PROFILE ALL THE THINGS! (well, not gift wrapper, cause it sucks.. but almost all the things!)

h2/graham.py

@@ -28,18 +28,17 @@ def graham_scan(points):
         sorted_points = sorted(points)
 
     UH = sorted_points[:2]
-    with Profiler("iterating upper hull", excluded=("calculating sidedness",)):
+    with Profiler("iterating points", excluded=("calculating sidedness",)):
         for s in sorted_points[2:]:
             while len(UH) > 1 and (sidedness(UH[-2], UH[-1], s) != Side.ABOVE):
                 del UH[-1]
             UH.append(s)
 
-    with Profiler("reversing list"):
     reversed_list = list(reversed(sorted_points))
     reversed_list.append(UH[0])
     LH = reversed_list[:2]
 
-    with Profiler("iterating lower hull", excluded=("calculating sidedness",)):
+    with Profiler("iterating points", excluded=("calculating sidedness",)):
         for s in reversed_list[2:]:
             while len(LH) > 1 and (sidedness(LH[-2], LH[-1], s) != Side.ABOVE):
                 del LH[-1]

h2/tmptest.py

@@ -10,6 +10,9 @@ from profile import Profiler
 from quick_hull import quick_hull
 import os.path
 
+import matplotlib.pyplot as plt
+
+
 #random.seed(1337_420)
 
 TimedResult = namedtuple("TimedResult", "algorithm points running_time")
@@ -96,9 +99,9 @@ def do_one_profile(num_points):
     points = {util.gen_point(0, 100) for _ in range(num_points)}
 
     tests = [
-        #("graham_scan", graham_scan),
+        ("graham_scan", graham_scan),
         #("gift_wrapper", rapper),
-        #("quick_hull", quick_hull),
+        ("quick_hull", quick_hull),
         ("mbc", mbc),
         ("mbc2", mbc2),
         ("mbc_no_shuffle", mbc_no_shuffle),
@@ -135,38 +138,94 @@ def do_one_profile(num_points):
     return results
 
 
-def do_profile():
+def plot_mbc(results, ax):
-    num_points = 60_000
-    #results = do_one_profile(num_points)
-    results = {"mbc": {"times": {"finding median": 0.006870746612548828, "partitioning set": 0.066436767578125, "flipping constraints": 0.13354206085205078, "shuffling constraints": 0.08272123336791992, "solving LP": 0.13545918464660645, "finding bridge points": 0.06052136421203613, "pruning between line points": 0.04519915580749512, "mbc": 0.5643129348754883, "other": 0.033562421798706055}, "total": 0.5643129348754883, "total_profiled": 0.5307505130767822, "unaccounted": 0.033562421798706055}, "mbc2": {"times": {"extra pruning step": 0.15866398811340332, "finding median": 0.00189971923828125, "partitioning set": 0.022511959075927734, "flipping constraints": 0.04117441177368164, "shuffling constraints": 0.030447006225585938, "solving LP": 0.05805325508117676, "finding bridge points": 0.025882959365844727, "pruning between line points": 0.014936208724975586, "mbc2": 0.3658268451690674, "other": 0.01225733757019043}, "total": 0.3658268451690674, "total_profiled": 0.35356950759887695, "unaccounted": 0.01225733757019043}, "mbc_no_shuffle": {"times": {"finding median": 0.006849050521850586, "partitioning set": 0.06539726257324219, "flipping constraints": 0.13605880737304688, "solving LP": 0.06955385208129883, "finding bridge points": 0.06419634819030762, "pruning between line points": 0.044390201568603516, "mbc_no_shuffle": 0.397723913192749, "other": 0.011278390884399414}, "total": 0.397723913192749, "total_profiled": 0.3864455223083496, "unaccounted": 0.011278390884399414}, "mbc2_no_shuffle": {"times": {"extra pruning step": 0.16416001319885254, "finding median": 0.002000570297241211, "partitioning set": 0.022954702377319336, "flipping constraints": 0.0455164909362793, "solving LP": 0.02709197998046875, "finding bridge points": 0.022936582565307617, "pruning between line points": 0.017188310623168945, "mbc2_no_shuffle": 0.30688953399658203, "other": 0.005040884017944336}, "total": 0.30688953399658203, "total_profiled": 0.3018486499786377, "unaccounted": 0.005040884017944336}}
-    print("================== RESULTS ==================")
-    print(json.dumps(results))
-
     algorithms = list(results.keys())
-
     steps = (
         "other",
         "finding median",
         "partitioning set",
         "flipping constraints",
-        "solving 2D",
+        "solving LP",
         "finding bridge points",
         "pruning between line points",
         "shuffling constraints",
         "extra pruning step",
     )
-
+    util.stacked_bar(ax=ax,
-    data = [[result["times"].get(step, 0) * 1000 for result in results.values()]
+                     data=[[result["times"].get(step, 0) * 1000 for result in results.values()] for step in steps],
-            for step in steps]
-
-    util.stacked_bar(data=data,
                      series_labels=steps,
                      category_labels=algorithms,
-                     show_values=True,
+                     value_format="{:.1f}")
-                     value_format="{:.1f}",
+
-                     y_label="time (ms)",
+
-                     grid=False,
+def plot_graham(result, ax):
-                     reverse=False)
+    steps = (
+        "other",
+        "sorting points",
+        "iterating points",
+        "calculating sidedness",
+    )
+    util.stacked_bar(ax=ax,
+                     data=[[result["times"][step] * 1000] for step in steps],
+                     series_labels=steps,
+                     category_labels=["graham scan"],
+                     value_format="{:.1f}")
+
+
+def plot_gift(result, ax):
+    steps = (
+        "other",
+        "calculating angle",
+        "calculating vector",
+    )
+    util.stacked_bar(ax=ax,
+                     data=[[result["times"][step] * 1000] for step in steps],
+                     series_labels=steps,
+                     category_labels=["gift wrapper"],
+                     value_format="{:.1f}")
+
+
+def plot_quick(result, ax):
+    steps = (
+        "other",
+        "partitioning set",
+        "finding farthest point from line",
+    )
+    util.stacked_bar(ax=ax,
+                     data=[[result["times"][step] * 1000] for step in steps],
+                     series_labels=steps,
+                     category_labels=["quickhull"],
+                     value_format="{:.1f}")
+
+
+def do_profile():
+    num_points = 60_000
+    results = do_one_profile(num_points)
+
+    print("================== RESULTS ==================")
+    print(json.dumps(results))
+
+    fig, (ax1, ax2, ax3) = plt.subplots(ncols=3, sharex=False, sharey=True, gridspec_kw={"width_ratios": (1, 1, 4)})
+
+    fig.add_subplot(111, frameon=False)
+    plt.tick_params(labelcolor='none', top='off', bottom='off', left='off', right='off')
+
+    plt.ylabel("time (ms)")
+
+    plt.subplots_adjust(wspace=0)
+
+    plot_graham(results["graham_scan"], ax1)
+
+    #plot_gift(results["gift_wrapper"], ax2)
+
+    plot_quick(results["quick_hull"], ax2)
+
+    plot_mbc({alg: data
+              for alg, data in results.items()
+              if alg.startswith("mbc")},
+             ax3)
+
+    plt.show()
 
 
 if __name__ == '__main__':

h2/util.py

@@ -134,9 +134,9 @@ class Side(Enum):
     BELOW = auto()
 
 
-def stacked_bar(data, series_labels, category_labels=None,
+def stacked_bar(ax, data, series_labels, category_labels=None,
-                show_values=False, value_format="{}", y_label=None,
+                show_values=True, value_format="{}", y_label=None,
-                grid=True, reverse=False):
+                grid=False, reverse=False):
     """
     Plots a stacked bar chart with the data and labels provided (https://stackoverflow.com/a/50205834).
 
@@ -171,28 +171,32 @@ def stacked_bar(data, series_labels, category_labels=None,
         category_labels = reversed(category_labels)
 
     for i, row_data in enumerate(data):
-        axes.append(plt.bar(ind, row_data, bottom=cum_size,
+        axes.append(ax.bar(ind, row_data, bottom=cum_size,
                             label=series_labels[i]))
         cum_size += row_data
 
     if category_labels:
+        plt.sca(ax)
         plt.xticks(ind, category_labels)
 
     if y_label:
         plt.ylabel(y_label)
 
-    plt.legend()
+    ax.legend()
+    # Reverse legend (https://stackoverflow.com/a/34576778)
+    handles, labels = ax.get_legend_handles_labels()
+    ax.legend(handles[::-1], labels[::-1])
 
     if grid:
-        plt.grid()
+        ax.grid()
 
     if show_values:
         for axis in axes:
             for bar in axis:
                 w, h = bar.get_width(), bar.get_height()
                 if h != 0:
-                    plt.text(bar.get_x() + w/2, bar.get_y() + h/2,
+                    ax.text(bar.get_x() + w/2, bar.get_y() + h/2,
                              value_format.format(h), ha="center",
                              va="center")
 
-    plt.show()
+    #plt.show()