def test_get_bundle_sort_ports(data_regression: DataRegressionFixture,
check: bool = True) -> Component:
lengths = {}
c = gf.Component("test_get_bundle_sort_ports")
ys_right = [0, 10, 20, 40, 50, 80]
pitch = 127.0
N = len(ys_right)
ys_left = [(i - N / 2) * pitch for i in range(N)]
right_ports = [
gf.Port(f"R_{i}", (0, ys_right[i]), 0.5, 180) for i in range(N)
]
left_ports = [
gf.Port(f"L_{i}", (-400, ys_left[i]), 0.5, 0) for i in range(N)
]
left_ports.reverse()
routes = gf.routing.get_bundle(right_ports, left_ports)
for i, route in enumerate(routes):
c.add(route.references)
lengths[i] = route.length
if check:
data_regression.check(lengths)
return c
def test_get_bundle_udirect(
data_regression: DataRegressionFixture, check: bool = True
) -> Component:
c = gf.Component("test_get_bundle_udirect")
pad = gf.partial(gf.c.pad, size=(10, 10))
pad_south = gf.components.pad_array(orientation=270, spacing=(15.0, 0), pad=pad)
pt = c << pad_south
pb = c << pad_south
pb.rotate(90)
pt.rotate(90)
pb.move((0, -100))
pbports = pb.get_ports_list()
ptports = pt.get_ports_list()
pbports.reverse()
routes = gf.routing.get_bundle(pbports, ptports, radius=5)
lengths = {}
for i, route in enumerate(routes):
c.add(route.references)
lengths[i] = route.length
if check:
data_regression.check(lengths)
return c
def test_get_bundle_west_to_north(
data_regression: DataRegressionFixture, check: bool = True
) -> Component:
lengths = {}
c = gf.Component("test_get_bundle_west_to_north")
pad = gf.partial(gf.c.pad, size=(10, 10))
c = gf.Component()
pad_south = gf.components.pad_array(orientation=270, spacing=(15.0, 0.0), pad=pad)
pad_north = gf.components.pad_array(orientation=90, spacing=(15.0, 0.0), pad=pad)
pl = c << pad_south
pb = c << pad_north
pl.rotate(90)
pb.move((100, -100))
pbports = pb.get_ports_list()
ptports = pl.get_ports_list()
c.add_ports(pbports, prefix="N")
c.add_ports(ptports, prefix="S")
routes = gf.routing.get_bundle(
pbports,
ptports,
bend=gf.components.wire_corner,
)
for i, route in enumerate(routes):
c.add(route.references)
lengths[i] = route.length
if check:
data_regression.check(lengths)
return c
def test_netlists(
component_type: str,
full_settings: bool,
data_regression: DataRegressionFixture,
check: bool = True,
component_factory=factory,
) -> None:
"""Write netlists for hierarchical circuits.
Checks that both netlists are the same
jsondiff does a hierarchical diff
Component -> netlist -> Component -> netlist
"""
c = component_factory[component_type]()
n = c.get_netlist(full_settings=full_settings)
if check:
data_regression.check(OmegaConf.to_container(n))
yaml_str = OmegaConf.to_yaml(n, sort_keys=True)
# print(yaml_str)
c2 = gf.read.from_yaml(yaml_str, component_factory=component_factory)
n2 = c2.get_netlist(full_settings=full_settings)
d = jsondiff.diff(n, n2)
# print(yaml_str)
# print(d)
# yaml_str2 = OmegaConf.to_yaml(n2, sort_keys=True)
# print(yaml_str2)
assert len(d) == 0, d
def _check_agent_state(self, state: Dict[str, Any],
data_regression: DataRegressionFixture):
"""
Given an agent state, test that it is as expected.
"""
del state['times'] # Delete variable timestamps
data_regression.check(state)
def test_prompt(capsys, monkeypatch, data_regression: DataRegressionFixture):
inputs = iter([
'',
'',
'',
'',
"24",
"Bond007",
"badpassword",
"baspassword",
"badpassword",
"badpassword",
"badpassword",
"badpassword",
])
def fake_input(prompt):
value = next(inputs)
print(f"{prompt}{value}".rstrip())
return value
monkeypatch.setattr(click.termui, "visible_prompt_func", fake_input)
assert prompt(text="What is your age", prompt_suffix="? ", type=click.INT) == 24
assert prompt(text="Username", type=click.STRING) == "Bond007"
assert prompt(text="Password", type=click.STRING, confirmation_prompt=True) == "badpassword"
assert prompt(
text="Password",
type=click.STRING,
confirmation_prompt="Are you sure about that? ",
) == "badpassword"
data_regression.check(list(StringList(capsys.readouterr().out.splitlines())))
def test_facing_ports(
data_regression: DataRegressionFixture,
check: bool = True,
):
dy = 200.0
xs1 = [-500, -300, -100, -90, -80, -55, -35, 200, 210, 240, 500, 650]
pitch = 10.0
N = len(xs1)
xs2 = [-20 + i * pitch for i in range(N // 2)]
xs2 += [400 + i * pitch for i in range(N // 2)]
a1 = 90
a2 = a1 + 180
ports1 = [Port(f"top_{i}", (xs1[i], 0), 0.5, a1) for i in range(N)]
ports2 = [Port(f"bottom_{i}", (xs2[i], dy), 0.5, a2) for i in range(N)]
c = gf.Component("test_facing_ports")
routes = get_bundle(ports1, ports2)
lengths = {}
for i, route in enumerate(routes):
c.add(route.references)
lengths[i] = route.length
if check:
data_regression.check(lengths)
difftest(c)
return c
def test_get_bundle_west_to_north2(
data_regression: DataRegressionFixture, check: bool = True
) -> Component:
lengths = {}
c = gf.Component("test_get_bundle_west_to_north2")
pbottom_facing_north = gf.port.port_array(
midpoint=(0, 0), orientation=90, pitch=(30, 0)
)
ptop_facing_west = gf.port.port_array(
midpoint=(100, 100), orientation=180, pitch=(0, -30)
)
routes = gf.routing.get_bundle(
pbottom_facing_north,
ptop_facing_west,
bend=gf.components.wire_corner,
)
for i, route in enumerate(routes):
c.add(route.references)
lengths[i] = route.length
if check:
data_regression.check(lengths)
return c
def test_via_Repo_class(
temp_repo,
capsys,
file_regression: FileRegressionFixture,
data_regression: DataRegressionFixture,
monkeypatch,
example_config,
):
with in_directory(temp_repo.path):
(temp_repo.path / "repo_helper.yml").write_text(example_config)
(temp_repo.path / "requirements.txt").touch()
(temp_repo.path / "tests").maybe_make()
(temp_repo.path / "tests" / "requirements.txt").touch()
(temp_repo.path / "README.rst").touch()
(temp_repo.path / "doc-source").mkdir()
(temp_repo.path / "doc-source" / "index.rst").touch()
(temp_repo.path / ".pre-commit-config.yaml").touch()
rh = RepoHelper(temp_repo.path)
rh.load_settings()
managed_files = rh.run()
data_regression.check(sorted(managed_files))
assert capsys.readouterr().out == ''
assert capsys.readouterr().err == ''
def test_netlists(
yaml_key: str,
full_settings: bool,
data_regression: DataRegressionFixture,
check: bool = True,
) -> None:
"""Write netlists for hierarchical circuits.
Checks that both netlists are the same
jsondiff does a hierarchical diff
Component -> netlist -> Component -> netlist
"""
yaml_string = yaml_strings[yaml_key]
c = from_yaml(yaml_string)
n = c.get_netlist(full_settings=full_settings)
if check:
data_regression.check(OmegaConf.to_container(n))
yaml_str = OmegaConf.to_yaml(n, sort_keys=True)
# print(yaml_str)
c2 = from_yaml(yaml_str)
n2 = c2.get_netlist(full_settings=full_settings)
d = jsondiff.diff(n, n2)
assert len(d) == 0, print(d)
return c2
def test_link_optical_ports_no_grouping(data_regression: DataRegressionFixture,
check: bool = True) -> Component:
c = gf.Component("test_link_optical_ports_no_grouping")
w = c << gf.components.straight_array(n=4, spacing=200)
d = c << gf.components.nxn(west=4, east=1)
d.y = w.y
d.xmin = w.xmax + 200
ports1 = [
w.ports["o7"],
w.ports["o8"],
]
ports2 = [
d.ports["o2"],
d.ports["o1"],
]
routes = get_bundle_same_axis_no_grouping(ports1, ports2, sort_ports=True)
# routes = gf.routing.get_bundle(ports1, ports2, sort_ports=True)
lengths = {}
for i, route in enumerate(routes):
c.add(route.references)
lengths[i] = route.length
if check:
data_regression.check(lengths)
return c
def test_components(yaml_index: int,
data_regression: DataRegressionFixture,
check: bool = True) -> None:
yaml = yaml_list[yaml_index]
c = gf.read.from_yaml(yaml)
difftest(c)
if check:
data_regression.check(c.to_dict())
def test_scan_list(data, data_regression: DataRegressionFixture, scan_no):
# Workaround for https://github.com/ESSS/pytest-regressions/issues/26
scan = data.scan_list[scan_no]
data_regression.check({
"intensity_list":
list(map(float, scan.intensity_list)),
"mass_list":
list(map(float, scan.mass_list)),
})
def test_write_wheel(builder,
advanced_file_regression: AdvancedFileRegressionFixture,
data_regression: DataRegressionFixture):
builder.write_wheel()
advanced_file_regression.check_file(builder.dist_info / "WHEEL")
# Check the file can be read by EmailMessage
with (builder.dist_info / "WHEEL").open() as fp:
data = message_from_file(fp)
data_regression.check(dict(data))
def test_settings(yaml_key: str,
data_regression: DataRegressionFixture,
check: bool = True) -> Component:
"""Avoid regressions when exporting settings."""
yaml_string = yaml_strings[yaml_key]
c = from_yaml(yaml_string)
if check:
data_regression.check(c.to_dict())
return c
def test_y_data(self, tic, data_regression: DataRegressionFixture):
assert tic.y_data[:10] == [
134909300.0,
135957800.0,
131716500.0,
130281100.0,
129322300.0,
127338400.0,
126183900.0,
123384600.0,
121993400.0,
118873000.0,
]
data_regression.check({"y_data": tic.y_data})
def test_x_data(self, tic, data_regression: DataRegressionFixture):
assert tic.x_data[:10] == [
0.047216666666666664,
0.05843333333333333,
0.06966666666666667,
0.08088333333333333,
0.09211666666666667,
0.10333333333333333,
0.11456666666666666,
0.12578333333333333,
0.137,
0.14823333333333333,
]
data_regression.check({"x_data": tic.x_data})
def test_get_bundle_u_indirect(data_regression: DataRegressionFixture,
angle,
check: bool = True,
dy=-200):
xs1 = [-100, -90, -80, -55, -35] + [200, 210, 240]
axis = "X" if angle in [0, 180] else "Y"
pitch = 10.0
N = len(xs1)
xs2 = [50 + i * pitch for i in range(N)]
a1 = angle
a2 = a1 + 180
if axis == "X":
ports1 = [
Port("top_{}".format(i), (0, xs1[i]), 0.5, a1) for i in range(N)
]
ports2 = [
Port("bottom_{}".format(i), (dy, xs2[i]), 0.5, a2)
for i in range(N)
]
else:
ports1 = [
Port("top_{}".format(i), (xs1[i], 0), 0.5, a1) for i in range(N)
]
ports2 = [
Port("bottom_{}".format(i), (xs2[i], dy), 0.5, a2)
for i in range(N)
]
c = gf.Component(f"test_get_bundle_u_indirect_{angle}_{dy}")
routes = get_bundle(ports1, ports2, bend=gf.components.bend_circular)
lengths = {}
for i, route in enumerate(routes):
c.add(route.references)
lengths[i] = route.length
if check:
data_regression.check(lengths)
difftest(c)
return c
def test_make_schema(data_regression: DataRegressionFixture):
data_regression.check(
make_schema(
author,
email,
username,
modname,
copyright_years,
repo_name,
pypi_name,
import_name,
keywords,
short_desc,
source_dir,
pure_python,
stubs_package,
on_pypi,
enable_tests,
enable_releases,
enable_pre_commit,
docker_shields,
docker_name,
manifest_additional,
py_modules,
console_scripts,
setup_pre,
additional_setup_args,
platforms,
rtfd_author,
preserve_custom_theme,
sphinx_html_theme,
extra_sphinx_extensions,
intersphinx_mapping,
sphinx_conf_preamble,
sphinx_conf_epilogue,
html_theme_options,
html_context,
enable_docs,
docs_dir,
imgbot_ignore,
mypy_deps,
mypy_plugins,
python_deploy_version,
python_versions,
tox_requirements,
tox_build_requirements,
tox_testenv_extras,
))
def _check_losses(
self, opt: Opt, test_name: str, data_regression: DataRegressionFixture
):
"""
Calculate and check distillation loss terms.
Given the input opt, run eval and check each of the loss terms to make sure that
they match what is expected.
"""
valid, _ = testing_utils.eval_model(opt, skip_test=True)
losses = {}
loss_types = self.LOSS_TYPES[test_name]
for loss_type in loss_types:
losses[loss_type] = round_sig(valid[loss_type].value(), sig=6)
basename = self._get_model_identifier() + '_' + test_name
data_regression.check(losses, basename=basename)
def test_confirm(capsys, monkeypatch, data_regression: DataRegressionFixture):
inputs = iter(['Y', 'N', '', ''])
def fake_input(prompt):
value = next(inputs)
print(f"{prompt}{value}".rstrip())
return value
monkeypatch.setattr(click.termui, "visible_prompt_func", fake_input)
assert confirm(text="Do you wish to delete all files in '/' ?", default=False) is True
assert confirm(text="Do you wish to delete all files in '/' ?", default=False) is False
assert confirm(text="Do you wish to delete all files in '/' ?", default=False) is False
assert confirm(text="Do you wish to delete all files in '/' ?", default=True) is True
data_regression.check(list(StringList(capsys.readouterr().out.splitlines())))
def test_get_bundle_u_direct_different_x(
data_regression: DataRegressionFixture,
check: bool = True) -> Component:
"""
.. code::
4----5
________
3----6 4| |
3| nxn |
2----7 2| |
1|________|
1----8
"""
c = gf.Component("test_get_bundle_u_direct_different_x")
w = c << gf.components.straight_array(n=4, spacing=200)
d = c << gf.components.nxn(west=4, east=0, north=0, south=0)
d.y = w.y
d.xmin = w.xmax + 200
ports1 = w.get_ports_list(orientation=0)
ports2 = d.get_ports_list(orientation=0)
ports1 = [
w.ports["o7"],
w.ports["o8"],
]
ports2 = [
d.ports["o2"],
d.ports["o1"],
]
routes = gf.routing.get_bundle(ports1, ports2)
lengths = {}
for i, route in enumerate(routes):
c.add(route.references)
lengths[i] = route.length
if check:
data_regression.check(lengths)
return c
def test_get_bundle_from_waypointsB(
data_regression: DataRegressionFixture,
check: bool = True,
) -> Component:
ys1 = np.array([0, 5, 10, 15, 30, 40, 50, 60]) + 0.0
ys2 = np.array([0, 10, 20, 30, 70, 90, 110, 120]) + 500.0
N = ys1.size
ports1 = [
Port(name=f"A_{i}", midpoint=(0, ys1[i]), width=0.5, orientation=0)
for i in range(N)
]
ports2 = [
Port(
name=f"B_{i}",
midpoint=(500, ys2[i]),
width=0.5,
orientation=180,
) for i in range(N)
]
p0 = ports1[0].position
c = gf.Component("B")
c.add_ports(ports1)
c.add_ports(ports2)
waypoints = [
p0 + (200, 0),
p0 + (200, -200),
p0 + (400, -200),
(p0[0] + 400, ports2[0].y),
]
routes = get_bundle_from_waypoints(ports1, ports2, waypoints)
lengths = {}
for i, route in enumerate(routes):
c.add(route.references)
lengths[i] = route.length
if check:
data_regression.check(lengths)
return c
def test_read_sparameters(component_type: str,
data_regression: DataRegressionFixture,
check: bool = True) -> None:
c = factory[component_type]()
sp = sim.read_sparameters_lumerical(component=c)
port_names = sp[0]
f = list(sp[1])
s = sp[2]
lenf = s.shape[0]
rows = s.shape[1]
cols = s.shape[2]
assert rows == cols == len(c.ports)
assert len(port_names) == len(c.ports)
if check:
data_regression.check(dict(port_names=port_names))
assert lenf == len(f)
def test_actions_manager_python_versions(
python_versions: List[str],
data_regression: DataRegressionFixture,
):
py_versions = {k: {"experimental": True} for k in python_versions}
class FakeActionsManager:
templates = SimpleNamespace()
templates.globals = {
"python_versions": py_versions,
"tox_py_versions": get_tox_python_versions(python_versions),
"third_party_version_matrix": {},
}
get_gh_actions_python_versions = ActionsManager.get_gh_actions_python_versions
get_gh_actions_matrix = ActionsManager.get_gh_actions_matrix
data_regression.check(
FakeActionsManager().get_gh_actions_python_versions()) # type: ignore
def test_suggest_classifiers_stage(tmp_pathplus, data_regression: DataRegressionFixture, stage): (tmp_pathplus / "repo_helper.yml").write_lines([ "modname: repo_helper", 'copyright_years: "2020"', 'author: "Dominic Davis-Foster"', 'email: "*****@*****.**"', 'version: "0.0.1"', 'username: "******"', "license: 'LGPLv3+'", "short_desc: 'Update multiple configuration files, build scripts etc. from a single location.'", ]) (tmp_pathplus / "requirements.txt").touch() (tmp_pathplus / "repo_helper").mkdir() with in_directory(tmp_pathplus): runner = CliRunner() result: Result = runner.invoke(suggest.classifiers, catch_exceptions=False, args=["-s", stage, "-l"]) assert result.exit_code == 0 classifiers = result.stdout.splitlines() data_regression.check(classifiers)
def test_get_bundle_optical2(data_regression: DataRegressionFixture,
check: bool = True) -> Component:
lengths = {}
c = gf.Component("test_get_bundle_optical2")
w = c << gf.components.straight_array(n=4, spacing=200)
d = c << gf.components.nxn(west=4, east=1)
d.y = w.y
d.xmin = w.xmax + 200
ports1 = w.get_ports_list(orientation=0)
ports2 = d.get_ports_list(orientation=180)
routes = gf.routing.get_bundle(ports1, ports2, sort_ports=True)
for i, route in enumerate(routes):
c.add(route.references)
lengths[i] = route.length
if check:
data_regression.check(lengths)
return c
def test_get_bundle_electrical(
data_regression: DataRegressionFixture, check: bool = True
) -> Component:
lengths = {}
c = gf.Component("test_get_bundle")
c1 = c << gf.components.pad()
c2 = c << gf.components.pad()
c2.move((200, 100))
routes = gf.routing.get_bundle(
[c1.ports["e3"]],
[c2.ports["e1"]],
bend=gf.components.wire_corner,
width=10,
# auto_widen=False,
auto_widen=True,
)
for i, route in enumerate(routes):
c.add(route.references)
lengths[i] = route.length
routes = gf.routing.get_bundle(
[c1.ports["e4"]],
[c2.ports["e3"]],
start_straight_length=20.0,
bend=gf.components.wire_corner,
width=10,
)
for i, route in enumerate(routes):
c.add(route.references)
lengths[i] = route.length
if check:
data_regression.check(lengths)
return c
def test_get_bundle_udirect(data_regression: DataRegressionFixture,
check: bool = True,
dy=200,
angle=270):
xs1 = [-100, -90, -80, -55, -35, 24, 0] + [200, 210, 240]
axis = "X" if angle in [0, 180] else "Y"
pitch = 10.0
N = len(xs1)
xs2 = [70 + i * pitch for i in range(N)]
if axis == "X":
ports1 = [Port(f"top_{i}", (0, xs1[i]), 0.5, angle) for i in range(N)]
ports2 = [
Port(f"bottom_{i}", (dy, xs2[i]), 0.5, angle) for i in range(N)
]
else:
ports1 = [Port(f"top_{i}", (xs1[i], 0), 0.5, angle) for i in range(N)]
ports2 = [
Port(f"bottom_{i}", (xs2[i], dy), 0.5, angle) for i in range(N)
]
c = gf.Component(name="test_get_bundle_udirect")
routes = get_bundle(ports1, ports2, bend=gf.components.bend_circular)
lengths = {}
for i, route in enumerate(routes):
c.add(route.references)
lengths[i] = route.length
if check:
data_regression.check(lengths)
difftest(c)
return c
def _regression(self, data_regression: DataRegressionFixture,
datatype: str):
import random
from parlai.core.worlds import create_task
from parlai.core.params import ParlaiParser
basename = f"{self.task}_{datatype}".replace(":", "_")
if self.stream:
datatype = datatype + ':stream'
if datatype == 'train:stream':
datatype = datatype + ':ordered'
random.seed(42)
opt = ParlaiParser(True, True).parse_kwargs(
model='fixed_response',
fixed_response='none',
task=self.task,
datatype=datatype,
batchsize=1,
)
world = create_task(opt, [])
acts = []
for _ in range(5):
world.parley()
act = self._safe(world.get_acts())
acts.append(act)
teacher = world.get_task_agent()
output = {
'acts': acts,
'num_episodes': teacher.num_episodes(),
'num_examples': teacher.num_examples(),
}
data_regression.check(output, basename=basename)
