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Merge branch 'development' into release/1.4.0
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‎drop-boxes/register-omero-metadata/backendinterface.py

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"""Interface to the image management server
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This module contains the functionality to upload and download
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imaging data (raw and metadata) form the OMERO server (v5.4).
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It requires that the following software be installed within the Python
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environment you are loading this module:
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* OMERO.cli (https://docs.openmicroscopy.org/omero/5.4.0/users/cli/index.html)
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* OMERO Python language bindings (https://docs.openmicroscopy.org/omero/5.4.0/developers/Python.html)
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This code is based on the following documentation:
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https://docs.openmicroscopy.org/omero/5.4.0/developers/Python.html
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It contains the following functions:
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* omero_connect - connects to server
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* TODO...
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"""
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def omero_connect(usr, pwd, host, port):
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"""
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Connects to the OMERO Server with the provided username and password.
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Args:
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usr: The username to log into OMERO
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pwd: a password associated with the given username
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host: the OMERO hostname
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port: the port at which the OMERO server can be reached
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Returns:
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Connected BlitzGateway to the OMERO Server with the provided credentials
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"""
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from omero.gateway import BlitzGateway
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conn = BlitzGateway(usr, pwd, host=host, port=port)
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connected = conn.connect()
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conn.setSecure(True)
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if not connected:
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print("Error: Connection not available")
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return conn
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def print_data_ids(conn):
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"""
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Prints all IDs of the data objects(Projects, Datasets, Images) associated with the logged in user on the OMERO server
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Args:
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conn: Established Connection to the OMERO Server via a BlitzGateway
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Returns:
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Nothing except a printed text output to console
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"""
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for project in conn.getObjects("Project"):
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print('project: ' + str(project.getName()) + ' -- ' + str(project.getId()))
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for dataset in project.listChildren():
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print('ds: ' + str(dataset.getName()) + ' -- ' + str(dataset.getId()))
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for image in dataset.listChildren():
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print('img: ' + str(image.getName()) + ' -- ' + str(image.getId()))
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def get_omero_dataset_id(conn, openbis_project_id, openbis_sample_id):
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"""
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Prints all IDs of the data objects(Projects, Datasets, Images) associated with the logged in user on the OMERO server
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Args:
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conn: Established Connection to the OMERO Server via a BlitzGateway
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openbis_project_id: Id specifying the project information stored on OpenBIS
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openbis_sample_id: Id specifying the sample information stored on OpenBIS
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Returns:
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omero_dataset_id: Id specifying the dataset information stored on OMERO
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"""
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omero_dataset_id = -1
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found_id = False
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my_exp_id = conn.getUser().getId()
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default_group_id = conn.getEventContext().groupId
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for project in conn.getObjects("Project"):
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if found_id:
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break
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if project.getName() == openbis_project_id:
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for dataset in project.listChildren():
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if dataset.getName() == openbis_sample_id:
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omero_dataset_id = dataset.getId()
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found_id = True
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break
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return omero_dataset_id
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def register_image_file(file_path, project_id, sample_id, usr, pwd, host, port=4064):
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"""
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This function imports an image file to an omero server using the OMERO.cli (using Bio-formats)
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This function assumes the OMERO.cli is installed
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Example:
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register_image_file("data/test_img.nd2", "project_x", "sample_y",
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"joe_usr", "joe_pwd", "192.168.2.2")
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Args:
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file_path (string): the path to the fastq file to validate
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project_id (string): the corresponding project ID in openBIS server
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sample_id (string): the corresponding sample ID in openBIS server
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usr (string): username for the OMERO server
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pwd (string): password for the OMERO server
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host (string): OMERO server address
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port (int): OMERO server port
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Returns:
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list of strings: list of newly generated omero IDs for registered images
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(a file can contain many images)
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"""
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import subprocess
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image_ids = []
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conn = omero_connect(usr, pwd, host, str(port))
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ds_id = get_omero_dataset_id(conn, project_id, sample_id)
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if ds_id != -1:
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cmd = "omero-importer -s " + host + " -p " + str(port) + " -u " + usr + " -w " + pwd + " -d " + str(int(ds_id)) + " " + file_path
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print("----cmd: " + cmd)
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proc = subprocess.Popen(cmd,
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stdout=subprocess.PIPE,
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stderr=subprocess.PIPE,
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shell=True,
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universal_newlines=True)
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std_out, std_err = proc.communicate()
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print("std_out: " + std_out)
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print("std_err: " + std_err)
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print("return_code: " + str(proc.returncode))
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if int(proc.returncode) == 0:
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print("-->" + std_out)
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fist_line = std_out.splitlines()[0]
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image_ids = fist_line[6:].split(',')
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print("id list: " + str(image_ids))
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else:
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print("return code fail")
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else:
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print("invalid sample_id")
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return image_ids
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def register_image_file_with_dataset_id(file_path, dataset_id, usr, pwd, host, port=4064):
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"""
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This function imports an image file to an omero server using the OMERO.cli (using Bio-formats)
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This function assumes the OMERO.cli is installed
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Example:
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register_image_file("data/test_img.nd2", 10,
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"joe_usr", "joe_pwd", "192.168.2.2")
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Args:
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file_path (string): the path to the fastq file to validate
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dataset_id (string): the ID of the omero dataset
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usr (string): username for the OMERO server
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pwd (string): password for the OMERO server
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host (string): OMERO server address
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port (int): OMERO server port
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Returns:
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list of strings: list of newly generated omero IDs for registered images
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(a file can contain many images)
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"""
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import subprocess
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image_ids = []
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ds_id = dataset_id
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if ds_id != -1:
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cmd = "omero-importer -s " + host + " -p " + str(port) + " -u " + usr + " -w " + pwd + " -d " + str(int(ds_id)) + " " + file_path
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proc = subprocess.Popen(cmd,
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stdout=subprocess.PIPE,
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stderr=subprocess.PIPE,
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shell=True,
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universal_newlines=True)
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std_out, std_err = proc.communicate()
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if int(proc.returncode) == 0:
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fist_line = std_out.splitlines()[0]
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image_ids = fist_line[6:].split(',')
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else:
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image_ids = -1
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else:
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image_ids = -1
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return image_ids
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########################################
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#functions to register numpy arrays
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def generate_array_plane(new_img):
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"""
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TODO
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"""
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img_shape = new_img.shape
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size_z = img_shape[4]
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size_t = img_shape[0]
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size_c = img_shape[1]
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for z in range(size_z): # all Z sections
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for c in range(size_c): # all channels
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for t in range(size_t): # all time-points
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new_plane = new_img[t, c, :, :, z]
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yield new_plane
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def create_array(conn, img, img_name, img_desc, ds):
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"""
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TODO
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"""
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dims = img.shape
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z = dims[4]
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t = dims[0]
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c = dims[1]
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new_img = conn.createImageFromNumpySeq(generate_array_plane(img),
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img_name,
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z, c, t,
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description=img_desc,
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dataset=ds)
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return new_img.getId()
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def register_image_array(img, img_name, img_desc, project_id, sample_id, usr, pwd, host, port=4064):
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"""
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This function imports a 5D (time-points, channels, x, y, z) numpy array of an image
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to an omero server using the OMERO Python bindings
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Example:
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register_image_array(hypercube, "tomo_0", "this is a tomogram",
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"project_x", "sample_y", "joe_usr", "joe_pwd", "192.168.2.2")
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Args:
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file_path (string): the path to the fastq file to validate
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project_id (string): the corresponding project ID in openBIS server
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sample_id (string): the corresponding sample ID in openBIS server
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usr (string): username for the OMERO server
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pwd (string): password for the OMERO server
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host (string): OMERO server address
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port (int): OMERO server port
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Returns:
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int: newly generated omero ID for registered image array
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"""
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img_id = -1
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save_flag = 0
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conn = omero_connect(usr, pwd, host, str(port))
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for project in conn.getObjects("Project"):
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if project.getName() == project_id:
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for dataset in project.listChildren():
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if dataset.getName() == sample_id:
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img_id = create_array(conn, img, img_name, img_desc, dataset)
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save_flag = 1
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break
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if save_flag == 1:
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break
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return int(img_id)
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def get_image_array(conn, image_id):
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"""
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This function retrieves an image from an OMERO server as a numpy array
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TODO
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"""
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import numpy as np
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image = conn.getObject("Image", image_id)
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#construct numpy array (t, c, x, y, z)
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size_x = image.getSizeX()
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size_y = image.getSizeY()
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size_z = image.getSizeZ()
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size_c = image.getSizeC()
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size_t = image.getSizeT()
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# X and Y fields have to be aligned this way since during generation of the image from the numpy array the 2darray is expected to be (Y,X)
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# See Documentation here https://downloads.openmicroscopy.org/omero/5.5.1/api/python/omero/omero.gateway.html#omero.gateway._BlitzGateway
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hypercube = np.zeros((size_t, size_c, size_y, size_x, size_z))
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pixels = image.getPrimaryPixels()
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for t in range(size_t):
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for c in range(size_c):
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for z in range(size_z):
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plane = pixels.getPlane(z, c, t) # get a numpy array.
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hypercube[t, c, :, :, z] = plane
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return hypercube
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################################
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def add_annotations_to_image(conn, image_id, key_value_data):
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"""
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TODO
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"""
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import omero
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map_ann = omero.gateway.MapAnnotationWrapper(conn)
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# Use 'client' namespace to allow editing in Insight & web
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namespace = omero.constants.metadata.NSCLIENTMAPANNOTATION
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map_ann.setNs(namespace)
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map_ann.setValue(key_value_data)
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map_ann.save()
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image = conn.getObject("Image", image_id)
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# NB: only link a client map annotation to a single object
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image.linkAnnotation(map_ann)
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return 0
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#########################
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##app
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from optparse import OptionParser
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###OMERO server info
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USERNAME = "usr"
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PASSWORD = "pwd"
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HOST = "host"
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PORT = 4064
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def get_args():
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parser = OptionParser()
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parser.add_option('-f', '--file', dest='file_path', default="None", help='file to register')
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parser.add_option('-d', '--dataset', dest='dataset_id', default="None", help='dataset id for registration')
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parser.add_option('-p', '--project', dest='project_id', default="None", help='project id for dataset id retrieval')
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parser.add_option('-s', '--sample', dest='sample_id', default="None", help='sample id for dataset id retrieval')
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(options, args) = parser.parse_args()
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return options
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if __name__ == '__main__':
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args = get_args()
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if args.file_path != "None":
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img_ids = register_image_file_with_dataset_id(args.file_path, int(args.dataset_id), USERNAME, PASSWORD, HOST)
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id_str = ""
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for id_i in img_ids:
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id_str = id_str + id_i + " "
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print id_str
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else:
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conn = omero_connect(USERNAME, PASSWORD, HOST, str(PORT))
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ds_id = get_omero_dataset_id(conn, str(args.project_id), str(args.sample_id))
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print ds_id

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