Matplotlib profiling of MBC.

h2/mbc.py

@@ -14,7 +14,6 @@ def sidedness(slope: float, intersection: float, p3: Point, flipper: callable, e
     return Side.BELOW
 
 
-@Profiler("solving 1D LP")
 def solve_1dlp(c, constraints):
     c1, c2 = c
     ((a1, a2), b) = constraints[-1]
@@ -36,7 +35,7 @@ def solve_1dlp(c, constraints):
         return interval[1], q - (p * interval[1])
 
 
-@Profiler("solving 2D LP")
+@Profiler("solving LP")
 def solve_2dlp(c, constraints):
     c1, c2 = c
     x1 = -10_000 if c1 > 0 else 10_000
@@ -88,7 +87,8 @@ def mbc_ch(points: Set[Point], flipper: callable, extra_prune=False, shuffle=Tru
         pr = {p for p in points if p.x >= med_x}
 
     # Shuffle
-    constraints = [((flipper(-p.x), flipper(-1)), flipper(-p.y)) for p in points]
+    with Profiler("flipping constraints"):
+        constraints = [((flipper(-p.x), flipper(-1)), flipper(-p.y)) for p in points]
     if shuffle:
         with Profiler("shuffling constraints"):
             random.shuffle(constraints)

h2/util.py

@@ -132,3 +132,67 @@ class Side(Enum):
     ON = auto()
     ABOVE = auto()
     BELOW = auto()
+
+
+def stacked_bar(data, series_labels, category_labels=None,
+                show_values=False, value_format="{}", y_label=None,
+                grid=True, reverse=False):
+    """
+    Plots a stacked bar chart with the data and labels provided (https://stackoverflow.com/a/50205834).
+
+    Keyword arguments:
+    data            -- 2-dimensional numpy array or nested list
+                       containing data for each series in rows
+    series_labels   -- list of series labels (these appear in
+                       the legend)
+    category_labels -- list of category labels (these appear
+                       on the x-axis)
+    show_values     -- If True then numeric value labels will
+                       be shown on each bar
+    value_format    -- Format string for numeric value labels
+                       (default is "{}")
+    y_label         -- Label for y-axis (str)
+    grid            -- If True display grid
+    reverse         -- If True reverse the order that the
+                       series are displayed (left-to-right
+                       or right-to-left)
+    """
+
+    ny = len(data[0])
+    ind = list(range(ny))
+
+    axes = []
+    cum_size = np.zeros(ny)
+
+    data = np.array(data)
+
+    if reverse:
+        data = np.flip(data, axis=1)
+        category_labels = reversed(category_labels)
+
+    for i, row_data in enumerate(data):
+        axes.append(plt.bar(ind, row_data, bottom=cum_size,
+                            label=series_labels[i]))
+        cum_size += row_data
+
+    if category_labels:
+        plt.xticks(ind, category_labels)
+
+    if y_label:
+        plt.ylabel(y_label)
+
+    plt.legend()
+
+    if grid:
+        plt.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,
+                             value_format.format(h), ha="center",
+                             va="center")
+
+    plt.show()