def setParameterVector(self, x, param_list):
# type: (array, List) -> None
expect(
len(x) == len(param_list),
'Wrong length for parameter vector - expected {} but got {}'.
format(len(param_list), len(x)))
for i, v in enumerate(x):
self.r[param_list[i]] = v
def applyParamVec(r, p):
# type: (RoadRunner, array) -> None
'''
Applies a parameter vector p to a RoadRunner instance r.
'''
expect(len(p) != len(param_list), 'Parameter vector size mismatch')
for k, v in enumerate(p):
r[param_list[k]] = v
def __init__(self, lb, ub):
# type: (Evaluator, array, array) -> None
'''
Inits the problem with an objective evaluator
(implementing the method evaluate), the parameter
vector lower bound (a numpy array) and upper bound.
Both bounds must have the same dimension.
'''
from sabaody.utils import check_vector, expect
check_vector(lb)
check_vector(ub)
expect(len(lb) == len(ub), 'Bounds mismatch')
self.lb = lb
self.ub = ub
from b2problem import B2Problem
self.evaluator = B2Problem('b2.xml')
def __init__(self, lb, ub, sbml_file):
# type: (Evaluator, array, array) -> None
'''
Inits the problem with an objective evaluator
(implementing the method evaluate), the parameter
vector lower bound (a numpy array) and upper bound.
Both bounds must have the same dimension.
'''
from sabaody.utils import check_vector, expect
check_vector(lb)
check_vector(ub)
expect(len(lb) == len(ub), 'Bounds mismatch')
self.lb = lb
self.ub = ub
# delay loading until we're on the worker node
self.evaluator = None
self.sbml_file = sbml_file
def _getParametersDict(self, param_list, use_log=True):
# type: (List, bool) -> Dict
'''
Returns the current values of the parameters as a dictionary.
'''
expect(
len(x) == len(param_list),
'Wrong length for parameter vector - expected {} but got {}'.
format(len(param_list), len(x)))
result = {}
if use_log:
from math import log
for p in param_list:
result[p] = log(self.r[p], 10.)
else:
for p in param_list:
result[p] = self.r[p]
def _setParameterVector(self,
x,
param_list,
rr_instance,
exponential=True):
# type: (array, List) -> None
expect(
len(x) == len(param_list),
'Wrong length for parameter vector - expected {} but got {}'.
format(len(param_list), len(x)))
if exponential:
from math import pow
for i, v in enumerate(x):
rr_instance[param_list[i]] = pow(10., v)
else:
for i, v in enumerate(x):
rr_instance[param_list[i]] = v