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Grid Visualization — Dashboard Generator
==========================================
Generates a base64-encoded PNG dashboard with two panels:
1. Grid topology with bus-type coloring and line-loading heat map
2. Frequency stability trace over time
Supports both GridObservation (single-agent) and ZoneObservation (multi-agent).
"""
import io
import base64
import logging
from typing import List, Optional, Sequence, Dict, Tuple
import matplotlib
matplotlib.use('Agg') # Non-interactive backend for server use
import matplotlib.pyplot as plt
from matplotlib.lines import Line2D
import networkx as nx
from .models import GridObservation
logger = logging.getLogger(__name__)
def _parse_line_endpoints(line_id: str) -> Optional[Tuple[int, int]]:
"""Parse line ID format 'L_<from>_<to>' into endpoint bus IDs.
Returns (from, to) on success, None on parse failure.
Requires exactly the format L_<int>_<int>.
"""
try:
parts = line_id.split('_')
if len(parts) == 3 and parts[0] == "L":
return int(parts[1]), int(parts[2])
except (ValueError, IndexError):
pass
return None
def generate_dashboard(
history: Sequence,
current_obs,
config: Optional[Dict] = None,
) -> str:
"""Generate a base64-encoded PNG dashboard image.
Args:
history: Sequence of observation objects for frequency trace.
current_obs: Current GridObservation or ZoneObservation for topology.
config: Optional grid config dict. When provided, line endpoints
are read from config (robust) instead of parsed from IDs.
Returns:
Base64-encoded PNG image string (without data URI prefix).
"""
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15, 6))
try:
# Support both GridObservation and ZoneObservation
buses = getattr(current_obs, "buses",
getattr(current_obs, "local_buses", []))
lines = getattr(current_obs, "lines", None)
if lines is None:
internal = getattr(current_obs, "internal_lines", [])
boundary = getattr(current_obs, "boundary_lines", [])
lines = list(internal) + list(boundary)
# Build line endpoint lookup from config if available
line_endpoints: Dict[str, Tuple[int, int]] = {}
if config:
for l_cfg in config.get("lines", []):
line_endpoints[l_cfg["id"]] = (l_cfg["from"], l_cfg["to"])
# --- Plot 1: Grid Topology ---
G = nx.Graph()
color_map = {}
for bus in buses:
G.add_node(bus.id)
if bus.type in ['generator', 'slack']:
color_map[bus.id] = '#2ecc71' # green
elif bus.type == 'load':
color_map[bus.id] = '#e74c3c' # red
elif bus.type == 'battery':
color_map[bus.id] = '#3498db' # blue
else:
color_map[bus.id] = '#f1c40f' # yellow (renewables)
# Build graph with line data as edge attributes
for line in lines:
# Get endpoints from config (preferred) or parse from ID
if line.id in line_endpoints:
u, v = line_endpoints[line.id]
else:
parsed = _parse_line_endpoints(line.id)
if parsed is None:
continue
u, v = parsed
G.add_edge(u, v, line_id=line.id, rho=line.rho,
connected=line.connected)
# Build edge colors in G.edges() order (correct alignment)
edge_colors = []
edge_styles = []
for u, v, data in G.edges(data=True):
connected = data.get('connected', True)
rho = abs(data.get('rho', 0.0))
if not connected:
edge_colors.append('lightgray')
edge_styles.append('dashed')
elif rho > 0.9:
edge_colors.append('#e74c3c') # red
edge_styles.append('solid')
elif rho > 0.7:
edge_colors.append('#e67e22') # orange
edge_styles.append('solid')
else:
edge_colors.append('#2ecc71') # green
edge_styles.append('solid')
node_colors = [color_map.get(n, 'gray') for n in G.nodes()]
# Use config coordinates if available (stable layout)
pos = None
if config:
bus_coords = {}
for b_cfg in config.get("buses", []):
if "lon" in b_cfg and "lat" in b_cfg:
bus_coords[b_cfg["id"]] = (b_cfg["lon"], b_cfg["lat"])
if len(bus_coords) == G.number_of_nodes():
pos = bus_coords
if pos is None and G.number_of_nodes() > 0:
pos = nx.spring_layout(G, seed=42)
if G.number_of_nodes() > 0 and pos:
# Draw solid edges
solid_edges = [
(u, v) for (u, v, _), s in zip(G.edges(data=True), edge_styles)
if s == 'solid'
]
solid_colors = [
c for c, s in zip(edge_colors, edge_styles) if s == 'solid'
]
dashed_edges = [
(u, v) for (u, v, _), s in zip(G.edges(data=True), edge_styles)
if s == 'dashed'
]
dashed_colors = [
c for c, s in zip(edge_colors, edge_styles) if s == 'dashed'
]
nx.draw_networkx_nodes(
G, pos, ax=ax1, node_color=node_colors, node_size=300
)
nx.draw_networkx_labels(G, pos, ax=ax1, font_size=8)
if solid_edges:
nx.draw_networkx_edges(
G, pos, ax=ax1, edgelist=solid_edges,
edge_color=solid_colors, width=2, style='solid'
)
if dashed_edges:
nx.draw_networkx_edges(
G, pos, ax=ax1, edgelist=dashed_edges,
edge_color=dashed_colors, width=1, style='dashed'
)
# Legend
legend_elements = [
Line2D([0], [0], marker='o', color='w',
markerfacecolor='#2ecc71', markersize=10,
label='Generator/Slack'),
Line2D([0], [0], marker='o', color='w',
markerfacecolor='#e74c3c', markersize=10,
label='Load'),
Line2D([0], [0], marker='o', color='w',
markerfacecolor='#3498db', markersize=10,
label='Battery'),
Line2D([0], [0], marker='o', color='w',
markerfacecolor='#f1c40f', markersize=10,
label='Renewable'),
]
ax1.legend(handles=legend_elements, loc='upper left', fontsize=7)
else:
ax1.text(0.5, 0.5, "No buses in observation",
ha='center', va='center', transform=ax1.transAxes)
ax1.set_title("Grid Topology & Loading")
# --- Plot 2: Frequency Trace ---
if history:
history_sorted = sorted(history, key=lambda h: h.timestep)
timesteps = [h.timestep for h in history_sorted]
freqs = [h.grid_frequency for h in history_sorted]
ax2.plot(timesteps, freqs, label='Frequency (Hz)',
color='#2980b9', linewidth=1.5)
ax2.axhline(y=50.0, color='k', linestyle='--', linewidth=0.8)
ax2.fill_between(timesteps, 49.5, 50.5,
color='green', alpha=0.1, label='Normal band')
ax2.legend(fontsize=8)
else:
ax2.text(0.5, 0.5, "No frequency history",
ha='center', va='center', transform=ax2.transAxes)
ax2.set_title("Frequency Stability")
ax2.set_xlabel("Timestep")
ax2.set_ylabel("Hz")
ax2.set_ylim(48.5, 51.5)
fig.tight_layout()
buf = io.BytesIO()
fig.savefig(buf, format='png', bbox_inches='tight')
buf.seek(0)
return base64.b64encode(buf.read()).decode('utf-8')
finally:
plt.close(fig) |