy = Box([x, y, z])
result = CheckSatisfiability(f_unsat, 0.001, b)
self.assertEqual(result, False)
self.assertEqual(b, b_copy) # Unchanged
def test_delta_sat(self):
result = CheckSatisfiability(f_sat, 0.001)
self.assertEqual(type(result), Box)
b = Box([x, y, z])
result = CheckSatisfiability(f_sat, 0.001, b)
self.assertEqual(result, True)
self.assertTrue(b[x].diam() < 0.1)
self.assertTrue(b[y].diam() < 0.1)
self.assertTrue(b[z].diam() < 0.1)
def test_dreal_orthogonal_sat():
"""
See whether a model initializes and can build correctly.
"""
model = Model("Test Model")
ssalg = SmallStepAlg()
dralg = DRealAlg()
with model.build():
test.premade_models.find_orthogonal()
model.gen_output_terms()
model.run_algebra(ssalg)
model.run_algebra(dralg)
print(model_graraphviz_trans(model).source())
controls = list()
for v in model.controls:
controls.append(v.final['dreal_exp'])
fun = forall(
controls,
logical_imply(
logical_and(model.assumption_term().final['dreal_exp'],
model.constraint_term().final['dreal_exp']),
model.guarantee_term().final['dreal_exp']))
print(fun)
result = CheckSatisfiability(fun, 0.01)
print(result)
def inverterLoopTanh(numInverters, numSolutions="all", a=-5.0):
epsilon = 1e-14
start = time.time()
vs = []
for i in range(numInverters):
vs.append(Variable("v" + str(i)))
allConstraints = []
# Store rambus oscillator constraints
for i in range(numInverters):
allConstraints.append(vs[i] >= -1)
allConstraints.append(vs[i] <= 1)
inputInd = i
outputInd = (i + 1) % numInverters
allConstraints.append(tanh(a * vs[inputInd]) - vs[outputInd] == 0.0)
allSolutions = []
while True:
if numSolutions != "all" and len(allSolutions) == numSolutions:
break
# Store constraints pruning search space so that
# old hyperrectangles are not considered
excludingConstraints = []
for solution in allSolutions:
singleExcludingConstraints = []
for i in range(numInverters):
singleExcludingConstraints.append(vs[i] < solution[i][0])
singleExcludingConstraints.append(vs[i] > solution[i][1])
excludingConstraints.append(singleExcludingConstraints)
# Add all the rambus oscillator constraints
f_sat = logical_and(*allConstraints)
# Add constraints so that old hyperrectangles are not considered
if len(excludingConstraints) > 0:
for constraints in excludingConstraints:
f_sat = logical_and(f_sat, logical_or(*constraints))
#print ("f_sat")
#print (f_sat)
result = CheckSatisfiability(f_sat, epsilon)
#print (result)
if result is None:
break
hyper = np.zeros((numInverters, 2))
for i in range(numInverters):
hyper[i, :] = [
result[vs[i]].lb() - 2 * epsilon,
result[vs[i]].ub() + 2 * epsilon
]
#print ("hyper", hyper)
allSolutions.append(hyper)
print("num solutions found", len(allSolutions))
end = time.time()
print("time taken", end - start)
return allSolutions
def inverterScMosfet(inputVoltage, numSolutions="all"):
epsilon = 1e-14
start = time.time()
Vdd = 1.0
sn = 3
sp = 2 * sn
outputVolt = Variable("outputVolt")
iP = Variable("iP")
iN = Variable("iN")
allConstraints = []
allConstraints.append(outputVolt >= 0.0)
allConstraints.append(outputVolt <= Vdd)
allConstraints.append(-iP - iN == 0)
allConstraints += mvs_id("n", 0.0, inputVoltage, outputVolt, iN, sn)
allConstraints += mvs_id("p", Vdd, inputVoltage, outputVolt, iP, sp)
allSolutions = []
while True:
if numSolutions != "all" and len(allSolutions) == numSolutions:
break
# Store constraints pruning search space so that
# old hyperrectangles are not considered
excludingConstraints = []
for solution in allSolutions:
singleExcludingConstraints = []
singleExcludingConstraints.append(outputVolt < solution[0][0])
singleExcludingConstraints.append(outputVolt > solution[0][1])
excludingConstraints.append(singleExcludingConstraints)
#print ("allConstraints")
#print (allConstraints)
f_sat = logical_and(*allConstraints)
if len(excludingConstraints) > 0:
for constraints in excludingConstraints:
f_sat = logical_and(f_sat, logical_or(*constraints))
#print ("f_sat")
#print (f_sat)
result = CheckSatisfiability(f_sat, epsilon)
#print (result)
if result is None:
break
hyper = np.zeros((1, 2))
hyper[0, :] = [
result[outputVolt].lb() - 2 * epsilon,
result[outputVolt].ub() + 2 * epsilon
]
#print ("hyper", hyper)
allSolutions.append(hyper)
print("num solutions found", len(allSolutions))
end = time.time()
print("time taken", end - start)
return allSolutions
def exampleFun(numSolutions="all"):
start = time.time()
epsilon = 1e-14
lenV = 1
x = Variable('x')
allSolutions = []
while True:
if numSolutions != "all" and len(allSolutions) == numSolutions:
break
allConstraints = []
allConstraints.append(2 * x * asin(cos(0.797) * sin(math.pi / x)) -
0.0331 * x >= 2 * math.pi - 2.097)
allConstraints.append(x >= 3)
allConstraints.append(x <= 64)
excludingConstraints = []
for solution in allSolutions:
singleExcludingConstraints = []
singleExcludingConstraints.append(x <= solution[0][0])
singleExcludingConstraints.append(x >= solution[0][1])
excludingConstraints.append(singleExcludingConstraints)
#print ("allConstraints")
#print (allConstraints)
#print ("numConstraints", len(allConstraints))
f_sat = logical_and(*allConstraints)
if len(excludingConstraints) > 0:
for constraints in excludingConstraints:
f_sat = logical_and(f_sat, logical_or(*constraints))
#print ("f_sat")
#print (f_sat)
result = CheckSatisfiability(f_sat, epsilon)
#print (result)
if result is None:
break
hyper = np.zeros((1, 2))
hyper[0, :] = [
result[x].lb() - 2 * epsilon, result[x].ub() + 2 * epsilon
]
print("hyper", hyper)
allSolutions.append(hyper)
print("num solutions found", len(allSolutions))
'''constraints = []
x = Variable('x')
#constraints.append(x >= 0.0)
#constraints.append(x <= 64.0)
constraints.append(2*math.pi - 2*x*asin(cos(0.797)*sin(math.pi/x)) == 2.097 - 0.0331*x)
f_sat = logical_and(*constraints)
result = CheckSatisfiability(f_sat, epsilon)
print (result)'''
end = time.time()
print("time taken", end - start)
def inverterTanh(inputVoltage, a=-5.0, numSolutions="all"):
epsilon = 1e-14
start = time.time()
outputVolt = Variable("outputVolt")
allConstraints = []
allConstraints.append(outputVolt >= -1.0)
allConstraints.append(outputVolt <= 1.0)
allConstraints.append(tanh(a * inputVoltage) - outputVolt == 0)
allSolutions = []
while True:
if numSolutions != "all" and len(allSolutions) == numSolutions:
break
# Store constraints pruning search space so that
# old hyperrectangles are not considered
excludingConstraints = []
for solution in allSolutions:
singleExcludingConstraints = []
singleExcludingConstraints.append(outputVolt < solution[0][0])
singleExcludingConstraints.append(outputVolt > solution[0][1])
excludingConstraints.append(singleExcludingConstraints)
#print ("allConstraints")
#print (allConstraints)
f_sat = logical_and(*allConstraints)
if len(excludingConstraints) > 0:
for constraints in excludingConstraints:
f_sat = logical_and(f_sat, logical_or(*constraints))
#print ("f_sat")
#print (f_sat)
result = CheckSatisfiability(f_sat, epsilon)
#print (result)
if result is None:
break
hyper = np.zeros((1, 2))
hyper[0, :] = [
result[outputVolt].lb() - 2 * epsilon,
result[outputVolt].ub() + 2 * epsilon
]
#print ("hyper", hyper)
allSolutions.append(hyper)
print("num solutions found", len(allSolutions))
end = time.time()
print("time taken", end - start)
return allSolutions
def test_boolean_if_then():
"""
Tests whether boolean constraints work. True is '1', false is '0'.
"""
a = Variable('a', Variable.Int)
b = Variable('b', Variable.Int)
fun = logical_and(
if_then_else(a == False, 20, -20) > 0,
if_then_else(b == True, 13, -12) > 0)
result = CheckSatisfiability(fun, 0.01)
print(result)
def test_dreal_interface_othro():
"""
Just an empty test to make pytest force a parse check.
"""
t = Variable('theta', Variable.Real)
a = Variable('a', Variable.Bool)
b = Variable('b', Variable.Bool)
c = Variable('c', Variable.Bool)
d = Variable('d', Variable.Bool)
fun = forall(
[t],
logical_imply(logical_and(t < 3, t > -3),
(((sin(t) * if_then_else(b == True, 1, -1) *
if_then_else(a == True, sin(t), cos(t))) +
(cos(t) * if_then_else(d == True, 1, -1) *
if_then_else(c == True, sin(t), cos(t)))) == 0)))
result = CheckSatisfiability(fun, 0.01)
print(result)
assert False
def test_minimize_via_forall(self):
# To minimize f(X) s.t. φ(x), this test encodes
# the problem into a first-order logic formula.
#
# ∃X. φ(X) ∧ [∀Y φ(Y) ⇒ (f(X) ≤ f(Y))]
#
# Here we use f(x) = sin(x)cos(x)
# φ(X) = (0 ≤ x) ∧ (x ≤ π)
def f(x):
return sin(x) * cos(x)
def phi(x):
return logical_and(0 <= x, x <= math.pi)
problem = logical_and(
phi(x),
forall([y], logical_and(logical_imply(phi(y),
f(x) <= f(y)))))
result = CheckSatisfiability(problem, 0.01)
self.assertTrue(result)
self.assertAlmostEqual(result[x].mid(), math.pi * 3 / 4, places=3)
def invoke_backend(self, _show):
"""Combine all of the SMT expressions into one expression to sent to dReal
solver to determine solvability
:param bool show: If true then the full SMT formula that was created is
printed
:returns: dReal model showing the values for each of the parameters
"""
formula = logical_and(*self.exprs)
# Prints the generated formula in full, remove serialize for shortened
if _show:
# nx.draw(self.dg)
# plt.show()
print(formula)
# Return None if not solvable, returns a dict-like structure giving the
# range of values for each Variable
model = CheckSatisfiability(formula, 10)
if model:
return model
else:
return "No solution found"
from dreal.symbolic import Variable, logical_and, sin, cos
from dreal.api import CheckSatisfiability, Minimize
x = Variable("x")
y = Variable("y")
z = Variable("z")
f_sat = logical_and(0 <= x, x <= 10, 0 <= y, y <= 10, 0 <= z, z <= 10,
sin(x) + cos(y) == z)
result = CheckSatisfiability(f_sat, 0.001)
print(result)
def rambusOscillatorTanh(numStages, g_cc=0.5, numSolutions="all", a=-5.0):
epsilon = 1e-14
start = time.time()
g_fwd = 1.0
lenV = numStages * 2
vs = []
vfwds = []
vccs = []
for i in range(lenV):
vs.append(Variable("v" + str(i)))
vfwds.append(Variable("vfwd" + str(i)))
vccs.append(Variable("vcc" + str(i)))
allConstraints = []
# Store rambus oscillator constraints
for i in range(lenV):
allConstraints.append(vs[i] >= -1)
allConstraints.append(vs[i] <= 1)
fwdInd = (i - 1) % lenV
ccInd = (i + lenV // 2) % lenV
allConstraints.append(vfwds[i] == tanh(a * vs[fwdInd]))
allConstraints.append(vccs[i] == tanh(a * vs[ccInd]))
allConstraints.append(g_fwd * vfwds[i] + (-g_fwd - g_cc) * vs[i] +
g_cc * vccs[i] == 0)
allSolutions = []
while True:
if numSolutions != "all" and len(allSolutions) == numSolutions:
break
# Store constraints pruning search space so that
# old hyperrectangles are not considered
excludingConstraints = []
for solution in allSolutions:
singleExcludingConstraints = []
for i in range(lenV):
singleExcludingConstraints.append(vs[i] < solution[i][0])
singleExcludingConstraints.append(vs[i] > solution[i][1])
excludingConstraints.append(singleExcludingConstraints)
# Add all the rambus oscillator constraints
f_sat = logical_and(*allConstraints)
# Add constraints so that old hyperrectangles are not considered
if len(excludingConstraints) > 0:
for constraints in excludingConstraints:
f_sat = logical_and(f_sat, logical_or(*constraints))
#print ("f_sat")
#print (f_sat)
result = CheckSatisfiability(f_sat, epsilon)
#print (result)
if result is None:
break
hyper = np.zeros((lenV, 2))
for i in range(lenV):
hyper[i, :] = [
result[vs[i]].lb() - 2 * epsilon,
result[vs[i]].ub() + 2 * epsilon
]
#print ("hyper", hyper)
allSolutions.append(hyper)
print("num solutions found", len(allSolutions))
end = time.time()
print("time taken", end - start)
return allSolutions
def schmittTriggerScMosfet(inputVoltage, numSolutions="all"):
epsilon = 1e-14
start = time.time()
lenV = 3
Vdd = 1.0
sn = 3
sp = 2 * sn
vs = []
tIs = []
nIs = []
for i in range(lenV):
vs.append(Variable("v" + str(i)))
nIs.append(Variable("nI" + str(i)))
for i in range(lenV * 2):
tIs.append(Variable("tI" + str(i)))
allConstraints = []
for i in range(lenV):
allConstraints.append(vs[i] >= 0.0)
allConstraints.append(vs[i] <= Vdd)
allConstraints += mvs_id('n', 0.0, inputVoltage, vs[1], tIs[0], sn)
allConstraints += mvs_id('n', vs[1], inputVoltage, vs[0], tIs[1], sn)
allConstraints += mvs_id('n', vs[1], vs[0], Vdd, tIs[2], sn)
allConstraints += mvs_id('p', Vdd, inputVoltage, vs[2], tIs[3], sp)
allConstraints += mvs_id('p', vs[2], inputVoltage, vs[0], tIs[4], sp)
allConstraints += mvs_id('p', vs[2], vs[0], 0.0, tIs[5], sp)
allConstraints.append(nIs[0] == -tIs[4] - tIs[1])
allConstraints.append(nIs[1] == -tIs[0] + tIs[1] + tIs[2])
allConstraints.append(nIs[2] == -tIs[3] + tIs[5] + tIs[4])
for i in range(lenV):
allConstraints.append(nIs[i] == 0.0)
allSolutions = []
while True:
if numSolutions != "all" and len(allSolutions) == numSolutions:
break
# Store constraints pruning search space so that
# old hyperrectangles are not considered
excludingConstraints = []
for solution in allSolutions:
singleExcludingConstraints = []
for i in range(lenV):
singleExcludingConstraints.append(vs[i] < solution[i][0])
singleExcludingConstraints.append(vs[i] > solution[i][1])
excludingConstraints.append(singleExcludingConstraints)
#print ("allConstraints")
#print (allConstraints)
f_sat = logical_and(*allConstraints)
if len(excludingConstraints) > 0:
for constraints in excludingConstraints:
f_sat = logical_and(f_sat, logical_or(*constraints))
#print ("f_sat")
#print (f_sat)
result = CheckSatisfiability(f_sat, epsilon)
#print (result)
if result is None:
break
hyper = np.zeros((lenV, 2))
for i in range(lenV):
hyper[i, :] = [
result[vs[i]].lb() - 2 * epsilon,
result[vs[i]].ub() + 2 * epsilon
]
#print ("hyper", hyper)
allSolutions.append(hyper)
print("num solutions found", len(allSolutions))
end = time.time()
print("time taken", end - start)
return allSolutions
def test_nested_forall():
"""
Test whether we can choose parameters for a system, such that there is a
satisfying solution over an entire range of values.
Basically, choose an origin (ox,oy) and the lengths of two arms (l1 & l2)
so that there is an angle (t1 & t2) for each arm, that allows it to reach
any point within a circle centered at (25,25) with radius 4.
We want to make sure that the lengths and origin the tool chooses allows
for
> there should:
> exists. l1 in (0,20) , l2 (0,20), ox (-20,20), oy (-20,20)
>
> such that:
> for all. px in (20, 30), py in (20,30)
>
> given assumptions:
> sqrt((25 - px)**2 + (25 - py)**2) <= 4
>
> there should:
> exists. t1 in (-pi, pi), t2 in (-pi,pi)
>
> with constraints:
> t2 > t1
>
> that meets the requirements:
> (px == l2*sin(t1) + l2*sin(t2) + ox)
> && (py == l1*cos(t1) + l2*cos(t2) + oy)
"""
# Parameters
l1 = Variable('l1', Variable.Real)
l2 = Variable('l2', Variable.Real)
ox = Variable('ox', Variable.Real)
oy = Variable('oy', Variable.Real)
param_bounds = logical_and(l1 > 0, l1 < 20, l2 > 0, l2 < 20, ox > -20,
ox < 20, oy > -20, oy < 20)
# Independent Variables
px = Variable('px', Variable.Real)
py = Variable('py', Variable.Real)
ivar_bounds = logical_and(px > 20, px < 30, py > 20, py < 30)
ivar_assum = sqrt((25 - px)**2 + (25 - py)**2) < 4
# Dependent Variables
t1 = Variable('t1', Variable.Real)
t2 = Variable('t2', Variable.Real)
dvar_bounds = logical_and(t1 >= -3.14, t1 <= 3.14, t2 >= -3.14, t2 <= 3.14,
t1 >= t2)
req = logical_and(px == l1 * sin(t1) + l2 * sin(t2) + ox,
py == l1 * cos(t1) + l2 * cos(t2) + oy)
def exists(vs, fun):
return logical_not(forall(vs, logical_not(fun)))
fun = logical_and(
param_bounds,
forall([px, py],
logical_imply(logical_and(ivar_bounds, ivar_assum),
exists([t1, t2], logical_and(dvar_bounds, req)))))
result = CheckSatisfiability(fun, 0.01)
print(result)
assert False
def rambusOscillatorLcMosfet(numStages, numSolutions = "all", g_cc = 0.5, Vtp = -0.4, Vtn = 0.4, Vdd = 1.8, Kn = 270*1e-6, Kp = -90*1e-6, Sn = 3.0):
epsilon = 1e-14
start = time.time()
#print ("Vtp", Vtp, "Vtn", Vtn, "Vdd", Vdd, "Kn", Kn, "Kp", Kp, "Sn", Sn)
g_fwd = 1.0
lenV = numStages*2
Sp = 2*Sn
vs = []
ifwdNs = []
ifwdPs = []
iccNs = []
iccPs = []
for i in range(lenV):
vs.append(Variable("v" + str(i)))
ifwdNs.append(Variable("ifwdN" + str(i)))
ifwdPs.append(Variable("ifwdP" + str(i)))
iccNs.append(Variable("iccN" + str(i)))
iccPs.append(Variable("iccP" + str(i)))
allConstraints = []
for i in range(lenV):
allConstraints.append(vs[i] >= 0.0)
allConstraints.append(vs[i] <= Vdd)
allConstraints.append(g_fwd*(-ifwdNs[i]-ifwdPs[i]) + g_cc*(-iccNs[i]-iccPs[i]) == 0)
fwdInd = (i-1)%lenV
ccInd = (i+lenV//2)%lenV
fwdConstraints = nFet(Vtn, Vdd, Kn, Sn, 0.0, vs[fwdInd], vs[i], ifwdNs[i])
fwdConstraints += pFet(Vtp, Vdd, Kp, Sp, Vdd, vs[fwdInd], vs[i], ifwdPs[i])
ccConstraints = nFet(Vtn, Vdd, Kn, Sn, 0.0, vs[ccInd], vs[i], iccNs[i])
ccConstraints += pFet(Vtp, Vdd, Kp, Sp, Vdd, vs[ccInd], vs[i], iccPs[i])
allConstraints += fwdConstraints + ccConstraints
allSolutions = []
while True:
if numSolutions != "all" and len(allSolutions) == numSolutions:
break
# Store constraints pruning search space so that
# old hyperrectangles are not considered
excludingConstraints = []
for solution in allSolutions:
singleExcludingConstraints = []
for i in range(lenV):
singleExcludingConstraints.append(vs[i] < solution[i][0])
singleExcludingConstraints.append(vs[i] > solution[i][1])
excludingConstraints.append(singleExcludingConstraints)
#print ("allConstraints")
#print (allConstraints)
f_sat = logical_and(*allConstraints)
if len(excludingConstraints) > 0:
for constraints in excludingConstraints:
f_sat = logical_and(f_sat, logical_or(*constraints))
#print ("f_sat")
#print (f_sat)
result = CheckSatisfiability(f_sat, epsilon)
#print (result)
if result is None:
break
hyper = np.zeros((lenV,2))
for i in range(lenV):
hyper[i,:] = [result[vs[i]].lb() - 1000*epsilon, result[vs[i]].ub() + 1000*epsilon]
#print ("hyper", hyper)
allSolutions.append(hyper)
print ("num solutions found", len(allSolutions))
end = time.time()
print ("time taken", end - start)
return allSolutions
def inverterLoopLcMosfet(numInverters, numSolutions = "all", Vtp = -0.4, Vtn = 0.4, Vdd = 1.8, Kn = 270*1e-6, Kp = -90*1e-6, Sn = 3.0):
epsilon = 1e-14
start = time.time()
#print ("Vtp", Vtp, "Vtn", Vtn, "Vdd", Vdd, "Kn", Kn, "Kp", Kp, "Sn", Sn)
Sp = 2*Sn
vs = []
iNs = []
iPs = []
for i in range(numInverters):
vs.append(Variable("v" + str(i)))
iNs.append(Variable("iN" + str(i)))
iPs.append(Variable("iP" + str(i)))
allConstraints = []
for i in range(numInverters):
allConstraints.append(vs[i] >= 0.0)
allConstraints.append(vs[i] <= Vdd)
allConstraints.append(-iNs[i]-iPs[i] == 0)
inputInd = i
outputInd = (i+1)%numInverters
allConstraints += nFet(Vtn, Vdd, Kn, Sn, 0.0, vs[inputInd], vs[outputInd], iNs[i])
allConstraints += pFet(Vtp, Vdd, Kp, Sp, Vdd, vs[inputInd], vs[outputInd], iPs[i])
allSolutions = []
while True:
if numSolutions != "all" and len(allSolutions) == numSolutions:
break
# Store constraints pruning search space so that
# old hyperrectangles are not considered
excludingConstraints = []
for solution in allSolutions:
singleExcludingConstraints = []
for i in range(numInverters):
singleExcludingConstraints.append(vs[i] < solution[i][0])
singleExcludingConstraints.append(vs[i] > solution[i][1])
excludingConstraints.append(singleExcludingConstraints)
#print ("allConstraints")
#print (allConstraints)
f_sat = logical_and(*allConstraints)
if len(excludingConstraints) > 0:
for constraints in excludingConstraints:
f_sat = logical_and(f_sat, logical_or(*constraints))
#print ("f_sat")
#print (f_sat)
result = CheckSatisfiability(f_sat, epsilon)
#print (result)
if result is None:
break
hyper = np.zeros((numInverters,2))
for i in range(numInverters):
hyper[i,:] = [result[vs[i]].lb() - 1000*epsilon, result[vs[i]].ub() + 1000*epsilon]
#print ("hyper", hyper)
allSolutions.append(hyper)
print ("num solutions found", len(allSolutions))
end = time.time()
print ("time taken", end - start)
return allSolutions
def schmittTriggerLcMosfet(inputVoltage, Vtp = -0.4, Vtn = 0.4, Vdd = 1.8, Kn = 270*1e-6, Kp = -90*1e-6, Sn = 3.0, numSolutions = "all"):
epsilon = 1e-14
start = time.time()
#print ("Vtp", Vtp, "Vtn", Vtn, "Vdd", Vdd, "Kn", Kn, "Kp", Kp, "Sn", Sn)
Sp = Sn *2.0
lenV = 3
vs = []
tIs = []
nIs = []
for i in range(lenV):
vs.append(Variable("v" + str(i)))
nIs.append(Variable("nI" + str(i)))
for i in range(lenV*2):
tIs.append(Variable("tI" + str(i)))
allConstraints = []
for i in range(lenV):
allConstraints.append(vs[i] >= 0.0)
allConstraints.append(vs[i] <= 1.8)
allConstraints += nFetLeak(Vtn, Vdd, Kn, Sn, 0.0, inputVoltage, vs[1], tIs[0])
allConstraints += nFetLeak(Vtn, Vdd, Kn, Sn, vs[1], inputVoltage, vs[0], tIs[1])
allConstraints += nFetLeak(Vtn, Vdd, Kn, Sn, vs[1], vs[0], Vdd, tIs[2])
allConstraints += pFetLeak(Vtp, Vdd, Kp, Sp, Vdd, inputVoltage, vs[2], tIs[3])
allConstraints += pFetLeak(Vtp, Vdd, Kp, Sp, vs[2], inputVoltage, vs[0], tIs[4])
allConstraints += pFetLeak(Vtp, Vdd, Kp, Sp, vs[2], vs[0], 0.0, tIs[5])
allConstraints.append(nIs[0] == -tIs[4] - tIs[1])
allConstraints.append(nIs[1] == -tIs[0] + tIs[1] + tIs[2])
allConstraints.append(nIs[2] == -tIs[3] + tIs[5] + tIs[4])
for i in range(lenV):
allConstraints.append(nIs[i] == 0.0)
allSolutions = []
while True:
if numSolutions != "all" and len(allSolutions) == numSolutions:
break
# Store constraints pruning search space so that
# old hyperrectangles are not considered
excludingConstraints = []
for solution in allSolutions:
singleExcludingConstraints = []
for i in range(lenV):
singleExcludingConstraints.append(vs[i] < solution[i][0])
singleExcludingConstraints.append(vs[i] > solution[i][1])
excludingConstraints.append(singleExcludingConstraints)
#print ("allConstraints")
#print (allConstraints)
#print ("numConstraints", len(allConstraints))
f_sat = logical_and(*allConstraints)
if len(excludingConstraints) > 0:
for constraints in excludingConstraints:
f_sat = logical_and(f_sat, logical_or(*constraints))
#print ("f_sat")
#print (f_sat)
result = CheckSatisfiability(f_sat, epsilon)
#print (result)
if result is None:
break
hyper = np.zeros((lenV,2))
for i in range(lenV):
hyper[i,:] = [result[vs[i]].lb() - 1000*epsilon, result[vs[i]].ub() + 1000*epsilon]
#print ("hyper", hyper)
allSolutions.append(hyper)
print ("num solutions found", len(allSolutions))
end = time.time()
print ("time taken", end - start)
return allSolutions
