def findTracks(pipeline, rad_var="error_x", multiplier="2.0", nFrames=20):
import PYME.Analysis.DeClump.deClump as deClump
if rad_var == "1.0":
delta_x = 0 * pipeline.mapping["x"] + multiplier
else:
delta_x = multiplier * pipeline.mapping[rad_var]
clumpIndices = deClump.findClumps(
pipeline.mapping["t"].astype("i"),
pipeline.mapping["x"].astype("f4"),
pipeline.mapping["y"].astype("f4"),
delta_x.astype("f4"),
nFrames,
)
numPerClump, b = np.histogram(clumpIndices, np.arange(clumpIndices.max() + 1.5) + 0.5)
trackVelocities = calcTrackVelocity(pipeline.mapping["x"], pipeline.mapping["y"], clumpIndices)
# print b
pipeline.selectedDataSource.clumpIndices = -1 * np.ones(len(pipeline.selectedDataSource["x"]))
pipeline.selectedDataSource.clumpIndices[pipeline.filter.Index] = clumpIndices
pipeline.selectedDataSource.clumpSizes = np.zeros(pipeline.selectedDataSource.clumpIndices.shape)
pipeline.selectedDataSource.clumpSizes[pipeline.filter.Index] = numPerClump[clumpIndices - 1]
pipeline.selectedDataSource.trackVelocities = np.zeros(pipeline.selectedDataSource.clumpIndices.shape)
pipeline.selectedDataSource.trackVelocities[pipeline.filter.Index] = trackVelocities
pipeline.selectedDataSource.setMapping("clumpIndex", "clumpIndices")
pipeline.selectedDataSource.setMapping("clumpSize", "clumpSizes")
pipeline.selectedDataSource.setMapping("trackVelocity", "trackVelocities")
def findTracks(pipeline, rad_var='error_x', multiplier='2.0', nFrames=20):
import PYME.Analysis.DeClump.deClump as deClump
if rad_var == '1.0':
delta_x = 0 * pipeline.mapping['x'] + multiplier
else:
delta_x = multiplier * pipeline.mapping[rad_var]
clumpIndices = deClump.findClumps(pipeline.mapping['t'].astype('i'),
pipeline.mapping['x'].astype('f4'),
pipeline.mapping['y'].astype('f4'),
delta_x.astype('f4'), nFrames)
numPerClump, b = np.histogram(clumpIndices,
np.arange(clumpIndices.max() + 1.5) + .5)
trackVelocities = calcTrackVelocity(pipeline.mapping['x'],
pipeline.mapping['y'], clumpIndices)
#print b
pipeline.selectedDataSource.clumpIndices = -1 * np.ones(
len(pipeline.selectedDataSource['x']))
pipeline.selectedDataSource.clumpIndices[
pipeline.filter.Index] = clumpIndices
pipeline.selectedDataSource.clumpSizes = np.zeros(
pipeline.selectedDataSource.clumpIndices.shape)
pipeline.selectedDataSource.clumpSizes[
pipeline.filter.Index] = numPerClump[clumpIndices - 1]
pipeline.selectedDataSource.trackVelocities = np.zeros(
pipeline.selectedDataSource.clumpIndices.shape)
pipeline.selectedDataSource.trackVelocities[
pipeline.filter.Index] = trackVelocities
pipeline.selectedDataSource.setMapping('clumpIndex', 'clumpIndices')
pipeline.selectedDataSource.setMapping('clumpSize', 'clumpSizes')
pipeline.selectedDataSource.setMapping('trackVelocity', 'trackVelocities')
# [email protected] # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program. If not, see <http://www.gnu.org/licenses/>. # ################ from pylab import * from PYME.Analysis.DeClump import deClump t = arange(0, 200, .02) print((len(t))) x = randn(10000) y = randn(10000) delta_x = .05*ones(x.shape) asg = deClump.findClumps(t.astype('i'), x.astype('f4'), y.astype('f4'), delta_x.astype('f4'), 2) print(asg)
# Copyright David Baddeley, 2012 # [email protected] # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program. If not, see <http://www.gnu.org/licenses/>. # ################ from pylab import * from PYME.Analysis.DeClump import deClump t = arange(0, 200, .02) print((len(t))) x = randn(10000) y = randn(10000) delta_x = .05 * ones(x.shape) asg = deClump.findClumps(t.astype('i'), x.astype('f4'), y.astype('f4'), delta_x.astype('f4'), 2) print(asg)