Finalizing measurements.

- fab task to download from remote
- attribute metric figures plus doc in ipynb
- updated some docs

README.md

@@ -3,6 +3,7 @@
 - clone [the racr repo](https://github.com/christoff-buerger/racr.git)
 - install racr
 - let scheme IDE know about racr
+  - racket: Create a symlink in `$RACKET_INSTALL_DIR/collects` pointing to `$RACR_REPO/racr/racket-bin/racr`
 
 # Links
 

doc/att-profiling-thoughts.md

+- X = {normal, flushed, noncached}
+- (X1,X2) = {(normal, flushed), (normal, noncached), (flushed, noncached)}
+
 # Meaningful percentages to calculate
 
-1) `total.X.computed / total.X.called` with X = {normal, flushed, noncached}
+1) {X}basline: `total.X.computed / total.X.called`
 - the baseline of the method X
 
-2) `total.normal.computed / total.Y.called` with Y = {flushed, noncached}
-- the efficiency of the incremental approach in comparison to the method Y,
-  i.e. the ratio between actual work done normally compared to possible work done with method Y
+2) ratio{X1}To{X2}: `total.{X1}.computed / total.{X2}.called`
+- the efficiency of the incremental approach in comparison to the method X2,
+  i.e. the ratio between actual work done in X1 compared to possible work done with method X2
 
-3) `(total.Y.computed / total.Y.called) - (total.normal.computed / total.Y.called)` with Y = {flushed, noncached}
-- = `baseline(Y) - ratio(normal, Y)`
-- the "speed-up" of the incremental approach in comparison to the method Y
+3) speedup{X1}To{X2}: `(total.{X2}.computed / total.{X2}.called) - (total.{X1}.computed / total.{X2}.called)`
+- = `baseline({X2}) - ratio({X1}, {X2})`
+- the "speed-up" of the incremental approach (normal or flushed) in comparison to the method X2

doc/glpk_ilp_gen.md

+# GLPK-ILP-Generator
+
+org.haec.optimizer.ilp.GLPK_ILPGenerator
+
+## Generation of ILP
+
+- Times: `/opt/luna/eclipse/logs/durations.csv`, times in milli-sec
+
+## Solving of ILP
+
+- Using GLPK
+- Times: `/home/rschoene/git/mquat/project_systems/gen_sys/*/sol.csv`, times in nano-sec
+- ILP: `/home/rschoene/git/mquat/project_systems/gen_sys/*/gip.glpk`
+- Solution: `/opt/luna/eclipse/logs/csvs/<timestamp>.csv`
+
+# Toy-Generator
+
+org.coolsoftware.requests.resource.request.ui.actions.ILPGenerator2
+
+## Generation of ILP
+
+- Times: `/home/rschoene/git/mquat/project_systems/gen_sys/*/gen.csv`, times in milli-sec
+
+## Solving of ILP
+
+- Using LP_solve
+- Times: `/home/rschoene/git/mquat/project_systems/gen_sys/*/sol.csv`, times in milli-sec
+- Solution: `/home/rschoene/git/mquat/project_systems/gen_sys/*/ilp-result-max-3.txt`
+
+# LP-Generator
+
+org.haec.optimizer.ilp.ILPGenerator
+
+## Generation of ILP
+
+- Times: `/home/rschoene/git/mquat/project_systems/gen_sys/*/gen.csv`, times in milli-sec
+
+## Solving of ILP
+
+- Using LP_solve
+- Times: `/home/rschoene/git/mquat/project_systems/gen_sys/*/sol.csv`, times in milli-sec
+
+# Schemas
+
+- `durations.csv`: problemName, timestamp¹, dSetup, dBinVar, dUsage, dProperty, dBuffer, dTotal
+- `*/gen.csv`: solver, timestamp², architectural constraints, resource negotation, nfp negotiation, objective function
+- `*/sol.csv`: solver, timestamp², rows, cols, duration
+
+¹: "DD.MM.YY HH:MM"
+
+²: "YYYY-MM-DD'T'HH:MM:SS.NNN" (Python datetime.datetime.isoformat())

fabfile.py

@@ -4,7 +4,8 @@ import ilp_measurement as measure
 import ilp_check as check
 import install
 import sockets
-from fabric.api import local, task
+import os
+from fabric.api import local, task, get, hosts, run
 
 @task
 def call_racket(f, *args):
@@ -30,3 +31,11 @@ def cloc(not_match, *args, **kwargs):
 	not_match = 'sockets|java|tricks|example-ast|larceny|Makefile|ls' + ('|'+not_match if not_match else '')
 	local('cloc . --exclude-dir=doc,gen,profiling,test,racket-bin,larceny-bin --not-match-f="{0}" {1} {2}'.format(not_match, ' '.join(args),
 		' '.join("{!s}={!r}".format(k,v) for (k,v) in kwargs.iteritems())))
+
+@task
+@hosts('rschoene@141.76.65.177')
+def dl(name, rdir = '~/git/racr-mquat/'):
+	#run('uname -a')
+	target = os.path.join(rdir, name)
+	print target
+	get(target, local_path = name)

ilp_measurement.py

@@ -200,17 +200,17 @@ def merge_att_measurements():
 	with open('profiling/att-percentages.csv', 'w') as fd:
 		w = csv.writer(fd)
 		w.writerow(['dir', 'normalBaseline', 'flushedBaseline', 'noncachedBaseline',
-			'ratioToFlushed', 'ratioToNoncached',
-			'speedupToFlushed', 'speedupToNoncached'])
+			'ratioNormalToFlushed', 'ratioNormalToNoncached', 'ratioFlushedToNoncached',
+			'speedupNormalToFlushed', 'speedupNormalToNoncached', 'speedupFlushedToNoncached'])
 		baseline = lambda att: att.computed * 1.0 / att.called if att.called > 0 else 0
-		ratio = lambda normal, y: normal.computed * 1.0 / y.called if y.called > 0 else 0
+		ratio = lambda x, y: x.computed * 1.0 / y.called if y.called > 0 else 0
 		for dir_name, total in totals.iteritems():
 			normal, flushed, noncached = total.normal, total.flushed, total.noncached
 			w.writerow([dir_name, baseline(normal), baseline(flushed), baseline(noncached),
-				ratio(normal, flushed), ratio(normal, noncached),
+				ratio(normal, flushed), ratio(normal, noncached), ratio(flushed, noncached),
 				baseline(flushed) - ratio(normal, flushed),
-				baseline(noncached) - ratio(normal, noncached)])
-
+				baseline(noncached) - ratio(normal, noncached),
+				baseline(noncached) - ratio(flushed, noncached)])
 
 @task(name = 'conflate-results')
 def conflate_results(pathname = '*', skip_gen = False, skip_sol = False, impls = 'larceny:plt-r6rs'):
@@ -245,7 +245,6 @@ def conflate_results(pathname = '*', skip_gen = False, skip_sol = False, impls =
 						impl = tokens[0].split('/')[-1]
 						gen_time = '.'.join(tokens[1:3])
 					row = [mod.isoformat(), impl, dirname(d), f.split('.')[0], gen_time]
-					#print row
 					writer.writerow(row)
 					os.rename(f, os.path.join(gen_old_dir, os.path.basename(f)))
 
@@ -256,13 +255,9 @@ def conflate_results(pathname = '*', skip_gen = False, skip_sol = False, impls =
 				with open(f) as fd:
 					contents = fd.readlines()
 				count = next(int(line[line.rindex(',')+1:-1]) for line in contents if line.startswith('to-ilp ,'))
-				print f, count, max_count
 				if count > max_count:
 					contents_hightest = contents
 					max_count = count
-#					sys.stdout.write('new highest {}\r'.format(f))
-#					sys.stdout.flush()
-#			sys.stdout.write('\n')
 			if len(att_measures) > 0:
 				with open(att_results, 'w') as fd:
 					w = csv.writer(fd)