def __get_1d_background_rgbs(self, qlwell):
rgbs = [None, None]
if well_channel_automatic_classification(qlwell, 0):
rgbs[0] = AUTO_THRESHOLD_FAM_BGCOLOR
else:
rgbs[0] = MANUAL_THRESHOLD_FAM_BGCOLOR
if well_channel_automatic_classification(qlwell, 1):
rgbs[1] = AUTO_THRESHOLD_VIC_BGCOLOR
else:
rgbs[1] = MANUAL_THRESHOLD_VIC_BGCOLOR
return rgbs
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 _compute_well_channel_metrics(qlwell, well_channel_metric, channel_num):
"""
Internal method for populating a WellChannelMetric object from statistics
determined by analyzing the QLWell's channel object.
This will populate the well_channel_metric object with information such
as positives and negatives, concentration, polydispersity, and other
metrics that have separate values for FAM and VIC channels.
:param qlwell: The QLWell object created by reading a QLP file.
:param well_channel_metric: The WellChannelMetric object to populate.
:param channel_num: Which channel to analyze.
"""
# for convenience
wcm = well_channel_metric
stats = qlwell.channels[channel_num].statistics
wcm.min_quality_gating = stats.min_quality_gate
wcm.min_quality_gating_conf = stats.min_quality_gate_conf
wcm.min_width_gate = stats.min_width_gate
wcm.min_width_gate_conf = stats.min_width_gate_conf
wcm.max_width_gate = stats.max_width_gate
wcm.max_width_gate_conf = stats.max_width_gate_conf
wcm.width_gating_sigma = stats.width_gating_sigma
# TODO: try to guarantee automatic threshold here?
wcm.threshold = stats.threshold
wcm.threshold_conf = stats.threshold_conf
wcm.auto_threshold_expected = False
wcm.concentration = stats.concentration
wcm.conc_lower_bound = stats.concentration_lower_bound
wcm.conc_upper_bound = stats.concentration_upper_bound
wcm.conc_calc_mode = stats.concentration_calc_mode
wcm.clusters_automatic = well_channel_automatic_classification(qlwell, channel_num)
wcm.decision_tree_flags = qlwell.channels[channel_num].decision_tree_flags
ap = accepted_peaks(qlwell)
if channel_num == 0:
ampfunc = fam_amplitudes
elif channel_num == 1:
ampfunc = vic_amplitudes
else:
raise ValueError, "Incompatible channel number: %s" % channel_num
wcm.amplitude_mean = np.mean(ampfunc(ap))
wcm.amplitude_stdev = np.std(ampfunc(ap))
allpeaks = qlwell.peaks
wcm.total_events_amplitude_mean = np.mean(ampfunc(allpeaks))
wcm.total_events_amplitude_stdev = np.std(ampfunc(allpeaks))
above_min_peaks = above_min_amplitude_peaks(qlwell)
quality_gated_peaks = quality_rejected(above_min_peaks, wcm.min_quality_gating, channel_num, include_vertical_streak_flagged=False)
wcm.quality_gated_peaks = len(quality_gated_peaks)
width_gated_peaks = width_rejected(above_min_peaks, wcm.min_width_gate, wcm.max_width_gate, channel_num)
wcm.width_gated_peaks = len(width_gated_peaks)
# TODO add min amplitude, vertical streak
wcm.s_value = separation_value(ap, channel_num, wcm.threshold)
p_plus, p, p_minus = rain_pvalues(ap, channel_num, wcm.threshold)
wcm.rain_p_plus = p_plus
wcm.rain_p = p
wcm.rain_p_minus = p_minus
## extra cluster events...
NEW_DROPLET_CLUSTER_METRICS_CALCULATOR.compute(qlwell, qlwell.channels[channel_num], wcm)
# DEFAULT_TEAVALS.compute(qlwell, qlwell.channels[channel_num], wcm)
DEFAULT_POLYD_CALC.compute(qlwell, qlwell.channels[channel_num], wcm)
DEFAULT_EXTRAC_CALC.compute(qlwell, qlwell.channels[channel_num], wcm)
DEFAULT_NTC_POSITIVE_CALCULATOR.compute(qlwell, qlwell.channels[channel_num], wcm)
wcm.baseline_mean = qlwell.channels[channel_num].statistics.baseline_mean
wcm.baseline_stdev = qlwell.channels[channel_num].statistics.baseline_stdev
wcm.cluster_conf = qlwell.channels[channel_num].statistics.cluster_conf
positive_peaks, negative_peaks, unclassified_peaks = well_observed_positives_negatives(qlwell, channel_num)
if len(positive_peaks) > 0 or len(negative_peaks) > 0:
wcm.positive_peaks = len(positive_peaks)
wcm.negative_peaks = len(negative_peaks)
wcm.positive_mean = np.mean(ampfunc(positive_peaks))
wcm.positive_stdev = np.std(ampfunc(positive_peaks))
wcm.negative_mean = np.mean(ampfunc(negative_peaks))
wcm.negative_stdev = np.std(ampfunc(negative_peaks))
wcm.positive_skew = skew(positive_peaks, channel_num)
wcm.positive_kurtosis = kurtosis(positive_peaks, channel_num)
wcm.nonpositive_skew = skew(negative_peaks, channel_num)
wcm.nonpositive_kurtosis = kurtosis(negative_peaks, channel_num)
# CLUSTER-TODO: this is not going to be right for clusters. Consider
# changing this.
wcm.concentration_rise_ratio = quartile_concentration_ratio(qlwell, peaks=ap,
channel_num=channel_num, threshold=wcm.threshold,
min_events=4000)
del positive_peaks
del negative_peaks
del unclassified_peaks
else:
wcm.nonpositive_skew = skew(ap, channel_num)
wcm.nonpositive_kurtosis = kurtosis(ap, channel_num)
del ap
# daisy chain just in case
return wcm
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)
