select closest number in array python
import numpy as np
def find_nearest(array, value):
array = np.asarray(array)
idx = (np.abs(array - value)).argmin()
return array[idx]
array = np.random.random(10)
print(array)
# [ 0.21069679 0.61290182 0.63425412 0.84635244 0.91599191 0.00213826
# 0.17104965 0.56874386 0.57319379 0.28719469]
value = 0.5
print(find_nearest(array, value))
# 0.568743859261closest point python
#kd-tree for quick nearest-neighbor lookup
import geopandas as gpd
import numpy as np
import pandas as pd
from scipy.spatial import cKDTree
from shapely.geometry import Point
gpd1 = gpd.GeoDataFrame([['John', 1, Point(1, 1)], ['Smith', 1, Point(2, 2)],
['Soap', 1, Point(0, 2)]],
columns=['Name', 'ID', 'geometry'])
gpd2 = gpd.GeoDataFrame([['Work', Point(0, 1.1)], ['Shops', Point(2.5, 2)],
['Home', Point(1, 1.1)]],
columns=['Place', 'geometry'])
def ckdnearest(gdA, gdB):
nA = np.array(list(gdA.geometry.apply(lambda x: (x.x, x.y))))
nB = np.array(list(gdB.geometry.apply(lambda x: (x.x, x.y))))
btree = cKDTree(nB)
dist, idx = btree.query(nA, k=1)
gdf = pd.concat(
[gdA.reset_index(drop=True), gdB.loc[idx, gdB.columns != 'geometry'].reset_index(drop=True),
pd.Series(dist, name='dist')], axis=1)
return gdf
ckdnearest(gpd1, gpd2)Copyright © 2021 Codeinu
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