def get_omero_data(image_id):
conn = omero.open_connection(username=USER,
password=PASSWORD,
group=GROUP,
port=PORT,
host=HOST)
image = omero.get_image(conn, image_id)
image_name = image.getName()
raw_img = omero.get_intensities(image)
# Images from OMERO come in zctxy dimensions and locally as zcxy.
# The easyest for the moment is to remove t from the omero image
if raw_img.shape[2] == 1:
raw_img = np.squeeze(raw_img, 2)
else:
raise Exception(
"Image has a time dimension. Time is not yet implemented for this analysis"
)
pixel_size = omero.get_pixel_size(image)
pixel_units = omero.get_pixel_size_units(image)
conn.close()
return {
'image_data': raw_img,
'image_name': image_name,
'pixel_size': pixel_size,
'pixel_units': pixel_units
}
def save_line_rois(data: dict, image_id):
conn = omero.open_connection(username=USER,
password=PASSWORD,
group=GROUP,
port=PORT,
host=HOST)
image = omero.get_image(conn, image_id)
nb_channels = image.getSizeC()
for c in range(nb_channels):
shapes = list()
for l in range(len(data[f'ch{c:02d}_peak_positions'])):
for p in range(2):
if data['resolution_axis'] == 1: # Y resolution -> horizontal rois
axis_len = image.getSizeX()
x1_pos = int((axis_len / 2) -
(axis_len * data['measured_band'] / 2))
y1_pos = data[f'ch{c:02d}_peak_positions'][l][p]
x2_pos = int((axis_len / 2) +
(axis_len * data['measured_band'] / 2))
y2_pos = data[f'ch{c:02d}_peak_positions'][l][p]
elif data[
'resolution_axis'] == 2: # X resolution -> vertical rois
axis_len = image.getSizeY()
y1_pos = int((axis_len / 2) -
(axis_len * data['measured_band'] / 2))
x1_pos = data[f'ch{c:02d}_peak_positions'][l][p]
y2_pos = int((axis_len / 2) +
(axis_len * data['measured_band'] / 2))
x2_pos = data[f'ch{c:02d}_peak_positions'][l][p]
else:
raise ValueError(
'Only axis 1 and 2 (X and Y) are supported')
line = omero.create_shape_line(
x1_pos=x1_pos + .5,
y1_pos=y1_pos + .5,
x2_pos=x2_pos + .5,
y2_pos=y2_pos + .5,
z_pos=data[f'ch{c:02d}_focus'],
t_pos=0,
line_name=f'ch{c:02d}_{l}_{p}',
# stroke_color=,
stroke_width=2)
shapes.append(line)
omero.create_roi(connection=conn, image=image, shapes=shapes)
conn.close()
def save_data_key_values(key_values, image_id):
conn = omero.open_connection(username=USER,
password=PASSWORD,
group=GROUP,
port=PORT,
host=HOST)
try:
map_ann = omero.create_annotation_map(connection=conn,
annotation=key_values,
namespace=True)
image = omero.get_image(conn, image_id)
omero.link_annotation(image, map_ann)
finally:
conn.close()
def save_data_table(table_name, names, desc, data, image_id):
conn = omero.open_connection(username=USER,
password=PASSWORD,
group=GROUP,
port=PORT,
host=HOST)
try:
table_ann = omero.create_annotation_table(connection=conn,
table_name=table_name,
column_names=names,
column_descriptions=desc,
values=data)
image = omero.get_image(conn, image_id)
omero.link_annotation(image, table_ann)
finally:
conn.close()
def save_spots_point_rois(names: list, data: list, image_id):
conn = omero.open_connection(username=USER,
password=PASSWORD,
group=GROUP,
port=PORT,
host=HOST)
image = omero.get_image(conn, image_id)
nb_channels = image.getSizeC()
for c in range(nb_channels):
shapes = list()
for x, y, z, l in zip(
data[names.index(f'ch{c:02d}_XWeightedCentroid')][0],
data[names.index(f'ch{c:02d}_YWeightedCentroid')][0],
data[names.index(f'ch{c:02d}_ZWeightedCentroid')][0],
data[names.index(f'ch{c:02d}_MaskLabels')][0],
):
shapes.append(
omero.create_shape_point(x, y, z, shape_name=f'ch{c:02d}_{l}'))
omero.create_roi(connection=conn, image=image, shapes=shapes)
conn.close()