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Changed 'latest' job in test and docs workflows to use Python 3.12 (#…
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…1122)

* Changed 'latest' job in test workflow to use Python 3.12

* Changed 'latest' job in docs workflow to use Python 3.12

* om_version check, doc build with latest

* update cannonball examples to use OpenMDAO InterpND

* adjust tolerance on cannonball load_case test

* update phase to use OM InterpND; add python 3.13 job to test workflow

* revert phase change

* fix for failing balanced field length tests.

* more generalization of the balanced field example

* PEP, require_pyoptsparse

* require_pyoptsparse

---------

Co-authored-by: swryan <[email protected]>
Co-authored-by: Rob Falck <[email protected]>
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3 people authored Nov 1, 2024
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6 changes: 3 additions & 3 deletions .github/workflows/dymos_docs_workflow.yml
Original file line number Diff line number Diff line change
Expand Up @@ -31,14 +31,15 @@ jobs:
SCIPY: '1.13'
PETSc: '3.19'
PYOPTSPARSE: 'v2.11.0'
OPENMDAO: 'dev'
OPENMDAO: 'latest'
OPTIONAL: '[docs]'
JAX: '0.4.28'
PUBLISH_DOCS: 1

# make sure the latest versions of things don't break the docs
# sticking with Python 3.12 for now, 3.13 requires NumPy 2.1 which does not work yet with PETSc/pyoptsparse
- NAME: latest
PY: 3
PY: '3.12'
NUMPY: 1
SCIPY: 1
PETSc: 3
Expand Down Expand Up @@ -268,7 +269,6 @@ jobs:
cd $HOME/work/dymos/dymos
ghp-import -n -p -f docs/dymos_book/_build/html
- name: Publish docs to openmdao.org
if: |
github.event_name == 'push' && github.ref == 'refs/heads/master' &&
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26 changes: 23 additions & 3 deletions .github/workflows/dymos_tests_workflow.yml
Original file line number Diff line number Diff line change
Expand Up @@ -60,6 +60,12 @@ on:
required: false
default: false

python313:
type: boolean
description: "Include 'python313' in test matrix"
required: false
default: false

oldest:
type: boolean
description: "Include 'oldest' in test matrix"
Expand Down Expand Up @@ -134,8 +140,9 @@ jobs:
EXCLUDE: ${{ github.event_name == 'workflow_dispatch' && ! inputs.no_mpi }}

# try latest versions
# sticking with Python 3.12 here, 3.13 requires NumPy 2.1 which does not work yet with pyoptsparse
- NAME: latest
PY: 3
PY: '3.12'
NUMPY: 1
SCIPY: 1
PETSc: 3.21.0
Expand All @@ -146,6 +153,19 @@ jobs:
JAX: 'latest'
EXCLUDE: ${{ github.event_name == 'workflow_dispatch' && ! inputs.latest }}

# Python 3.13 (requires NumPy 2.1 which does not work yet with pyoptsparse)
- NAME: python313
PY: '3.13'
NUMPY: 2
SCIPY: 1
PETSc: 3
# PYOPTSPARSE: 'latest'
SNOPT: 7.7
OPENMDAO: 'dev'
OPTIONAL: '[test]'
JAX: 'latest'
EXCLUDE: ${{ github.event_name == 'workflow_dispatch' && ! inputs.python313 }}

# oldest supported versions
- NAME: oldest
PY: 3.9
Expand Down Expand Up @@ -237,9 +257,9 @@ jobs:
if [[ "${{ matrix.OPENMPI }}" && "${{ matrix.MPI4PY }}" ]]; then
conda install openmpi=${{ matrix.OPENMPI }} mpi4py=${{ matrix.MPI4PY }} petsc4py=${{ matrix.PETSc }} -q -y
elif [[ "${{ matrix.MPI4PY }}" ]]; then
conda install mpi4py=${{ matrix.MPI4PY }} petsc4py=${{ matrix.PETSc }} -q -y
conda install mpich mpi4py=${{ matrix.MPI4PY }} petsc4py=${{ matrix.PETSc }} -q -y
else
conda install mpi4py petsc4py=${{ matrix.PETSc }} -q -y
conda install mpich mpi4py petsc4py=${{ matrix.PETSc }} -q -y
fi
export OMPI_MCA_rmaps_base_oversubscribe=1
export OMPI_MCA_btl=^openib
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Original file line number Diff line number Diff line change
Expand Up @@ -168,6 +168,7 @@
"source": [
"import openmdao.api as om\n",
"import openmdao.func_api as omf\n",
"from dymos.utils.misc import om_version",
"\n",
"def wrap_ode_func(num_nodes, flight_mode, grad_method='jax', jax_jit=True):\n",
" \"\"\"\n",
Expand Down Expand Up @@ -223,7 +224,10 @@
" meta.declare_coloring('*', method=grad_method)\n",
" meta.declare_partials(of='*', wrt='*', method=grad_method)\n",
" \n",
" return om.ExplicitFuncComp(meta, use_jax=grad_method == 'jax', use_jit=jax_jit)\n",
" if om_version()[0] > (3, 35, 0):\n",
" return om.ExplicitFuncComp(meta, derivs_method=grad_method, use_jit=jax_jit)\n",
" else:\n",
" return om.ExplicitFuncComp(meta, use_jax=grad_method == 'jax', use_jit=jax_jit)\n",
" \n",
" "
]
Expand Down
Binary file modified docs/dymos_book/examples/brachistochrone/brachistochrone_fbd.png
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Original file line number Diff line number Diff line change
Expand Up @@ -100,9 +100,9 @@
"outputs": [],
"source": [
"import numpy as np\n",
"from scipy.interpolate import interp1d\n",
"\n",
"import openmdao.api as om\n",
"from openmdao.components.interp_util.interp import InterpND\n",
"\n",
"import dymos as dm\n",
"from dymos.models.atmosphere.atmos_1976 import USatm1976Data\n",
Expand Down Expand Up @@ -158,7 +158,7 @@
"## The cannonball ODE component\n",
"\n",
"This component computes the state rates and the kinetic energy of the cannonball.\n",
"By calling the `declare_coloring` method wrt all inputs and using method `'cs'`, we're telling OpenMDAO to automatically determine the sparsity pattern of the outputs with respect to the inputs, **and** to automatically compute those outputs using complex-step approximation."
"By calling the `declare_coloring` method wrt all inputs and using method `'fd'`, we're telling OpenMDAO to automatically determine the sparsity pattern of the outputs with respect to the inputs, **and** to automatically compute those outputs using a finite-difference approximation."
]
},
{
Expand Down Expand Up @@ -198,17 +198,17 @@
" self.add_output('r_dot', shape=nn, units='m/s', tags=['dymos.state_rate_source:r'])\n",
" self.add_output('ke', shape=nn, units='J')\n",
"\n",
" # Ask OpenMDAO to compute the partial derivatives using complex-step\n",
" # Ask OpenMDAO to compute the partial derivatives using finite-difference\n",
" # with a partial coloring algorithm for improved performance, and use\n",
" # a graph coloring algorithm to automatically detect the sparsity pattern.\n",
" self.declare_coloring(wrt='*', method='cs')\n",
" self.declare_coloring(wrt='*', method='fd')\n",
"\n",
" alt_data = USatm1976Data.alt * om.unit_conversion('ft', 'm')[0]\n",
" rho_data = USatm1976Data.rho * om.unit_conversion('slug/ft**3', 'kg/m**3')[0]\n",
" self.rho_interp = interp1d(np.array(alt_data, dtype=complex),\n",
" np.array(rho_data, dtype=complex),\n",
" kind='linear')\n",
"\n",
" self.rho_interp = InterpND(points=np.array(alt_data),\n",
" values=np.array(rho_data),\n",
" method='slinear')\n",
" \n",
" def compute(self, inputs, outputs):\n",
"\n",
" gam = inputs['gam']\n",
Expand All @@ -220,11 +220,7 @@
"\n",
" GRAVITY = 9.80665 # m/s**2\n",
"\n",
" # handle complex-step gracefully from the interpolant\n",
" if np.iscomplexobj(h):\n",
" rho = self.rho_interp(inputs['h'])\n",
" else:\n",
" rho = self.rho_interp(inputs['h']).real\n",
" rho = self.rho_interp.interpolate(h)\n",
"\n",
" q = 0.5*rho*inputs['v']**2\n",
" qS = q * S\n",
Expand Down Expand Up @@ -457,7 +453,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.0"
"version": "3.12.6"
}
},
"nbformat": 4,
Expand Down
189 changes: 189 additions & 0 deletions dymos/examples/balanced_field/balanced_field_length.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,189 @@
import openmdao.api as om
import dymos as dm


def make_balanced_field_length_problem(ode_class, tx):
"""
Create a balanced field length problem and optionally set default values into it.
Parameters
----------
ode_class : System class
The Dymos ODE System class.
tx_class : Transcription
Transcription to use.
Returns
-------
_type_
_description_
"""
p = om.Problem()

p.driver = om.pyOptSparseDriver()
p.driver.declare_coloring()

# Use IPOPT if available, with fallback to SLSQP
p.driver.options['optimizer'] = 'IPOPT'
p.driver.options['print_results'] = True

p.driver.opt_settings['print_level'] = 0
p.driver.opt_settings['mu_strategy'] = 'adaptive'

p.driver.opt_settings['bound_mult_init_method'] = 'mu-based'
p.driver.opt_settings['mu_init'] = 0.01
p.driver.opt_settings['nlp_scaling_method'] = 'gradient-based'

# First Phase: Brake release to V1 - both engines operable
br_to_v1 = dm.Phase(ode_class=ode_class, transcription=tx,
ode_init_kwargs={'mode': 'runway'})
br_to_v1.set_time_options(fix_initial=True, duration_bounds=(1, 1000), duration_ref=10.0)
br_to_v1.add_state('r', fix_initial=True, lower=0, ref=1000.0, defect_ref=1000.0)
br_to_v1.add_state('v', fix_initial=True, lower=0, ref=100.0, defect_ref=100.0)
br_to_v1.add_parameter('alpha', val=0.0, opt=False, units='deg')
br_to_v1.add_timeseries_output('*')

# Second Phase: Rejected takeoff at V1 - no engines operable
rto = dm.Phase(ode_class=ode_class, transcription=tx,
ode_init_kwargs={'mode': 'runway'})
rto.set_time_options(fix_initial=False, duration_bounds=(1, 1000), duration_ref=1.0)
rto.add_state('r', fix_initial=False, lower=0, ref=1000.0, defect_ref=1000.0)
rto.add_state('v', fix_initial=False, lower=0, ref=100.0, defect_ref=100.0)
rto.add_parameter('alpha', val=0.0, opt=False, units='deg')
rto.add_timeseries_output('*')

# Third Phase: V1 to Vr - single engine operable
v1_to_vr = dm.Phase(ode_class=ode_class, transcription=tx,
ode_init_kwargs={'mode': 'runway'})
v1_to_vr.set_time_options(fix_initial=False, duration_bounds=(1, 1000), duration_ref=1.0)
v1_to_vr.add_state('r', fix_initial=False, lower=0, ref=1000.0, defect_ref=1000.0)
v1_to_vr.add_state('v', fix_initial=False, lower=0, ref=100.0, defect_ref=100.0)
v1_to_vr.add_parameter('alpha', val=0.0, opt=False, units='deg')
v1_to_vr.add_timeseries_output('*')

# Fourth Phase: Rotate - single engine operable
rotate = dm.Phase(ode_class=ode_class, transcription=tx,
ode_init_kwargs={'mode': 'runway'})
rotate.set_time_options(fix_initial=False, duration_bounds=(1.0, 5), duration_ref=1.0)
rotate.add_state('r', fix_initial=False, lower=0, ref=1000.0, defect_ref=1000.0)
rotate.add_state('v', fix_initial=False, lower=0, ref=100.0, defect_ref=100.0)
rotate.add_control('alpha', order=1, opt=True, units='deg', lower=0, upper=10, ref=10,
val=[0, 10], control_type='polynomial')
rotate.add_timeseries_output('*')

# Fifth Phase: Climb to target speed and altitude at end of runway.
climb = dm.Phase(ode_class=ode_class, transcription=tx,
ode_init_kwargs={'mode': 'climb'})
climb.set_time_options(fix_initial=False, duration_bounds=(1, 100), duration_ref=1.0)
climb.add_state('r', fix_initial=False, lower=0, ref=1000.0, defect_ref=1000.0)
climb.add_state('h', fix_initial=True, lower=0, ref=1.0, defect_ref=1.0)
climb.add_state('v', fix_initial=False, lower=0, ref=100.0, defect_ref=100.0)
climb.add_state('gam', fix_initial=True, lower=0, ref=0.05, defect_ref=0.05)
climb.add_control('alpha', opt=True, units='deg', lower=-10, upper=15, ref=10)
climb.add_timeseries_output('*')

# Instantiate the trajectory and add phases
traj = dm.Trajectory()
p.model.add_subsystem('traj', traj)
traj.add_phase('br_to_v1', br_to_v1)
traj.add_phase('rto', rto)
traj.add_phase('v1_to_vr', v1_to_vr)
traj.add_phase('rotate', rotate)
traj.add_phase('climb', climb)

all_phases = ['br_to_v1', 'v1_to_vr', 'rto', 'rotate', 'climb']
groundroll_phases = ['br_to_v1', 'v1_to_vr', 'rto', 'rotate']

# Add parameters common to multiple phases to the trajectory
traj.add_parameter('m', val=174200., opt=False, units='lbm',
desc='aircraft mass',
targets={phase: ['m'] for phase in all_phases})

# Handle parameters which change from phase to phase.
traj.add_parameter('T_nominal', val=27000 * 2, opt=False, units='lbf', static_target=True,
desc='nominal aircraft thrust',
targets={'br_to_v1': ['T']})

traj.add_parameter('T_engine_out', val=27000, opt=False, units='lbf', static_target=True,
desc='thrust under a single engine',
targets={'v1_to_vr': ['T'], 'rotate': ['T'], 'climb': ['T']})

traj.add_parameter('T_shutdown', val=0.0, opt=False, units='lbf', static_target=True,
desc='thrust when engines are shut down for rejected takeoff',
targets={'rto': ['T']})

traj.add_parameter('mu_r_nominal', val=0.03, opt=False, units=None, static_target=True,
desc='nominal runway friction coefficient',
targets={'br_to_v1': ['mu_r'], 'v1_to_vr': ['mu_r'], 'rotate': ['mu_r']})

traj.add_parameter('mu_r_braking', val=0.3, opt=False, units=None, static_target=True,
desc='runway friction coefficient under braking',
targets={'rto': ['mu_r']})

traj.add_parameter('h_runway', val=0., opt=False, units='ft',
desc='runway altitude',
targets={phase: ['h'] for phase in groundroll_phases})

# Here we're omitting some constants that are common throughout all phases for the sake of brevity.
# Their correct defaults are specified in add_input calls to `wrap_ode_func`.

# Standard "end of first phase to beginning of second phase" linkages
# Alpha changes from being a parameter in v1_to_vr to a polynomial control
# in rotate, to a dynamic control in `climb`.
traj.link_phases(['br_to_v1', 'v1_to_vr'], vars=['time', 'r', 'v'])
traj.link_phases(['v1_to_vr', 'rotate'], vars=['time', 'r', 'v', 'alpha'])
traj.link_phases(['rotate', 'climb'], vars=['time', 'r', 'v', 'alpha'])
traj.link_phases(['br_to_v1', 'rto'], vars=['time', 'r', 'v'])

# Less common "final value of r must match at ends of two phases".
traj.add_linkage_constraint(phase_a='rto', var_a='r', loc_a='final',
phase_b='climb', var_b='r', loc_b='final',
ref=1000)

# Define the constraints and objective for the optimal control problem
v1_to_vr.add_boundary_constraint('v_over_v_stall', loc='final', lower=1.2, ref=100)

rto.add_boundary_constraint('v', loc='final', equals=0., ref=100, linear=True)

rotate.add_boundary_constraint('F_r', loc='final', equals=0, ref=100000)

climb.add_boundary_constraint('h', loc='final', equals=35, ref=35, units='ft', linear=True)
climb.add_boundary_constraint('gam', loc='final', equals=5, ref=5, units='deg', linear=True)
climb.add_path_constraint('gam', lower=0, upper=5, ref=5, units='deg')
climb.add_boundary_constraint('v_over_v_stall', loc='final', lower=1.25, ref=1.25)

rto.add_objective('r', loc='final', ref=1000.0)

#
# Setup the problem and set the initial guess
#
p.setup(check=True)

br_to_v1.set_time_val(initial=0.0, duration=35.0)
br_to_v1.set_state_val('r', [0, 2500.0])
br_to_v1.set_state_val('v', [0.0001, 100.0])
br_to_v1.set_parameter_val('alpha', 0.0, units='deg')

v1_to_vr.set_time_val(initial=35.0, duration=35.0)
v1_to_vr.set_state_val('r', [2500, 300.0])
v1_to_vr.set_state_val('v', [100, 110.0])
v1_to_vr.set_parameter_val('alpha', 0.0, units='deg')

rto.set_time_val(initial=35.0, duration=1.0)
rto.set_state_val('r', [2500, 5000.0])
rto.set_state_val('v', [110, 0.0001])
rto.set_parameter_val('alpha', 0.0, units='deg')

rotate.set_time_val(initial=35.0, duration=5.0)
rotate.set_state_val('r', [1750, 1800.0])
rotate.set_state_val('v', [80, 85.0])
rotate.set_control_val('alpha', 0.0, units='deg')

climb.set_time_val(initial=30.0, duration=20.0)
climb.set_state_val('r', [5000, 5500.0], units='ft')
climb.set_state_val('v', [160, 170.0], units='kn')
climb.set_state_val('h', [0.0, 35.0], units='ft')
climb.set_state_val('gam', [0.0, 5.0], units='deg')
climb.set_control_val('alpha', 5.0, units='deg')

return p
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