Changeset 826 for soft/giet_vm/applications/rosenfeld/scripts/create_graph.py

Timestamp:

Jul 13, 2017, 11:01:58 AM (7 years ago)

Author:

meunier

Message:

• Mise à jour NR2 et Rosenfeld

File:

• soft/giet_vm/applications/rosenfeld/scripts/create_graph.py (modified) (4 diffs)

soft/giet_vm/applications/rosenfeld/scripts/create_graph.py

@@ -22 +22 @@
 from common import *
 
+# Creates graphes for random images with a density varying from 0 to 100%
 
-use_rand_images = True
-with_features = False
 
-threads = [1, 2, 4, 8, 16, 32, 64]
+with_features = True
+
+threads = [1, 4, 16, 64]
 use_dsk = True
 img_size = 2048
-granularity = 1
+granularities = [1, 4, 16]
 rand_seed = 7
 
@@ -36 +37 @@
 pyconf_file   = os.path.join(scripts_path, "config.py")
 
-base_data_dir  = "data"    # For timing information extracted
+base_data_dir  = "data_2016_09_21"    # For timing information extracted
 base_graph_dir = "graphes" # For storing generated graphes
 
 
-# Each of these configuration must have been run with both features activated and deactivated
+# if with_features, each of these configuration must have been run with both features activated and deactivated
 configs = [
         #{'SLOW':'1', 'FAST':'0', 'PARMERGE':'0', 'ARSP':'0'},
-        #{'SLOW':'0', 'FAST':'1', 'PARMERGE':'0', 'ARSP':'0'},
-        #{'SLOW':'0', 'FAST':'1', 'PARMERGE':'1', 'ARSP':'0'},
+        {'SLOW':'0', 'FAST':'1', 'PARMERGE':'0', 'ARSP':'0'},
+        {'SLOW':'0', 'FAST':'1', 'PARMERGE':'1', 'ARSP':'0'},
         {'SLOW':'0', 'FAST':'1', 'PARMERGE':'1', 'ARSP':'1'},
 ]
@@ -87 +88 @@
 
 
+# Phase 1: Extracting execution times
 exec_time = {}
 for config in configs:
@@ -93 +95 @@
     for thread in threads:
         exec_time[fconfig][thread] = {}
-        for ftrs in features: # Features or No features
-            exec_time[fconfig][thread][ftrs] = {}
-            for density in range(0, 101):
-                exec_time[fconfig][thread][ftrs][density] = {}
-                random_img_file = get_random_img_file(density, img_size, img_size, granularity, rand_seed)
-                img_basename = os.path.splitext(random_img_file)[0]
-                log_file = get_filename(data_dir, thread, config, ftrs == "FT", img_basename)
-                lines = open(log_file, 'r')
-                for line in lines:
-                    tokens = line.split()
-                    if len(tokens) == 0:
-                        continue
-                    tag = tokens[0]
-                    pattern = re.compile('\[STEP_([0-9]+)\]')
-                    match = pattern.match(tag)
-                    if match:
-                        step = int(match.group(1))
-                        nb_step = max(int(step) + 1, nb_step)
-                        value = tokens[len(tokens) - 1]
-                        exec_time[fconfig][thread][ftrs][density][step] = value
-                        #print("exec_time[fconfig][%d][%s][%d][%s] = %s" % (thread, ftrs, density, step, exec_time[fconfig][thread][ftrs][density][step]))
+        for granularity in granularities:
+            exec_time[fconfig][thread][granularity] = {}
+            for ftrs in features: # Features or No features
+                exec_time[fconfig][thread][granularity][ftrs] = {}
+                for density in range(0, 101):
+                    exec_time[fconfig][thread][granularity][ftrs][density] = {}
+                    random_img_file = get_random_img_file(density, img_size, img_size, granularity, rand_seed)
+                    #random_img_file = get_short_random_img_file(density, granularity)
+                    img_basename = os.path.splitext(random_img_file)[0]
+                    log_file = get_filename(data_dir, thread, config, ftrs == "FT", img_basename)
+                    lines = open(log_file, 'r')
+                    for line in lines:
+                        tokens = line.split()
+                        if len(tokens) == 0:
+                            continue
+                        tag = tokens[0]
+                        pattern = re.compile('\[STEP_([0-9]+)\]')
+                        match = pattern.match(tag)
+                        if match:
+                            step = int(match.group(1))
+                            nb_step = max(int(step) + 1, nb_step)
+                            value = tokens[len(tokens) - 1]
+                            exec_time[fconfig][thread][granularity][ftrs][density][step] = value
+                            #print("exec_time[fconfig][%d][%d][%s][%d][%s] = %s" % (thread, granularity, ftrs, density, step, exec_time[fconfig][thread][granularity][ftrs][density][step]))
 
                     
 
-
+# Phase 2: Creating plots
 for config in configs:
     fconfig = frozenset(config.items())
     for thread in threads:
-        plotter = Stack(["red", "blue", "#CAFE01", "#CA01FE", "#01CAFE"], "Légende", "X", "Y")
-        X = [x for x in range(0, 101)]
-        plotter.add_x(X)
-        assert(nb_step == 4)
-        YPAR1 = [float(int(exec_time[fconfig][thread]["NF"][density][0]) / math.pow(img_size, 2)) for density in range(0, 101)] # Parallel Labeling
-        YPAR2 = [float(int(exec_time[fconfig][thread]["NF"][density][1]) / math.pow(img_size, 2)) for density in range(0, 101)] # Merging (Parallel or Pyramidal)
-        YPTC2 = [float(int(exec_time[fconfig][thread]["NF"][density][2]) / math.pow(img_size, 2)) for density in range(0, 101)] # Parallel Transitive Closure
-        YPAR3 = [float(int(exec_time[fconfig][thread]["NF"][density][3]) / math.pow(img_size, 2)) for density in range(0, 101)] # Parallel Relabeling
+        for granularity in granularities:
+            plotter = Stack(["red", "blue", "green", "orange", "pink", "purple"], "Légende", "X", "Y")
+            X = [x for x in range(0, 101)]
+            plotter.add_x(X)
+            assert(nb_step == 5)
+            # Parallel Labeling
+            YPAR1 = [float(int(exec_time[fconfig][thread][granularity]["NF"][density][0]) / math.pow(img_size, 2)) for density in range(0, 101)]
+            # Merging (Parallel or Pyramidal)
+            YPAR2 = [float(int(exec_time[fconfig][thread][granularity]["NF"][density][1]) / math.pow(img_size, 2)) for density in range(0, 101)]
+            # Parallel Transitive Closure
+            YPTC2 = [float(int(exec_time[fconfig][thread][granularity]["NF"][density][2]) / math.pow(img_size, 2)) for density in range(0, 101)]
+            # Propagate Features if Features and ARSP, nothing otherwise
+            YPRF2 = [float(int(exec_time[fconfig][thread][granularity]["NF"][density][3]) / math.pow(img_size, 2)) for density in range(0, 101)]
+            # Parallel Relabelling
+            YPAR3 = [float(int(exec_time[fconfig][thread][granularity]["NF"][density][4]) / math.pow(img_size, 2)) for density in range(0, 101)]
 
-        plotter.add_y(YPAR1)
-        plotter.add_y(YPAR2)
-        plotter.add_y(YPTC2)
-        # Not displaying PAR3
+            plotter.add_y(YPAR1)
+            plotter.add_y(YPAR2)
+            plotter.add_y(YPTC2)
+            plotter.add_y(YPRF2)
+            # displaying PAR3
+            plotter.add_y(YPAR3)
 
-        if with_features:
-            YPAR1f = [float(int(exec_time[fconfig][thread]["FT"][density][0]) / math.pow(img_size, 2)) for density in range(0, 101)] # Parallel Labeling
-            YPAR2f = [float(int(exec_time[fconfig][thread]["FT"][density][1]) / math.pow(img_size, 2)) for density in range(0, 101)] # Merging (Parallel or Pyramidal)
-            deltaYPAR1 = [max(0, x - y) for x, y in zip (YPAR1f, YPAR1)]
-            deltaYPAR2 = [max(0, x - y) for x, y in zip (YPAR2f, YPAR2)]
-            YFTC = [x + y for x, y in zip (deltaYPAR1, deltaYPAR2)] # Features Computation
-            plotter.add_y(YFTC)
+            if with_features:
+                YPAR1F = [float(int(exec_time[fconfig][thread][granularity]["FT"][density][0]) / math.pow(img_size, 2)) for density in range(0, 101)]
+                YPAR2F = [float(int(exec_time[fconfig][thread][granularity]["FT"][density][1]) / math.pow(img_size, 2)) for density in range(0, 101)]
+                YPTC2F = [float(int(exec_time[fconfig][thread][granularity]["FT"][density][2]) / math.pow(img_size, 2)) for density in range(0, 101)]
+                YPRF2F = [float(int(exec_time[fconfig][thread][granularity]["FT"][density][3]) / math.pow(img_size, 2)) for density in range(0, 101)]
+                YPAR3F = [float(int(exec_time[fconfig][thread][granularity]["FT"][density][4]) / math.pow(img_size, 2)) for density in range(0, 101)]
+                TotalNF = [x + y + z + t + u for x, y, z, t, u in zip(YPAR1, YPAR2, YPTC2, YPRF2, YPAR3)]     # Total No Features
+                TotalFT = [x + y + z + t + u for x, y, z, t, u in zip(YPAR1F, YPAR2F, YPTC2F, YPRF2F, YPAR3F)] # Total with Features
+                YFCT = [max(0, x - y) for x, y in zip(TotalFT, TotalNF)] # Difference = Features Computation Time
+                plotter.add_y(YFCT)
 
-        plotter.plot()
-        graph_name = get_graph_filename(graph_dir, thread, config, ".pdf")
-        print("# Creating graph %s" % short_path(graph_name))
-        plotter.save(graph_name)
+            plotter.plot()
+            graph_name = get_graph_filename(graph_dir, thread, granularity, config, ".pdf")
+            print("# Creating graph %s" % short_path(graph_name))
+            plotter.save(graph_name)