LMT-analysis v1.0.3 implemented: fixes #10, closes #10

- Event "approach contact" corrected - Events "follow zone" and "side walk" updated: they no longer compute on a detection where the head and tail are not detected - Fix a problem with the Nest3_ event. The stop condition necessary is now considered correctly - Fix an head/tail problem condition in the followzone event BootstrapVue3 updated to v0.3.11
ntorquet · Oct 5, 2022 · 23705bd · 23705bd
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diff --git a/README.md b/README.md
@@ -48,7 +48,7 @@ django-admin startproject lmt_toolkit_analysis
 ## Javascript Requirements and installations
 - vue-cli
 - axios
-- bootstrap-vue-3
+- bootstrap-vue-3@0.3.11
 - bootstrap-icons-vue
 - vue3-popper
 - chart.js (for plots)

diff --git a/frontend/package-lock.json b/frontend/package-lock.json
diff --git a/frontend/package.json b/frontend/package.json
@@ -8,9 +8,11 @@
   },
   "dependencies": {
     "@meforma/vue-toaster": "^1.3.0",
+    "@popperjs/core": "^2.11.6",
     "axios": "^0.27.2",
+    "bootstrap": "^5.2.2",
     "bootstrap-icons-vue": "^1.8.1",
-    "bootstrap-vue-3": "^0.1.14",
+    "bootstrap-vue-3": "^0.3.11",
     "chart.js": "^3.8.0",
     "core-js": "^3.8.3",
     "stylus": "^0.58.1",

diff --git a/frontend/src/views/VersionHistory.vue b/frontend/src/views/VersionHistory.vue
@@ -6,25 +6,66 @@
     Some important changes will impact the results. This page gives you an history of all changes so that you know if a new analysis is needed.
   </b-card>
 
-  <table class="table table-striped table-hover">
-    <thead>
-      <tr>
-        <th style="width: 5%">Version</th>
-        <th style="width: 10%">Date</th>
-        <th>Changes / Notes</th>
-        <th>Release</th>
-      </tr>
-    </thead>
-    <tr>
-      <td>v0.1</td>
-      <td>2022 september</td>
-      <td>
+  <b-table-simple striped hover>
+    <b-thead>
+      <b-tr>
+        <b-th style="width: 5%">Version</b-th>
+        <b-th style="width: 10%">Date</b-th>
+        <b-th>LMT-toolkit Changes / Notes</b-th>
+        <b-th>LMT-analysis Changes / Notes</b-th>
+        <b-th>LMT-analysis release</b-th>
+      </b-tr>
+    </b-thead>
+    <b-tr>
+      <b-td><a href="https://github.com/ntorquet/lmt_toolkit_analysis/releases/tag/v0.1" target="_blank">
+        <b-badge variant="dark" pill><b-icon-github></b-icon-github> v0.1.1</b-badge></a>
+      </b-td>
+      <b-td>2022 october</b-td>
+      <b-td>
         <strong>Pre release version</strong>:<br />
+        Wrong message color if temperature higher than 26°C corrected<br />
+        BootstrapVue3 updated to v0.3.11
+      </b-td>
+      <b-td>
+        LMT-analysis upgraded (v1.0.0 to v1.0.3):
+        <b-list-group>
+          <b-list-group-item class="d-flex justify-content-between align-items-center">
+            Event "approach contact" corrected
+            <a href="https://github.com/fdechaumont/lmt-analysis/releases/tag/v1.0.1" target="_blank"><b-badge variant="secondary" pill><b-icon-github></b-icon-github> v1.0.1</b-badge></a>
+          </b-list-group-item>
+          <b-list-group-item class="d-flex justify-content-between align-items-center">
+            Events "follow zone" and "side walk" updated: they no longer compute on a detection where the head and tail are not detected
+            <a href="https://github.com/fdechaumont/lmt-analysis/releases/tag/v1.0.1" target="_blank"><b-badge variant="secondary" pill><b-icon-github></b-icon-github> v1.0.1</b-badge></a>
+          </b-list-group-item>
+          <b-list-group-item class="d-flex justify-content-between align-items-center">
+            Fix a problem with the Nest3_ event. The stop condition necessary is now considered correctly
+            <a href="https://github.com/fdechaumont/lmt-analysis/releases/tag/v1.0.2" target="_blank"><b-badge variant="secondary" pill><b-icon-github></b-icon-github> v1.0.2</b-badge></a>
+          </b-list-group-item>
+          <b-list-group-item class="d-flex justify-content-between align-items-center">
+            Fix an head/tail problem condition in the followzone event
+            <a href="https://github.com/fdechaumont/lmt-analysis/releases/tag/v1.0.3" target="_blank"><b-badge variant="secondary" pill><b-icon-github></b-icon-github> v1.0.3</b-badge></a>
+          </b-list-group-item>
+        </b-list-group>
+      </b-td>
+      <b-td>
+        <a href="https://github.com/fdechaumont/lmt-analysis/releases/tag/v1.0.3" target="_blank"><b-badge variant="secondary" pill><b-icon-github></b-icon-github> v1.0.3</b-badge></a>
+      </b-td>
+    </b-tr>
+    <b-tr>
+      <b-td><a href="https://github.com/ntorquet/lmt_toolkit_analysis/releases/tag/v0.1" target="_blank">
+        <b-badge variant="dark" pill><b-icon-github></b-icon-github> v0.1</b-badge></a>
+      </b-td>
+      <b-td>2022 september</b-td>
+      <b-td>
+        <strong>Pre release version</strong><br />
+      </b-td>
+      <b-td>
+
         Initial code for reliability. Analysis code is a fork of <a href="https://github.com/fdechaumont/lmt-analysis" target="_blank">lmt-analysis</a> on July 13, 2022.
-      </td>
-      <td><a href="https://github.com/ntorquet/lmt_toolkit_analysis/releases/tag/v0.1" target="_blank"><b-icon-github></b-icon-github> LMT-toolkit analysis v0.1</a></td>
-    </tr>
-  </table>
+      </b-td>
+      <b-td>Pre release corresponding to <a href="https://github.com/fdechaumont/lmt-analysis/releases/tag/v1.0.0" target="_blank"><b-badge variant="secondary" pill><b-icon-github></b-icon-github> v1.0.0</b-badge></a></b-td>
+    </b-tr>
+  </b-table-simple>
 </template>
 
 <script>

diff --git a/lmt_toolkit_analysis/lmttoolkitanalysis/LMT/__init__.py b/lmt_toolkit_analysis/lmttoolkitanalysis/LMT/__init__.py
@@ -1,4 +1,5 @@
-"""
-Created 13 aout 2019
+'''
+Created on 13 aout 2018
+
 @author: Fab
-"""
+'''
diff --git a/lmt_toolkit_analysis/lmttoolkitanalysis/LMT/lmtanalysis/Animal.py b/lmt_toolkit_analysis/lmttoolkitanalysis/LMT/lmtanalysis/Animal.py
@@ -1,5 +1,5 @@
 '''
-Created on 7 sept 2017
+Created on 7 sept. 2017
 @author: Fab
 '''
 
@@ -622,7 +622,9 @@ def getMeanBodyLength (self, tmin=0, tmax=None):
                 continue
 
             a = self.detectionDictionnary.get( key )
-            bodySizeList.append(a.getBodySize())
+
+            if (a.isHeadAndTailDetected()):
+                bodySizeList.append(a.getBodySize())
 
         mean = np.nanmean(bodySizeList)
         print( "mean animal bodysize: "  , mean )

diff --git a/lmt_toolkit_analysis/lmttoolkitanalysis/LMT/lmtanalysis/BuildEventApproachContact.py b/lmt_toolkit_analysis/lmttoolkitanalysis/LMT/lmtanalysis/BuildEventApproachContact.py
@@ -15,63 +15,105 @@
 from .Measure import *
 from .EventTimeLineCache import EventTimeLineCached
 
+
 def flush( connection ):
     ''' flush event in database '''
     deleteEventTimeLineInBase(connection, "Approach contact" )
 
 def reBuildEvent( connection, file, tmin=None, tmax=None , pool = None ): 
 
+    '''
+    This event represents the approaches that is just before a contact (longer than 3 frames); if the speeds of the two animals
+    involved in the contact are not different enough, the animal approaching cannot be defined and therefore the event is not computed 
+    for this contact.
+    This event is a reduction of distance between two animals, one going more quickly than the other, until they get in contact.
+    This event ends at the frame just before the contact and lasts the whole time of approach.
+    '''
+
     #pool = AnimalPool( )
     #pool.loadAnimals( connection )
     #pool.loadDetection( start = tmin, end = tmax )
     if ( pool == None ):
         pool = AnimalPool( )
         pool.loadAnimals( connection )
         pool.loadDetection( start = tmin, end = tmax , lightLoad=True )
-
-    contactDicoDico = {}
+
+    eventName = "Approach contact"        
+    print ( eventName )
+    print('Computing ', eventName)
+
+    #upload the timelines of interest
+    contactDico = {}
     approachDico = {}
     for animal in range( 1 , pool.getNbAnimals()+1 ):
         for idAnimalB in range( 1 , pool.getNbAnimals()+1 ):
             if ( animal == idAnimalB ):
                 continue
-            ''' I take the dictionnary of event of the contact event, that's why I put DicoDico '''
-            contactDicoDico[animal, idAnimalB] = EventTimeLineCached( connection, file, "Contact", animal, idAnimalB, minFrame=tmin, maxFrame=tmax ).getDictionnary()
-            ''' This one is the dico of event '''
-            approachDico[animal, idAnimalB] = EventTimeLineCached( connection, file, "Social approach", animal, idAnimalB, minFrame=tmin, maxFrame=tmax ) #fait une matrice de toutes les approches à deux possibles
-
+            #charge the contact timelines as a dictionary of timelines
+            contactDico[animal, idAnimalB] = EventTimeLineCached( connection, file, "Contact", animal, idAnimalB, minFrame=tmin, maxFrame=tmax )
+            #charge the approach timelines as a dictionary of timelines
+            approachDico[animal, idAnimalB] = EventTimeLineCached( connection, file, "Approach", animal, idAnimalB, minFrame=tmin, maxFrame=tmax ) #fait une matrice de toutes les approches à deux possibles
+
+    #initiate the timeline of approach before a contact
+    appContactTimeLineDico = {}
+    appContactTimeLineDicoDico = {}
+    for animal in range( 1 , pool.getNbAnimals()+1 ):
+        for idAnimalB in range( 1 , pool.getNbAnimals()+1 ):
+            if ( animal == idAnimalB ):
+                continue
+
+            appContactTimeLineDico[ animal, idAnimalB ] = EventTimeLine( None, eventName , animal , idAnimalB , None , None , loadEvent=False )
+            appContactTimeLineDicoDico[ animal, idAnimalB ] = {}
+
+    #upload the dictionary for each approach timeline
+    approachDicoDico = {}
     for animal in range( 1 , pool.getNbAnimals()+1 ):
-
         for idAnimalB in range( 1 , pool.getNbAnimals()+1 ):
             if( animal == idAnimalB ):
                 continue
 
-            eventName = "Approach contact"        
-            print ( eventName )
+            #upload the dictionary for each approach timeline:
+            approachDicoDico[animal, idAnimalB] = approachDico[animal, idAnimalB].getDictionary()
 
-            appContactTimeLine = EventTimeLine( None, eventName , animal , idAnimalB , None , None , loadEvent=False )
-
-            for eventApp in approachDico[animal, idAnimalB].eventList:
-
-                ''' new code: '''
+    #check who approached who before the contact
+    for animal in range( 1 , pool.getNbAnimals()+1 ):
+        for idAnimalB in range( 1 , pool.getNbAnimals()+1 ):
+            if( animal == idAnimalB ):
+                continue
+
+            #clean the contact timeline to keep only events longer than 3 frames
+            contactDico[animal, idAnimalB].mergeCloseEvents(numberOfFrameBetweenEvent=1)
+            contactDico[animal, idAnimalB].removeEventsBelowLength(maxLen=3)
+
+
+            for contactEvent in contactDico[animal, idAnimalB].eventList:
+                frameBeforeContact = contactEvent.startFrame - 1
+                #if the frame before the contact is within the approach timeline of A to B, then add the corresponding approach event to the approach contact timeline
+                if frameBeforeContact in approachDicoDico[animal, idAnimalB]:
+                    #print('A approaches B')
+                    approachEvent = approachDico[animal, idAnimalB].getEventAt( frameBeforeContact )
+                    for t in range (approachEvent.startFrame, frameBeforeContact + 1):
+                        appContactTimeLineDicoDico[animal, idAnimalB][t] = True
 
-                for t in range( eventApp.endFrame - TIME_WINDOW_BEFORE_EVENT, eventApp.endFrame + TIME_WINDOW_BEFORE_EVENT + 1 ):
-
-                    if ( t in contactDicoDico[animal, idAnimalB] ):
-                        appContactTimeLine.eventList.append(eventApp)
-                        break
-
-
-                ''' old code(slow)
+                #if the frame before the contact is within the approach timeline of B to A, then add the corresponding approach event to the approach contact timeline
+                elif frameBeforeContact in approachDicoDico[idAnimalB, animal]:
+                    #print('B approaches A')
+                    approachEvent = approachDico[idAnimalB, animal].getEventAt( frameBeforeContact )
+                    for t in range (approachEvent.startFrame, frameBeforeContact + 1):
+                        appContactTimeLineDicoDico[idAnimalB, animal][t] = True
 
-                bug: est ce que ca n aurait pas du etre eventContact.startFrame ? ou eventApp.endFrame-TIME_WINDOW_BEFORE_EVENT, eventApp.endFrame+TIME_WINDOW_BEFORE_EVENT ?
+                #if the frame before the contact is not within any approach timeline, then go to the next contact event
+                else:
+                    #print('Not possible to decide who is approaching who.')
+                    continue
 
-                for eventContact in contactDicoDico[animal, idAnimalB].eventList:
-                    if (eventApp.overlapInT(eventContact.endFrame-TIME_WINDOW_BEFORE_EVENT, eventContact.endFrame+TIME_WINDOW_BEFORE_EVENT) == True):
-                        appContactTimeLine.eventList.append(eventApp)
-                '''
-
-            appContactTimeLine.endRebuildEventTimeLine(connection)
+
+    for animal in range( 1 , pool.getNbAnimals()+1 ):
+        for idAnimalB in range( 1 , pool.getNbAnimals()+1 ):
+            if( animal == idAnimalB ):
+                continue
+            appContactTimeLineDico[animal, idAnimalB].reBuildWithDictionnary( appContactTimeLineDicoDico[animal, idAnimalB] )
+            appContactTimeLineDico[animal, idAnimalB].endRebuildEventTimeLine( connection )
 
     # log process
     from .TaskLogger import TaskLogger

diff --git a/...analysis/LMT/lmtanalysis/BuildEventExclusiveCleanOralOralSideSideNoseAnogenitalContact.py b/...analysis/LMT/lmtanalysis/BuildEventExclusiveCleanOralOralSideSideNoseAnogenitalContact.py
@@ -5,16 +5,16 @@
 '''
 import sqlite3
 from time import *
-from lmtanalysis.Chronometer import Chronometer
-from lmtanalysis.Animal import *
-from lmtanalysis.Detection import *
-from lmtanalysis.Measure import *
+from .Chronometer import Chronometer
+from .Animal import *
+from .Detection import *
+from .Measure import *
 import matplotlib.pyplot as plt
 import numpy as np
-from lmtanalysis.Event import *
-from lmtanalysis.Measure import *
-from lmtanalysis.EventTimeLineCache import EventTimeLineCached
-from lmtanalysis.BehaviouralSequencesUtil import exclusiveEventList, contactTypeList
+from .Event import *
+from .Measure import *
+from .EventTimeLineCache import EventTimeLineCached
+from .BehaviouralSequencesUtil import exclusiveEventList, contactTypeList
 
 def flush( connection ):
     ''' flush event in database '''

diff --git a/...oolkit_analysis/lmttoolkitanalysis/LMT/lmtanalysis/BuildEventExclusiveMoveStopIsolated.py b/...oolkit_analysis/lmttoolkitanalysis/LMT/lmtanalysis/BuildEventExclusiveMoveStopIsolated.py
@@ -5,16 +5,16 @@
 '''
 import sqlite3
 from time import *
-from lmtanalysis.Chronometer import Chronometer
-from lmtanalysis.Animal import *
-from lmtanalysis.Detection import *
-from lmtanalysis.Measure import *
+from .Chronometer import Chronometer
+from .Animal import *
+from .Detection import *
+from .Measure import *
 import matplotlib.pyplot as plt
 import numpy as np
-from lmtanalysis.Event import *
-from lmtanalysis.Measure import *
-from lmtanalysis.EventTimeLineCache import EventTimeLineCached
-from lmtanalysis.BehaviouralSequencesUtil import exclusiveEventList
+from .Event import *
+from .Measure import *
+from .EventTimeLineCache import EventTimeLineCached
+from .BehaviouralSequencesUtil import exclusiveEventList
 
 def flush( connection ):
     ''' flush event in database '''

diff --git a/lmt_toolkit_analysis/lmttoolkitanalysis/LMT/lmtanalysis/BuildEventExclusiveUndetected.py b/lmt_toolkit_analysis/lmttoolkitanalysis/LMT/lmtanalysis/BuildEventExclusiveUndetected.py
@@ -5,16 +5,16 @@
 '''
 import sqlite3
 from time import *
-from lmtanalysis.Chronometer import Chronometer
-from lmtanalysis.Animal import *
-from lmtanalysis.Detection import *
-from lmtanalysis.Measure import *
+from .Chronometer import Chronometer
+from .Animal import *
+from .Detection import *
+from .Measure import *
 import matplotlib.pyplot as plt
 import numpy as np
-from lmtanalysis.Event import *
-from lmtanalysis.Measure import *
-from lmtanalysis.EventTimeLineCache import EventTimeLineCached
-from lmtanalysis.BehaviouralSequencesUtil import exclusiveEventList
+from .Event import *
+from .Measure import *
+from .EventTimeLineCache import EventTimeLineCached
+from .BehaviouralSequencesUtil import exclusiveEventList
 
 def flush( connection ):
     ''' flush event in database '''

diff --git a/lmt_toolkit_analysis/lmttoolkitanalysis/LMT/lmtanalysis/BuildEventFollowZone.py b/lmt_toolkit_analysis/lmttoolkitanalysis/LMT/lmtanalysis/BuildEventFollowZone.py
@@ -83,7 +83,7 @@ def reBuildEvent( connection, file, tmin=None, tmax=None, pool = None ):
 
     for idAnimalB in pool.animalDictionnary.keys():
         print(pool.animalDictionnary[idAnimalB])
-        meanSizeB = pool.animalDictionnary[idAnimalB].getMeanBodyLength( tmax = tmax )
+        #meanSizeB = pool.animalDictionnary[idAnimalB].getMeanBodyLength( tmax = tmax )
 
         for animal in pool.animalDictionnary.keys():
             if( idAnimalB == animal ):
@@ -94,6 +94,8 @@ def reBuildEvent( connection, file, tmin=None, tmax=None, pool = None ):
 
     for idAnimalB in pool.animalDictionnary.keys():
 
+        meanSizeB = pool.animalDictionnary[idAnimalB].getMeanBodyLength( tmax = tmax )
+
         for animal in pool.animalDictionnary.keys():
             if( animal == idAnimalB ):
                 continue
@@ -149,6 +151,8 @@ def reBuildEvent( connection, file, tmin=None, tmax=None, pool = None ):
                     speedA = pool.animalDictionnary[animal].getSpeed(t)
                     speedB = pool.animalDictionnary[idAnimalB].getSpeed(t)
                     #angleB = pool.animalList[idAnimalB].getDirection(t)
+                    if not pool.animalDictionnary[animal].getDetectionAt( t ).isHeadAndTailDetected():
+                        continue
                     angleA = pool.animalDictionnary[animal].getDirection(t)
 
                     if (speedA == None or speedB == None):
@@ -171,11 +175,12 @@ def reBuildEvent( connection, file, tmin=None, tmax=None, pool = None ):
                         for time in range( t-15, t+1, 2):
                         #time = t
                             try:
-                                angleB = pool.animalDictionnary[idAnimalB].getDirection(time)
-                                if ( checkZone( dicA[t].massX, dicA[t].massY, angleA, meanSizeB, dicB[time].massX, dicB[time].massY, angleB ) == True):
-
-                                    resultIso[t] = True
-                                    break
+                                if pool.animalDictionnary[idAnimalB].getDetectionAt( time ).isHeadAndTailDetected():
+                                    angleB = pool.animalDictionnary[idAnimalB].getDirection(time)
+                                    if ( checkZone( dicA[t].massX, dicA[t].massY, angleA, meanSizeB, dicB[time].massX, dicB[time].massY, angleB ) == True):
+
+                                        resultIso[t] = True
+                                        break
                             except:
                                 pass