def GetBounds(self):
"""Get a bounds.Bounds object."""
lower_bounds = {1: 1}
upper_bounds = {1: 1} # the default for H2O is 1
bound_str = self.field_map.get("BOUND", "")
for line in bound_str.strip().split('\t'):
if not line:
continue
tokens = line.split(None)
cid = int(tokens[0][1:])
try:
b_lower = float(tokens[1])
except ValueError:
b_lower = None
if len(tokens) == 2:
b_upper = b_lower
elif len(tokens) == 3:
try:
b_upper = float(tokens[2])
except ValueError:
b_upper = None
else:
raise ValueError(
"Parsing error in BOUND definition for %s: %s" %
(self.name, line))
lower_bounds[cid] = b_lower
upper_bounds[cid] = b_upper
default_lb, default_ub = self.c_range
return bounds.Bounds(lower_bounds,
upper_bounds,
default_lb=default_lb,
default_ub=default_ub)
def testSpecifics(self):
# NOTE(flamholz): values are > 0 on purpose. Logs won't work o.w.
default_lb = 10
default_ub = 100
lb_dict = {'a': 0.0002}
ub_dict = {'a': 30, 'hobos': 11}
b = bounds.Bounds(lower_bounds=lb_dict,
upper_bounds=ub_dict,
default_lb=default_lb,
default_ub=default_ub)
expected_lb, expected_ub = [], []
keys = ('a', 'askdjn', 'hobos', None, 1, 0.232)
for t in keys:
lb, ub = default_lb, default_ub
if t in lb_dict:
lb = lb_dict[t]
if t in ub_dict:
ub = ub_dict[t]
expected_ub.append(ub)
expected_lb.append(lb)
self.assertEquals(lb, b.GetLowerBound(t))
self.assertEquals(ub, b.GetUpperBound(t))
expected_lb = np.matrix(expected_lb)
expected_ub = np.matrix(expected_ub)
lb, ub = b.GetBounds(keys)
self.assertTrue((lb == expected_lb).all())
self.assertTrue((ub == expected_ub).all())
lb, ub = b.GetLnBounds(keys)
expected_lb = np.log(expected_lb)
expected_ub = np.log(expected_ub)
self.assertTrue((lb == expected_lb).all())
self.assertTrue((ub == expected_ub).all())
def testDefaults(self):
default_lb = 10
default_ub = 100
b = bounds.Bounds(default_lb=default_lb, default_ub=default_ub)
keys = ('a', 'askdjn', 'hobos', None, 1, 0.232)
for t in keys:
self.assertEquals(default_lb, b.GetLowerBound(t))
self.assertEquals(default_ub, b.GetUpperBound(t))
lb, ub = b.GetBounds(keys)
n = len(keys)
expected_lb = np.matrix(np.ones((n, 1))) * default_lb
expected_ub = np.matrix(np.ones((n, 1))) * default_ub
self.assertTrue((lb == expected_lb).all())
self.assertTrue((ub == expected_ub).all())
lb, ub = b.GetLnBounds(keys)
expected_lb = np.matrix(np.ones((n, 1))) * np.log(default_lb)
expected_ub = np.matrix(np.ones((n, 1))) * np.log(default_ub)
self.assertTrue((lb == expected_lb).all())
self.assertTrue((ub == expected_ub).all())
def DefaultConcentrationBounds(self):
"""Default Bounds objects."""
return bounds.Bounds(default_lb=self.DEFAULT_CONC_LB,
default_ub=self.DEFAULT_CONC_UB)
def MyBounds(self):
my_lb, my_ub = 1e-8, 15e-3
return bounds.Bounds(default_lb=my_lb, default_ub=my_ub)
def WideBounds(self):
my_lb, my_ub = 1e-8, 20e-3
return bounds.Bounds(default_lb=my_lb, default_ub=my_ub)
def NormalBounds(self):
my_lb, my_ub = 1e-6, 1e-2
return bounds.Bounds(default_lb=my_lb, default_ub=my_ub)
