75 lines
2.6 KiB
Python
75 lines
2.6 KiB
Python
import pandas as pd
|
|
import numpy as np
|
|
import matplotlib.pyplot as plt
|
|
from pathlib import Path
|
|
|
|
plt.rcParams.update({
|
|
'font.size': 16,
|
|
'font.family': 'serif',
|
|
'axes.labelsize': 18,
|
|
'axes.titlesize': 20,
|
|
'xtick.labelsize': 14,
|
|
'ytick.labelsize': 14,
|
|
'legend.fontsize': 14,
|
|
'figure.dpi': 300,
|
|
'axes.linewidth': 1.5,
|
|
'xtick.direction': 'in',
|
|
'ytick.direction': 'in',
|
|
'xtick.major.size': 6,
|
|
'ytick.major.size': 6,
|
|
'xtick.minor.size': 3,
|
|
'ytick.minor.size': 3,
|
|
})
|
|
|
|
|
|
def load_csv_with_standard_decimal(file_path):
|
|
with open(file_path, 'r') as f:
|
|
scene_line = f.readline().strip()
|
|
scene_name = scene_line.split(': ')[1].split('_')[0]
|
|
df = pd.read_csv(file_path, skiprows=1)
|
|
return df, scene_name
|
|
|
|
def calculate_distance(row):
|
|
origin = np.array([row['XR_Origin_X'], row['XR_Origin_Y'], row['XR_Origin_Z']])
|
|
tracked = np.array([row['TrackedObject_X'], row['TrackedObject_Y'], row['TrackedObject_Z']])
|
|
return np.linalg.norm(tracked - origin)
|
|
|
|
def process_position_data(data_dir):
|
|
data_by_scene = {}
|
|
all_distances = []
|
|
csv_files = list(Path(data_dir).glob('**/P*_PositionData*.csv'))
|
|
for file_path in csv_files:
|
|
df, scene_name = load_csv_with_standard_decimal(str(file_path))
|
|
df['Distance'] = df.apply(calculate_distance, axis=1)
|
|
all_distances.extend(df['Distance'])
|
|
if scene_name not in data_by_scene:
|
|
data_by_scene[scene_name] = []
|
|
data_by_scene[scene_name].extend(df['Distance'])
|
|
return all_distances, data_by_scene
|
|
|
|
def plot_boxplots(all_distances, data_by_scene):
|
|
plt.figure(figsize=(10, 7))
|
|
data = [distances for _, distances in sorted(data_by_scene.items())]
|
|
labels = [scene for scene in sorted(data_by_scene.keys())]
|
|
data = [all_distances] + data
|
|
labels = ['All Scenes'] + labels
|
|
box = plt.boxplot(
|
|
data, labels=labels, showmeans=True, meanline=True, showfliers=False,
|
|
boxprops=dict(linewidth=2), whiskerprops=dict(linewidth=2), capprops=dict(linewidth=2),
|
|
medianprops=dict(linewidth=2, color='black'), meanprops=dict(linewidth=2, color='C1')
|
|
)
|
|
plt.ylabel('Distance to Tracked Object (units)')
|
|
plt.xlabel('Scene')
|
|
plt.title('Distribution of Distances to Tracked Objects by Scene')
|
|
plt.xticks(rotation=20)
|
|
plt.grid(axis='y', linestyle='--', linewidth=1, alpha=0.7)
|
|
plt.tight_layout()
|
|
plt.savefig('boxplot_distances.png', dpi=600)
|
|
plt.close()
|
|
|
|
def main():
|
|
all_distances, data_by_scene = process_position_data('Recordings')
|
|
plot_boxplots(all_distances, data_by_scene)
|
|
|
|
if __name__ == "__main__":
|
|
main() |