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updated testing

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This commit is contained in:
Benoît Sierro
2021-06-10 16:20:39 +02:00
parent 69c89f04c4
commit 03b29f29f4
46 changed files with 428 additions and 411 deletions
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162
testing/test_initialize.py
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@@ -6,7 +6,8 @@ import numpy as np
import toml
from scgenerator import defaults, utils, math
from scgenerator.errors import *
from scgenerator.physics import units
from scgenerator.physics import pulse, units
from scgenerator.utils.parameter import BareConfig, BareParams
def load_conf(name):
@@ -38,12 +39,6 @@ class TestParamSequence(unittest.TestCase):
l.append(vary_list)
s.append(utils.format_variable_list(vary_list))
def test_init_config_not_affected_by_iteration(self):
for param_seq in self.iterconf(["almost_equal", "equal", "no_variations"]):
config = deepcopy(param_seq.config)
for _ in utils.required_simulations(param_seq.config):
self.assertEqual(config.items(), param_seq.config.items())
def test_no_variations_yields_only_num_and_id(self):
for param_seq in self.iterconf(["no_variations"]):
for vary_list, _ in utils.required_simulations(param_seq.config):
@@ -55,34 +50,30 @@ class TestParamSequence(unittest.TestCase):
class TestInitializeMethods(unittest.TestCase):
def test_validate_types(self):
conf = lambda s: load_conf("validate_types/" + s)
with self.assertRaisesRegex(TypeError, "belong"):
init._validate_types(conf("bad1"))
with self.assertRaisesRegex(TypeError, "valid list of behaviors"):
init._validate_types(conf("bad2"))
with self.assertRaisesRegex(ValueError, r"'behaviors\[3\]' must be a str in"):
init.Config(**conf("bad2"))
with self.assertRaisesRegex(TypeError, "single, real, non-negative number"):
init._validate_types(conf("bad3"))
with self.assertRaisesRegex(TypeError, "value must be of type <class 'float'>"):
init.Config(**conf("bad3"))
with self.assertRaisesRegex(TypeError, "'parallel' is not a valid variable parameter"):
init._validate_types(conf("bad4"))
with self.assertRaisesRegex(TypeError, "Variable parameters should be specified in a list"):
init._validate_types(conf("bad5"))
init.Config(**conf("bad4"))
with self.assertRaisesRegex(
TypeError,
"value '0' of type .*int.* for key 'repeat' is not valid, must be a strictly positive integer",
TypeError, "'variable intensity_noise' value must be of type <class 'list'>"
):
init._validate_types(conf("bad6"))
init.Config(**conf("bad5"))
with self.assertRaisesRegex(ValueError, "'repeat' must be positive"):
init.Config(**conf("bad6"))
with self.assertRaisesRegex(
ValueError,
r"Variable parameters lists should contain at least 1 element",
ValueError, "variable parameter 'intensity_noise' must not be empty"
):
init._ensure_consistency(conf("bad7"))
init.Config(**conf("bad7"))
self.assertIsNone(init._validate_types(conf("good")))
self.assertIsNone(init.Config(**conf("good")).hr_w)
def test_ensure_consistency(self):
conf = lambda s: load_conf("ensure_consistency/" + s)
@@ -90,68 +81,66 @@ class TestInitializeMethods(unittest.TestCase):
MissingParameterError,
r"1 of '\['t0', 'width'\]' is required and no defaults have been set",
):
init._ensure_consistency(conf("bad1"))
init.Config(**conf("bad1"))
with self.assertRaisesRegex(
MissingParameterError,
r"1 of '\['peak_power', 'mean_power', 'energy', 'width', 't0'\]' is required when 'soliton_num' is specified and no defaults have been set",
):
init._ensure_consistency(conf("bad2"))
init.Config(**conf("bad2"))
with self.assertRaisesRegex(
MissingParameterError,
r"2 of '\['dt', 't_num', 'time_window'\]' are required and no defaults have been set",
):
init._ensure_consistency(conf("bad3"))
init.Config(**conf("bad3"))
with self.assertRaisesRegex(
DuplicateParameterError,
r"got multiple values for parameter 'width'",
):
init._ensure_consistency(conf("bad4"))
init.Config(**conf("bad4"))
with self.assertRaisesRegex(
MissingParameterError,
r"'capillary_thickness' is a required parameter for fiber model 'hasan' and no defaults have been set",
):
init._ensure_consistency(conf("bad5"))
init.Config(**conf("bad5"))
with self.assertRaisesRegex(
MissingParameterError,
r"1 of '\['capillary_spacing', 'capillary_outer_d'\]' is required for fiber model 'hasan' and no defaults have been set",
):
init._ensure_consistency(conf("bad6"))
init.Config(**conf("bad6"))
self.assertLessEqual(
{"model": "pcf"}.items(), init._ensure_consistency(conf("good1"))["fiber"].items()
{"model": "pcf"}.items(), init.Config(**conf("good1")).__dict__.items()
)
self.assertNotIn("gas", init._ensure_consistency(conf("good1")))
self.assertNotIn("gamma", init._ensure_consistency(conf("good4"))["fiber"])
self.assertIsNone(init.Config(**conf("good4")).gamma)
self.assertLessEqual(
{"raman_type": "agrawal"}.items(),
init._ensure_consistency(conf("good2"))["simulation"].items(),
init.Config(**conf("good2")).__dict__.items(),
)
self.assertLessEqual(
{"name": "no name"}.items(), init._ensure_consistency(conf("good3")).items()
{"name": "no name"}.items(), init.Config(**conf("good3")).__dict__.items()
)
self.assertLessEqual(
{"capillary_nested": 0, "capillary_resonance_strengths": []}.items(),
init._ensure_consistency(conf("good4"))["fiber"].items(),
init.Config(**conf("good4")).__dict__.items(),
)
self.assertLessEqual(
dict(he_mode=(1, 1)).items(),
init._ensure_consistency(conf("good5"))["fiber"].items(),
init.Config(**conf("good5")).__dict__.items(),
)
self.assertLessEqual(
dict(temperature=300, pressure=1e5, gas_name="vacuum", plasma_density=0).items(),
init._ensure_consistency(conf("good5"))["gas"].items(),
init.Config(**conf("good5")).__dict__.items(),
)
self.assertLessEqual(
@@ -165,62 +154,75 @@ class TestInitializeMethods(unittest.TestCase):
"upper_wavelength_interp_limit"
],
).items(),
init._ensure_consistency(conf("good6"))["simulation"].items(),
init.Config(**conf("good6")).__dict__.items(),
)
def setup_conf_custom_field(self, path) -> BareParams:
conf = load_conf(path)
conf = BareParams(**conf)
init.build_sim_grid_in_place(conf)
return conf
def test_setup_custom_field(self):
d = np.load("testing/configs/custom_field/init_field.npz")
t = d["time"]
field = d["field"]
conf = load_conf("custom_field/no_change")
conf = init.build_sim_grid(conf)
result = init.setup_custom_field(conf)
self.assertAlmostEqual(conf["field_0"].real.max(), field.real.max(), 4)
self.assertTrue(result)
conf = load_conf("custom_field/peak_power")
conf = init.build_sim_grid(conf)
result = init.setup_custom_field(conf)
self.assertAlmostEqual(math.abs2(conf["field_0"]).max(), 20000, 4)
self.assertTrue(result)
self.assertNotAlmostEqual(conf["wavelength"], 1593e-9)
conf = load_conf("custom_field/mean_power")
conf = init.build_sim_grid(conf)
result = init.setup_custom_field(conf)
self.assertAlmostEqual(np.trapz(math.abs2(conf["field_0"]), conf["t"]), 0.22 / 40e6, 4)
self.assertTrue(result)
conf = load_conf("custom_field/recover1")
conf = init.build_sim_grid(conf)
result = init.setup_custom_field(conf)
self.assertAlmostEqual(math.abs2(conf["field_0"] - field).sum(), 0)
self.assertTrue(result)
conf = load_conf("custom_field/recover2")
conf = init.build_sim_grid(conf)
result = init.setup_custom_field(conf)
self.assertAlmostEqual((math.abs2(conf["field_0"]) / 0.9 - math.abs2(field)).sum(), 0)
self.assertTrue(result)
conf = load_conf("custom_field/wavelength_shift1")
result = init.compute_init_parameters(conf)
self.assertAlmostEqual(
units.m.inv(result["w"])[np.argmax(math.abs2(result["spec_0"]))], 1050e-9
conf = self.setup_conf_custom_field("custom_field/no_change")
result, conf.width, conf.peak_power, conf.energy, conf.field_0 = pulse.setup_custom_field(
conf
)
self.assertAlmostEqual(conf.field_0.real.max(), field.real.max(), 4)
self.assertTrue(result)
conf = load_conf("custom_field/wavelength_shift1")
conf["pulse"]["wavelength"] = 1593e-9
result = init.compute_init_parameters(conf)
conf = self.setup_conf_custom_field("custom_field/peak_power")
result, conf.width, conf.peak_power, conf.energy, conf.field_0 = pulse.setup_custom_field(
conf
)
conf.wavelength = pulse.correct_wavelength(conf.wavelength, conf.w_c, conf.field_0)
self.assertAlmostEqual(math.abs2(conf.field_0).max(), 20000, 4)
self.assertTrue(result)
self.assertNotAlmostEqual(conf.wavelength, 1593e-9)
conf = self.setup_conf_custom_field("custom_field/mean_power")
result, conf.width, conf.peak_power, conf.energy, conf.field_0 = pulse.setup_custom_field(
conf
)
self.assertAlmostEqual(np.trapz(math.abs2(conf.field_0), conf.t), 0.22 / 40e6, 4)
self.assertTrue(result)
conf = self.setup_conf_custom_field("custom_field/recover1")
result, conf.width, conf.peak_power, conf.energy, conf.field_0 = pulse.setup_custom_field(
conf
)
self.assertAlmostEqual(math.abs2(conf.field_0 - field).sum(), 0)
self.assertTrue(result)
conf = self.setup_conf_custom_field("custom_field/recover2")
result, conf.width, conf.peak_power, conf.energy, conf.field_0 = pulse.setup_custom_field(
conf
)
self.assertAlmostEqual((math.abs2(conf.field_0) / 0.9 - math.abs2(field)).sum(), 0)
self.assertTrue(result)
conf = self.setup_conf_custom_field("custom_field/wavelength_shift1")
result = init.Params.from_bare(conf)
self.assertAlmostEqual(units.m.inv(result.w)[np.argmax(math.abs2(result.spec_0))], 1050e-9)
conf = self.setup_conf_custom_field("custom_field/wavelength_shift1")
conf.wavelength = 1593e-9
result = init.Params.from_bare(conf)
conf = load_conf("custom_field/wavelength_shift2")
conf = init.Config(**conf)
for target, (variable, config) in zip(
[1050e-9, 1321e-9, 1593e-9], init.ParamSequence(conf)
):
init.build_sim_grid_in_place(conf)
self.assertAlmostEqual(
units.m.inv(config["w"])[np.argmax(math.abs2(config["spec_0"]))], target
units.m.inv(config.w)[np.argmax(math.abs2(config.spec_0))], target
)
print(config["wavelength"], target)
print(config.wavelength, target)
if __name__ == "__main__":