Merge branch 'feature/cp2' into develop

rowers/dataprep.py

@@ -96,7 +96,7 @@ queuelow = django_rq.get_queue('low')
 queuehigh = django_rq.get_queue('default')
 
 from rowsandall_app.settings import SITE_URL
-from rowers.mytypes import otwtypes,otetypes
+from rowers.mytypes import otwtypes,otetypes,rowtypes
 from rowers import mytypes
 
 from rowers.database import *
@@ -1016,6 +1016,53 @@ def fetchcperg(rower,theworkouts):
 
     return cpdf
 
+def fetchcp_new(rower,workouts):
+
+    data = []
+    for workout in workouts:
+        cpfile = 'media/cpdata_{id}.parquet.gz'.format(id=workout.id)
+        try:
+            df = pd.read_parquet(cpfile)
+            data.append(df)
+        except OSError:
+            # CP data file doesn't exist yet. has to be created
+            strokesdf = getsmallrowdata_db(['power','workoutid','time'],ids = [workout.id])
+            if not strokesdf.empty:
+                totaltime = strokesdf['time'].max()
+                try:
+                    powermean = strokesdf['power'].mean()
+                except KeyError:
+                    powermean = 0
+
+                if powermean != 0:
+                    thesecs = totaltime
+                    maxt = 1.05 * thesecs
+
+                    if maxt > 0:
+                        logarr = datautils.getlogarr(maxt)
+                        dfgrouped = strokesdf.groupby(['workoutid'])
+                        delta, cpvalues, avgpower = datautils.getcp(dfgrouped, logarr)
+                        filename = 'media/cpdata_{id}.parquet.gz'.format(id=workout.id)
+                        df = pd.DataFrame({
+                            'delta':delta,
+                            'cp':cpvalues,
+                            'id':workout.id,
+                        })
+                        df.to_parquet(filename,engine='fastparquet',compression='GZIP')
+                        data.append(df)
+
+
+    if len(data) == 0:
+        return pd.Series(),pd.Series(),0
+    if len(data)>1:
+        df = pd.concat(data,axis=0)
+
+    df = df.groupby(['delta']).max()
+
+
+    df = df.sort_values(['delta']).reset_index()
+
+    return df['delta'],df['cp'],0
 
 def fetchcp(rower,theworkouts,table='cpdata'):
     # get all power data from database (plus workoutid)
@@ -1434,7 +1481,7 @@ def save_workout_database(f2, r, dosmooth=True, workouttype='rower',
 
     isbreakthrough = False
     ishard = False
-    if workouttype == 'water':
+    if workouttype in rowtypes:
         df = getsmallrowdata_db(['power', 'workoutid', 'time'], ids=[w.id])
         try:
             powermean = df['power'].mean()
@@ -1448,15 +1495,26 @@ def save_workout_database(f2, r, dosmooth=True, workouttype='rower',
                 logarr = datautils.getlogarr(maxt)
                 dfgrouped = df.groupby(['workoutid'])
                 delta, cpvalues, avgpower = datautils.getcp(dfgrouped, logarr)
+                filename = 'media/cpdata_{id}.parquet.gz'.format(id=w.id)
+                cpdf = pd.DataFrame({
+                    'delta':delta,
+                    'cp':cpvalues,
+                    'id':w.id,
+                })
+                cpdf.to_parquet(filename,engine='fastparquet',compression='GZIP')
 
-                res, btvalues, res2 = utils.isbreakthrough(
+                if workouttype in otwtypes:
-                    delta, cpvalues, r.p0, r.p1, r.p2, r.p3, r.cpratio)
+                    res, btvalues, res2 = utils.isbreakthrough(
+                        delta, cpvalues, r.p0, r.p1, r.p2, r.p3, r.cpratio)
+                elif workouttype in otetypes:
+                    res, btvalues, res2 = utils.isbreakthrough(
+                        delta, cpvalues, r.ep0, r.ep1, r.ep2, r.ep3, r.ecpratio)
             else:
                 res = 0
                 res2 = 0
             if res:
                 isbreakthrough = True
-                res = datautils.updatecp(delta, cpvalues, r)
+                res = datautils.updatecp(delta, cpvalues, r,workouttype=workouttype)
             if res2 and not isbreakthrough:
                 ishard = True
 

rowers/datautils.py

@@ -8,12 +8,24 @@ import numpy as np
 from scipy.interpolate import griddata
 from scipy import optimize
 
+from rowers.mytypes import otwtypes,otetypes,rowtypes
+
 #p0 = [500,350,10,8000]
 p0 = [190,200,33,16000]
 
-def updatecp(delta,cpvalues,r):
+def updatecp(delta,cpvalues,r,workouttype='water'):
-    cp2 = r.p0/(1+delta/r.p2)
+    if workouttype in otwtypes:
-    cp2 += r.p1/(1+delta/r.p3)
+        p0 = r.p0
+        p1 = r.p1
+        p2 = r.p2
+        p3 = r.p3
+    else:
+        p0 = r.ep0
+        p1 = r.ep1
+        p2 = r.ep2
+        p3 = r.ep3
+    cp2 = p0/(1+delta/p2)
+    cp2 += p1/(1+delta/p3)
 
     delta = delta.append(delta)
     cp = cpvalues.append(cp2)
@@ -31,11 +43,18 @@ def updatecp(delta,cpvalues,r):
     res = cpfit(powerdf)
     p1 = res[0]
 
-    r.p0 = p1[0]
+    if workouttype in otwtypes:
-    r.p1 = p1[1]
+        r.p0 = p1[0]
-    r.p2 = p1[2]
+        r.p1 = p1[1]
-    r.p3 = p1[3]
+        r.p2 = p1[2]
-    r.cpratio = res[3]
+        r.p3 = p1[3]
+        r.cpratio = res[3]
+    else:
+        r.ep0 = p1[0]
+        r.ep1 = p1[1]
+        r.ep2 = p1[2]
+        r.ep3 = p1[3]
+        r.ecpratio = res[3]
 
     r.save()
 
@@ -89,7 +108,10 @@ def cpfit(powerdf):
 
 def getlogarr(maxt):
     maxlog10 = np.log10(maxt-5)
-    logarr = np.arange(50)*maxlog10/50.
+    #print(maxlog10,round(maxlog10))
+    aantal = 10*round(maxlog10)
+    logarr = np.arange(aantal+1)/10.
+    
     res = []
     for la in logarr:
         try:

rowers/forms.py

@@ -1036,7 +1036,7 @@ analysischoices = (
     ('flexall','Cumulative Flex Chart'),
     ('stats','Statistics'),
     ('compare','Compare'),
-    ('cp','CP Chart')
+    ('cp','CP chart'),
     )
 
 

rowers/models.py

@@ -2985,6 +2985,13 @@ def auto_delete_file_on_delete(sender, instance, **kwargs):
     except FileNotFoundError:
         pass
 
+    # remove parquet file
+    try:
+        dirname = 'media/cpdata_{id}.parquet.gz'.format(id=instance.id)
+        os.remove(dirname)
+    except FileNotFoundError:
+        pass
+
 @receiver(models.signals.post_delete,sender=Workout)
 def update_duplicates_on_delete(sender, instance, **kwargs):
     if instance.id:

rowers/templates/user_analysis_select.html

@@ -2,7 +2,7 @@
 {% load staticfiles %}
 {% load rowerfilters %}
 
-{% block title %}Workouts{% endblock %}
+{% block title %}Analysis{% endblock %}
 
 {% block main %}
 <script>
@@ -16,14 +16,14 @@
 <script src="https://code.jquery.com/jquery-1.9.1.min.js"></script>
 <script>
   $(function() {
-  
+
   // Get the form fields and hidden div
   var modality = $("#id_modality");
   var hidden = $("#id_waterboattype");
 
-  
+
   // Hide the fields.
-  // Use JS to do this in case the user doesn't have JS 
+  // Use JS to do this in case the user doesn't have JS
   // enabled.
 
   hidden.hide();
@@ -32,8 +32,8 @@
   hidden.show();
   }
 
-  
+
-  // Setup an event listener for when the state of the 
+  // Setup an event listener for when the state of the
   // checkbox changes.
   modality.change(function() {
     // Check to see if the checkbox is checked.
@@ -48,10 +48,10 @@
   // Make sure that the hidden fields are indeed
   // hidden.
   hidden.hide();
-      
+
-      // You may also want to clear the value of the 
+      // You may also want to clear the value of the
-      // hidden fields here. Just in case somebody 
+      // hidden fields here. Just in case somebody
-      // shows the fields, enters data to them and then 
+      // shows the fields, enters data to them and then
       // unticks the checkbox.
       //
       // This would do the job:
@@ -67,7 +67,7 @@
 <script>
   // script for chart options form
   $(function() {
-  
+
       // Get the form fields and hidden div
       var functionfield = $("#id_function");
       var plotfield = $("#id_plotfield").parent().parent();
@@ -82,14 +82,16 @@
       var spmmax = $("#id_spmmax").parent().parent();
       var workmin = $("#id_workmin").parent().parent();
       var workmax = $("#id_workmax").parent().parent();
-      
+
-      var xaxis = $("#id_xaxis").parent().parent();      
+      var xaxis = $("#id_xaxis").parent().parent();
-      var yaxis1 = $("#id_yaxis1").parent().parent();      
+      var yaxis1 = $("#id_yaxis1").parent().parent();
-      var yaxis2 = $("#id_yaxis2").parent().parent();      
+      var yaxis2 = $("#id_yaxis2").parent().parent();
-      var plottype = $("#id_plottype").parent().parent();      
+      var plottype = $("#id_plottype").parent().parent();
+
+			var reststrokes = $("#id_includereststrokes").parent().parent();
 
       // Hide the fields.
-      // Use JS to do this in case the user doesn't have JS 
+      // Use JS to do this in case the user doesn't have JS
       // enabled.
       plotfield.hide();
       x_param.hide();
@@ -102,6 +104,11 @@
       yaxis1.hide();
       yaxis2.hide();
       plottype.hide();
+			reststrokes.hide();
+			workmin.hide();
+			workmax.hide();
+			spmmin.hide();
+			spmmax.hide();
 
       if (functionfield.val() == 'boxplot') {
 	  plotfield.show();
@@ -136,8 +143,8 @@
 	  plottype.show();
       }
 
-  
+
-      // Setup an event listener for when the state of the 
+      // Setup an event listener for when the state of the
       // checkbox changes.
       functionfield.change(function() {
 	  // Check to see if the checkbox is checked.
@@ -161,6 +168,7 @@
 	      yaxis1.hide();
 	      yaxis2.hide();
 	      plottype.hide();
+				reststrokes.show();
 	  }
 	  else if (Value=='histo') {
 	      plotfield.show();
@@ -178,6 +186,7 @@
 	      yaxis1.hide();
 	      yaxis2.hide();
 	      plottype.hide();
+				reststrokes.show();
 
 	  }
 	  else if (Value=='trendflex') {
@@ -196,6 +205,7 @@
 	      yaxis1.hide();
 	      yaxis2.hide();
 	      plottype.hide();
+				reststrokes.show();
 
 	  }
 	  else if (Value=='flexall') {
@@ -214,6 +224,7 @@
 	      binsize.hide();
 	      plottype.hide();
 	      errorbars.hide();
+				reststrokes.show();
 	  }
 	  else if (Value=='stats') {
 	      xaxis.hide();
@@ -227,6 +238,7 @@
 	      binsize.hide();
 	      errorbars.hide();
 	      plottype.hide();
+				reststrokes.show();
 	  }
 	  else if (Value=='compare') {
 	      xaxis.show();
@@ -244,10 +256,29 @@
 	      binsize.hide();
 	      plottype.show();
 	      errorbars.hide();
+				reststrokes.show();
+	  }
+		else if (Value=='cp') {
+	      plotfield.hide();
+	      spmmin.hide();
+	      spmmax.hide();
+	      workmin.hide();
+	      workmax.hide();
+	      x_param.hide();
+	      y_param.hide();
+	      groupby.hide();
+	      palette.hide();
+	      binsize.hide();
+	      errorbars.hide();
+	      xaxis.hide();
+	      yaxis1.hide();
+	      yaxis2.hide();
+	      plottype.hide();
+				reststrokes.hide();
 	  }
       });
-  });      
+  });
-      
+
 </script>
 
 <div id="id_css_res">
@@ -285,9 +316,9 @@
       <input type="submit" value="GO"></input>
     </form>
     <form enctype="multipart/form-data" action="" method="post">
-      
+
       {% if workouts %}
-      
+
       <input type="checkbox" onClick="toggle(this)" /> Toggle All<br/>
       <table width="100%" class="listtable">
 	{{ form.as_table }}

rowers/views/analysisviews.py

@@ -500,6 +500,60 @@ def histodata(workouts, options):
 
     return(script,div)
 
+def cpdata(workouts, options):
+    userid = options['userid']
+
+
+    u = User.objects.get(id=userid)
+    r = u.rower
+
+
+    ids = [w.id for w in workouts]
+    delta, cpvalue, avgpower = dataprep.fetchcp_new(r,workouts)
+    powerdf = pd.DataFrame({
+        'Delta':delta,
+        'CP':cpvalue,
+    })
+
+
+    if powerdf.empty:
+        return('','<p>No valid data found</p>')
+
+    powerdf = powerdf[powerdf['CP']>0]
+    powerdf.dropna(axis=0,inplace=True)
+    powerdf.sort_values(['Delta','CP'],ascending=[1,0],inplace=True)
+    powerdf.drop_duplicates(subset='Delta',keep='first',inplace=True)
+
+    rowername = r.user.first_name+" "+r.user.last_name
+
+    if len(powerdf) !=0 :
+        res = interactive_otwcpchart(powerdf,promember=True,rowername=rowername)
+        script = res[0]
+        div = res[1]
+        p1 = res[2]
+        ratio = res[3]
+        r.p0 = p1[0]
+        r.p1 = p1[1]
+        r.p2 = p1[2]
+        r.p3 = p1[3]
+        r.cpratio = ratio
+        r.save()
+        paulslope = 1
+        paulintercept = 1
+        message = res[4]
+    else:
+        script = ''
+        div = '<p>No ranking pieces found.</p>'
+        paulslope = 1
+        paulintercept = 1
+        p1 = [1,1,1,1]
+        message = ""
+
+    scripta = script.split('\n')[2:-1]
+    script = ''.join(scripta)
+
+    return (script,div)
+
 def statsdata(workouts, options):
     includereststrokes = options['includereststrokes']
     spmmin = options['spmmin']
@@ -726,7 +780,7 @@ def analysis_view_data(request,userid=0):
     elif function == 'compare':
         script,div = comparisondata(workouts,options)
     elif function == 'cp':
-        script, div = cpdata(workouts,options)
+        script, div = cpdata(workouts, options)
     else:
         script = ''
         div = 'Unknown analysis functions'