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https://github.com/DJ2LS/FreeDATA
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95 lines
2.8 KiB
Python
95 lines
2.8 KiB
Python
import math
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def haversine(lat1, lon1, lat2, lon2):
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"""
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Calculate the great circle distance in kilometers between two points
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on the Earth (specified in decimal degrees).
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Parameters:
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lat1, lon1: Latitude and longitude of point 1.
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lat2, lon2: Latitude and longitude of point 2.
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Returns:
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float: Distance between the two points in kilometers.
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"""
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# Radius of the Earth in kilometers. Use 3956 for miles
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R = 6371.0
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# Convert latitude and longitude from degrees to radians
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lat1 = math.radians(lat1)
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lon1 = math.radians(lon1)
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lat2 = math.radians(lat2)
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lon2 = math.radians(lon2)
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# Difference in coordinates
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dlon = lon2 - lon1
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dlat = lat2 - lat1
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# Haversine formula
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a = math.sin(dlat / 2) ** 2 + math.cos(lat1) * math.cos(lat2) * math.sin(dlon / 2) ** 2
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c = 2 * math.atan2(math.sqrt(a), math.sqrt(1 - a))
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distance = R * c
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return distance
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def maidenhead_to_latlon(grid_square):
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"""
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Convert a Maidenhead locator to latitude and longitude coordinates.
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The output coordinates represent the southwestern corner of the grid square.
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Parameters:
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grid_square (str): The Maidenhead locator.
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Returns:
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tuple: A tuple containing the latitude and longitude (in that order) of the grid square's center.
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"""
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if len(grid_square) < 4 or len(grid_square) % 2 != 0:
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raise ValueError("Grid square must be at least 4 characters long and an even length.")
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grid_square = grid_square.upper()
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lon = -180 + (ord(grid_square[0]) - ord('A')) * 20
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lat = -90 + (ord(grid_square[1]) - ord('A')) * 10
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lon += (int(grid_square[2]) * 2)
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lat += int(grid_square[3])
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if len(grid_square) >= 6:
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lon += (ord(grid_square[4]) - ord('A')) * (5 / 60)
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lat += (ord(grid_square[5]) - ord('A')) * (2.5 / 60)
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if len(grid_square) == 8:
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lon += int(grid_square[6]) * (5 / 600)
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lat += int(grid_square[7]) * (2.5 / 600)
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# Adjust to the center of the grid square
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if len(grid_square) <= 4:
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lon += 1
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lat += 0.5
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elif len(grid_square) == 6:
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lon += 2.5 / 60
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lat += 1.25 / 60
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else:
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lon += 2.5 / 600
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lat += 1.25 / 600
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return lat, lon
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def distance_between_locators(locator1, locator2):
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"""
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Calculate the distance between two Maidenhead locators and return the result as a dictionary.
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Parameters:
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locator1 (str): The first Maidenhead locator.
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locator2 (str): The second Maidenhead locator.
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Returns:
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dict: A dictionary containing the distances in kilometers and miles.
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"""
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lat1, lon1 = maidenhead_to_latlon(locator1)
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lat2, lon2 = maidenhead_to_latlon(locator2)
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km = haversine(lat1, lon1, lat2, lon2)
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miles = km * 0.621371
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return {'kilometers': km, 'miles': miles}
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