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FastAnalysis tutorial

Benjamin Gallois

Benjamin Gallois

FastTrack creator
Copyright (C) FastTrack.
Permission is granted to copy, distribute and/or modify this document.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.

Get started with FastAnalysis#

FastAnalysis is a python library that simplifies the importation of a tracking analysis performed with FastTrack. Easily select data for a given object or a given timepoint.

Package installation#

The FastAnalysis package can be installed following the provided instruction at https://github.com/FastTrackOrg/FastAnalysis.

import sys
!{sys.executable} -m pip install fastanalysis

Package usage#

import fastanalysis as fa

Load the tracking data and get the basic information.#

data = fa.Load("tracking.txt")
print("Total objects: ", data.getObjectNumber())
Total objects: 14
print("Keys: ", data.getKeys())
Keys: ['xHead', 'yHead', 'tHead', 'xTail', 'yTail', 'tTail', 'xBody', 'yBody', 'tBody', 'curvature', 'areaBody', 'perimeterBody', 'headMajorAxisLength', 'headMinorAxisLength', 'headExcentricity', 'tailMajorAxisLength', 'tailMinorAxisLength', 'tailExcentricity', 'bodyMajorAxisLength', 'bodyMinorAxisLength', 'bodyExcentricity', 'imageNumber', 'id']

Select the tracking data for a given object#

data.getObjects(0)
xHeadyHeadtHeadxTailyTailtTailxBodyyBodytBodycurvature...headMinorAxisLengthheadExcentricitytailMajorAxisLengthtailMinorAxisLengthtailExcentricitybodyMajorAxisLengthbodyMinorAxisLengthbodyExcentricityimageNumberid
0514.327333.1205.816190499.960327.7276.102260508.345330.8765.9439500.000348...2.986260.92138811.407502.064610.98348517.75782.862270.98692400
14512.965332.5755.866170499.435327.7596.052000507.626330.6735.9510200.000370...2.949200.92158910.630101.796320.98561916.59122.559000.98803410
28510.519331.4175.888830495.784327.3666.128890504.484329.7586.0208800.000285...3.026470.93193711.808201.976100.98589817.95812.761520.98810620
42508.379330.5425.978240493.210327.4606.159440502.213329.2916.0839200.000217...3.100270.92864911.670101.976230.98555818.08202.706410.98873530
56503.990331.7644.889370496.990322.5096.183440501.029327.8565.3787600.001812...2.920670.9146808.251743.012760.93096613.09475.194180.91796540
..................................................................
2414515.720332.2330.047758504.152332.7586.219550510.844332.4560.0315500.000053...2.836200.8910317.969852.214980.96060413.37942.480610.9826621950
2428514.518331.2296.173800502.533333.4480.410982509.848332.0910.1881330.000454...3.014480.8952299.275581.867100.97953114.09093.118600.9752011960
2442515.022333.3016.039930503.432330.3606.110450510.456332.1446.0461900.000040...2.862680.8945788.454941.973920.97236513.74232.443180.9840691970
2456514.364332.3220.089009501.409333.2716.061220509.183332.6990.0302770.000309...2.706090.9261439.873312.720560.96128815.09903.040300.9795181980
2470514.682333.1746.045460503.418331.4820.110999510.000332.4726.1645600.000434...2.905090.8811788.319822.311970.96061413.21192.862640.9762451990

190 rows × 23 columns

Select the tracking data for a list of objects#

data.getObjects([0, 2, 4])
xHeadyHeadtHeadxTailyTailtTailxBodyyBodytBodycurvature...headMinorAxisLengthheadExcentricitytailMajorAxisLengthtailMinorAxisLengthtailExcentricitybodyMajorAxisLengthbodyMinorAxisLengthbodyExcentricityimageNumberid
0514.3270333.1205.816190499.9600327.7276.102260508.3450330.8765.9439500.000348...2.986260.92138811.407502.064610.98348517.75782.862270.98692400
223.9978287.7153.70646034.9722278.8363.99819029.2056283.5053.8484400.000714...3.022240.87828411.092502.613040.97185816.56703.009620.98336102
4480.5800213.4821.282360478.1250228.5201.533030479.4280220.5431.4256700.000539...3.452080.87382811.803602.224890.98207517.92043.029780.98560404
14512.9650332.5755.866170499.4350327.7596.052000507.6260330.6735.9510200.000370...2.949200.92158910.630101.796320.98561916.59122.559000.98803410
1619.4579293.0224.28861025.5579281.2064.18379021.8962288.3024.2337900.000041...3.105270.8937778.954531.953080.97592415.14972.606900.98508412
..................................................................
2449477.5150253.2590.494507466.0410261.0180.831531472.8820256.3820.6224160.000357...3.183300.8903229.949442.331950.97214515.84643.121300.9804091982
2456514.3640332.3220.089009501.4090333.2716.061220509.1830332.6990.0302770.000309...2.706090.9261439.873312.720560.96128815.09903.040300.9795181980
2462413.9010332.3865.582420401.1560322.8155.799440408.5330328.3565.6579200.000666...3.249540.92055511.510302.472300.97666018.49793.051430.9863001994
2463479.2630250.7160.644442465.5060258.4760.362501473.8190253.7840.5034160.000200...2.964350.93026211.552501.764070.98827318.13292.751700.9884191992
2470514.6820333.1746.045460503.4180331.4820.110999510.0000332.4726.1645600.000434...2.905090.8811788.319822.311970.96061413.21192.862640.9762451990

544 rows × 23 columns

Select the tracking data for a given image#

data.getFrames(100)
xHeadyHeadtHeadxTailyTailtTailxBodyyBodytBodycurvature...headMinorAxisLengthheadExcentricitytailMajorAxisLengthtailMinorAxisLengthtailExcentricitybodyMajorAxisLengthbodyMinorAxisLengthbodyExcentricityimageNumberid
1220471.9020331.890000.269094460.4110335.53600.205151467.340333.34000.2859300.000054...3.023250.8793429.42872.362850.96809014.06882.711880.9812461000
1221394.0560311.183005.862420380.7090302.96605.533100388.653307.86805.7105700.000782...3.186650.91114112.05672.132180.98423818.02803.116680.9849431009
1222294.9150323.621005.928470280.3880319.39406.078460289.216321.96406.0063400.000511...3.085210.90804111.15571.664430.98880717.28672.575670.9888381002
1223219.1200191.089000.631238205.3180198.12800.088934213.337194.04100.4375130.000843...3.960580.88192710.67983.266380.95208117.76984.407370.9687531003
1224191.985048.839601.338080185.160062.87220.851539188.64855.64791.0732400.001664...3.498890.86710112.00512.620740.97588118.39143.786920.9785721005
1225504.05209.828320.558700489.462018.42430.514300497.87813.46940.5317250.000089...3.411340.91230312.33651.994890.98683919.57192.784730.98982610013
1226304.1520202.554005.721260290.9760193.59605.719690298.600198.77705.6952400.000052...3.280290.90531511.63251.985470.98532618.47332.687150.9893641007
1227413.6920329.851000.026077399.8350331.48400.161337408.339330.48200.1138990.000115...3.073540.91478610.46481.936150.98273616.16562.631910.98665710012
122884.2595119.739003.79733096.9216110.71603.73422090.450115.32903.7564200.000192...3.526030.85367012.64272.158300.98532118.53392.842530.98816910010
1229364.406035.894100.353083348.850040.42746.276460357.95937.77400.2516170.000484...3.373840.92017111.34583.336960.95577018.61913.795430.9790031004
1230490.663044.942200.503424476.704052.56560.472187485.12547.97060.4955290.000124...3.275670.92236810.99151.971340.98378518.27922.724580.98882910011
1231510.174040.702705.941170497.300034.72025.673400505.11038.34865.8304100.000431...3.116210.90213410.28662.083100.97928116.23742.872590.9842271006

12 rows × 23 columns

Select the tracking data for a list of images#

data.getFrames([100, 102])
xHeadyHeadtHeadxTailyTailtTailxBodyyBodytBodycurvature...headMinorAxisLengthheadExcentricitytailMajorAxisLengthtailMinorAxisLengthtailExcentricitybodyMajorAxisLengthbodyMinorAxisLengthbodyExcentricityimageNumberid
1220471.9020331.890000.269094460.4110335.53600.205151467.3400333.34000.2859300.000054...3.023250.8793429.428702.362850.96809014.06882.711880.9812461000
1221394.0560311.183005.862420380.7090302.96605.533100388.6530307.86805.7105700.000782...3.186650.91114112.056702.132180.98423818.02803.116680.9849431009
1222294.9150323.621005.928470280.3880319.39406.078460289.2160321.96406.0063400.000511...3.085210.90804111.155701.664430.98880717.28672.575670.9888381002
1223219.1200191.089000.631238205.3180198.12800.088934213.3370194.04100.4375130.000843...3.960580.88192710.679803.266380.95208117.76984.407370.9687531003
1224191.985048.839601.338080185.160062.87220.851539188.648055.64791.0732400.001664...3.498890.86710112.005102.620740.97588118.39143.786920.9785721005
1225504.05209.828320.558700489.462018.42430.514300497.878013.46940.5317250.000089...3.411340.91230312.336501.994890.98683919.57192.784730.98982610013
1226304.1520202.554005.721260290.9760193.59605.719690298.6000198.77705.6952400.000052...3.280290.90531511.632501.985470.98532618.47332.687150.9893641007
1227413.6920329.851000.026077399.8350331.48400.161337408.3390330.48200.1138990.000115...3.073540.91478610.464801.936150.98273616.16562.631910.98665710012
122884.2595119.739003.79733096.9216110.71603.73422090.4500115.32903.7564200.000192...3.526030.85367012.642702.158300.98532118.53392.842530.98816910010
1229364.406035.894100.353083348.850040.42746.276460357.959037.77400.2516170.000484...3.373840.92017111.345803.336960.95577018.61913.795430.9790031004
1230490.663044.942200.503424476.704052.56560.472187485.125047.97060.4955290.000124...3.275670.92236810.991501.971340.98378518.27922.724580.98882910011
1231510.174040.702705.941170497.300034.72025.673400505.110038.34865.8304100.000431...3.116210.90213410.286602.083100.97928116.23742.872590.9842271006
1244471.4650333.537000.001856455.8950333.13700.067247465.2880333.37806.2743800.000043...3.020420.92220111.221602.375280.97734117.82542.667390.9887411020
1245396.0970314.669005.861210381.8960308.44705.874390390.4180312.18005.8703400.000174...3.301170.89973711.373001.843610.98677417.80032.684290.9885641029
1246294.3930324.256005.943700279.2910320.19506.066590288.5890322.69606.0208800.000204...3.054220.91695111.740101.616880.99047117.89232.528350.9899661022
1247220.4620188.585000.373316205.5400192.79700.203012214.4550190.28100.2741690.000333...4.104330.85991510.676802.459920.97309617.73993.509930.9802311023
1248440.7830245.341000.994409432.8300259.22901.086010437.0160251.92101.0574800.000134...3.148100.90116512.806901.984030.98792719.21852.573220.9909961028
1249181.716048.267401.795220183.281064.69471.403630182.458056.22881.6187000.003078...3.549040.87775613.013903.974630.95222019.45174.327840.9749351025
1250501.16507.834230.516324484.943016.98560.489818494.558011.56410.5100980.000011...3.437800.92519512.715001.937350.98832421.22122.826280.99109210213
1251299.4490204.642005.764900288.1070193.91805.171220294.7050200.16005.5066500.004240...3.511180.91843610.650602.644290.96868917.96874.105680.9735461027
1252423.3440226.693001.685010423.8160242.81901.563020423.5670234.34301.5962000.000203...3.482680.85736612.903702.012380.98776419.01442.792580.9891561021
1253419.6690331.305000.240837405.4400333.29206.160820413.7010332.13700.1049040.000355...3.164410.90444410.927102.835840.96573716.71113.409280.97896810212
125474.8227119.963003.81445087.7565110.91203.72207080.8288115.76003.7493500.000395...3.660700.85866212.484002.126600.98538418.73892.972670.98733710210
1255372.356033.297500.324467357.087035.50026.115410365.944034.22380.1091670.000586...3.469470.90275911.640002.454000.97752417.88633.818490.9769461024
1256486.907043.341600.455006472.011050.96010.484798480.885046.42570.4720280.000043...3.400550.92001110.946802.101200.98140519.03972.830450.98888810211
1257506.598042.846105.625700494.800035.60515.914810501.873039.94925.7496800.000309...3.319370.8894439.903122.086010.97756315.91513.017960.9818561026

26 rows × 23 columns

Select the tracking data for a list of images and a list of objects#

data.getObjectsInFrames(ids=[0,2,4], indexes=[100,102])
xHeadyHeadtHeadxTailyTailtTailxBodyyBodytBodycurvature...headMinorAxisLengthheadExcentricitytailMajorAxisLengthtailMinorAxisLengthtailExcentricitybodyMajorAxisLengthbodyMinorAxisLengthbodyExcentricityimageNumberid
1220471.902331.89000.269094460.411335.53600.205151467.340333.34000.2859300.000054...3.023250.8793429.42872.362850.96809014.06882.711880.9812461000
1222294.915323.62105.928470280.388319.39406.078460289.216321.96406.0063400.000511...3.085210.90804111.15571.664430.98880717.28672.575670.9888381002
1229364.40635.89410.353083348.85040.42746.276460357.95937.77400.2516170.000484...3.373840.92017111.34583.336960.95577018.61913.795430.9790031004
1244471.465333.53700.001856455.895333.13700.067247465.288333.37806.2743800.000043...3.020420.92220111.22162.375280.97734117.82542.667390.9887411020
1246294.393324.25605.943700279.291320.19506.066590288.589322.69606.0208800.000204...3.054220.91695111.74011.616880.99047117.89232.528350.9899661022
1255372.35633.29750.324467357.08735.50026.115410365.94434.22380.1091670.000586...3.469470.90275911.64002.454000.97752417.88633.818490.9769461024

6 rows × 23 columns

Check if a list of objects is in a frame#

data.isObjectsInFrame(ids=[0,2,4], index=100)
[True, True, True]

Basic plotting#

  • Plot the velocity distribution for given objects
import matplotlib.pyplot as plt
%matplotlib inline
plotObj = fa.Plot(data)
plotObj.velocityDistribution(ids=[0, 1], key="Body", pooled=False, subplots=True);

png

plotObj.velocityDistribution(ids=[0, 1], key="Body", pooled=False, subplots=False);

png

plotObj.velocityDistribution(ids=[0, 1], key="Body", pooled=True);

png

Using seaborn on extracted data#

  • Plot the distribution of positions.
import seaborn as sns
data_object_0 = data.getObjects(0)
sns.jointplot(data=data_object_0, x="xBody", y="yBody");

png

# All objects pooled
sns.kdeplot(data=data.getObjects(list(range(data.getObjectNumber()))), x="xBody", y="yBody", shade=True);

png

  • Compare the distributions of displacements.
tmp = data.getObjects([0,2,4])
tmp["displacement"] = (tmp["xBody"]**2 + tmp["yBody"]**2)**0.5
sns.violinplot(data=tmp, x="id", y="displacement");

png

sns.boxplot(data=tmp, x="id", y="displacement");

png

sns.boxenplot(data=tmp, x="id", y="displacement");

png