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#
# This file is part of CasADi.
#
# CasADi -- A symbolic framework for dynamic optimization.
# Copyright (C) 2010-2023 Joel Andersson, Joris Gillis, Moritz Diehl,
# KU Leuven. All rights reserved.
# Copyright (C) 2011-2014 Greg Horn
#
# CasADi is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License as published by the Free Software Foundation; either
# version 3 of the License, or (at your option) any later version.
#
# CasADi is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
# Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public
# License along with CasADi; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
#
from casadi import *
# CasADi provides a mechanism to add assertions in an MX expression graph
# This can be useful to debug yor code, e.g. debugging why the end-result of a computation yields NaN
# Consider this example:
x = MX.sym("x")
y = sin(x)
z = sqrt(y)
f = Function("f", [x], [z])
z0 = f(5)
print(z0)
# For some mysterious reason we get NaN here
# Next, we add an assertion:
y = y.attachAssert(y>0, "bummer") # Add assertion here
z = sqrt(y)
f = Function("f", [x],[z])
try:
z0 = f(5)
except Exception as e:
print("An exception was raised here:")
print(e)
# You can combine this with Callback to do powerful assertions
class Dummy(Callback):
def __init__(self, name, opts={}):
Callback.__init__(self)
self.construct(name, opts)
def get_n_in(self): return 1
def get_n_out(self): return 1
def eval(self, arg):
import numpy
x = arg[0]
m = max(numpy.real(numpy.linalg.eig(blockcat([[x,-1],[-1,2]]))[0]))
print("m=",m)
return [int(m>2)]
foo = Dummy("foo")
y = sin(x)
y = y.attachAssert(foo(y), "you are in trouble") # Add assertion here
z = sqrt(y)
f = Function("f", [x],[z])
z0 = f(5)
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