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src/a/s/Assimulo-2.5.1/assimulo/examples/ida_basic_backward.py   Assimulo(Download)
import nose
from assimulo.solvers import IDA
from assimulo.problem import Implicit_Problem
 
def run_example(with_plots=True):
 
    #Define an Assimulo problem
    imp_mod = Implicit_Problem(f,t0=5, y0=0.02695, yd0=-0.02695,
              name = 'IDA Example: $\dot y + y = 0$ (reverse time)')
 

src/a/s/Assimulo-2.5.1/assimulo/examples/ida_with_initial_sensitivity.py   Assimulo(Download)
import nose
from assimulo.solvers import IDA
from assimulo.problem import Implicit_Problem
 
def run_example(with_plots=True):
 
    #Create an Assimulo implicit problem
    imp_mod = Implicit_Problem(f,y0,yd0,p0=p0,name='Example: Computing Sensitivities')
 
    #Sets the options to the problem

src/a/s/Assimulo-2.5.1/assimulo/examples/ida_with_parameters.py   Assimulo(Download)
import nose
from assimulo.solvers import IDA
from assimulo.problem import Implicit_Problem
 
def run_example(with_plots=True):
 
    #Create an Assimulo implicit problem
    imp_mod = Implicit_Problem(f, y0, yd0,p0=p0)
 
    #Create an Assimulo implicit solver (IDA)

src/a/s/Assimulo-2.5.1/assimulo/examples/ida_with_jac_spgmr.py   Assimulo(Download)
import nose
from assimulo.solvers import IDA
from assimulo.problem import Implicit_Problem
 
 
 
    #Defines an Assimulo implicit problem
    imp_mod = Implicit_Problem(res,y0,yd0,name = 'Example using the Jacobian Vector product')
 
    imp_mod.jacv = jacv #Sets the jacobian

src/a/s/Assimulo-2.5.1/assimulo/examples/ida_with_jac.py   Assimulo(Download)
import pylab as P
from assimulo.solvers import IDA
from assimulo.problem import Implicit_Problem
import nose
 
 
    #Create an Assimulo implicit problem
    imp_mod = Implicit_Problem(f,y0,yd0,name = 'Example using an analytic Jacobian')
 
    #Sets the options to the problem

src/a/s/Assimulo-2.5.1/assimulo/examples/glimda_vanderpol.py   Assimulo(Download)
import nose
from assimulo.solvers import GLIMDA,IDA
from assimulo.problem import Implicit_Problem
 
def run_example(with_plots=True):
 
    #Define an Assimulo problem
    imp_mod = Implicit_Problem(f,y0,yd0,
              name = 'Glimbda Example: Van der Pol (implicit)')
 

src/a/s/Assimulo-2.5.1/assimulo/examples/radau5dae_vanderpol.py   Assimulo(Download)
import nose
from assimulo.solvers import Radau5DAE
from assimulo.problem import Implicit_Problem
 
def run_example(with_plots=True):
 
    #Define an Assimulo problem
    imp_mod = Implicit_Problem(f,y0,yd0)
    imp_mod.name = 'Van der Pol (implicit)'
 

src/a/s/Assimulo-2.5.1/assimulo/examples/radau5dae_time_events.py   Assimulo(Download)
import nose
from assimulo.solvers import Radau5DAE
from assimulo.problem import Implicit_Problem
 
 
class VanDerPolProblem(Implicit_Problem):

src/a/s/Assimulo-2.5.1/assimulo/examples/ida_with_disc.py   Assimulo(Download)
import nose
from assimulo.solvers import IDA
from assimulo.problem import Implicit_Problem
 
"""
class Extended_Problem(Implicit_Problem):
 
    #Sets the initial conditons directly into the problem
    y0 = [0.0, -1.0, 0.0]
    yd0 = [-1.0, 0.0, 0.0]

src/a/s/Assimulo-2.5.1/assimulo/tests/solvers/test_sundials.py   Assimulo(Download)
from assimulo.solvers.sundials import *
from assimulo.problem import Explicit_Problem
from assimulo.problem import Implicit_Problem
from assimulo.exception import *
 
        yd0 = [1.0]
 
        self.problem = Implicit_Problem(f,y0,yd0)
        self.simulator = IDA(self.problem)
 
    @testattr(stddist = True)
    def test_time_limit(self):
        f = lambda t,y,yd: yd-y
 
        exp_mod = Implicit_Problem(f,1.0,1.0)
        f = lambda t,y,yd: y**0.25-yd
 
        prob = Implicit_Problem(f,[1.0],[1.0])
 
        sim = IDA(prob)
            assert solver.t == t
 
        prob = Implicit_Problem(f, [1.0],[1.0])
        prob.handle_result = handle_result
 

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