![]() ![]() Performing a Voronoi tesselation of the region, as suggested in the comments, is one such possibility. If you do not have the Matlab Mapping Toolbox, you could look at the third party library M_Map M_Map home page, which offers some of the same functionality.Įdit: If the cloud of points for Zip codes has a bounding region that is non convex, you may need a more general computational geometry technique to find a better approximation to the bounding region. The only complication would be what coordinate system to work in, you might need to do a bit of work going between (lat, lon) and map (x,y) coordinates. The input array str can be a string array, character vector, or cell array of character vectors. The result K would be a vector of points enclosing the input X, Y vector of points, that could be used to draw a polygon. Syntax newStr split (str) newStr split (str,delimiter) newStr split (str,delimiter,dim) newStr,match split ( ) Description example newStr split (str) divides str at whitespace characters and returns the result as the output array newStr. How to seperate fractional and decimal part in a real number Follow 731 views (last 30 days) Show older comments DSP Masters on Vote 4 Link Commented: Les Beckham on Accepted Answer: Walter Roberson Hi, Please help me in seperating fractional and decimal part in a real number. You could probably get a good approximation of the boundary by using computational geometry, e.g finding the 2D convex hull of each Zip code's set of points using the Matlab convhull function K = convhull(X,Y) ![]() Intervals_count(group_num) = intervals_count(group_num) + 1 Įx.If you have a dense cloud of known points within each Zip code with coordinates, using machine learning to find the boundary enclosing those points sounds like overkill. K convhull (X,Y) The result K would be a vector of points enclosing the input X, Y vector of points, that could be used to draw a polygon. 2: intervals_count = zeros(intervals, 1) You could probably get a good approximation of the boundary by using computational geometry, e.g finding the 2D convex hull of each Zip code's set of points using the Matlab convhull function. Intervals_count = sum(interval_num = ii - 1)Įx. 1: intervals_count = zeros(intervals, 1) newStr,match split ( ) additionally returns an array, match, that contains all occurrences of delimiters at which the split function splits str. Then, it's just a question of counting how many of each number exist. newStr split (str,delimiter,dim) divides each element of str into a vector oriented along the dimension specified by dim. Hints: The semicolon at the end of a MATLAB command line suppressed MATLAB output for that command, but semicolon are also used for separating rows in array. interval_num = floor((data - min_range) / intervals_size) Now we can calculate the "interval number" in which a given data falls by subtracting the minimum value from the data, dividing the result by the interval size, and flooring the result. Based on your location, we recommend that you select. Intervals_size = (max_range - min_range) / intervals % Size of each interval Choose a web site to get translated content where available and see local events and offers. All tokens after it on the same line are ignored, and the space can be used to. intervals = 10 ĭata = rand(1200, 1) * max_range % 1200 random numbers between 0 and 100 The most valuable character for clean MATLAB code is, the comment character. If I've understood correctly, you want to distribute N = 1200 values into intervals buckets. ![]()
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