Geometry size

[1]:

import pandas as pd

blocks_gdf = pd.read_pickle('./../../data/saint_petersburg/blocks.pickle')

Utils

[2]:

import matplotlib.pyplot as plt
import geopandas as gpd

def plot(gdf: gpd.GeoDataFrame):
    columns = [c for c in gdf.columns if c != 'geometry']
    n = len(columns)

    fig, axes = plt.subplots(1, n, figsize=(6.4*n, 4.8))

    if n == 1:
        axes = [axes]

    for ax, col in zip(axes, columns):
        gdf.plot(column=col, legend=True, ax=ax)
        ax.set_title(col)
        ax.set_axis_off()

    plt.tight_layout()
    plt.show()

Area and length

[3]:

from blocksnet.analysis.geometry.size import calculate_area_length

area_length_gdf = calculate_area_length(blocks_gdf)
area_length_gdf.head()

[3]:

	geometry	site_area	site_length
0	POLYGON ((349424.859 6631180.891, 349424.751 6...	0.032316	6.386234
1	POLYGON ((352083.617 6633950.146, 352240.448 6...	137101.088247	2193.855496
2	POLYGON ((346700.642 6618453.176, 346681.107 6...	95239.084434	1508.777966
3	POLYGON ((347043.363 6618261.219, 347042.608 6...	125919.330984	2248.336940
4	POLYGON ((354879.039 6618859.116, 354845.405 6...	169860.164494	2001.684796

[4]:

plot(area_length_gdf)

../../../_images/examples_analysis_geometry_size_6_0.png

Centerlines

[5]:

from blocksnet.analysis.geometry.size import calculate_centerlines

centerlines_gdf = calculate_centerlines(blocks_gdf)
centerlines_gdf.head()

100%|██████████| 9533/9533 [00:20<00:00, 467.55it/s]

[5]:

	geometry	centerline_length
0	POLYGON ((349424.859 6631180.891, 349424.751 6...	0.420355
1	POLYGON ((352083.617 6633950.146, 352240.448 6...	608.992589
2	POLYGON ((346700.642 6618453.176, 346681.107 6...	462.121387
3	POLYGON ((347043.363 6618261.219, 347042.608 6...	913.262413
4	POLYGON ((354879.039 6618859.116, 354845.405 6...	659.375702

[6]:

plot(centerlines_gdf)

../../../_images/examples_analysis_geometry_size_9_0.png

Centroids

[7]:

from blocksnet.analysis.geometry.size import calculate_centroids

centroids_gdf = calculate_centroids(blocks_gdf)
centroids_gdf.head()

[7]:

	geometry	x	y
0	POLYGON ((349424.859 6631180.891, 349424.751 6...	349423.315419	6.631181e+06
1	POLYGON ((352083.617 6633950.146, 352240.448 6...	351918.279458	6.633874e+06
2	POLYGON ((346700.642 6618453.176, 346681.107 6...	346828.961266	6.618483e+06
3	POLYGON ((347043.363 6618261.219, 347042.608 6...	347066.360124	6.618306e+06
4	POLYGON ((354879.039 6618859.116, 354845.405 6...	355059.964903	6.618810e+06

So obviously we get two beautiful gradients

[9]:

plot(centroids_gdf)

../../../_images/examples_analysis_geometry_size_13_0.png

Radiuses

[11]:

from blocksnet.analysis.geometry.size import calculate_radiuses

radiuses_gdf = calculate_radiuses(blocks_gdf)
radiuses_gdf.head()

100%|██████████| 9533/9533 [00:00<00:00, 42059.87it/s]
100%|██████████| 9533/9533 [00:03<00:00, 2723.84it/s]

[11]:

	geometry	outer_radius	inner_radius
0	POLYGON ((349424.859 6631180.891, 349424.751 6...	1.596071	0.010049
1	POLYGON ((352083.617 6633950.146, 352240.448 6...	463.873510	108.748374
2	POLYGON ((346700.642 6618453.176, 346681.107 6...	251.353455	106.237627
3	POLYGON ((347043.363 6618261.219, 347042.608 6...	343.209085	109.514588
4	POLYGON ((354879.039 6618859.116, 354845.405 6...	350.224510	143.134306

[12]:

plot(radiuses_gdf)

../../../_images/examples_analysis_geometry_size_16_0.png