16602741704

Committed 29 Jul 2025 05:09PM UTC coverage: 93.339% (-0.3%) from 93.677%

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github

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Commit Message

Merge ef78cf9ed into 4da5754d6

Coverage Stats

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

158 existing lines in 8 files now uncovered.

33701 of 36106 relevant lines covered (93.34%)

4.36 hits per line

Source File
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73.08

/dymos/examples/hyper_sensitive/hyper_sensitive_ode.py

UNCOV 1	import numpy as np	×
UNCOV 2	import openmdao.api as om	×
3
4
UNCOV 5	class HyperSensitiveODE(om.ExplicitComponent):	×
6
UNCOV 7	def initialize(self):	×
8	self.options.declare('num_nodes', types=int)	4✔
9
UNCOV 10	def setup(self):	×
11	nn = self.options['num_nodes']	4✔
12
13	# inputs
14	self.add_input('x', val=np.zeros(nn), desc='state')	4✔
15	self.add_input('xL', val=np.zeros(nn), desc='cost_state')	4✔
16
17	self.add_input('u', val=np.zeros(nn), desc='control')	4✔
18
19	self.add_output('x_dot', val=np.zeros(nn), desc='state rate', units='1/s')	4✔
20	self.add_output('L', val=np.zeros(nn), desc='Lagrangian', units='1/s')	4✔
21
22	# Setup partials
23	self.declare_partials(of='x_dot', wrt='x', rows=np.arange(nn), cols=np.arange(nn), val=-1)	4✔
24	self.declare_partials(of='x_dot', wrt='u', rows=np.arange(nn), cols=np.arange(nn), val=1)	4✔
25
26	self.declare_partials(of='L', wrt='x', rows=np.arange(nn), cols=np.arange(nn))	4✔
27	self.declare_partials(of='L', wrt='u', rows=np.arange(nn), cols=np.arange(nn))	4✔
28
UNCOV 29	def compute(self, inputs, outputs):	×
30	x = inputs['x']	4✔
31	u = inputs['u']	4✔
32
33	outputs['x_dot'] = -x + u	4✔
34	outputs['L'] = (x 2 + u 2) / 2	4✔
35
UNCOV 36	def compute_partials(self, inputs, jacobian):	×
37	x = inputs['x']	4✔
38	u = inputs['u']	4✔
39
40	jacobian['L', 'x'] = x	4✔
41	jacobian['L', 'u'] = u	4✔