def drift_correct(pipeline):
global id_filter
import numpy as np
import matplotlib.pyplot as plt
#pipeline=visgui.pipeline
filters = {'error_x': [0, 10]}
if 'sig' in pipeline.keys():
dialog = wx.TextEntryDialog(None, 'Diameter (nm): ', 'Enter Fiducial Size', str(pipeline.mdh.getOrDefault('Analysis.FiducialSize', 1000)))
sig = [330., 370.]
if dialog.ShowModal() == wx.ID_OK:
size = float(dialog.GetValue())
sigE = float(np.sqrt((size/(np.sqrt(2)*2.35))**2 + 135.**2)) # Expected std of the bead + expected std of psf
sig = [0.95*sigE, 1.05*sigE]
filters['sig'] = sig
if 'fitError_z0' in pipeline.keys():
filters['fitError_z0'] = [0,30]
recipe = pipeline.recipe
filt_fiducials = FilterTable(recipe, inputName='Fiducials',
outputName='filtered_fiducials', filters=filters)
filt_fiducials.configure_traits(kind='modal')
#print('Adding fiducial filter module')
#recipe.add_module(filt_fiducials)
dbs = DBSCANClustering(recipe,inputName='filtered_fiducials', outputName='clumped_fiducials', columns=['x', 'y'],
searchRadius=500, minClumpSize=10, clumpColumnName='fiducialID')
recipe.add_modules_and_execute([filt_fiducials, dbs])
fids = recipe.namespace['clumped_fiducials']
fid_ids = [int(id) for id in set(fids['fiducialID']) if id > 0]
id_filter = FilterTableByIDs(recipe, inputName='clumped_fiducials', outputName='selected_fiducials',
idColumnName='fiducialID', ids = fid_ids)
#recipe.add_module(id_filter)
fc = FiducialCorrection(recipe, inputLocalizations=pipeline.selectedDataSourceKey,
inputFiducials='selected_fiducials',
outputName='corrected_localizations', outputFiducials='corrected_fiducials')
recipe.add_modules_and_execute([id_filter, fc])
pipeline.selectDataSource('corrected_localizations')
def OnSelROIFT(self, event):
try:
#old glcanvas
x0, y0 = self.visFr.glCanvas.selectionStart
x1, y1 = self.visFr.glCanvas.selectionFinish
except AttributeError:
#new glcanvas
x0, y0 = self.visFr.glCanvas.selectionSettings.start
x1, y1 = self.visFr.glCanvas.selectionSettings.finish
filters = {}
filters['x'] = [float(min(x0, x1)), float(max(x0, x1))] # must ensure all values are eventually scalars to avoid issue with recipe yaml output
filters['y'] = [float(min(y0, y1)), float(max(y0, y1))] # ditto
recipe = self.visFr.pipeline.recipe
ftable = FilterTable(recipe, inputName=self.visFr.pipeline.selectedDataSourceKey,
outputName='selectedROI', filters=filters)
if not ftable.configure_traits(kind='modal'):
return
recipe.add_module(ftable)
recipe.execute()