71 lines
2.7 KiB
Python
71 lines
2.7 KiB
Python
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import seaborn as sb
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import numpy as np
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import osmnx as ox
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from geopy.distance import distance
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from matplotlib import pyplot as plt
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def evaluate_coverage_distance(df):
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sb.set_style("dark")
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f, axes = plt.subplots(2, 2, figsize=(12,8))
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axes[0][0].title.set_text(f"Coverage of [2011-2015]: {len(df)} / 5000 = {len(df)/5000*100:.2f}%")
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axes[0][1].title.set_text(f"Coverage of [2016-2020]: {len(df)} / 5000 = {len(df)/5000*100:.2f}%")
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sb.countplot(x="year_pre", data=df, ax=axes[0][0], palette=['#432371'])
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sb.countplot(x="year_post", data=df, ax=axes[0][1], palette=["#FAAE7B"])
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axes[0][0].set_xlabel('')
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axes[0][1].set_xlabel('')
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d1, i1 = zip(*get_closest_distances(df, 'pre'))
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d2, i2 = zip(*get_closest_distances(df, 'post'))
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sb.lineplot(x=range(len(d1)), y=d1, ax=axes[1][0])
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sb.lineplot(x=range(len(d2)), y=d2, ax=axes[1][1])
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axes[1][0].title.set_text(f"Top 50 closest distance of [2011-2015] panoramas")
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axes[1][1].title.set_text(f"Top 50 closest distance of [2016-2020] panoramas")
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return f
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def get_closest_distances(df, suffix='pre', n=50):
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lat = df[f'lat_{suffix}'].values
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lon = df[f'lon_{suffix}'].values
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D = np.sqrt(np.square(lat[:,np.newaxis] - lat) + np.square(lon[:,np.newaxis] - lon))
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D = np.tril(D) + np.triu(np.ones_like(D))
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d = []
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for i in range(n):
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x, y = np.unravel_index(D.argmin(), D.shape)
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_d = distance((lat[x], lon[x]), (lat[y], lon[y])).m
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d.append((_d, x))
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D[x,:] = D[:,x] = 1
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return sorted(d)
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def evaluate_spatial_distribution(df, city):
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sb.set_style("white")
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G = ox.graph_from_place(city, network_type='drive')
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try:
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G = ox.simplify_graph(G)
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except:
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G = G
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f, (ax1, ax2) = plt.subplots(1, 2, figsize=(24,12))
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ox.plot.plot_graph(G,
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ax=ax1,
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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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save=False,
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show=False)
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ax1.scatter(df.lon_anchor, df.lat_anchor, s=3, c='red', alpha=0.5)
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ax1.scatter(df.lon_pre, df.lat_pre, s=3, c='blue', alpha=0.5)
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ox.plot.plot_graph(G,
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ax=ax2,
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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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save=False,
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show=False)
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ax2.scatter(df.lon_anchor, df.lat_anchor, s=3, c='red', alpha=0.5)
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ax2.scatter(df.lon_post, df.lat_post, s=3, c='blue', alpha=0.5)
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plt.show()
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