distance

In R - I have imported a polyline shapefile that is not straight (represents a winding interstate highway) into the environment. I have read a .csv file that contains points (latitude/longitude in decimal degrees) into the environment. All of those points lie along the polyline. If I take two random points I can calculate the "as the crow flies" distance between them using great circle distance calculation. But what is needed is distance traveled along the polyline. See reference image: https://i.stack.imgur.com/zhorb.png Is anyone aware of an R package that can calculate the distance between

I have two dataframes. Each one contains locations (X,Y) and a value for that point. For each point in the first dataframe I want to find the closest point in the second dataframe and then find the difference. I have code that is working, but it uses a for loop, which is slow. Any suggestions for how to speed this up? I know that it is generally a good idea to get rid of for loops in pandas, for performance, but I don't see how to do that in this case. Here is some sample code: import pandas as pd import numpy as np df1=pd.DataFrame(np.random.rand(10,3), columns=['val', 'X', 'Y']) df2=pd

I am using python for this job and being very objective here, I want to find a 'pythonic' way to remove from an array of arrays the "duplicates" that are close each other from a threshold. For example, give this array: [[ 5.024, 1.559, 0.281], [ 6.198, 4.827, 1.653], [ 6.199, 4.828, 1.653]] observe that [ 6.198, 4.827, 1.653] and [ 6.199, 4.828, 1.653] are really close to each other, their Euclidian distance is 0.0014 , so they are almost "duplicates", I want my final output to be just: [[ 5.024, 1.559, 0.281], [ 6.198, 4.827, 1.653]] The algorithm that I have right now is: to_delete = []; for

i researched a little in this topic, but there are many opinions that don't exactly give a clear image. My problem is this: I'm developing a gps-based app for Android, in wich i want to know distance between my current location specified by Androids LocationManager, and other location in real time. I tried Haversine formula, a Law of Cosines formula, then I discovered, that Android SDK gives me a simple function Location.distanceTo(Location) - i'm not sure what method does this function runs on. So, the point is, wich one will be good for me to use, in situations when real distance between

It seems like the answer to this should be simple, but I am stumped. I have a matrix of Nx3 matrix where there 1st 2nd and 3rd columns are the X Y and Z coordinates of the nth item. I want to calculate the distance from the origin to the item. In a non vectorized form this is easy. distance = norm([x y z]); or distance = sqrt(x^2+y^2+z^2); However, in vectorized form its not so simple. When you pass a matrix to norm it no longer returns the Euclidean length. distance = norm(matrix); %doesn't work and distance = sqrt(x(:,1).*x(:,1)+y(:,2).*y(:,2)+z(:,3).*z(:,3)); %just seems messy Is there a

In php, given a latitude and longitude point, a bearing (in degrees), and a distance (in feet or km or whatever) how do I figure out what the new lat lng point is? here is what I tried, but it's wrong. function destinationPoint($lat, $lng, $brng, $dist) { $meters = $dist/3.2808399; // dist in meters $dist = $meters/1000; // dist in km $rad = 6371; // earths mean radius $dist = $dist/$rad; // convert dist to angular distance in radians $brng = deg2rad($brng); // conver to radians $lat1 = deg2rad($lat); $lon1 = deg2rad($lng); $lat2 = asin(sin($lat1)*cos($dist) + cos($lat1)*sin($dist)*cos($brng)