Workaround to avoid writing extra code latency output in new profile library

bin/coz-plot/coz-plot.r

@@ -59,7 +59,7 @@ l <- levels(dat$Location)
 # Reorder the line factor by slope
 dat$Location <- factor(dat$Location, levels=l[rev(order(slopes))], ordered=TRUE)
 
-dat <- subset(dat, slopes[dat$Location] > 0.0)
+#dat <- subset(dat, slopes[dat$Location] > 0.0)
 
 # Graph it
 ggplot(dat, aes(x=Speedup, y=Progress.Speedup, color=Location, shape=Progress.Point, weight=Progress.Count, size=Progress.Count)) +

bin/pycoz/profile.py

@@ -208,7 +208,7 @@ def read_profile(filename):
       elif command == 'progress-point':
         # Log a performance change for a single progress point during the current experiment
         if current_exp:
-          m = measurement(data['name'], data['type'], int(data['delta']), current_exp)
+          m = measurement(data['name'], data['type'], float(data['delta']), current_exp)
           buffered_profile.add_measurement(m)
       
       elif command == 'samples':

lib/profiler.cpp

@@ -220,11 +220,15 @@ void profiler::profiler_thread(spinlock& l) {
           size_t queue_len = _begin_point.load()->get_count() - _end_point.load()->get_count();
           float latency = period * queue_len;
           
-          output << "latency-point\t"
+          // "Period" is computed as duration / delta. latency is just this time queue length,
+          // so fake a "delta" to produce the right output by dividing by queue length
+          float fake_delta = (float)delta / queue_len;
+          
+          output << "progress-point\t"
                  << "name=latency\t"
                  << "type=latency\t"
-                 << "latency=" << latency << "\t"
-                 << "delta=" << delta << "\n";
+                 //<< "latency=" << latency << "\t"
+                 << "delta=" << fake_delta << "\n";
         }
     
         output.flush();