示例#1
0
    def command(self):
        from qtools.lib.mplot import plot_cluster_2d, cleanup as plt_cleanup
        app = self.load_wsgi_app()

        image_root = app.config['qlb.image_store']
        image_source = QLBImageSource(image_root)

        # enforce config.ini
        if len(self.args) < 2:
            raise ValueError, self.__class_.usage

        analysis_group_id = int(self.args[0])
        if len(self.args) == 3:
            reprocess_config = Session.query(ReprocessConfig).filter_by(code=self.args[1]).one()
            reprocess_config_id = reprocess_config.id
        else:
            reprocess_config = None
            reprocess_config_id = None

        if reprocess_config:
            data_root = app.config['qlb.reprocess_root']
            storage = QLPReprocessedFileSource(data_root, reprocess_config)
        else:
            storage = QLStorageSource(app.config)

        analysis_group = Session.query(AnalysisGroup).get(analysis_group_id)
        if not analysis_group:
            raise ValueError, "No analysis group for id %s" % analysis_group_id

        plates = analysis_group.plates
        for plate in plates:
            # TODO: UGH THIS CODE INVARIANT SUCKS (should merge QLReprocessedFile/QLStorageSources)
            if reprocess_config:
                plate_path = storage.full_path(analysis_group, plate)
            else:
                plate_path = storage.plate_path(plate)
            print "Reading %s" % plate_path
            qlplate = get_plate(plate_path)
            if not qlplate:
                print "Could not read plate: %s" % plate.name
                continue
            print "Generating thumbnails for %s" % plate.name
            for name, qlwell in sorted(qlplate.analyzed_wells.items()):
                # TODO abstract into utility image generation function (thumbnail.py?)

                threshold_fallback = qlwell.clustering_method == QLWell.CLUSTERING_TYPE_THRESHOLD
                fig = plot_cluster_2d(qlwell.peaks,
                                      width=60,
                                      height=60,
                                      thresholds=[qlwell.channels[0].statistics.threshold,
                                                  qlwell.channels[1].statistics.threshold],
                                      boundaries=[0,0,12000,24000],
                                      show_axes=False,
                                      antialiased=True,
                                      unclassified_alpha=0.5,
                                      use_manual_clusters=not well_channel_automatic_classification(qlwell),
                                      highlight_thresholds=threshold_fallback)
                image_path = image_source.get_path('%s/%s_2d.png' % (plate.qlbplate.id, name))
                print image_path
                fig.savefig(image_path, format='png', dpi=72)
                plt_cleanup(fig)
示例#2
0
def write_images_stats_for_plate(dbplate, qlplate, image_source, overwrite=False, override_plate_type=None):
    """
    Write plate metrics to the database and thumbnails to local storage,
    as dictated by image_source.

    Metrics will be related to the supplied dbplate (Plate model)
    qlplate is a QLPlate object derived from reading the QLP file.
    """
    if image_source.subdir_exists(str(dbplate.id)):
        if not overwrite:
            return
    else:
        image_source.make_subdir(str(dbplate.id))
    
    max_amplitudes = (24000, 12000)
    show_only_gated = False # keep default behavior
    if qlplate:
        for well_name, qlwell in sorted(qlplate.analyzed_wells.items()):
            # TODO: common lib?
            if well_channel_automatic_classification(qlwell, 0):
                fig = plot_fam_peaks(qlwell.peaks,
                                     threshold=qlwell.channels[0].statistics.threshold,
                                     max_amplitude=max_amplitudes[0])
            else:
                fig = plot_fam_peaks(qlwell.peaks,
                                     threshold=qlwell.channels[0].statistics.threshold,
                                     threshold_color='red',
                                     max_amplitude=max_amplitudes[0],
                                     background_rgb=MANUAL_THRESHOLD_FAM_BGCOLOR)
            fig.savefig(image_source.get_path('%s/%s_%s.png' % (dbplate.id, well_name, 0)), format='png', dpi=72)
            plt_cleanup(fig)

            if well_channel_automatic_classification(qlwell, 1):
                fig = plot_vic_peaks(qlwell.peaks,
                                     threshold=qlwell.channels[1].statistics.threshold,
                                     max_amplitude=max_amplitudes[1])
            else:
                fig = plot_vic_peaks(qlwell.peaks,
                                     threshold=qlwell.channels[1].statistics.threshold,
                                     threshold_color='red',
                                     max_amplitude=max_amplitudes[1],
                                     background_rgb=MANUAL_THRESHOLD_VIC_BGCOLOR)
                
            fig.savefig(image_source.get_path('%s/%s_%s.png' % (dbplate.id, well_name, 1)), format='png', dpi=72)
            plt_cleanup(fig)

            if qlwell.clusters_defined:
                threshold_fallback = qlwell.clustering_method == QLWell.CLUSTERING_TYPE_THRESHOLD
                fig = plot_cluster_2d(qlwell.peaks,
                                      width=60,
                                      height=60,
                                      thresholds=[qlwell.channels[0].statistics.threshold,
                                                  qlwell.channels[1].statistics.threshold],
                                      boundaries=[0,0,12000,24000],
                                      show_axes=False,
                                      antialiased=True,
                                      unclassified_alpha=0.5,
                                      use_manual_clusters=not well_channel_automatic_classification(qlwell),
                                      highlight_thresholds=threshold_fallback)
                fig.savefig(image_source.get_path('%s/%s_2d.png' % (dbplate.id, well_name)), format='png', dpi=72)
                plt_cleanup(fig)
        
        pm = [pm for pm in dbplate.plate.metrics if pm.reprocess_config_id is None]
        for p in pm:
            Session.delete(p)

        plate = dbplate_tree(dbplate.plate.id)
        
        # override plate_type if supplied (another artifact of bad abstraction)
        if override_plate_type:
            plate.plate_type = override_plate_type

        # this relies on apply_template/apply_setup working correctly on plate addition
        # verify on DR 10005 plate that this works
        if plate.plate_type and plate.plate_type.code in beta_plate_types:
            plate_metrics = get_beta_plate_metrics(plate, qlplate)
        else:
            plate_metrics = process_plate(plate, qlplate)
        Session.add(plate_metrics)