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testcdl.py
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testcdl.py
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#testcdl
from CDL_utils import *
import cv2
def test_cdl_box():
cd = cdl_utils()
cd.load_np_cdl('cdl_chicago.npy')
min_lon = -89
max_lon = -88
min_lat = 41
max_lat = 42
dat = cd.get_cdl_box_data(min_lon, max_lon, min_lat, max_lat)
img = np.zeros((int(-1/cd.x_step) + 5, int(1/cd.y_step) +5, 3))
dict_ = {1: [0.0,255.0,255.0],5: [0.0,255.0,0.0],3: [0.0,0.0,0.0]}
for i in range(dat.shape[0]):
for j in range(dat.shape[1]):
if dat[i,j] in dict_:
img[i,j] = dict_[dat[i,j]]
cv2.imwrite("cdl41428889.png", img)
print(dat.shape)
print(img.shape)
return img
def test_cdl_proportion():
cd = cdl_utils()
cd.load_np_cdl('cdl_chicago.npy')
min_lon = -89.0
max_lon = -88.92
min_lat = 41.89
max_lat = 42
dat = cd.get_cdl_box_data(min_lon, max_lon, min_lat, max_lat)
unique_elements, counts_elements = np.unique(dat, return_counts=True)
proportion = cd.get_proportion(dat)
return proportion
def test_cdl_indices_geo():
cd = cdl_utils()
cd.load_np_cdl('cdl_chicago.npy')
p1 = (41.5, -88)
p2 = (41.7, -87.5)
p3 = (40.7, -87.6)
p4 = (40.6, -88.1)
ind = cd.get_cdl_indices_geo(p1, p2, p3, p4)
vals = cd.get_cdl_by_indices(ind, cd.cdl_data)
proportion = cd.get_proportion(np.array(vals))
print(len(ind), proportion)
return
test_cdl_indices_geo()