Seems like d3 has you covered: https://github.com/d3/d3-geo#geoContains d3.geoContains(object, point) Returns true if and only if the specified GeoJSON object contains the specified point, or false if the object does not contain the point. The point must be specified as a two-element array [longitude, latitude] in degrees. For Point and MultiPoint geometries, an exact test is … Read more
Use the Ray Casting algorithm for checking if a point (marker) lies inside of a polygon: function isMarkerInsidePolygon(marker, poly) { var polyPoints = poly.getLatLngs(); var x = marker.getLatLng().lat, y = marker.getLatLng().lng; var inside = false; for (var i = 0, j = polyPoints.length – 1; i < polyPoints.length; j = i++) { var xi = … Read more
Not really clear what kind of data structures you actually have. Also, all your expected results are False, so that’s kind of hard to check. Assuming GeoSeries and GeoDataFrames, I would do this: from shapely.geometry import Point, Polygon import geopandas polys = geopandas.GeoSeries({ ‘foo’: Polygon([(5, 5), (5, 13), (13, 13), (13, 5)]), ‘bar’: Polygon([(10, 10), … Read more
Let’s assume you want to draw an N-sided polygon of radius r, centred at (0,0). Then the n vertices are given by: x[n] = r * cos(2*pi*n/N) y[n] = r * sin(2*pi*n/N) where 0 <= n < N. Note that cos and sin here are working in radians, not degrees (this is pretty common in … Read more
Here is a possible solution to my problem. Geographical coordinates must be stored properly. Example np.array([[Lon_A, Lat_A], [Lon_B, Lat_B], [Lon_C, Lat_C]]) Create the polygon Create the point to be tested Use polygon.contains(point) to test if point is inside (True) or outside (False) the polygon. Here is the missing part of the code: from shapely.geometry import … Read more
The answer turns out to be quite simple: import numpy from PIL import Image, ImageDraw # polygon = [(x1,y1),(x2,y2),…] or [x1,y1,x2,y2,…] # width = ? # height = ? img = Image.new(‘L’, (width, height), 0) ImageDraw.Draw(img).polygon(polygon, outline=1, fill=1) mask = numpy.array(img)
For graphics, I’d rather not prefer integers. Many systems use integers for UI painting (pixels are ints after all), but macOS, for example, uses float for everything. macOS only knows points and a point can translate to one pixel, but depending on monitor resolution, it might translate to something else. On retina screens half a … Read more