Bar plots on stats

.gitignore

@@ -9,4 +9,6 @@ single_rules_both.txt
 graph_subst_single.pb
 /tmp
 bert_time.txt
-bert_old_time.txt
+bert_old_time.txt
+*.pdf
+*.png

analysis/stats.py

@@ -1,16 +1,57 @@
 from __future__ import print_function
 import argparse
 import numpy as np
+import matplotlib.pyplot as plt
 
 def get_args():
     parser = argparse.ArgumentParser(description='Analysis script, get the statistics we want')
     parser.add_argument('--mode', type=str, default='runtime',
         help='Mode of analysis')
-    parser.add_argument('--file', type=str,
+    parser.add_argument('--file', type=str, default='data.txt',
         help='File for the input data to analyze')
 
     return parser.parse_args()
 
+def plot_runtime_and_speed(benchmark_name, result):
+
+    width = 0.8
+    x_locs = [0, 1, 2, 3, 6, 7]
+    x_locs = [a + width/2 for a in x_locs]
+    colors = ['b', 'g', 'r', 'c', 'm', 'y', 'k']
+
+    fig, ax1 = plt.subplots()
+    ax1.bar(x_locs[0], result['orig_runtime'], width=width, label='Original', color=colors[0])
+    ax1.bar(x_locs[1], result['taso'], width=width, label='TASO', color=colors[1])
+    ax1.bar(x_locs[2], result['greedy'], width=width, label='Greedy', color=colors[2])
+    ax1.bar(x_locs[3], result['ilp'], width=width, label='ILP', color=colors[3])
+
+    runtimes = [result['orig_runtime'], result['taso'], result['greedy'], result['ilp']]
+
+    #low = min(runtimes)
+    #high = max(runtimes)
+    #ax1.set_ylim(low-0.5*(high-low), high+0.5*(high-low))
+    ax1.set_ylabel('Graph runtime (milliseconds)')
+
+    ax2 = ax1.twinx()
+    ax2.bar(x_locs[4], result['taso_total_time'], width=width, label='TASO total', color=colors[4])
+    ax2.bar(x_locs[4], result['taso_best_time'], width=width, label='TASO best', color=colors[5])
+    ax2.bar(x_locs[5], result['ilp_time'], width=width, label='Sat.+ILP', color=colors[6])
+
+    plt.xticks(x_locs, ['' for _ in range(len(x_locs))])
+
+    ax2.set_ylabel('Optimizer time (seconds)')
+    ax1.set_xlabel(benchmark_name)
+
+    lines, labels = ax1.get_legend_handles_labels()
+    lines2, labels2 = ax2.get_legend_handles_labels()
+    #ax2.legend(lines + lines2, labels + labels2, fontsize=10)
+    ax2.legend(lines + lines2, labels + labels2, loc='upper center', bbox_to_anchor=(0.5, 1.15), ncol=4, fancybox=True, shadow=True, prop={'size': 12})
+
+    plt.savefig("{}.png".format(benchmark_name), bbox_inches='tight')
+    plt.close()
+
+
+
 def runtime_stats(args):
     with open(args.file, 'r') as f:
         content = f.readlines()
@@ -29,11 +70,53 @@ def runtime_stats(args):
     print("Start graph runtime: mean {}, std {}".format(start_mean, start_std))
     print("Extracted graph runtime: mean {}, std {}".format(ext_mean, ext_std))
 
+def plot_bars(args):
+    results = {
+        "bert": {
+            "orig_runtime": 1.8964,
+            "taso": 1.7415,
+            "greedy": 1.8903,
+            "ilp": 1.7410,
+            "taso_total_time": 13.98,
+            "taso_best_time": 3.410,
+            "ilp_time": 3.022,
+        },
+        "nasrnn": {
+            "orig_runtime": 1.8601,
+            "taso": 1.2890,
+            "greedy": 1.1446,
+            "ilp": 1.1106,
+            "taso_total_time": 175.4, 
+            "taso_best_time": 121.1,
+            "ilp_time": 28.47,
+        },
+        "resnext50": {
+            "orig_runtime": 6.0775,
+            "taso": 5.8144,
+            "greedy": 5.5850,
+            "ilp": 5.5704,
+            "taso_total_time": 25.00,
+            "taso_best_time": 5.909,
+            "ilp_time": 1.314,
+        }
+    }
+
+    plt.rcParams.update({'font.size': 16})
+    #plt.rcParams.update({'figure.autolayout': True})
+
+    for (benchmark, result) in results.items():
+        plot_runtime_and_speed(benchmark, result)
+
+
+
+
 def main():
     # Parse arguments
     args = get_args()
     if args.mode == 'runtime':
         runtime_stats(args)
+    elif args.mode == 'plot':
+        plot_bars(args)
 
 if __name__ == '__main__':
     try: