def show_spec_in_graph(graph, vertex, spec, pos, weight, file_name):
dist = 1.0 - squareform(pdist(spec.T, 'cosine'))
plt.figure()
plt.stem(dist[vertex, :], markerfmt=' ')
rim = graph.new_vertex_property('vector<double>')
rim.set_2d_array(np.array([0, 0, 0, 1]))
rim[graph.vertex(vertex)] = [0.8941176471, 0.1019607843, 0.1098039216, 1]
rim_width = graph.new_vertex_property('float', vals=0.5)
rim_width.a[vertex] = 2
shape = graph.new_vertex_property('int', vals=0)
shape[graph.vertex(vertex)] = 2
size = graph.new_vertex_property('double', vals=10)
size.a[vertex] = 15
correlation = graph.new_vertex_property('double', vals=2)
correlation.a = dist[vertex, :]
vorder = graph.new_vertex_property('int', vals=0)
vorder.a[vertex] = 1
palette = sns.cubehelix_palette(256)
cmap = colors.ListedColormap(palette)
gt_draw.graph_draw(graph, pos=pos, vertex_color=rim, vorder=vorder,
vertex_pen_width=rim_width,
vertex_shape=shape, vertex_fill_color=correlation,
vcmap=cmap, vertex_size=size, edge_color=[0, 0, 0, 0.7],
edge_pen_width=weight, output=file_name + '.png',
output_size=(1200, 1200))
plt.figure()
utils.plot_colorbar(cmap, np.arange(0, 1.01, 0.2), file_name)
def plot(graph, weights, pos, station_values, name):
palette = sns.color_palette('RdBu', n_colors=256)
cmap = colors.ListedColormap(palette[::-1])
weights = weights.copy()
weights.a -= np.min(weights.a)
weights.a *= 2 / np.max(weights.a)
weights.a += 0.2
gt_draw.graph_draw(graph, pos=pos, vertex_color=[0, 0, 0, 0.5],
vertex_fill_color=station_values, vcmap=cmap,
vertex_size=5, edge_color=[0, 0, 0, 0.7],
edge_pen_width=weights,
output=name + '_temp.svg')
gt_draw.graph_draw(graph, pos=pos, vertex_color=[0, 0, 0, 0.5],
vertex_fill_color=station_values, vcmap=cmap,
vertex_size=10, edge_color=[0, 0, 0, 0.7],
edge_pen_width=weights,
output=name + '_temp.png', output_size=(1200, 1200))
min_val = np.min(station_values.a)
max_val = np.max(station_values.a)
step = (max_val - min_val) / 5
labels = np.array(['{0:.2f}'.format(x)
for x in np.arange(min_val, max_val, step)])
plt.figure()
utils.plot_colorbar(cmap, labels, name)
