diff --git a/server/data_processing/area_processing.py b/server/data_processing/area_processing.py
index 30a5679476b1b154da7a0613727fb2ca8aaa0b5b..eed3dfc93d711846541fb92e116cdce0b8778082 100644
--- a/server/data_processing/area_processing.py
+++ b/server/data_processing/area_processing.py
@@ -1,8 +1,63 @@
+import math
+from itertools import groupby
from math import pi, cos
EARTH = 6378.137 # Radius of the earth in kilometer
METER = (1 / ((2 * pi / 360) * EARTH)) / 1000 # 1 meter in degree
+
+# check if lidar points is within range of the area selected
+def inArea(position, areaRange):
+ y, x, _ = position # position to be checked
+ if (abs(areaRange[0][0]) > x > abs(areaRange[1][0])) and (abs(areaRange[0][1]) > abs(y) > abs(areaRange[1][1])):
+ return True
+ else:
+ return False
+
+# find distance between two points
+def distance(point1, point2):
+ y1, x1 = point1
+ y2, x2 = point2
+ return math.sqrt(abs(y2 - y1)**2 + abs(x2 - x1)**2)
+
+# find the closest point in json list
+def closest_points(point, list, coords_taken):
+ closest_point_found = None
+ closest_dist = float('inf')
+ for current_point in list:
+ dist = distance(point, current_point['properties']['sub_div_center'][0])
+ if dist < closest_dist and current_point not in coords_taken:
+ closest_dist = dist
+ closest_point_found = current_point
+ return closest_point_found
+
+# Calculation of height in an area from las files
+def find_height(points):
+ print(points, " 5 ")
+ height_differences = [] # final container for height data
+
+ # sort the points
+ sorted_coords = sorted(points, key=lambda coord: (coord[0], coord[1]))
+
+ # group the sorted points that has the same xy- coordinates together
+ groupCoords = [list(group) for key, group in groupby(sorted_coords, key=lambda coord: (coord[0], coord[1]))]
+
+ # loop through the groups to find the difference in height
+ for group in groupCoords:
+ if len(group) < 2 or group[0] == group[1]:
+ continue # jump over iteration if there is only one coordinate or lidar registered the same point twice
+
+ # find max and min height
+ min_height = min(coords[2] for coords in group)
+ max_height = max(coords[2] for coords in group)
+
+ # difference between them
+ difference = max_height - min_height
+ height_differences.append(difference)
+
+ # list of thickness in an area
+ return height_differences
+
def calculate_corners(lat, lng, area_offset):
"""Calculate corners of polygon based on a center coordinate
diff --git a/server/data_processing/process_lidar_data.py b/server/data_processing/process_lidar_data.py
index 3cbba72579733978ea97bc2255a30ace465d5288..ad4f1041b2c1f4a790c39c4a11eb12aa188853f5 100644
--- a/server/data_processing/process_lidar_data.py
+++ b/server/data_processing/process_lidar_data.py
@@ -3,11 +3,10 @@ import laspy
import json
import math
import utm # src: https://github.com/Turbo87/utm
-from itertools import groupby
-from server.data_processing.area_processing import calculate_corners, define_gridareas
+from server.data_processing.area_processing import (calculate_corners, define_gridareas, inArea,
+ find_height, closest_points)
-
-# hard coded files for test data
+# hard coded files for test datas
lazData_path = ["server/example_lidar_data/ot_N_000005_1.laz", "server/example_lidar_data/ot_N_000033_1.laz"]
# Info about data
@@ -30,58 +29,6 @@ def about_laz_file():
return [las.header.version, las.header.point_count, las.header.scale, las.header.offset]
-# check if lidar points is within range of the area selected
-def inArea(position, areaRange):
- y, x, _ = position # position to be checked
- if (abs(areaRange[0][0]) > x > abs(areaRange[1][0])) and (abs(areaRange[0][1]) > abs(y) > abs(areaRange[1][1])):
- return True
- else:
- return False
-
-# find distance between two points
-def distance(point1, point2):
- y1, x1 = point1
- y2, x2 = point2
- return math.sqrt(abs(y2 - y1)**2 + abs(x2 - x1)**2)
-
-# find the closest point in json list
-def closest_points(point, list, coords_taken):
- closest_point_found = None
- closest_dist = float('inf')
- for current_point in list:
- dist = distance(point, current_point['properties']['sub_div_center'][0])
- if dist < closest_dist and current_point not in coords_taken:
- closest_dist = dist
- closest_point_found = current_point
- return closest_point_found
-
-# Calculation of height in an area from las files
-def find_height(points):
- print(points, " 5 ")
- height_differences = [] # final container for height data
-
- # sort the points
- sorted_coords = sorted(points, key=lambda coord: (coord[0], coord[1]))
-
- # group the sorted points that has the same xy- coordinates together
- groupCoords = [list(group) for key, group in groupby(sorted_coords, key=lambda coord: (coord[0], coord[1]))]
-
- # loop through the groups to find the difference in height
- for group in groupCoords:
- if len(group) < 2 or group[0] == group[1]:
- continue # jump over iteration if there is only one coordinate or lidar registered the same point twice
-
- # find max and min height
- min_height = min(coords[2] for coords in group)
- max_height = max(coords[2] for coords in group)
-
- # difference between them
- difference = max_height - min_height
- height_differences.append(difference)
-
- # list of thickness in an area
- return height_differences
-
# find the height of an area based on the coordinates of it's center
# and it's affiliations (subId and groupId) (soon to be implemented
def calculate_area_data(center, body_of_water):