CERC/matsim-proto
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Visualizer cleanup

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This commit is contained in:
Ruben1729 2024-02-14 16:54:41 -05:00
parent 26f867093f
commit 268ceb5d0f
1 changed files with 44 additions and 37 deletions
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matsim_visualizer.py
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@ -8,28 +8,34 @@ from collections import defaultdict
import matplotlib.cm as cm import matplotlib.cm as cm
import matplotlib.colors as colors import matplotlib.colors as colors
class MatsimVisualizer(): class MatsimVisualizer():
def __init__(self, network_file_path, events_file_path): def __init__(self, network_file_path, events_file_path, output_file_path):
self.network_file_path = network_file_path self._nodes = None
self.events_file_path = events_file_path self._links = None
self.G = nx.Graph() self._pos = None
self.pos = None
self.traffic_per_tick = defaultdict(lambda: defaultdict(int))
self.cumulative_traffic = defaultdict(lambda: defaultdict(int))
self.cmap = cm.viridis
self.norm = None self.norm = None
self._output_file_path = output_file_path
self._network_file_path = network_file_path
self._events_file_path = events_file_path
self._G = nx.Graph()
self._traffic_per_tick = defaultdict(lambda: defaultdict(int))
self._cumulative_traffic = defaultdict(lambda: defaultdict(int))
self._cmap = cm.viridis
def load_data(self): def load_data(self):
# Load network data # Load network data
with gzip.open(self.network_file_path, 'rb') as file: with gzip.open(self._network_file_path, 'rb') as file:
network_doc = xmltodict.parse(file.read().decode('utf-8')) network_doc = xmltodict.parse(file.read().decode('utf-8'))
# Parse nodes # Parse nodes
self.nodes = {node['@id']: (float(node['@x']), float(node['@y'])) for node in self._nodes = {node['@id']: (float(node['@x']), float(node['@y'])) for node in
network_doc['network']['nodes']['node']} network_doc['network']['nodes']['node']}
# Parse links # Parse links
self.links = [{ self._links = [{
'id': link['@id'], 'id': link['@id'],
'from': link['@from'], 'from': link['@from'],
'to': link['@to'] 'to': link['@to']
@ -38,7 +44,7 @@ class MatsimVisualizer():
link_state = defaultdict(list) link_state = defaultdict(list)
# Load and parse the events file # Load and parse the events file
with gzip.open(self.events_file_path, 'rb') as file: with gzip.open(self._events_file_path, 'rb') as file:
events_doc = xmltodict.parse(file.read().decode('utf-8')) events_doc = xmltodict.parse(file.read().decode('utf-8'))
for event in events_doc['events']['event']: for event in events_doc['events']['event']:
@ -49,51 +55,52 @@ class MatsimVisualizer():
if link_id is not None and event_type is not None and tick is not None: if link_id is not None and event_type is not None and tick is not None:
if event_type == 'entered link' or event_type == 'vehicle enters traffic': if event_type == 'entered link' or event_type == 'vehicle enters traffic':
self.traffic_per_tick[tick][link_id] += 1 self._traffic_per_tick[tick][link_id] += 1
link_state[link_id].append(vehicle_id) link_state[link_id].append(vehicle_id)
elif event_type == 'left link' or event_type == 'vehicle leaves traffic': elif event_type == 'left link' or event_type == 'vehicle leaves traffic':
self.traffic_per_tick[tick][link_id] -= 1 self._traffic_per_tick[tick][link_id] -= 1
link_state[link_id].remove(vehicle_id) link_state[link_id].remove(vehicle_id)
for link in self.links: for link in self._links:
self.cumulative_traffic[0][link['id']] = 0 self._cumulative_traffic[0][link['id']] = 0
# Accumulate the counts to get the total number of vehicles on each link up to each tick # Accumulate the counts to get the total number of vehicles on each link up to each tick
actual_tick = 0 actual_tick = 0
sorted_ticks = sorted(self.traffic_per_tick.keys()) sorted_ticks = sorted(self._traffic_per_tick.keys())
for tick in sorted_ticks: for tick in sorted_ticks:
if actual_tick not in self.cumulative_traffic: if actual_tick not in self._cumulative_traffic:
# Start with the vehicle counts of the previous tick # Start with the vehicle counts of the previous tick
self.cumulative_traffic[actual_tick] = defaultdict(int, self.cumulative_traffic.get(actual_tick - 1, {})) self._cumulative_traffic[actual_tick] = defaultdict(int, self._cumulative_traffic.get(actual_tick - 1, {}))
# Apply the changes recorded for the current tick # Apply the changes recorded for the current tick
for link_id, change in self.traffic_per_tick[tick].items(): for link_id, change in self._traffic_per_tick[tick].items():
self.cumulative_traffic[actual_tick][link_id] += change self._cumulative_traffic[actual_tick][link_id] += change
actual_tick += 1 # Move to the next tick actual_tick += 1 # Move to the next tick
def create_graph(self): def create_graph(self):
for node_id, coords in self.nodes.items(): for node_id, coords in self._nodes.items():
self.G.add_node(node_id, pos=coords) self._G.add_node(node_id, pos=coords)
for link in self.links: for link in self._links:
self.G.add_edge(link['from'], link['to']) self._G.add_edge(link['from'], link['to'])
self.pos = nx.get_node_attributes(self.G, 'pos') self._pos = nx.get_node_attributes(self._G, 'pos')
def setup_color_mapping(self): def setup_color_mapping(self):
# Find max traffic to setup the normalization instance # Find max traffic to setup the normalization instance
max_traffic = max(max(self.cumulative_traffic[tick].values()) for tick in self.cumulative_traffic) max_traffic = max(max(self._cumulative_traffic[tick].values()) for tick in self._cumulative_traffic)
self.norm = colors.Normalize(vmin=0, vmax=max_traffic) self.norm = colors.Normalize(vmin=0, vmax=max_traffic)
def update(self, frame_number): def update(self, frame_number):
tick = sorted(self.cumulative_traffic.keys())[frame_number] tick = sorted(self._cumulative_traffic.keys())[frame_number]
traffic_data = self.cumulative_traffic[tick] traffic_data = self._cumulative_traffic[tick]
edge_colors = [self.cmap(self.norm(traffic_data.get(link['id'], 0))) for link in self.links] edge_colors = [self._cmap(self.norm(traffic_data.get(link['id'], 0))) for link in self._links]
edge_widths = [2 + self.norm(traffic_data.get(link['id'], 0)) * 3 for link in self.links] edge_widths = [10 + self.norm(traffic_data.get(link['id'], 0)) * 10 for link in self._links]
plt.cla() plt.cla()
nx.draw(self.G, self.pos, node_size=0, node_color='blue', width=edge_widths, edge_color=edge_colors, with_labels=False, nx.draw(self._G, self._pos, node_size=0, node_color='blue', width=edge_widths, edge_color=edge_colors,
edge_cmap=self.cmap) with_labels=False,
edge_cmap=self._cmap)
plt.title(f"Time: {tick}") plt.title(f"Time: {tick}")
@ -104,10 +111,10 @@ class MatsimVisualizer():
fig, ax = plt.subplots() fig, ax = plt.subplots()
sm = plt.cm.ScalarMappable(cmap=self.cmap, norm=self.norm) sm = plt.cm.ScalarMappable(cmap=self._cmap, norm=self.norm)
sm.set_array([]) sm.set_array([])
plt.colorbar(sm, ax=ax, label='Traffic Density') plt.colorbar(sm, ax=ax, label='Traffic Density')
ani = FuncAnimation(fig, self.update, frames=len(self.cumulative_traffic), repeat=False) ani = FuncAnimation(fig, self.update, frames=len(self._cumulative_traffic), repeat=False)
ani.save('traffic_animation.gif', writer='ffmpeg', fps=5) ani.save(f"{self._output_file_path}/traffic_animation.gif", writer='ffmpeg', fps=5)
plt.show() plt.show()