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# Copyright (c) Meta Platforms, Inc. and affiliates.
from collections import Counter, defaultdict
from typing import Dict
import matplotlib.pyplot as plt
import numpy as np
import plotly.graph_objects as go
from .parser import (
filter_area,
filter_node,
filter_way,
match_to_group,
parse_area,
parse_node,
parse_way,
Patterns,
)
from .reader import OSMData
def recover_hierarchy(counter: Counter) -> Dict:
"""Recover a two-level hierarchy from the flat group labels."""
groups = defaultdict(dict)
for k, v in sorted(counter.items(), key=lambda x: -x[1]):
if ":" in k:
prefix, group = k.split(":")
if prefix in groups and isinstance(groups[prefix], int):
groups[prefix] = {}
groups[prefix][prefix] = groups[prefix]
groups[prefix] = {}
groups[prefix][group] = v
else:
groups[k] = v
return dict(groups)
def bar_autolabel(rects, fontsize):
"""Attach a text label above each bar in *rects*, displaying its height."""
for rect in rects:
width = rect.get_width()
plt.gca().annotate(
f"{width}",
xy=(width, rect.get_y() + rect.get_height() / 2),
xytext=(3, 0), # 3 points vertical offset
textcoords="offset points",
ha="left",
va="center",
fontsize=fontsize,
)
def plot_histogram(counts, fontsize, dpi):
fig, ax = plt.subplots(dpi=dpi, figsize=(8, 20))
labels = []
for k, v in counts.items():
if isinstance(v, dict):
labels += list(v.keys())
v = list(v.values())
else:
labels.append(k)
v = [v]
bars = plt.barh(
len(labels) + -len(v) + np.arange(len(v)), v, height=0.9, label=k
)
bar_autolabel(bars, fontsize)
ax.set_yticklabels(labels, fontsize=fontsize)
ax.axes.xaxis.set_ticklabels([])
ax.xaxis.tick_top()
ax.invert_yaxis()
plt.yticks(np.arange(len(labels)))
plt.xscale("log")
plt.legend(ncol=len(counts), loc="upper center")
def count_elements(elems: Dict[int, str], filter_fn, parse_fn) -> Dict:
"""Count the number of elements in each group."""
counts = Counter()
for elem in filter(filter_fn, elems.values()):
group = parse_fn(elem.tags)
if group is None:
continue
counts[group] += 1
counts = recover_hierarchy(counts)
return counts
def plot_osm_histograms(osm: OSMData, fontsize=8, dpi=150):
counts = count_elements(osm.nodes, filter_node, parse_node)
plot_histogram(counts, fontsize, dpi)
plt.title("nodes")
counts = count_elements(osm.ways, filter_way, parse_way)
plot_histogram(counts, fontsize, dpi)
plt.title("ways")
counts = count_elements(osm.ways, filter_area, parse_area)
plot_histogram(counts, fontsize, dpi)
plt.title("areas")
def plot_sankey_hierarchy(osm: OSMData):
triplets = []
for node in filter(filter_node, osm.nodes.values()):
label = parse_node(node.tags)
if label is None:
continue
group = match_to_group(label, Patterns.nodes)
if group is None:
group = match_to_group(label, Patterns.ways)
if group is None:
group = "null"
if ":" in label:
key, tag = label.split(":")
if tag == "yes":
tag = key
else:
key = tag = label
triplets.append((key, tag, group))
keys, tags, groups = list(zip(*triplets))
counts_key_tag = Counter(zip(keys, tags))
counts_key_tag_group = Counter(triplets)
key2tags = defaultdict(set)
for k, t in zip(keys, tags):
key2tags[k].add(t)
key2tags = {k: sorted(t) for k, t in key2tags.items()}
keytag2group = dict(zip(zip(keys, tags), groups))
key_names = sorted(set(keys))
tag_names = [(k, t) for k in key_names for t in key2tags[k]]
group_names = []
for k in key_names:
for t in key2tags[k]:
g = keytag2group[k, t]
if g not in group_names and g != "null":
group_names.append(g)
group_names += ["null"]
key2idx = dict(zip(key_names, range(len(key_names))))
tag2idx = {kt: i + len(key2idx) for i, kt in enumerate(tag_names)}
group2idx = {n: i + len(key2idx) + len(tag2idx) for i, n in enumerate(group_names)}
key_counts = Counter(keys)
key_text = [f"{k} {key_counts[k]}" for k in key_names]
tag_counts = Counter(list(zip(keys, tags)))
tag_text = [f"{t} {tag_counts[k, t]}" for k, t in tag_names]
group_counts = Counter(groups)
group_text = [f"{k} {group_counts[k]}" for k in group_names]
fig = go.Figure(
data=[
go.Sankey(
orientation="h",
node=dict(
pad=15,
thickness=20,
line=dict(color="black", width=0.5),
label=key_text + tag_text + group_text,
x=[0] * len(key_names)
+ [1] * len(tag_names)
+ [2] * len(group_names),
color="blue",
),
arrangement="fixed",
link=dict(
source=[key2idx[k] for k, _ in counts_key_tag]
+ [tag2idx[k, t] for k, t, _ in counts_key_tag_group],
target=[tag2idx[k, t] for k, t in counts_key_tag]
+ [group2idx[g] for _, _, g in counts_key_tag_group],
value=list(counts_key_tag.values())
+ list(counts_key_tag_group.values()),
),
)
]
)
fig.update_layout(autosize=False, width=800, height=2000, font_size=10)
fig.show()
return fig
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