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Added cap limits on graphs.

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Surprisingly hard to understand what the cap limit should be.
This commit is contained in:
Michael Whittaker 2021-02-02 23:00:23 -08:00
parent 1616a855f1
commit bdd4e8925e
1 changed files with 31 additions and 7 deletions
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38
quorums/viz.py
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@ -34,7 +34,7 @@ def plot_node_load_on(ax: plt.Axes,
write_fraction: Optional[Distribution] = None):
_plot_node_load_on(ax,
strategy,
nodes or list(strategy.qs.nodes()),
nodes or list(strategy.nodes()),
scale=1,
scale_by_node_capacity=True,
read_fraction=read_fraction,
@ -61,7 +61,7 @@ def plot_node_utilization_on(ax: plt.Axes,
write_fraction: Optional[Distribution] = None):
_plot_node_load_on(ax,
strategy,
nodes or list(strategy.qs.nodes()),
nodes or list(strategy.nodes()),
scale=strategy.capacity(read_fraction, write_fraction),
scale_by_node_capacity=True,
read_fraction=read_fraction,
@ -86,13 +86,28 @@ def plot_node_throughput_on(ax: plt.Axes,
nodes: Optional[List[Node[T]]] = None,
read_fraction: Optional[Distribution] = None,
write_fraction: Optional[Distribution] = None):
nodes = nodes or list(strategy.nodes())
d = distribution.canonicalize_rw(read_fraction, write_fraction)
fr = sum(weight * fr for (fr, weight) in d.items())
fw = 1 - fr
node_limits = [
fr * strategy.x_read_probability[node.x] / node_load +
fw * strategy.x_write_probability[node.x] / node_load
for node in nodes
for node_load in [strategy.node_load(
node,
read_fraction=read_fraction,
write_fraction=write_fraction
)]
]
_plot_node_load_on(ax,
strategy,
nodes or list(strategy.qs.nodes()),
nodes,
scale=strategy.capacity(read_fraction, write_fraction),
scale_by_node_capacity=False,
read_fraction=read_fraction,
write_fraction=write_fraction)
write_fraction=write_fraction,
node_limits=node_limits)
def _plot_node_load_on(ax: plt.Axes,
@ -101,7 +116,8 @@ def _plot_node_load_on(ax: plt.Axes,
scale: float,
scale_by_node_capacity: bool,
read_fraction: Optional[Distribution] = None,
write_fraction: Optional[Distribution] = None):
write_fraction: Optional[Distribution] = None,
node_limits: List[float] = None):
d = distribution.canonicalize_rw(read_fraction, write_fraction)
x_list = [node.x for node in nodes]
x_index = {x: i for (i, x) in enumerate(x_list)}
@ -113,6 +129,7 @@ def _plot_node_load_on(ax: plt.Axes,
bar_heights[x_index[x]] = 1
return bar_heights
width = 0.8
def plot_quorums(sigma: Dict[FrozenSet[T], float],
fraction: float,
bottoms: np.array,
@ -127,7 +144,7 @@ def _plot_node_load_on(ax: plt.Axes,
bar_heights,
bottom=bottoms,
color=cmap(0.75 - i * 0.5 / len(sigma)),
edgecolor='white', width=0.8)
edgecolor='white', width=width)
for j, (bar_height, bottom) in enumerate(zip(bar_heights, bottoms)):
text = ''.join(str(x) for x in sorted(list(quorum))) # type: ignore
@ -136,6 +153,7 @@ def _plot_node_load_on(ax: plt.Axes,
ha='center', va='center')
bottoms += bar_heights
# Plot the quorums.
fr = sum(weight * fr for (fr, weight) in d.items())
fw = 1 - fr
read_capacities = np.array([node.read_capacity for node in nodes])
@ -145,6 +163,12 @@ def _plot_node_load_on(ax: plt.Axes,
matplotlib.cm.get_cmap('Reds'))
plot_quorums(sigma.sigma_w, fw, bottoms,
write_capacities, matplotlib.cm.get_cmap('Blues'))
# Plot the limits, if there are any.
if node_limits is not None:
for (i, limit) in enumerate(node_limits):
ax.plot([i - width/2, i + width/2], [limit, limit], color='black')
ax.set_xticks(x_ticks)
ax.set_xticklabels(str(x) for x in x_list)
@ -171,7 +195,7 @@ def _group(segments: Dict[T, Segment]) -> Dict[Segment, List[T]]:
def plot_load_distribution_on(ax: plt.Axes,
strategy: Strategy[T],
nodes: Optional[List[Node[T]]] = None):
nodes = nodes or list(strategy.qs.nodes())
nodes = nodes or list(strategy.nodes())
# We want to plot every node's load distribution. Multiple nodes might
# have the same load distribution, so we group the nodes by their