adds distance pieces to OTE ranking piece (PRO)

The PRO ranking piece calculation for erg pieces now also calculates
distance based pieces.

rowers/views.py

@@ -3779,6 +3779,8 @@ def oterankings_view(request,theuser=0,
     rankingdurations.append(datetime.time(hour=1))
     rankingdurations.append(datetime.time(hour=1,minute=15))
 
+    rankingdistances = [100,500,1000,2000,5000,6000,10000,21097,42195,100000]
+    
     thedistances = []
     theworkouts = []
     thesecs = []
@@ -3874,21 +3876,29 @@ def oterankings_view(request,theuser=0,
 	form = PredictedPieceForm(request.POST)
         clean = form.is_valid()
 	value = form.cleaned_data['value']
-        hourvalue,value = divmod(value,60)
+        hourvalue,tvalue = divmod(value,60)
         hourvalue = int(hourvalue)
-        minutevalue = int(value)
-        value = int(60*(value-minutevalue))
+        minutevalue = int(tvalue)
+        tvalue = int(60*(tvalue-minutevalue))
         if hourvalue >= 24:
             hourvalue = 23
-	rankingdurations.append(datetime.time(minute=minutevalue,
-                                              hour=hourvalue,
-                                              second=value))
+        pieceunit = form.cleaned_data['pieceunit']
+        if pieceunit == 'd':
+            rankingdistances.append(value)
+        else:
+	    rankingdurations.append(datetime.time(
+                minute=minutevalue,
+                hour=hourvalue,
+                second=tvalue
+            ))
     else:
 	form = PredictedPieceForm()
 
 
     cpredictions = []
 
+
+
     for rankingduration in rankingdurations:
 	t = 3600.*rankingduration.hour
 	t += 60.*rankingduration.minute
@@ -3900,6 +3910,9 @@ def oterankings_view(request,theuser=0,
 	pwr = p1[0]/(1+t/p1[2])
 	pwr += p1[1]/(1+t/p1[3])
 
+        velo = (pwr/2.8)**(1./3.)
+        p = 500./velo
+        d = t*velo
         
 	if pwr <= 0:
 	    pwr = 50.
@@ -3912,16 +3925,78 @@ def oterankings_view(request,theuser=0,
                 pwr2 = pwr
 
             a = {
+                'distance':int(d),
 	        'duration':timedeltaconv(t),
 	        'power':int(pwr),
-                'upper':int(pwr2)}
+                'upper':int(pwr2),
+                'pace':timedeltaconv(p)}
+
 	    cpredictions.append(a)
 
 
-    del form.fields["pieceunit"]
+    # initiation - get 10 min power, then use Paul's law
+
+    t_10 = 600.
+    power_10 = p1[0]/(1+t_10/p1[2])
+    power_10 += p1[1]/(1+t_10/p1[3])
+
+    velo_10 = (power_10/2.8)**(1./3.)
+    pace_10 = 500./velo_10
+    distance_10 = t_10*velo_10
+
+    paulslope = 5. 
+    
+    for rankingdistance in rankingdistances:
+
+        delta = paulslope * np.log(rankingdistance/distance_10)/np.log(2)
+        
+        
+        p = pace_10+delta
+        velo = 500./p
+        t = rankingdistance/velo
+        
+	pwr2 = p1[0]/(1+t/p1[2])
+	pwr2 += p1[1]/(1+t/p1[3])
+        pwr2 *= ratio
+
+	if pwr2 <= 0:
+	    pwr2 = 50.
+	
+	velo2 = (pwr2/2.8)**(1./3.)
+
+	if np.isnan(velo2) or velo2 <= 0:
+	    velo2 = 1.0
+	    
+	t2 = rankingdistance/velo2
+	
+	pwr3 = p1[0]/(1+t2/p1[2])
+	pwr3 += p1[1]/(1+t2/p1[3])
+        pwr3 *= ratio
+
+        
+	if pwr3 <= 0:
+	    pwr3 = 50.
+	
+	velo3 = (pwr3/2.8)**(1./3.)
+	if np.isnan(velo3) or velo3 <= 0:
+	    velo3 = 1.0
+	    
+	t3 = rankingdistance/velo3
+	p3 = 500./velo3
+
+	a = {
+            'distance':rankingdistance,
+	    'duration':timedeltaconv(t3),
+	    'power':'--',
+	    'upper':int(pwr3),
+            'pace':timedeltaconv(p3)}
+
+        cpredictions.append(a)
+
+        #    del form.fields["pieceunit"]
 
     messages.error(request,message)
-    return render(request, 'otwrankings.html',
+    return render(request, 'oterankings.html',
 		  {'rankingworkouts':theworkouts,
 		   'interactiveplot':script,
 		   'the_div':div,