Exemplo n.º 1
0
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")
Exemplo n.º 2
0
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')
Exemplo n.º 3
0
# [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)
Exemplo n.º 4
0
# 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)