def stem_acquire():
data = black
if current_frame:
img.seek(current_frame)
data = tobytes(img)
time.sleep(3)
return data
def stem_acquire():
data = black
if current_frame:
img.seek(current_frame)
data = tobytes(img)
time.sleep(3)
return data
def preview_scan():
data = black
if current_frame:
img.seek(current_frame)
data = tobytes(img)
time.sleep(2)
return data
def preview_scan():
data = black
if current_frame:
img.seek(current_frame)
data = tobytes(img)
time.sleep(2)
return data
def test_tiff_stem_acquire(passive_acquisition_server, tmpdir,
mock_tiff_tiltseries_writer):
id = 1234
request = jsonrpc_message({
'id': id,
'method': 'connect',
'params': {
'path': tmpdir.strpath,
'fileNameRegex': r'.*\.tif'
}
})
response = requests.post(passive_acquisition_server.url, json=request)
assert response.status_code == 200, response.content
request = jsonrpc_message({
'id': id,
'method': 'stem_acquire'
})
tilt_series = []
for _ in range(0, 1000):
response = requests.post(passive_acquisition_server.url, json=request)
assert response.status_code == 200, response.content
# No images left to fetch
result = response.json()['result']
if result is None:
continue
url = result['imageUrl']
response = requests.get(url)
tilt_series.append(response.content)
if len(tilt_series) == mock_tiff_tiltseries_writer.series_size:
break
# make sure we got all the images
assert len(tilt_series) == mock_tiff_tiltseries_writer.series_size
# Now check we got the write images
with Image.open(test_image()) as image_stack:
for i in range(0, image_stack.n_frames):
md5 = hashlib.md5()
md5.update(tilt_series[i])
image_stack.seek(i)
image_slice = tobytes(image_stack)
expected_md5 = hashlib.md5()
expected_md5.update(image_slice)
assert md5.hexdigest() == expected_md5.hexdigest()
def _dm3_extractor(file):
"""
Extract metadata and image data from a DM3 file.
:param file: The the DM3 file.
:type file: The file-like object.
:return A tuple contain the metadata and image data.
"""
dm3_file = dm3.DM3(file)
info = {k: v.decode('utf8') for k, v in dm3_file.info.items()}
image = Image.fromarray(dm3_file.imagedata)
image_data = tobytes(image)
return (info, image_data)
def _dm3_extractor(file):
"""
Extract metadata and image data from a DM3 file.
:param file: The the DM3 file.
:type file: The file-like object.
:return A tuple contain the metadata and image data.
"""
dm3_file = dm3.DM3(file)
info = {k: v.decode('utf8') for k, v in dm3_file.info.items()}
image = Image.fromarray(dm3_file.imagedata)
image_data = tobytes(image)
return (info, image_data)
def test_dm3_stem_acquire(passive_acquisition_server, tmpdir,
mock_dm3_tiltseries_writer):
id = 1234
angle_regex = r'.*_([n,p]{1}[\d,\.]+)degree.*\.dm3'
request = jsonrpc_message({
'id': id,
'method': 'connect',
'params': {
'path': tmpdir.strpath,
'fileNameRegex': angle_regex,
'fileNameRegexGroups': ['angle'],
'groupRegexSubstitutions': {
'angle': [{
'n': '-',
'p': '+'
}]
}
}
})
response = requests.post(passive_acquisition_server.url, json=request)
assert response.status_code == 200, response.content
request = jsonrpc_message({
'id': id,
'method': 'stem_acquire'
})
tilt_series = []
tilt_series_metadata = []
for _ in range(0, 1000):
response = requests.post(passive_acquisition_server.url, json=request)
assert response.status_code == 200, response.content
# No images left to fetch
result = response.json()['result']
if result is None:
continue
url = result['imageUrl']
response = requests.get(url)
tilt_series.append(response.content)
if 'meta' in result:
tilt_series_metadata.append(result['meta'])
if len(tilt_series) == mock_dm3_tiltseries_writer.series_size:
break
# make sure we got all the images
assert len(tilt_series) == mock_dm3_tiltseries_writer.series_size
# Now check we got the write images
for (i, (filename, fp)) in enumerate(test_dm3_tilt_series()):
dm3_file = dm3.DM3(fp)
expected_metadata \
= {k: v.decode('utf8') for k, v in dm3_file.info.items()}
expected_metadata['fileName'] = filename
angle = re.match(angle_regex, filename).group(1)
angle = angle.replace('n', '-')
angle = angle.replace('p', '+')
expected_metadata['angle'] = angle
assert tilt_series_metadata[i] == expected_metadata
md5 = hashlib.md5()
md5.update(tilt_series[i])
image = Image.fromarray(dm3_file.imagedata)
tiff_image_data = tobytes(image)
expected_md5 = hashlib.md5()
expected_md5.update(tiff_image_data)
assert md5.hexdigest() == expected_md5.hexdigest()