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#1704 choose faster options for testing batch study #1762

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Oct 27, 2021
Merged

#1704 choose faster options for testing batch study #1762

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4fb3d8f
#1704 choose faster options for testing batch study
valentinsulzer Oct 27, 2021
67db4e0
#1704 remove logger
valentinsulzer Oct 27, 2021
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8 changes: 4 additions & 4 deletions pybamm/models/standard_variables.py
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -176,12 +176,12 @@ def __init__(self):
bounds=(0, 1),
)
self.c_s_n_rxav = pybamm.Variable(
"R-X-averaged negative particle concentration",
"Average negative particle concentration",
domain="current collector",
bounds=(0, 1),
)
self.c_s_p_rxav = pybamm.Variable(
"R-X-averaged positive particle concentration",
"Average positive particle concentration",
domain="current collector",
bounds=(0, 1),
)
Expand Down Expand Up @@ -221,11 +221,11 @@ def __init__(self):
auxiliary_domains={"secondary": "current collector"},
)
self.q_s_n_rxav = pybamm.Variable(
"R-X-averaged negative particle concentration gradient",
"Average negative particle concentration gradient",
domain="current collector",
)
self.q_s_p_rxav = pybamm.Variable(
"R-X-averaged positive particle concentration gradient",
"Average positive particle concentration gradient",
domain="current collector",
)

Expand Down
68 changes: 19 additions & 49 deletions tests/unit/test_batch_study.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,38 +6,27 @@
import unittest

spm = pybamm.lithium_ion.SPM()
dfn = pybamm.lithium_ion.DFN()
spm_uniform = pybamm.lithium_ion.SPM({"particle": "uniform profile"})
casadi_safe = pybamm.CasadiSolver(mode="safe")
casadi_fast = pybamm.CasadiSolver(mode="fast")
cccv = pybamm.Experiment(
[
(
"Discharge at C/5 for 10 hours or until 3.3 V",
"Rest for 1 hour",
"Charge at 1 A until 4.1 V",
"Hold at 4.1 V until 10 mA",
"Rest for 1 hour",
),
]
* 3
)
gitt = pybamm.Experiment(
[("Discharge at C/20 for 1 hour", "Rest for 1 hour")] * 20,
)
exp1 = pybamm.Experiment([("Discharge at C/5 for 10 minutes", "Rest for 1 hour")])
exp2 = pybamm.Experiment([("Discharge at C/20 for 10 minutes", "Rest for 1 hour")])

bs_false_only_models = pybamm.BatchStudy(models={"SPM": spm, "DFN": dfn})
bs_false_only_models = pybamm.BatchStudy(
models={"SPM": spm, "SPM uniform": spm_uniform}
)
bs_true_only_models = pybamm.BatchStudy(
models={"SPM": spm, "DFN": dfn}, permutations=True
models={"SPM": spm, "SPM uniform": spm_uniform}, permutations=True
)
bs_false = pybamm.BatchStudy(
models={"SPM": spm, "DFN": dfn},
models={"SPM": spm, "SPM uniform": spm_uniform},
solvers={"casadi safe": casadi_safe, "casadi fast": casadi_fast},
experiments={"cccv": cccv, "gitt": gitt},
experiments={"exp1": exp1, "exp2": exp2},
)
bs_true = pybamm.BatchStudy(
models={"SPM": spm, "DFN": dfn},
models={"SPM": spm, "SPM uniform": spm_uniform},
solvers={"casadi safe": casadi_safe, "casadi fast": casadi_fast},
experiments={"gitt": gitt},
experiments={"exp2": exp2},
permutations=True,
)

Expand All @@ -47,7 +36,9 @@ def test_solve(self):
# Tests for exceptions
for name in pybamm.BatchStudy.INPUT_LIST:
with self.assertRaises(ValueError):
pybamm.BatchStudy(models={"SPM": spm, "DFN": dfn}, **{name: {None}})
pybamm.BatchStudy(
models={"SPM": spm, "SPM uniform": spm_uniform}, **{name: {None}}
)

# Tests for None when only models are given with permutations=False
bs_false_only_models.solve(t_eval=[0, 3600])
Expand All @@ -59,6 +50,7 @@ def test_solve(self):

# Tests for BatchStudy when permutations=False
bs_false.solve()
bs_false.plot(testing=True)
self.assertEqual(2, len(bs_false.sims))
for num in range(len(bs_false.sims)):
output_model = bs_false.sims[num].model.name
Expand All @@ -80,6 +72,7 @@ def test_solve(self):

# Tests for BatchStudy when permutations=True
bs_true.solve()
bs_true.plot(testing=True)
self.assertEqual(4, len(bs_true.sims))
for num in range(len(bs_true.sims)):
output_model = bs_true.sims[num].model.name
Expand All @@ -99,39 +92,16 @@ def test_solve(self):
]
self.assertIn(output_experiment, experiments_list)

def test_plot(self):
# Tests for BatchStudy when permutations=False
bs_false.solve()
bs_false.plot(testing=True)
self.assertEqual(2, len(bs_false.sims))

sols = [sim.solution for sim in bs_false.sims]
for num in range(len(bs_false.sims)):
output_model = sols[num].all_models[0].name
models_list = [model.name for model in bs_false.models.values()]
self.assertIn(output_model, models_list)

# Tests for BatchStudy when permutations=True
bs_true.solve()
bs_true.plot(testing=True)
self.assertEqual(4, len(bs_true.sims))

sols = [sim.solution for sim in bs_true.sims]
for num in range(len(bs_true.sims)):
output_model = sols[num].all_models[0].name
models_list = [model.name for model in bs_true.models.values()]
self.assertIn(output_model, models_list)

def test_create_gif(self):
bs = pybamm.BatchStudy({"spm": pybamm.lithium_ion.SPM()})
bs.solve([0, 3600])
bs.solve([0, 10])

# create a GIF before calling the plot method
bs.create_gif(number_of_images=5, duration=1)
bs.create_gif(number_of_images=3, duration=1)

# create a GIF after calling the plot method
bs.plot(testing=True)
bs.create_gif(number_of_images=5, duration=1)
bs.create_gif(number_of_images=3, duration=1)

os.remove("plot.gif")

Expand Down