126 lines
4.1 KiB
Python
126 lines
4.1 KiB
Python
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from util import constants as C
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import osmnx as ox
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import pandas as pd
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import pickle as pkl
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from tqdm import tqdm
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from matplotlib import pyplot as plt
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import seaborn as sb
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sb.set()
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def plot_samples(
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meta_file_path="/home/haosheng/dataset/camera/deployment/verified_0425.csv"):
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data = pd.read_csv(meta_file_path)
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for city, place in list(C.CITIES.items()):
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with open(f"/home/haosheng/dataset/camera/shape/graph/{city}.pkl", "rb") as f:
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G = pkl.load(f)
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ox.plot.plot_graph(G,
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figsize=(12, 12),
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bgcolor='white',
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node_color='#696969',
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edge_color="#A9A9A9",
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edge_linewidth=0.8,
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node_size=0,
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edge_alpha=0.5,
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save=False,
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show=False)
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sample = data.query(f'city == "{city}"')
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plt.scatter(
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sample.lon_anchor,
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sample.lat_anchor,
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s=0.2,
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c='blue',
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alpha=1)
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plt.tight_layout()
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plt.savefig(f"figures/samples_{city}.png")
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print(f"Save figure to [figures/samples_{city}.png]")
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def plot_prepost(
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meta_file_path="/home/haosheng/dataset/camera/deployment/verified_prepost_0425.csv"):
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data = pd.read_csv(meta_file_path)
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for city, place in list(C.CITIES.items())[:10]:
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with open(f"/home/haosheng/dataset/camera/shape/graph/{city}.pkl", "rb") as f:
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G = pkl.load(f)
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ox.plot.plot_graph(G,
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figsize=(12, 12),
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bgcolor='white',
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node_color='#696969',
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edge_color="#A9A9A9",
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edge_linewidth=0.8,
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node_size=0,
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edge_alpha=0.5,
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save=False,
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show=False)
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print("Generating the plot .. ")
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pre = data.query(
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f'camera_count > 0 and split == "pre" and city == "{city}"')
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post = data.query(
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f'camera_count > 0 and split == "post" and city == "{city}"')
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plt.scatter(
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pre.lon_anchor,
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pre.lat_anchor,
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s=150,
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facecolors='none',
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edgecolors='red',
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linewidth=2.0,
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marker='o')
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plt.scatter(
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post.lon_anchor,
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post.lat_anchor,
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s=120,
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c='black',
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marker='x')
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plt.tight_layout()
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plt.savefig(f"figures/prepost_spatial_distribution_{city}.png")
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print(
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f"Save figure to [figures/prepost_spatial_distribution_{city}.png]")
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def plot_post(
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meta_file_path="/home/haosheng/dataset/camera/deployment/verified_0425.csv"):
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data = pd.read_csv(meta_file_path)
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for city, place in C.CITIES.items():
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with open(f"/home/haosheng/dataset/camera/shape/graph/{city}.pkl", "rb") as f:
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G = pkl.load(f)
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ox.plot.plot_graph(G,
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figsize=(12, 12),
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bgcolor='white',
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node_color='#696969',
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edge_color="#A9A9A9",
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edge_linewidth=0.8,
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node_size=0,
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edge_alpha=0.5,
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save=False,
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show=False)
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print("Generating the plot .. ")
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pre = data.query(f'camera_count > 0 and city == "{city}"')
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post = data.query(f'camera_count > 0 and city == "{city}"')
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plt.scatter(
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pre.lon_anchor,
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pre.lat_anchor,
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color='red',
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#color='#BE0000',
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s=30,
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linewidth=2.0,
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marker='o',
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alpha=1)
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plt.tight_layout()
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plt.savefig(f"figures/post_spatial_distribution_{city}.png")
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print(f"Save figure to [figures/post_spatial_distribution_{city}.png]")
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def plot_spatial_distribution():
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plot_samples()
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plot_prepost()
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plot_post()
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