OpenMDAO / dymos / 16605512492

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Hull problem Rework (#1201)

* Changed Hull problem to solve a more simpler version of the problem

* Updated docs to match the test case

* reworked hull problem to use a parameter

* updated docs

* Changed latest workflow to numpy 2.2

* fixed scipy to a 1.15

* putopsparse to 2.13.1

* petsc to 3.23

* unpinned all version except PetSc

11 of 11 new or added lines in 2 files covered. (100.0%)

83 existing lines in 6 files now uncovered.

33776 of 36106 relevant lines covered (93.55%)

4.36 hits per line

Source File
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73.08
/dymos/examples/hyper_sensitive/hyper_sensitive_ode.py
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import numpy as np
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import openmdao.api as om
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class HyperSensitiveODE(om.ExplicitComponent):




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    def initialize(self):




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        self.options.declare('num_nodes', types=int)




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    def setup(self):




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        nn = self.options['num_nodes']




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        # inputs










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        self.add_input('x', val=np.zeros(nn), desc='state')




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        self.add_input('xL', val=np.zeros(nn), desc='cost_state')




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        self.add_input('u', val=np.zeros(nn), desc='control')




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        self.add_output('x_dot', val=np.zeros(nn), desc='state rate', units='1/s')




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        self.add_output('L', val=np.zeros(nn), desc='Lagrangian', units='1/s')




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        # Setup partials










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        self.declare_partials(of='x_dot', wrt='x', rows=np.arange(nn), cols=np.arange(nn), val=-1)




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        self.declare_partials(of='x_dot', wrt='u', rows=np.arange(nn), cols=np.arange(nn), val=1)




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        self.declare_partials(of='L', wrt='x', rows=np.arange(nn), cols=np.arange(nn))




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        self.declare_partials(of='L', wrt='u', rows=np.arange(nn), cols=np.arange(nn))




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    def compute(self, inputs, outputs):




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        x = inputs['x']




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        u = inputs['u']




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        outputs['x_dot'] = -x + u




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        outputs['L'] = (x ** 2 + u ** 2) / 2




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    def compute_partials(self, inputs, jacobian):




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        x = inputs['x']




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        u = inputs['u']




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        jacobian['L', 'x'] = x




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        jacobian['L', 'u'] = u




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