.NET Equivalent of SQL Server STDistance
来源： https://stackoverflow.com/questions/15975066/net-equivalent-of-sql-server-stdistance
geographic-distance
.NET Equivalent of SQL Server STDistance
来源： https://stackoverflow.com/questions/15975066/net-equivalent-of-sql-server-stdistance
Measuring geographic distance with scipy
问题 I fail to use the outcome of scipy 's pdist function. I am interested in the real geographic distance (preferred unit: km). Take the following coordinates: from scipy.spatial.distance import pdist coordinates = [ (42.057, -71.08), (39.132, -84.5155) ] distance = pdist(coordinates) print distance # [ 13.75021037] But what's the unit? Google says the distance between these two points is 1179 km. How do I get there from 13.75021037? 回答1: Using the latest Python 3, this now gives a deprecation
Measuring geographic distance with scipy
问题 I fail to use the outcome of scipy 's pdist function. I am interested in the real geographic distance (preferred unit: km). Take the following coordinates: from scipy.spatial.distance import pdist coordinates = [ (42.057, -71.08), (39.132, -84.5155) ] distance = pdist(coordinates) print distance # [ 13.75021037] But what's the unit? Google says the distance between these two points is 1179 km. How do I get there from 13.75021037? 回答1: Using the latest Python 3, this now gives a deprecation
Get pitch, roll and yaw relative to geographic north on iOS?
问题 I see that I can retrieve CMAttitude from a device and from it I can read 3 values which I need (pitch, roll and yaw). As I understand, this CMAttitude object is managed by CoreMotion which is a Sensor Fusion manager for calculating correct results from compass, gyro and accelerometer together (on Android it is SensorManager Class). So my questions are: Are those values (pitch, roll and yaw) relative to the magnetic north and gravity? If above is correct, how can I modify it to give me
Python module for storing and querying geographical coordinates
问题 Is there a Python module where I can create objects with a geographical location coordinate (latitude and longitude), and query all the objects for ones which are within a 5km distance (i.e. radius) of a given coordinate? I've been trying to store the latitude and longitude as keys in dictionaries (as they're indexed by key) and use some distance finding algorithms to query them. But this feels like a horrible hack. Essentially something like PostGIS for PostgreSQL, but all within my Python
Distance of wgs point from a wgs defined line segment
问题 I searched but I could not find a complete answer. In C# if at all possible. I need the shortest distance between a WGS point and a WGS point defined line segment on a sphere (Earth exactly). float DistanceInKilometres(PointF LineStartA, PointF LineEndB, PointF ThePoint) EDIT: Perhaps an illustration would help Please note that this is an ideal example. 'The point' could be anywhere on the surface of the sphere, the segment start-end, too. Obviously, I'm not looking for the distance through
Finding nearest neighbor between 2 sets of dated points
问题 I have 2 sets of points, set1 and set2 . Both sets of points have a data associated with the point. Points in set1 are "ephemeral", and only exist on the given date. Points in set2 are "permanent", are constructed at a given date, and then exist forever after that date. set.seed(1) dates <- seq(as.Date('2011-01-01'),as.Date('2011-12-31'),by='days') set1 <- data.frame(lat=40+runif(10000), lon=-70+runif(10000),date=sample(dates,10000,replace=TRUE)) set2 <- data.frame(lat=40+runif(100), lon=-70
SQL Geometry VS decimal(8,6) Lat, Long Performance
问题 I was looking into performance of selecting closest points within certain proximity to given coordinate. Options are to ether use two decimal(8,6) - lat, long columns or single geography column and work with that. I am only interested which is faster? 回答1: TL;DR Geography is ~10 times faster. Ok so I have set up test: Couple of tables one with id,lat,long (int, decimal(8,6),decimal(8,6)) other with id,coord (int, geography) . Then insert 47k of random data. For indexing first table I used
Finding nearest neighbor between 2 sets of dated points
I have 2 sets of points, set1 and set2 . Both sets of points have a data associated with the point. Points in set1 are "ephemeral", and only exist on the given date. Points in set2 are "permanent", are constructed at a given date, and then exist forever after that date. set.seed(1) dates <- seq(as.Date('2011-01-01'),as.Date('2011-12-31'),by='days') set1 <- data.frame(lat=40+runif(10000), lon=-70+runif(10000),date=sample(dates,10000,replace=TRUE)) set2 <- data.frame(lat=40+runif(100), lon=-70+runif(100),date=sample(dates,100,replace=TRUE)) Here's my problem: For each point in set1 (ephemeral)