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#!/usr/bin/env python
"""
An Jython dropbox for importing HCS image datasets produced by the scripts that generate platonic screening data.
The folder loaded to the dropbox folder should have the same name as the plate that the data will be attached to.
"""
import os
from ch.systemsx.cisd.openbis.generic.shared.api.v1.dto import SearchCriteria, SearchSubCriteria
from ch.systemsx.cisd.openbis.dss.etl.dto.api.v1 import SimpleImageDataConfig, ImageMetadata, Location, Channel, ChannelColorComponent
from ch.systemsx.cisd.openbis.plugin.screening.shared.api.v1.dto import Geometry
class ImageDataSetFlexible(SimpleImageDataConfig):
"""
Extracts tile number, channel code and well code for a given relative path to an image.
Will be called for each file found in the incoming directory which has the allowed image extension.
Example file name: bDZ01-1A_wD17_s3_z123_t321_cGFP
Returns:
ImageMetadata
"""
def extractImageMetadata(self, imagePath):
image_tokens = ImageMetadata()
basename = os.path.splitext(imagePath)[0]
#
token_dict = {}
for token in basename.split("_"):
token_dict[token[:1]] = token[1:]
image_tokens.well = token_dict["w"]
fieldText = token_dict["s"]
try:
image_tokens.tileNumber = int(fieldText)
except ValueError:
raise Exception("Cannot parse field number from '" + fieldText + "' in '" + basename + "' file name.")
image_tokens.channelCode = token_dict["c"]
return image_tokens
"""
Overrides the default implementation which returns (1, maxTileNumber) geometry.
Calculates the width and height of the matrix of tiles (a.k.a. fields or sides) in the well.
Parameter imageMetadataList: a list of metadata for each encountered image
Parameter maxTileNumber: the biggest tile number among all encountered images
Returns:
Geometry
"""
def getTileGeometry(self, imageTokens, maxTileNumber):
return Geometry.createFromRowColDimensions(maxTileNumber / 3, 3);
"""
Overrides the default implementation which does the same thing (to demonstrate how this can be done).
For a given tile number and tiles geometry returns (x,y) which describes where the tile is
located on the well.
Parameter tileNumber: number of the tile
Parameter tileGeometry: the geometry of the well matrix
Returns:
Location
"""
def getTileCoordinates(self, tileNumber, tileGeometry):
columns = tileGeometry.getWidth()
row = ((tileNumber - 1) / columns) + 1
col = ((tileNumber - 1) % columns) + 1
return Location(row, col)
def process(transaction):
incoming = transaction.getIncoming()
space = "PLATONIC"
if incoming.isDirectory():
imageDataset = ImageDataSetFlexible()
imageDataset.setSegmentationImageDatasetType()
splittedDataSetFolderName = incoming.getName().split('.')
plateName = splittedDataSetFolderName[0]
imageDataset.setPlate(space, plateName)
newDataset = transaction.createNewImageDataSet(imageRegistrationDetails, incoming);
if len(splittedDataSetFolderName) > 2:
newDataset.setPropertyValue("$ANALYSIS_PROCEDURE", splittedDataSetFolderName[2])
searchService = transaction.getSearchService()
searchCriteria = SearchCriteria()
searchCriteria.addMatchClause(SearchCriteria.MatchClause.createAttributeMatch(SearchCriteria.MatchClauseAttribute.TYPE, "HCS_IMAGE_RAW"))
sampleCriteria = SearchCriteria()
sampleCriteria.addMatchClause(SearchCriteria.MatchClause.createAttributeMatch(SearchCriteria.MatchClauseAttribute.SPACE, space))
sampleCriteria.addMatchClause(SearchCriteria.MatchClause.createAttributeMatch(SearchCriteria.MatchClauseAttribute.CODE, plateName))
searchCriteria.addSubCriteria(SearchSubCriteria.createSampleCriteria(sampleCriteria))
dataSets = searchService.searchForDataSets(searchCriteria)
if dataSets.size() > 0:
newDataset.setParentDatasets([dataSets[0].getDataSetCode()])
transaction.moveFile(incoming.getPath(), newDataset)