File size: 2,373 Bytes
035b725 | 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 | import json
from pathlib import Path
import pandas as pd
import plotly.express as px
import plotly.io as pio
input_path = Path('triangulated_lamps.csv')
output_dir = Path('output')
output_dir.mkdir(exist_ok=True)
chart_path = output_dir / 'lamp_map_2d.png'
meta_path = output_dir / 'lamp_map_2d.png.meta.json'
csv_out = output_dir / 'lamp_map_2d_points.csv'
if not input_path.exists():
raise FileNotFoundError(f'Không tìm thấy file input: {input_path.resolve()}')
df = pd.read_csv(input_path)
required_cols = ['lamp_id', 'x_m_local', 'y_m_local', 'mean_ray_distance_m']
for c in required_cols:
if c not in df.columns:
raise ValueError(f'Thiếu cột bắt buộc: {c}')
df['lamp_id'] = df['lamp_id'].astype(str)
df['x_m_local'] = pd.to_numeric(df['x_m_local'], errors='coerce')
df['y_m_local'] = pd.to_numeric(df['y_m_local'], errors='coerce')
df['mean_ray_distance_m'] = pd.to_numeric(df['mean_ray_distance_m'], errors='coerce')
df = df.dropna(subset=['x_m_local', 'y_m_local']).copy()
df = df.sort_values('lamp_id', key=lambda s: s.astype(int))
df['label'] = 'Lamp ' + df['lamp_id']
df['ray_err_m'] = df['mean_ray_distance_m'].round(2)
df.to_csv(csv_out, index=False, encoding='utf-8-sig')
fig = px.scatter(
df,
x='x_m_local',
y='y_m_local',
color='mean_ray_distance_m',
text='lamp_id',
hover_name='label',
hover_data={
'x_m_local': ':.2f',
'y_m_local': ':.2f',
'mean_ray_distance_m': ':.2f'
},
title='2D Lamp Map (local XY)<br><span style="font-size: 18px; font-weight: normal;">Source: triangulated_lamps.csv | Color representation mean ray distance</span>'
)
fig.update_traces(
textposition='top center',
marker=dict(size=14, line=dict(width=1, color='white')),
cliponaxis=False
)
fig.update_xaxes(title_text='X local (m)')
fig.update_yaxes(title_text='Y local (m)', scaleanchor='x', scaleratio=1)
fig.write_image(str(chart_path))
with open(meta_path, 'w', encoding='utf-8') as f:
json.dump({
'caption': '2D map of lamps in the local XY system',
'description': 'Scatter plot the triangulated lamps in the local coordinate system, coloring them according to mean ray distance to check spatial stability.'
}, f, ensure_ascii=False)
print(str(chart_path))
print(str(csv_out)) |