From 4be698eb92e595960bef604aec3451e723d43bd1 Mon Sep 17 00:00:00 2001
From: rschoene <rene.schoene@tu-dresden.de>
Date: Thu, 22 Oct 2015 17:15:34 +0200
Subject: [PATCH] WIP: again towards working graph creation
---
ilp-measurement.ipynb | 191 +++++++++++++++++++++++++++++++++---------
ilp_measurement.py | 15 +++-
scheme.properties | 4 +-
3 files changed, 166 insertions(+), 44 deletions(-)
diff --git a/ilp-measurement.ipynb b/ilp-measurement.ipynb
index 230d618..2959b96 100644
--- a/ilp-measurement.ipynb
+++ b/ilp-measurement.ipynb
@@ -89,13 +89,15 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 163,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"def get_average_times(dat, dirCol, stepCol, timeCol):\n",
+ " if dat.size == 1:\n",
+ " return np.array([np.array([dat.item()[timeCol]])])\n",
" dat.sort(order=['dir', 'step'])\n",
" result = {}\n",
" for (c_dir, c_step), rows in groupby(dat, key=set_keys('dir','step')):\n",
@@ -112,12 +114,34 @@
" result2 = []\n",
" for c_dir, rows in result.iteritems():\n",
" inner = []\n",
- " for row in rows:\n",
- " inner.append(row[1])\n",
- " result2.append(inner)\n",
+ " result2.append([row[1] for row in rows])\n",
+ "# for row in rows:\n",
+ "# inner.append(row[1])\n",
+ "# result2.append(inner)\n",
" return np.array([np.array(rows) for rows in result2])"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": 100,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "gen (8, 31)\n",
+ "sol (8, 23)\n"
+ ]
+ }
+ ],
+ "source": [
+ "print 'gen', larceny_dats['update']['normal'].shape\n",
+ "print 'sol', glpk_dats['update'].shape"
+ ]
+ },
{
"cell_type": "code",
"execution_count": 7,
@@ -160,14 +184,16 @@
},
{
"cell_type": "code",
- "execution_count": 58,
+ "execution_count": 165,
"metadata": {
- "collapsed": true
+ "collapsed": false
},
"outputs": [],
"source": [
"no_split, split_change_only, split_both = 0, 1, 2\n",
+ "dat, dat2, dat3 = None, None, None\n",
"def read_single_result(f, name, dtype, data_column, since):\n",
+ " global dat, dat2, dat3\n",
" def convdate(text):\n",
" return datetime.strptime(text, '%Y-%m-%dT%H:%M:%S.%f')\n",
" def convdir(text):\n",
@@ -181,11 +207,13 @@
" if since:\n",
" dat = dat[dat['timestamp'] > since ]\n",
" dat2 = get_average_times(dat, 1, 2, data_column).transpose()\n",
+ " len_dat = 1 if len(dat.shape) == 0 else len(dat)\n",
" if dat2.size == 0:\n",
" print 'Did not load any record for {}'.format(name)\n",
" else:\n",
" print 'Loaded {0} records for {1} ({2[0]}x{2[1]} unique) ~= {3} run(s)'.format(\n",
- " len(dat), name, dat2.shape, safe_div(len(dat),dat2.size))\n",
+ " len_dat, name, dat2.shape, safe_div(len_dat,dat2.size))\n",
+ " dat3 = dat2\n",
" return dat2\n",
"\n",
"def read_results(prefix, name, dtype, data_column, since, splitted = no_split):\n",
@@ -295,10 +323,10 @@
},
{
"cell_type": "code",
- "execution_count": 60,
+ "execution_count": 166,
"metadata": {
"collapsed": false,
- "scrolled": true
+ "scrolled": false
},
"outputs": [
{
@@ -314,7 +342,7 @@
"Loaded 63 records for res_normal_plt-r6rs (7x4 unique) ~= 2 run(s)\n",
"Loaded 28 records for res_flush_plt-r6rs (7x4 unique) ~= 1 run(s)\n",
"Loaded 147 records for res_noncached_plt-r6rs (7x14 unique) ~= 1 run(s)\n",
- "Did not load any record for update_normal_larceny\n",
+ "Loaded 264 records for update_normal_larceny (8x31 unique) ~= 1 run(s)\n",
"Did not load any record for update_flush_larceny\n",
"Did not load any record for update_noncached_larceny\n",
"Did not load any record for sw_normal_larceny\n",
@@ -323,15 +351,15 @@
"Did not load any record for res_normal_larceny\n",
"Did not load any record for res_flush_larceny\n",
"Did not load any record for res_noncached_larceny\n",
- "Did not load any record for update_normal_java\n",
- "Did not load any record for update_flush_java\n",
- "Did not load any record for update_noncached_java\n",
- "Did not load any record for sw_normal_java\n",
- "Did not load any record for sw_flush_java\n",
- "Did not load any record for sw_noncached_java\n",
- "Did not load any record for res_normal_java\n",
- "Did not load any record for res_flush_java\n",
- "Did not load any record for res_noncached_java\n"
+ "Loaded 88 records for update_normal_java (1x31 unique) ~= 2 run(s)\n",
+ "Loaded 1 records for update_flush_java (1x1 unique) ~= 1 run(s)\n",
+ "Loaded 1 records for update_noncached_java (1x1 unique) ~= 1 run(s)\n",
+ "Loaded 1 records for sw_normal_java (1x1 unique) ~= 1 run(s)\n",
+ "Loaded 1 records for sw_flush_java (1x1 unique) ~= 1 run(s)\n",
+ "Loaded 1 records for sw_noncached_java (1x1 unique) ~= 1 run(s)\n",
+ "Loaded 1 records for res_normal_java (1x1 unique) ~= 1 run(s)\n",
+ "Loaded 1 records for res_flush_java (1x1 unique) ~= 1 run(s)\n",
+ "Loaded 1 records for res_noncached_java (1x1 unique) ~= 1 run(s)\n"
]
}
],
@@ -343,7 +371,7 @@
},
{
"cell_type": "code",
- "execution_count": 61,
+ "execution_count": 167,
"metadata": {
"collapsed": false,
"scrolled": true
@@ -357,11 +385,11 @@
"Did not load any record for sw_java\n",
"Did not load any record for res_java\n",
"Loaded 1656 records for update_glpk (8x23 unique) ~= 9 run(s)\n",
- "Did not load any record for sw_glpk\n",
- "Did not load any record for res_glpk\n",
- "Did not load any record for update_gurobi\n",
- "Did not load any record for sw_gurobi\n",
- "Did not load any record for res_gurobi\n"
+ "Loaded 1 records for sw_glpk (1x1 unique) ~= 1 run(s)\n",
+ "Loaded 1 records for res_glpk (1x1 unique) ~= 1 run(s)\n",
+ "Loaded 216 records for update_gurobi (8x27 unique) ~= 1 run(s)\n",
+ "Loaded 1 records for sw_gurobi (1x1 unique) ~= 1 run(s)\n",
+ "Loaded 1 records for res_gurobi (1x1 unique) ~= 1 run(s)\n"
]
}
],
@@ -386,16 +414,16 @@
},
{
"cell_type": "code",
- "execution_count": 64,
+ "execution_count": 70,
"metadata": {
"collapsed": false,
"scrolled": false
},
"outputs": [],
"source": [
- "def draw_gen(params):\n",
+ "def draw_gen(changeName, strategy, params):\n",
" # needed number of axes equals ax_nr+1 now\n",
- " name = 'gen_{}'.format(changeName)\n",
+ " name = 'gen_{0}_{1}'.format(changeName, strategy)\n",
" f, ax_arr = plt.subplots(nrows = ax_nr+1, ncols = 3, sharex=True, sharey=True)\n",
" f.set_size_inches(25.5,3.5*(ax_nr+1))\n",
" one_plot = ax_arr.shape[1] == 1\n",
@@ -445,7 +473,7 @@
},
{
"cell_type": "code",
- "execution_count": 65,
+ "execution_count": 71,
"metadata": {
"collapsed": false
},
@@ -498,7 +526,7 @@
},
{
"cell_type": "code",
- "execution_count": 66,
+ "execution_count": 72,
"metadata": {
"collapsed": false,
"scrolled": true
@@ -524,12 +552,21 @@
},
{
"cell_type": "code",
- "execution_count": 68,
+ "execution_count": 168,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Change = update\n",
+ "Stategy = normal\n",
+ "Stategy = flush\n"
+ ]
+ },
{
"ename": "IndexError",
"evalue": "too many indices for array",
@@ -537,7 +574,7 @@
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mIndexError\u001b[0m Traceback (most recent call last)",
- "\u001b[1;32m<ipython-input-68-e8120160290e>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 16\u001b[0m gen_params.append([ax_nr, line_def[i], color_def[i], '{2:d} x ({4}*{5}*{6})'.format(*specs[i]),\n\u001b[0;32m 17\u001b[0m \u001b[0msafe\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mracket_dats\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mchange\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mstrategy\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mSTART_STEP\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 18\u001b[1;33m \u001b[0msafe\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlarceny_dats\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mchange\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mstrategy\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mSTART_STEP\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 19\u001b[0m safe(java_dat[change][strategy],i)])\n\u001b[0;32m 20\u001b[0m \u001b[0mlast_res\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcurrent_res\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+ "\u001b[1;32m<ipython-input-168-4ac34798cab4>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 18\u001b[0m gen_params.append([ax_nr, line_def[i], color_def[i], '{2:d} x ({4}*{5}*{6})'.format(*specs[i]),\n\u001b[0;32m 19\u001b[0m \u001b[0msafe\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mracket_dats\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mchange\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mstrategy\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mSTART_STEP\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 20\u001b[1;33m \u001b[0msafe\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlarceny_dats\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mchange\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mstrategy\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mSTART_STEP\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 21\u001b[0m safe(java_dats[change][strategy],i)])\n\u001b[0;32m 22\u001b[0m \u001b[0mlast_res\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcurrent_res\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m<ipython-input-10-27c199385393>\u001b[0m in \u001b[0;36msafe\u001b[1;34m(a, i, start)\u001b[0m\n\u001b[0;32m 3\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0ma\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mstart\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 4\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0mIndexError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 5\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mzeros\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msize\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[1;31mIndexError\u001b[0m: too many indices for array"
]
@@ -546,7 +583,9 @@
"source": [
"START_STEP, MAX_PLOTS_IN_ONE = 0, 7\n",
"for change in kinds['changes']:\n",
+ " print 'Change = {}'.format(change)\n",
" for strategy in kinds['strategies']:\n",
+ " print 'Stategy = {}'.format(strategy)\n",
" current_plot, ax_nr, last_res = 0, 0, -1\n",
" gen_params = []\n",
" for i in xrange(len(specs)):\n",
@@ -556,16 +595,16 @@
" ax_nr += 1\n",
" current_plot = 0\n",
"# params.append([ax_nr, safe(racket_dats[change][strategy],i,START_STEP), safe(larceny_dats[change][strategy],i,START_STEP),\n",
- "# safe(glpk_dat[change][strategy],i), safe(gurobi_dat[change][strategy],i),\n",
+ "# safe(glpk_dats[change][strategy],i), safe(gurobi_dats[change][strategy],i),\n",
"# line_def[i], color_def[i], '{2:d} x ({4}*{5}*{6})'.format(*specs[i]),\n",
- "# safe(java_dat[change][strategy],i), safe(java_glpk_dat[change][strategy],i)])\n",
+ "# safe(java_dats[change][strategy],i), safe(java_glpk_dats[change][strategy],i)])\n",
" gen_params.append([ax_nr, line_def[i], color_def[i], '{2:d} x ({4}*{5}*{6})'.format(*specs[i]),\n",
" safe(racket_dats[change][strategy],i,START_STEP),\n",
" safe(larceny_dats[change][strategy],i,START_STEP),\n",
- " safe(java_dat[change][strategy],i)])\n",
+ " safe(java_dats[change][strategy],i)])\n",
" last_res = current_res\n",
" try:\n",
- " draw_gen(gen_params)\n",
+ " draw_gen(change, strategy, gen_params)\n",
" except:\n",
" print 'Error while drawing gen in {0}-{1}'.format(change, strategy)\n",
" sol_params = []\n",
@@ -576,19 +615,89 @@
" ax_nr += 1\n",
" current_plot = 0\n",
" sol_params.append([ax_nr, line_def[i], color_def[i], '{2:d} x ({4}*{5}*{6})'.format(*specs[i]),\n",
- " safe(glpk_dat[change][strategy],i),\n",
- " safe(gurobi_dat[change][strategy],i),\n",
- " safe(java_glpk_dat[change][strategy],i)])\n",
+ " safe(glpk_dats[change][strategy],i),\n",
+ " safe(gurobi_dats[change][strategy],i),\n",
+ " safe(java_glpk_dats[change][strategy],i)])\n",
" try:\n",
- " draw_sol(params)\n",
+ " draw_sol(change, params)\n",
" except:\n",
" print 'Error while drawing sol in {0}-{1}'.format(change, strategy)\n",
" try:\n",
- " draw_comp_sol(params)\n",
+ " draw_comp_sol(change, params)\n",
" except:\n",
" print 'Error while drawing comp-sol in {0}-{1}'.format(change, strategy)\n"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": 82,
+ "metadata": {
+ "collapsed": false,
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "{u'res': {u'flush': array([], dtype=float64),\n",
+ " u'noncached': array([], dtype=float64),\n",
+ " u'normal': array([], dtype=float64)},\n",
+ " u'sw': {u'flush': array([], dtype=float64),\n",
+ " u'noncached': array([], dtype=float64),\n",
+ " u'normal': array([], dtype=float64)},\n",
+ " u'update': {u'flush': array([], dtype=float64),\n",
+ " u'noncached': array([], dtype=float64),\n",
+ " u'normal': array([[ 0.17 , 0.187 , 1.766 , 11.3 , 0.3 , 0.403 ,\n",
+ " 3.304 , 22.73 , 1.439 , 2.375 , 3.521 , 6.308 ,\n",
+ " 10.359 , 12.319 , 15.182 , 18.13 , 22.5205, 27.992 ,\n",
+ " 32.143 , 25.217 , 30.606 , 38.144 , 45.88 , 4.294 ,\n",
+ " 9.545 , 16.402 , 24.272 , 0.362 , 0.711 , 1.518 , 3.948 ],\n",
+ " [ 0.5 , 0.46 , 0.223 , 0.916 , 0.9 , 0.123 ,\n",
+ " 0.446 , 2.267 , 0.257 , 0.488 , 0.852 , 1.224 ,\n",
+ " 1.964 , 2.78 , 2.6 , 3.274 , 4.2555, 5.503 ,\n",
+ " 4.899 , 4.107 , 4.98 , 6.655 , 7.133 , 0.958 ,\n",
+ " 1.695 , 2.673 , 3.984 , 0.68 , 0.142 , 0.239 , 0.649 ],\n",
+ " [ 0.5 , 0.45 , 0.228 , 0.915 , 0.1 , 0.117 ,\n",
+ " 0.441 , 2.266 , 0.261 , 0.489 , 0.879 , 1.255 ,\n",
+ " 1.953 , 2.79 , 2.602 , 3.252 , 3.577 , 5.444 ,\n",
+ " 4.878 , 4.54 , 4.959 , 6.679 , 7.165 , 0.949 ,\n",
+ " 1.507 , 2.679 , 3.977 , 0.73 , 0.141 , 0.241 , 0.65 ],\n",
+ " [ 0.5 , 0.43 , 0.225 , 0.902 , 0.11 , 0.115 ,\n",
+ " 0.443 , 2.256 , 0.25 , 0.488 , 0.858 , 1.209 ,\n",
+ " 1.958 , 2.93 , 2.636 , 3.272 , 3.5695, 5.444 ,\n",
+ " 4.8705, 4.77 , 4.979 , 6.732 , 7.151 , 0.937 ,\n",
+ " 1.52 , 2.692 , 3.995 , 0.68 , 0.147 , 0.231 , 0.675 ],\n",
+ " [ 0.4 , 0.28 , 0.35 , 0.83 , 0.6 , 0.64 ,\n",
+ " 0.8 , 0.225 , 0.129 , 0.222 , 0.263 , 0.525 ,\n",
+ " 0.714 , 0.919 , 1.202 , 1.385 , 1.607 , 1.866 ,\n",
+ " 1.475 , 1.88 , 2.163 , 2.395 , 2.83 , 0.326 ,\n",
+ " 0.862 , 1.473 , 2.274 , 0.26 , 0.62 , 0.178 , 0.253 ],\n",
+ " [ 0.5 , 0.39 , 0.45 , 0.102 , 0.1 , 0.87 ,\n",
+ " 0.171 , 0.27 , 0.162 , 0.272 , 0.359 , 0.636 ,\n",
+ " 0.952 , 1.311 , 1.965 , 2.199 , 2.3975, 3.42 ,\n",
+ " 2.397 , 2.855 , 2.935 , 3.413 , 4.4 , 0.534 ,\n",
+ " 1.105 , 2.147 , 2.773 , 0.44 , 0.8 , 0.145 , 0.381 ],\n",
+ " [ 0.5 , 0.39 , 0.14 , 0.153 , 0.1 , 0.12 ,\n",
+ " 0.103 , 0.257 , 0.186 , 0.253 , 0.42 , 0.852 ,\n",
+ " 0.945 , 1.319 , 1.926 , 1.779 , 2.23 , 2.445 ,\n",
+ " 2.262 , 2.565 , 2.833 , 3.318 , 3.743 , 0.456 ,\n",
+ " 1.298 , 1.967 , 2.767 , 0.46 , 0.77 , 0.162 , 0.334 ],\n",
+ " [ 0.4 , 0.4 , 0.51 , 0.144 , 0.9 , 0.8 ,\n",
+ " 0.135 , 0.36 , 0.162 , 0.443 , 0.343 , 0.681 ,\n",
+ " 0.933 , 1.357 , 1.623 , 1.834 , 2.4315, 2.626 ,\n",
+ " 2.098 , 2.467 , 2.755 , 4.685 , 3.96 , 0.542 ,\n",
+ " 1.199 , 2.159 , 2.642 , 0.38 , 0.93 , 0.151 , 0.331 ]])}}"
+ ]
+ },
+ "execution_count": 82,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "larceny_dats"
+ ]
+ },
{
"cell_type": "markdown",
"metadata": {},
diff --git a/ilp_measurement.py b/ilp_measurement.py
index a589a6f..7e43d83 100644
--- a/ilp_measurement.py
+++ b/ilp_measurement.py
@@ -297,8 +297,18 @@ def clean(dryrun = False):
total += secure_remove({'profiling/splitted': ['*.csv']}, globbing = True, dryrun = dryrun)
print 'Removed {} files.'.format(total)
+dummy_values = {'timestamp': '1970-01-01T00:00:00.00', 'dir': 'dummy-001', 'step': '01-dummy', 'attname': 'dummyatt'}
+
@task(name = 'distinction-of-changes')
def change_distinction():
+ def maybe_insert_dummy(f):
+ with open(f, 'a+') as fd:
+ header = next(fd)
+ if not next(fd, False):
+ # insert dummy data
+ keys = (key.strip() for key in header.split(','))
+ values = [dummy_values.get(key, '0') for key in keys]
+ fd.write(','.join(values))
with open(change_kinds) as fd:
d = json.load(fd)
unnormal = '-v -e ' + ' -e '.join((c for c in d['strategies'] if c != 'normal'))
@@ -313,6 +323,7 @@ def change_distinction():
sol_target = 'profiling/splitted/sol_{0}_{1}.csv'.format(change, sol_name)
local_quiet('tail -n +2 profiling/sol-header > {0}'.format(sol_target))
local_quiet('tail -n +2 {0} | grep -e {1} | cat >> {2}'.format(f, change, sol_target))
+ maybe_insert_dummy(sol_target)
# att percentages (only per change kinds)
f = 'profiling/att-percentages.csv'
@@ -320,6 +331,7 @@ def change_distinction():
local_quiet('head -n 1 profiling/att-percentages.csv > {}'.format(target))
local_quiet('tail -n +2 {0} | grep -e {1} | cat >> {2}'.format(
f, change, target))
+ maybe_insert_dummy(target)
for strategy in d['strategies']:
sys.stdout.write('.')
@@ -330,13 +342,14 @@ def change_distinction():
shutil.copy('profiling/gen-header', gen_target)
local_quiet('tail -n +2 {0} | grep -e {1} | grep {2} | cat >> {3}'.format(
f, change, get_strategy_pattern(strategy), gen_target))
+ maybe_insert_dummy(gen_target)
# att totals
f = 'profiling/all-att-results.csv'
target = 'profiling/splitted/att_{0}_{1}.csv'.format(change, strategy)
local_quiet('head -n 1 profiling/att-totals.csv > {}'.format(target))
local_quiet('tail -n +2 {0} | grep -e {1} | grep {2} | cat >> {3}'.format(
f, change, get_strategy_pattern(strategy), target))
-
+ maybe_insert_dummy(target)
@task(name = 'prepare-noncached')
def prepare_noncached():
diff --git a/scheme.properties b/scheme.properties
index b61fe58..2fb18ca 100644
--- a/scheme.properties
+++ b/scheme.properties
@@ -5,6 +5,6 @@ timing = 0
log.info = 1
log.debug = 0
measure.lp.write = 0
-measure.profiling = 0
-measure.flush = 1
+measure.profiling = 1
+measure.flush = 0
measure.non-chached = 0
--
GitLab