Hi again, still trying to accomplish the filling of certain paths only inside U.S. It ocurred to me that set_clip_path could work but so far, I have not been able to show the curve in the map.
Could someone point out what is missing? Thanks #!/usr/bin/env python """http://www.scipy.org/Cookbook/Finding_Convex_Hull"""; import numpy as n, pylab as p, time import matplotlib.pyplot as plt import matplotlib.patches as mpatches import matplotlib.path as mpath from matplotlib.patches import Polygon from mpl_toolkits.basemap import Basemap import sys import numpy as np import matplotlib.cm as cm def _angle_to_point(point, centre): '''calculate angle in 2-D between points and x axis''' delta = point - centre res = n.arctan(delta[1] / delta[0]) if delta[0] < 0: res += n.pi return res def _draw_triangle(p1, p2, p3, **kwargs): tmp = n.vstack((p1,p2,p3)) x,y = [x[0] for x in zip(tmp.transpose())] p.fill(x,y, **kwargs) # commented out to see result def area_of_triangle(p1, p2, p3): '''calculate area of any triangle given co-ordinates of the corners''' return n.linalg.norm(n.cross((p2 - p1), (p3 - p1)))/2. def convex_hull(points, graphic=True, smidgen=0.0075): '''Calculate subset of points that make a convex hull around points Recursively eliminates points that lie inside two neighbouring points until only convex hull is remaining. :Parameters: points : ndarray (2 x m) array of points for which to find hull graphic : bool use pylab to show progress? smidgen : float offset for graphic number labels - useful values depend on your data range :Returns: hull_points : ndarray (2 x n) convex hull surrounding points ''' # Commenting these 2 lines out shows the plotting of the country border # if graphic: # p.clf() n_pts = points.shape[1] print "POINTS shape[1]:%d" %(n_pts) assert(n_pts > 5) centre = points.mean(1) angles = n.apply_along_axis(_angle_to_point, 0, points, centre) pts_ord = points[:,angles.argsort()] pts = [x[0] for x in zip(pts_ord.transpose())] prev_pts = len(pts) + 1 k = 0 while prev_pts > n_pts: prev_pts = n_pts n_pts = len(pts) if graphic: p.gca().patches = [] i = -2 while i < (n_pts - 2): Aij = area_of_triangle(centre, pts[i], pts[(i + 1) % n_pts]) Ajk = area_of_triangle(centre, pts[(i + 1) % n_pts], \ pts[(i + 2) % n_pts]) Aik = area_of_triangle(centre, pts[i], pts[(i + 2) % n_pts]) if Aij + Ajk < Aik: if graphic: p.plot((pts[i + 1][0],),(pts[i + 1][1],)) # without green circle marker del pts[i+1] i += 1 n_pts = len(pts) k += 1 return n.asarray(pts) if __name__ == "__main__": x1 = -124. x2 = -57. y1 = 18. y2 = 51. m = Basemap(resolution='i',projection='stere', lat_0=39., lon_0=-98.,llcrnrlat=y1,urcrnrlat=y2,llcrnrlon=x1,urcrnrlon=x2) point0 = [] point1 = [] cpaths = (m.drawcountries()).get_paths() for cpath in cpaths: vs = cpath.vertices for v in vs: x=v[0] y=v[1] point0.append(x) point1.append(y) nonumpy = [] nonumpy.append(point0) nonumpy.append(point1) points = n.array(nonumpy) hull_pts = convex_hull(points) poly = Polygon(hull_pts) USpath = poly.get_path() USpatch = mpatches.PathPatch(USpath,facecolor='none',edgecolor='none') ax = plt.gca() ax.add_patch(USpatch) # Add my curve Path = mpath.Path pathdata = [] pathdata.append((Path.MOVETO,m(-120.,35.))) pathdata.append((Path.LINETO,m(-100.,35.))) pathdata.append((Path.LINETO,m(-100.,30.))) pathdata.append((Path.LINETO,m(-90.,28.))) pathdata.append((Path.LINETO,m(-90,25))) pathdata.append((Path.LINETO,m(-100,25))) pathdata.append((Path.CURVE3,m(-120.,35.))) codes,verts = zip(*pathdata) im = ax.imshow(verts,cmap=cm.gray,clip_path=USpatch,clip_on=True) im.set_clip_path(USpatch) m.drawparallels(np.arange(20,60,5),labels=[1,0,0,0],color='black') m.drawmeridians(np.arange(-140,60,10),labels=[0,0,0,1],color='black') plt.gcf().savefig('./ch.png') ------------------------------------------------------------------------------ All the data continuously generated in your IT infrastructure contains a definitive record of customers, application performance, security threats, fraudulent activity and more. Splunk takes this data and makes sense of it. Business sense. IT sense. Common sense. http://p.sf.net/sfu/splunk-d2dcopy1 _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
