def test_plots():
G = ox.graph_from_place('Piedmont, California, USA', network_type='drive', simplify=False)
G2 = ox.simplify_graph(G, strict=False)
# test getting colors
co = ox.get_colors(n=5, return_hex=True)
nc = ox.get_node_colors_by_attr(G2, 'osmid')
ec = ox.get_edge_colors_by_attr(G2, 'length')
# save a plot to disk as png
fig, ax = ox.plot_graph(G, save=True, file_format='png')
# save a plot to disk as svg
G_simplified = ox.simplify_graph(G)
fig, ax = ox.plot_graph(G_simplified, show=False, save=True, close=True, file_format='svg')
G_projected = ox.project_graph(G_simplified)
fig, ax = ox.plot_graph(G_projected)
fig, ax = ox.plot_graph(G_projected, fig_height=5, fig_width=5, margin=0.05, axis_off=False, bgcolor='y',
file_format='png', filename='x', dpi=180, annotate=True, node_color='k', node_size=5,
node_alpha=0.1, node_edgecolor='b', node_zorder=5, edge_color='r', edge_linewidth=2,
edge_alpha=0.1, use_geom=False, show=False, save=True, close=True)
fig, ax = ox.plot_figure_ground(G=G_simplified, file_format='png')
fig, ax = ox.plot_figure_ground(point=(33.694981, -117.841375), file_format='png')
fig, ax = ox.plot_figure_ground(address='Denver, Colorado, USA', file_format='png')
def test_plots():
G = ox.graph_from_place('Piedmont, California, USA', network_type='drive', simplify=False)
G2 = ox.simplify_graph(G, strict=False)
# test getting colors
co = ox.get_colors(n=5, return_hex=True)
nc = ox.get_node_colors_by_attr(G2, 'osmid')
ec = ox.get_edge_colors_by_attr(G2, 'length')
# save a plot to disk as png
fig, ax = ox.plot_graph(G, save=True, file_format='png')
# save a plot to disk as svg
G_simplified = ox.simplify_graph(G)
fig, ax = ox.plot_graph(G_simplified, show=False, save=True, close=True, file_format='svg')
G_projected = ox.project_graph(G_simplified)
fig, ax = ox.plot_graph(G_projected)
fig, ax = ox.plot_graph(G_projected, fig_height=5, fig_width=5, margin=0.05, axis_off=False, bgcolor='y',
file_format='png', filename='x', dpi=180, annotate=True, node_color='k', node_size=5,
node_alpha=0.1, node_edgecolor='b', node_zorder=5, edge_color='r', edge_linewidth=2,
edge_alpha=0.1, use_geom=False, show=False, save=True, close=True)
fig, ax = ox.plot_figure_ground(G=G_simplified, file_format='png')
fig, ax = ox.plot_figure_ground(point=(33.694981, -117.841375), file_format='png')
fig, ax = ox.plot_figure_ground(address='Denver, Colorado, USA', file_format='png')
def load_data(self, file_path, origin):
r_earth = 6378137
mat_contents = sio.loadmat(file_path)
array_mat = mat_contents
var = array_mat['var_pred']
pol = array_mat['Y_pred']
coord = mat_contents['central_coord']
min0 = min(coord[0])
min1 = min(coord[1])
max0 = max(coord[0])
max1 = max(coord[1])
bottom_left = (min0, min1)
bottom_right = (min0, max1)
top_right = (max0, max1)
top_left = (max0, min1)
grid = nx.Graph()
nodes_visualized = []
for n in range(len(coord)):
# Origin[0] = lat Origin[1] = long
new_latitude = origin[0] + (1*coord[n][0] / r_earth) * (180 / math.pi)
new_longitude = origin[1] + (1*coord[n][1] / r_earth) * (180 / math.pi) / math.cos(new_latitude * math.pi / 180)
print(str(new_latitude) + str(new_longitude))
nodes_visualized.append((new_latitude, new_longitude))
x, y, _, _ = utm.from_latlon(new_latitude, new_longitude)
grid.add_node(n, lat=new_latitude, lon=new_longitude, pol=pol[n][-1], var=var[n][-1], y=y, x=x)
for n, data in self.graph.nodes(data=True):
node = self.graph.nodes()[n] # Returns the node attribute's dictionary.
grid_copy = copy.deepcopy(grid)
pol_var_dist = []
total_dist = 0.0
for grid_node in range(4):
node_location, dist = ox.get_nearest_node(grid_copy, (node['y'], node['x']), method='euclidean', return_dist=True)
print(dist)
pol = grid_copy.node[node_location]['pol']
var = grid_copy.node[node_location]['var']
pol_var_dist.append((pol, var, dist))
total_dist += dist
grid_copy.remove_node(node_location)
summed_pol = 0.0
summed_var = 0.0
for m in range(4):
summed_pol += (1 - (pol_var_dist[m][2] / total_dist)) * pol_var_dist[m][0]
summed_var += (1 - pol_var_dist[m][2] / total_dist) * pol_var_dist[m][1]
summed_var = summed_var / 3
summed_pol = summed_pol / 3
data['pol'] = summed_pol
data['var'] = summed_var
print("pol " + str(summed_pol))
print("finished")
nc = ox.get_node_colors_by_attr(self.graph, 'pol', cmap='plasma', num_bins=20)
fig, ax = ox.plot_graph(self.G, fig_height=6, node_zorder=2,
edge_color='#dddddd', node_color=nc, use_geom=True, show=False, close=False) # node_color=nc
for lat, long in nodes_visualized:
ax.scatter(long, lat, c='red', alpha=0.1, s=2)
ax.set_title("Imported FRF Pollution")
plt.show()
def grid_weighting_nodes(self, meters, n):
self.planner = randomplanner.planner(self.kalman.env)
coords = self.env.grid_weight_nodes(self.north, self.south, self.east, self.west, meters, n)
nc = ox.get_node_colors_by_attr(self.env.graph, 'grid_weight', cmap='plasma', num_bins=20)
fig, ax = ox.plot_graph(self.env.G, fig_height=6, node_color=nc, node_zorder=2,
edge_color='#dddddd', use_geom=True, show=False, close=False)
for lat, long in coords:
print("(" + str(lat) + ", " + str(long) +")")
ax.scatter(long, lat, c='red', alpha=0.2, s=2)
ax.set_title("Weighted nodes from Grid")
plt.show()
def plot_node_elevation(self):
G_proj = ox.project_graph(self.G)
nc = ox.get_node_colors_by_attr(G_proj,
'elevation',
cmap='plasma',
num_bins=20)
fig, ax = ox.plot_graph(G_proj,
fig_height=6,
node_color=nc,
node_size=12,
node_zorder=2,
edge_color='#dddddd')
def grid_weighting_nodes_dist(self, meters, n, dist):
self.planner = randomplanner.planner(self.kalman.env)
coords = self.planner.grid_weight_nodes_max_dist(self.north, self.south, self.east, self.west, meters, n, dist)
nc = ox.get_node_colors_by_attr(self.planner.graph, 'grid_weight', cmap='plasma', num_bins=20)
fig, ax = ox.plot_graph(self.planner.env.G, fig_height=6, node_color=nc, node_zorder=2,
edge_color='#dddddd', use_geom=True, show=False, close=False)
for lat, long in coords:
print("(" + str(lat) + ", " + str(long) +")")
ax.scatter(long, lat, c='red', alpha=0.3, s=3)
ax.set_title("Weighted nodes from Grid")
for node in self.planner.graph.nodes():
lat = self.planner.env.G.node[node]['lat']
long = self.planner.env.G.node[node]['long']
data = self.planner.graph.node[node]['grid_weight']
print(str(long) + ", " + str(lat) + ", " + str(data))
ax.annotate(long, lat, str(data))
plt.show()
print('Average street grade in {} is {:.1f}%'.format(place, avg_grade*100))
med_grade = np.median(edge_grades)
print('Median street grade in {} is {:.1f}%'.format(place, med_grade*100))
# In[24]:
G_proj = ox.project_graph(G)
# In[25]:
nc = ox.get_node_colors_by_attr(G_proj, 'elevation', cmap='plasma', num_bins=20)
fig, ax = ox.plot_graph(G_proj, fig_height=6, node_color=nc, node_size=12, node_zorder=2, edge_color='#dddddd')
# In[46]:
origin = ox.get_nearest_node(G, (42.3778, -72.5198))
destination = ox.get_nearest_node(G, (42.3898, -72.5283))
bbox = ox.bbox_from_point((42.384, -72.524), distance=1500, project_utm=True)
# In[47]:
def impedance(length, grade):
graph = ox.graph_from_place(place_query, network_type='all')
ox.plot_graph(graph)
# add elevation to each of the nodes, using the google elevation API, then calculate edge grades
graph = ox.add_node_elevations(graph, api_key=apikey)
graph = ox.add_edge_grades(graph)
''' Convert the network into nodes geodataframe and edges geodataframe respectively '''
nodes, edges = ox.graph_to_gdfs(graph, nodes=True, edges=True)
# In[5]:
''' Convert into UTM format '''
graph_proj = ox.project_graph(graph)
# get one color for each node, by elevation, then plot the network
nc = ox.get_node_colors_by_attr(graph_proj,
'elevation',
cmap='viridis',
num_bins=20)
fig, ax = ox.plot_graph(graph_proj, node_color=nc, node_zorder=2)
plt.tight_layout()
''' Convert the projected network into nodes geodataframe and edges geodataframe respectively '''
nodes_proj, edges_proj = ox.graph_to_gdfs(graph_proj, nodes=True, edges=True)
# In[6]:
# Find the elevation rises by multiplying edge length together with grade / slope
for u, v, k, data in graph_proj.edges(keys=True, data=True):
data['rise'] = data['length'] * data['grade']
# In[7]:
'''Get the convex hull of the whole network system'''
# region = edges.unary_union.convex_hull
G = ox.graph_from_bbox(north,
south,
east,
west,
network_type='drive',
simplify=True,
truncate_by_edge=True)
env = PolEnv(G)
kalman = kalman(env)
kalman.wipe_initilize()
kalman.update(500, (34.05, -117.0), 50) # bot right
kalman.update(500, (34.05, -117.05), 100) # bot left
nc = ox.get_node_colors_by_attr(env.graph, 'pol', cmap='plasma', num_bins=20)
fig, ax = ox.plot_graph(kalman.env.graph,
fig_height=6,
node_color=nc,
node_size=12,
node_zorder=2,
edge_color='#dddddd',
use_geom=True)
kalman.update(20, (34.025, -117.025), 100)
nc = ox.get_node_colors_by_attr(kalman.env.graph,
'pol',
cmap='plasma',
num_bins=20)
fig, ax = ox.plot_graph(env.graph,
fig_height=6,
node_color=nc,
