def cluster2d(self, id=None, *args, **kwargs):
from qtools.lib.mplot import plot_cluster_2d, cleanup, render as plt_render
from qtools.lib.nstats.peaks import accepted_peaks
response.content_type = 'image/png'
qlwell = self.__qlwell_from_threshold_form(id)
self.__set_threshold_context(qlwell)
max_amplitudes = [self.form_result['max_fam_amplitude'], self.form_result['max_vic_amplitude']]
boundaries = (-2000,-2000,max_amplitudes[1],max_amplitudes[0])
# to emulate current behavior -- include gated events
peaks = accepted_peaks(qlwell)
threshold_fallback = qlwell.clustering_method == QLWell.CLUSTERING_TYPE_THRESHOLD
fig = plot_cluster_2d(peaks,
thresholds=(c.fam_threshold, c.vic_threshold),
boundaries=boundaries,
use_manual_clusters=not well_channel_automatic_classification(qlwell),
highlight_thresholds=threshold_fallback)
response.content_type = 'image/png'
imgdata = plt_render(fig, dpi=72)
cleanup(fig)
return imgdata
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)
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)