I am working in a discrete 2D grid of points in which there are "shapes" that I would like to create points outside of. I have been able to identify the vertices of these points and take convex hulls. So far, this leads to this and all is good and well. The purple here is the shape in question and the red line is the convex contour I have computed.
What I would like to do now is create two neighborhoods of points outside this shape. The first one is a set of points directly outside (as close as the grid size will allow), the second is another set of points but offset some distance away (the distance is not fixed, but rather an input).
I have attempted to write this in Python and get okay results. Here is an example of my current output. The problem is I notice the offsets are not perfect, for example look at the bottom most point in the image I attached. It kinks downwards whereas the original shape does not. It's not too bad in this example, but in other cases where the shape is smaller or if I take a smaller offset it gets worse. I also have an issue where the offsets sometimes overlap, even if they are supposed to be some distance away. I would also like there to be one line in each section of the contour, not two lines (for example in the top left).
My current attempt uses the Shapely package to handle most of the computational geometry. An outline of what I do once I have found the vertices of the convex contour is to offset these vertices by some amount, and interpolate along each pair of vertices to obtain many points alone these lines. Afterwards I use a coordinate transform to identify all points to the nearest grid point. This is how I obtain my final set of points. Below is the actual code I have written.
How can I improve this so I don't run into the issues I described?
Function #1 - Computes the offset points
def OutsidePoints(vertices, dist):
poly_line = LinearRing(vertices)
poly_line_offset = poly_line.buffer(dist, resolution=1, join_style=2, mitre_limit=1).exterior
new_vertices = list(poly_line_offset.coords)
new_vertices = np.asarray(new_vertices)
shape = sg.Polygon(new_vertices)
points = []
for t in np.arange(0, shape.length, step_size):
temp_points = np.transpose(shape.exterior.interpolate(t).xy)
points.append(temp_points[0])
points = np.array(points)
points = np.unique(points, axis=0)
return points
Function #2 - Transforming these points into points that are on my grid
def IndexFinder(points):
index_points = invCoordinateTransform(points)
for i in range(len(index_points)):
for j in range(2):
index_points[i][j] = math.floor(index_points[i][j])
index_points = np.unique(index_points, axis=0)
return index_points
Many thanks!