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#!/usr/bin/env python
#
# Author: Patrick Hung (patrickh @caltech)
# Author: Mike McKerns (mmckerns @caltech and @uqfoundation)
# Copyright (c) 1997-2016 California Institute of Technology.
# Copyright (c) 2016-2024 The Uncertainty Quantification Foundation.
# License: 3-clause BSD. The full license text is available at:
# - https://github.com/uqfoundation/mystic/blob/master/LICENSE
"""
forward_model example
"""
from mystic.forward_model import *
if __name__=='__main__':
from mystic.models import mogi; ForwardMogiFactory = mogi.ForwardFactory
import random
from numpy import *
xstations = array([random.uniform(-500,500) for i in range(300)])+1250.
ystations = 0*xstations - 200.
stations = array((xstations, ystations))
A = CostFactory()
A.addModel(ForwardMogiFactory, 4, 'mogi1', outputFilter=PickComponent(2))
A.addModel(ForwardMogiFactory, 4, 'mogi2', outputFilter=PickComponent(2))
fe = A.getForwardEvaluator(stations)
p = [random.random() for i in range(8)]
c = fe(p)
print(len(c))
print(sum(c).shape)
print(A)
# End of file
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