def mask_merge(label_layer) -> None:
"""merge JSON/Markdown from build/devices into build/mask"""
gdspath = CONFIG["mask_gds"]
write_labels(gdspath=gdspath, label_layer=label_layer)
merge_json()
merge_markdown()
merge_test_metadata(gdspath=gdspath)
def test_mask(
precision: float = 1e-9,
labels_prefix: str = "opt",
layer_label: Tuple[int, int] = layer_label,
) -> Component:
"""Returns mask."""
workspace_folder = CONFIG["samples_path"] / "mask_pack"
build_path = workspace_folder / "build"
mask_path = build_path / "mask"
shutil.rmtree(build_path, ignore_errors=True)
mask_path.mkdir(parents=True, exist_ok=True)
gdspath = mask_path / "sample_mask.gds"
# markdown_path = gdspath.with_suffix(".md")
# json_path = gdspath.with_suffix(".json")
# test_metadata_path = gdspath.with_suffix(".tp.json")
components = [
spiral_te(length=length) for length in np.array([2, 4, 6]) * 1e4
]
components += [
coupler_te(length=length, gap=0.2) for length in [10, 20, 30, 40]
]
c = gf.pack(components)
m = c[0]
m.name = "sample_mask"
m.write_gds_with_metadata(gdspath)
csvpath = write_labels(gdspath=gdspath,
prefix=labels_prefix,
label_layer=layer_label)
assert gdspath.exists()
assert csvpath.exists()
return m
def merge_metadata(
gdspath: Path,
labels_prefix: str = "opt",
layer_label: Tuple[int, int] = gf.LAYER.TEXT,
) -> DictConfig:
"""Merges all mask metadata and returns test metadata
This function works well only when you define the mask in YAML
Exports a YAML file with only the cells information that have a valid test and measurement label
For the cells that need to be measure we add test labels
This is the automatic version of write_labels combined with merge_test_metadata
.. code::
CSV labels -------
|--> merge_test_metadata dict
|
YAML metatada ----
Args:
gdspath: GDSpath
labels_prefix
layer_label: layer for the labels
"""
mdpath = gdspath.with_suffix(".md")
yaml_path = gdspath.with_suffix(".yml")
test_metadata_path = gdspath.with_suffix(".tp.yml")
build_directory = gdspath.parent.parent
doe_directory = build_directory / "cache_doe"
labels_path = write_labels(gdspath=gdspath,
prefix=labels_prefix,
layer_label=layer_label)
# jsonpath = gdspath.with_suffix(".yml")
# merge_json(doe_directory=doe_directory, jsonpath=jsonpath, **kwargs)
mask_metadata = merge_yaml(doe_directory=doe_directory,
yaml_path=yaml_path)
merge_markdown(reports_directory=doe_directory, mdpath=mdpath)
tm = merge_test_metadata(
labels_prefix=labels_prefix,
mask_metadata=mask_metadata,
labels_path=labels_path,
)
test_metadata_path.write_text(OmegaConf.to_yaml(tm))
return tm
def merge_metadata(
gdspath: Path,
labels_prefix: str = "opt",
label_layer: Tuple[int, int] = gf.LAYER.LABEL,
**kwargs
) -> None:
"""Merges all JSON metadata into a big JSON.
Args:
gdspath: GDSpath
labels_prefix
label_layer: layer for the labels
"""
mdpath = gdspath.with_suffix(".md")
jsonpath = gdspath.with_suffix(".json")
build_directory = gdspath.parent.parent
doe_directory = build_directory / "doe"
write_labels(gdspath=gdspath, prefix=labels_prefix, label_layer=label_layer)
merge_json(doe_directory=doe_directory, jsonpath=jsonpath, **kwargs)
merge_markdown(reports_directory=doe_directory, mdpath=mdpath)
merge_test_metadata(gdspath, labels_prefix=labels_prefix)
def write_mask_labels(gdspath: str, label_layer) -> None:
"""Find test and measurement labels."""
if gdspath is None:
gdspath = CONFIG["mask_gds"]
write_labels(gdspath=gdspath, label_layer=label_layer)
