def haus_dist(net1, net2, kx, ky, x0=0, y0=0):
# Get the limits and data
LEFT, RIGHT, BOTTOM, TOP = get_limits(net1)
gridlist = partitions((LEFT, RIGHT, BOTTOM, TOP), kx, ky, x0=x0, y0=y0)
edges1 = [net1.edges[e]['geometry'] for e in net1.edges()]
edges2 = [net2.edges[e]['geometry'] for e in net2.edges()]
# Compute Hausdorff distance
C = compute_hausdorff(gridlist, edges1, edges2)
C_vals = np.array([C[bound] for bound in gridlist])
C_masked = np.ma.array(C_vals, mask=np.isnan(C_vals))
# Plot the deviation
DPI = 72
fig = plt.figure(figsize=(700 / DPI, 500 / DPI), dpi=DPI)
ax = plt.subplot()
plot_network_pair(ax, net1, net2)
plot_deviation(ax, gridlist, C_masked, colormap=cm.Greens)
add_colorbar(fig,
ax,
colormap=cm.Greens,
vmin=0.0,
vmax=max(C_masked),
devname="Hausdorff distance")
fig.savefig("{}{}.png".format(
figpath,
str(sub) + '-haus-comp-' + str(kx) + '-' + str(ky) + suffix),
bbox_inches='tight')
return C
leg_data = [Line2D([0], [0], color=c_actual, markerfacecolor=c_actual,
marker='o',markersize=40, label='Actual distribution network'),
Line2D([0], [0], color=c_synth, markerfacecolor=c_synth,
marker='o',markersize=40, label='Synthetic distribution network'),
Patch(facecolor='white', edgecolor='black', hatch="./",
label='Grid cells with no actual network data')]
#%% Hausdorff distance between networks
kx = 7
ky = 7
x0 = 0.05
y0 = 0
LEFT,RIGHT,BOTTOM,TOP = get_limits(area_data)
gridlist = partitions((LEFT,RIGHT,BOTTOM,TOP),kx,ky,x0=x0,y0=y0)
act_edges,syn_edges = get_edges(area_data)
C = compute_hausdorff(gridlist,act_edges,syn_edges)
C_vals = np.array([C[bound] for bound in gridlist])
C_masked = np.ma.array(C_vals, mask=np.isnan(C_vals))
# Plot the Hausdorff deviation
fig = plt.figure(figsize=(30,25))
ax = fig.add_subplot(1,1,1)
for area in area_data:
plot_gdf(ax,area_data[area]['df_lines'],area_data[area]['df_buses'],
c_actual)
plot_gdf(ax,area_data[area]['df_synth'],area_data[area]['df_cords'],
c_synth)
return
def get_polygon(boundary):
"""Gets the vertices for the boundary polygon"""
vert1 = [boundary.west_edge, boundary.north_edge]
vert2 = [boundary.east_edge, boundary.north_edge]
vert3 = [boundary.east_edge, boundary.south_edge]
vert4 = [boundary.west_edge, boundary.south_edge]
return np.array([vert1, vert2, vert3, vert4])
cords = np.array([list(synth_net.nodes[n]['cord']) for n in synth_net])
LEFT, BOTTOM = np.min(cords, 0)
RIGHT, TOP = np.max(cords, 0)
gridlist = partitions((LEFT, RIGHT, BOTTOM, TOP), 5, 5)
DPI = 72
fig = plt.figure(figsize=(700 / DPI, 500 / DPI), dpi=DPI)
ax = plt.subplot()
ax.set_xlim(LEFT, RIGHT)
ax.set_ylim(BOTTOM, TOP)
# Get the boxes for the valid comparisons
verts_valid = [get_polygon(bound) for i, bound in enumerate(gridlist)]
c = PolyCollection(verts_valid, edgecolor='black', facecolor='white')
ax.add_collection(c)
i = 4
suffix = str(sub) + '-' + str(i)
tree = nx.read_gpickle(outpath + str(sub) + '-ensemble-' + str(i) + '.gpickle')