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ca09663 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 | import numpy as np
import plotly.graph_objects as go
from data_loader import ARTIFACT_COLORS, ARTIFACT_LABEL_MAP
CHANNEL_SPACING = 1.0
def build_eeg_figure(
signal: np.ndarray,
channel_names: list[str],
sampling_rate_hz: float,
start_time_s: float = 0.0,
annotations: list[dict] | None = None,
title: str = "EEG Signal",
) -> go.Figure:
n_channels, n_samples = signal.shape
time_axis = start_time_s + np.arange(n_samples) / sampling_rate_hz
normalized = np.zeros_like(signal, dtype=np.float32)
for i in range(n_channels):
p2p = np.nanpercentile(signal[i], 97.5) - np.nanpercentile(signal[i], 2.5)
if p2p > 0:
normalized[i] = signal[i] / p2p * CHANNEL_SPACING * 0.8
else:
normalized[i] = 0.0
fig = go.Figure()
if annotations:
_add_artifact_shapes(fig, annotations, start_time_s, time_axis[-1], n_channels)
for i in range(n_channels):
ch_data = normalized[i]
offset = -i * CHANNEL_SPACING
name = channel_names[i] if i < len(channel_names) else f"Ch{i}"
fig.add_trace(go.Scatter(
x=time_axis,
y=ch_data + offset,
mode="lines",
name=name,
line=dict(width=0.8, color=f"hsl({(i * 37) % 360}, 70%, 65%)"),
hovertemplate=(
f"<b>{name}</b><br>"
"Time: %{x:.3f}s<br>"
"Amplitude: %{customdata:.1f} uV<extra></extra>"
),
customdata=signal[i],
))
y_ticks = [-i * CHANNEL_SPACING for i in range(n_channels)]
y_labels = [channel_names[i] if i < len(channel_names) else f"Ch{i}" for i in range(n_channels)]
fig.update_layout(
title=dict(text=title, font=dict(size=14)),
xaxis=dict(
title="Time (s)",
showgrid=True,
gridcolor="rgba(128,128,128,0.2)",
zeroline=False,
dtick=1.0,
),
yaxis=dict(
tickvals=y_ticks,
ticktext=y_labels,
showgrid=False,
zeroline=False,
),
height=max(500, n_channels * 30 + 120),
margin=dict(l=110, r=20, t=50, b=50),
plot_bgcolor="rgb(15, 15, 25)",
paper_bgcolor="rgb(10, 10, 20)",
font=dict(color="rgb(200, 200, 210)", size=11),
showlegend=False,
hovermode="x unified",
dragmode="zoom",
)
return fig
def _add_artifact_shapes(
fig: go.Figure,
annotations: list[dict],
view_start: float,
view_end: float,
n_channels: int,
) -> None:
y_top = CHANNEL_SPACING
y_bottom = -(n_channels - 0.5) * CHANNEL_SPACING
for ann in annotations:
onset = max(ann["onset_s"], view_start)
end = min(ann["end_s"], view_end)
if onset >= end:
continue
label = ann.get("label", ann.get("raw_label", ""))
color = ann.get("color", "rgba(128, 128, 128, 0.3)")
strong_color = color.replace("0.25)", "0.35)")
fig.add_shape(
type="rect",
x0=onset, x1=end,
y0=y_bottom, y1=y_top,
fillcolor=strong_color,
line=dict(width=1, color=strong_color.replace("0.35)", "0.7)")),
layer="below",
)
mid_x = (onset + end) / 2
if (end - onset) > 0.2:
fig.add_annotation(
x=mid_x,
y=y_top + CHANNEL_SPACING * 0.3,
text=f"<b>{label}</b>",
showarrow=False,
font=dict(size=11, color="white"),
bgcolor=strong_color.replace("0.35)", "0.85)"),
borderpad=3,
)
def build_artifact_legend() -> str:
items = []
for label, color in ARTIFACT_COLORS.items():
if label in ("Clean", "Background"):
continue
rgba_solid = color.replace("0.25)", "0.85)")
items.append(
f'<div style="display:flex;align-items:center;margin:4px 0;">'
f'<span style="display:inline-block;width:16px;height:16px;'
f'background:{rgba_solid};border-radius:3px;margin-right:8px;'
f'flex-shrink:0;"></span>'
f'<span style="font-size:13px;">{label}</span></div>'
)
return '<div style="padding:4px;">' + "".join(items) + "</div>"
def build_metadata_html(info: dict) -> str:
rows = [
("Recording ID", info.get("recording_id", "N/A")),
("Dataset", info.get("dataset_id", "N/A")),
("Subject", info.get("subject", "N/A")),
("Session", info.get("session", "N/A")),
("Task", info.get("task", "N/A")),
("Duration", f"{info.get('duration_s', 0):.1f} s"),
("Channels", f"{info.get('n_channels', 0)} ({info.get('n_eeg_channels', 0)} EEG)"),
("Sampling Rate", f"{info.get('sampling_rate_hz', 0):.0f} Hz"),
("Reference", info.get("reference", "N/A")),
("Montage", info.get("montage_name", "N/A")),
("Format", info.get("archival_format", "N/A")),
("Roundtrip", info.get("roundtrip_class", "N/A")),
]
html = '<div style="font-family:monospace; font-size:13px; line-height:1.8;">'
for label, value in rows:
html += (
f'<div><span style="color:#888;min-width:130px;display:inline-block;">'
f'{label}:</span> <span style="color:#e0e0e0;">{value}</span></div>'
)
html += "</div>"
return html
def build_annotation_summary(annotations: list[dict]) -> str:
if not annotations:
return (
'<div style="color:#888; font-size:13px; padding:8px;">'
'No artifact annotations in this window. '
'Try navigating to a different time region.</div>'
)
counts: dict[str, int] = {}
total_dur: dict[str, float] = {}
for ann in annotations:
label = ann.get("label", "Unknown")
counts[label] = counts.get(label, 0) + 1
total_dur[label] = total_dur.get(label, 0) + ann.get("duration_s", 0)
html = '<div style="font-family:monospace; font-size:13px; line-height:1.8; padding:4px;">'
html += f'<div style="color:#fff; margin-bottom:6px;"><b>Artifacts found: {len(annotations)}</b></div>'
for label in sorted(counts.keys()):
color = ARTIFACT_COLORS.get(label, "rgba(128,128,128,0.5)")
rgba_solid = color.replace("0.25)", "0.85)")
html += (
f'<div style="display:flex;align-items:center;margin:2px 0;">'
f'<span style="display:inline-block;width:12px;height:12px;'
f'background:{rgba_solid};border-radius:2px;margin-right:8px;'
f'flex-shrink:0;"></span>'
f'<span style="color:#e0e0e0;">{label}</span>: '
f'<span style="color:#aaa;">{counts[label]}x, {total_dur[label]:.1f}s total</span>'
f'</div>'
)
html += "</div>"
return html
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