def test_filenames(db_with_dark_and_scan, tmpdir):
"""Test exported file names and sizes from Exporter."""
db = db_with_dark_and_scan
config = an.AnalysisConfig()
config.read(fn)
ld = an.AnalysisStream(config)
ld.db = db.v1
ep_config = pdfstream.callbacks.analysis.ExportConfig()
ep_config.read(fn)
ep_config.tiff_base = str(tmpdir)
ep = pdfstream.callbacks.analysis.Exporter(ep_config)
ld.subscribe(ep)
for name, doc in db[-1].canonical(fill="yes", strict_order=True):
ld(name, doc)
tiff_base = Path(ep_config.tiff_base)
# test tiff names and sizes
tiffs = list(tiff_base.rglob("*.tiff"))
for tiff in tiffs:
size_in_mb = tiff.stat().st_size // (2**20)
assert size_in_mb == 16
print(tiff.name)
# test array names
txts = list(tiff_base.rglob("*.txt"))
for txt in txts:
print(txt.name)
def test_user_mask1(db_with_img_and_bg_img):
db = db_with_img_and_bg_img
config = an.AnalysisConfig()
config.read(fn)
ld = an.AnalysisStream(config)
ld.db = db.v1
for name, doc in db[-1].canonical(fill="yes", strict_order=True):
if name == "start":
doc = dict(**doc, user_config={"auto_mask": False})
ld(name, doc)
def test_Visualizer(db_with_dark_and_scan):
db = db_with_dark_and_scan
config = an.AnalysisConfig()
config.read(fn)
ld = an.AnalysisStream(config)
ld.db = db.v1
config1 = pdfstream.callbacks.analysis.VisConfig()
config1.read(fn)
config1.fig = plt.figure()
cb = pdfstream.callbacks.analysis.Visualizer(config1)
ld.subscribe(cb)
for name, doc in db[-1].canonical(fill="yes", strict_order=True):
ld(name, doc)
cb.show_figs()
def test_AnalysisStream(db_with_img_and_bg_img, use_db):
db = db_with_img_and_bg_img
config = an.AnalysisConfig()
config.read(fn)
config.raw_db = db
ld = an.AnalysisStream(config)
# validate that output data
out_validator = Validator(analysis_out_schemas)
ld.subscribe(out_validator)
# validate the input data
in_validator = Validator(analysis_in_schemas)
for name, doc in db[-1].canonical(fill="yes", strict_order=True):
in_validator(name, doc)
ld(name, doc)
def test_AnalysisStream_with_UserConfig(db_with_img_and_bg_img, user_config):
"""Test the analysis stream with user configuration of masking."""
db = db_with_img_and_bg_img
config = an.AnalysisConfig()
config.read(fn)
ld = an.AnalysisStream(config)
ld.db = db.v1
# validate that output data
out_validator = Validator(analysis_out_schemas)
ld.subscribe(out_validator)
# validate the input data
in_validator = Validator(analysis_in_schemas)
for name, doc in db[-1].canonical(fill="yes", strict_order=True):
if name == "start":
doc = dict(**doc, user_config=user_config)
in_validator(name, doc)
ld(name, doc)
def test_Exporter(db_with_dark_and_scan, tmpdir):
db = db_with_dark_and_scan
config = an.AnalysisConfig()
config.read(fn)
config.raw_db = db
ld = an.AnalysisStream(config)
ep_config = pdfstream.callbacks.analysis.ExportConfig()
ep_config.read(fn)
ep_config.tiff_base = str(tmpdir)
ep = pdfstream.callbacks.analysis.Exporter(ep_config)
ld.subscribe(ep)
for name, doc in db[-1].canonical(fill="yes", strict_order=True):
ld(name, doc)
tiff_base = Path(ep_config.tiff_base)
assert len(list(tiff_base.rglob("*.tiff"))) > 0
assert len(list(tiff_base.rglob("*.csv"))) > 0
assert len(list(tiff_base.rglob("*.json"))) > 0
def test_AnalysisStream(db_with_img_and_bg_img, use_db):
db = db_with_img_and_bg_img
config = an.AnalysisConfig()
config.read(fn)
ld = an.AnalysisStream(config)
if use_db:
ld.db = db.v1
# validate that output data
out_validator = Validator(analysis_out_schemas)
ld.subscribe(out_validator)
ld.subscribe(
lambda name, doc: print(list(map(type, doc["data"].values()))),
name="event")
# validate the input data
in_validator = Validator(analysis_in_schemas)
for name, doc in db[-1].canonical(fill="yes", strict_order=True):
in_validator(name, doc)
# test no numpy array
ld(name, doc)
def test_ExporterXpdan(db_with_dark_and_scan, tmpdir):
"""Test ExporterXpaan. It should output the correct files in a two layer directory."""
db = db_with_dark_and_scan
config = an.AnalysisConfig()
config.read(fn)
config.raw_db = db
ld = an.AnalysisStream(config)
ep_config = pdfstream.callbacks.analysis.ExportConfig()
ep_config.read(fn)
ep_config.tiff_base = str(tmpdir)
ep = pdfstream.callbacks.analysis.ExporterXpdan(ep_config)
ld.subscribe(ep)
for name, doc in db[-1].canonical(fill="yes", strict_order=True):
ld(name, doc)
tiff_base = Path(ep_config.tiff_base)
data_folder = tiff_base.joinpath("Ni")
assert data_folder.is_dir()
for dir_name in ("dark_sub", "integration", "meta", "mask", "iq", "sq",
"fq", "pdf", "scalar_data"):
assert data_folder.joinpath(dir_name).is_dir()
assert len(list(data_folder.joinpath(dir_name).glob("*.*"))) > 0