haversine

CLLocation Category for Calculating Bearing w/ Haversine function

∥☆過路亽.° 提交于 2019-11-26 18:46:06
I'm trying to write a category for CLLocation to return the bearing to another CLLocation. I believe I'm doing something wrong with the formula (calculous is not my strong suit). The returned bearing is always off. I've been looking at this question and tried applying the changes that were accepted as a correct answer and the webpage it references: Calculating bearing between two CLLocationCoordinate2Ds http://www.movable-type.co.uk/scripts/latlong.html Thanks for any pointers. I've tried incorporating the feedback from that other question and I'm still just not getting something. Thanks Here

Vectorised Haversine formula with a pandas dataframe

回眸只為那壹抹淺笑 提交于 2019-11-26 16:45:48
I know that to find the distance between two latitude, longitude points I need to use the haversine function: def haversine(lon1, lat1, lon2, lat2): lon1, lat1, lon2, lat2 = map(radians, [lon1, lat1, lon2, lat2]) dlon = lon2 - lon1 dlat = lat2 - lat1 a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2 c = 2 * asin(sqrt(a)) km = 6367 * c return km I have a DataFrame where one column is latitude and another column is longitude. I want to find out how far these points are from a set point, -56.7213600, 37.2175900. How do I take the values from the DataFrame and put them into the function?

Fast Haversine Approximation (Python/Pandas)

末鹿安然 提交于 2019-11-26 11:49:48
Each row in a Pandas dataframe contains lat/lng coordinates of 2 points. Using the Python code below, calculating the distances between these 2 points for many (millions) of rows takes a very long time! Considering that the 2 points are under 50 miles apart and accuracy is not very important, is it possible to make the calculation faster? from math import radians, cos, sin, asin, sqrt def haversine(lon1, lat1, lon2, lat2): """ Calculate the great circle distance between two points on the earth (specified in decimal degrees) """ # convert decimal degrees to radians lon1, lat1, lon2, lat2 = map

CLLocation Category for Calculating Bearing w/ Haversine function

妖精的绣舞 提交于 2019-11-26 06:36:02
问题 I\'m trying to write a category for CLLocation to return the bearing to another CLLocation. I believe I\'m doing something wrong with the formula (calculous is not my strong suit). The returned bearing is always off. I\'ve been looking at this question and tried applying the changes that were accepted as a correct answer and the webpage it references: Calculating bearing between two CLLocationCoordinate2Ds http://www.movable-type.co.uk/scripts/latlong.html Thanks for any pointers. I\'ve tried

Haversine formula with php

試著忘記壹切 提交于 2019-11-26 06:29:31
问题 I want to use this formula with php. I have a database with some values of latitute and longitude saved. I want to find, with a certain value of latitude and longitude in input, all the distances (in km) from this point with each point in the database. To do this, I used the formula on googlemaps api: ( 6371 * acos( cos( radians(37) ) * cos( radians( lat ) ) * cos( radians( lng ) - radians(-122) ) + sin( radians(37) ) * sin( radians( lat ) ) ) ) Of course using that in php I replaced radians

Measuring the distance between two coordinates in PHP

五迷三道 提交于 2019-11-26 05:52:55
Hi I have the need to calculate the distance between two points having the lat and long. I would like to avoid any call to external API. I tried to implement the Haversine Formula in PHP: Here is the code: class CoordDistance { public $lat_a = 0; public $lon_a = 0; public $lat_b = 0; public $lon_b = 0; public $measure_unit = 'kilometers'; public $measure_state = false; public $measure = 0; public $error = ''; public function DistAB() { $delta_lat = $this->lat_b - $this->lat_a ; $delta_lon = $this->lon_b - $this->lon_a ; $earth_radius = 6372.795477598; $alpha = $delta_lat/2; $beta = $delta_lon

Using the Haversine Formula in Javascript

你。 提交于 2019-11-26 05:31:21
问题 I\'m trying to use the Haversine Distance Formula (as found here: http://www.movable-type.co.uk/scripts/latlong.html) but I can\'t get it to work, please see the following code function test() { var lat2 = 42.741; var lon2 = -71.3161; var lat1 = 42.806911; var lon1 = -71.290611; var R = 6371; // km //has a problem with the .toRad() method below. var dLat = (lat2-lat1).toRad(); var dLon = (lon2-lon1).toRad(); var a = Math.sin(dLat/2) * Math.sin(dLat/2) + Math.cos(lat1.toRad()) * Math.cos(lat2

Vectorised Haversine formula with a pandas dataframe

无人久伴 提交于 2019-11-26 04:55:17
问题 I know that to find the distance between two latitude, longitude points I need to use the haversine function: def haversine(lon1, lat1, lon2, lat2): lon1, lat1, lon2, lat2 = map(radians, [lon1, lat1, lon2, lat2]) dlon = lon2 - lon1 dlat = lat2 - lat1 a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2 c = 2 * asin(sqrt(a)) km = 6367 * c return km I have a DataFrame where one column is latitude and another column is longitude. I want to find out how far these points are from a set

Measuring the distance between two coordinates in PHP

我只是一个虾纸丫 提交于 2019-11-26 01:56:00
问题 Hi I have the need to calculate the distance between two points having the lat and long. I would like to avoid any call to external API. I tried to implement the Haversine Formula in PHP: Here is the code: class CoordDistance { public $lat_a = 0; public $lon_a = 0; public $lat_b = 0; public $lon_b = 0; public $measure_unit = \'kilometers\'; public $measure_state = false; public $measure = 0; public $error = \'\'; public function DistAB() { $delta_lat = $this->lat_b - $this->lat_a ; $delta_lon

Fast Haversine Approximation (Python/Pandas)

房东的猫 提交于 2019-11-26 01:08:37
问题 Each row in a Pandas dataframe contains lat/lng coordinates of 2 points. Using the Python code below, calculating the distances between these 2 points for many (millions) of rows takes a very long time! Considering that the 2 points are under 50 miles apart and accuracy is not very important, is it possible to make the calculation faster? from math import radians, cos, sin, asin, sqrt def haversine(lon1, lat1, lon2, lat2): \"\"\" Calculate the great circle distance between two points on the