import numpy as np
import pandas as pd
import holoviews as hv
import networkx as nx

hv.extension('bokeh')

%opts Graph [width=400 height=400]

# Declare abstract edges
N = 8
node_indices = np.arange(N, dtype=np.int32)
source = np.zeros(N, dtype=np.int32)
target = node_indices

padding = dict(x=(-1.2, 1.2), y=(-1.2, 1.2))

simple_graph = hv.Graph(((source, target),)).redim.range(**padding)
simple_graph

simple_graph.nodes + simple_graph.edgepaths

def bezier(start, end, control, steps=np.linspace(0, 1, 100)):
    return (1-steps)**2*start + 2*(1-steps)*steps*control+steps**2*end

x, y = simple_graph.nodes.array([0, 1]).T

paths = []
for node_index in node_indices:
    ex, ey = x[node_index], y[node_index]
    paths.append(np.column_stack([bezier(x[0], ex, 0), bezier(y[0], ey, 0)]))
    
bezier_graph = hv.Graph(((source, target), (x, y, node_indices), paths)).redim.range(**padding)
bezier_graph

bezier_graph.options(inspection_policy='edges')

%%opts Graph [tools=['hover', 'box_select']] (edge_hover_line_color='green' node_hover_fill_color='red')
bezier_graph.options(inspection_policy='nodes')

%%opts Graph [color_index='Type' edge_color_index='Weight'] (cmap='Set1' edge_cmap='viridis')
node_labels = ['Output']+['Input']*(N-1)
np.random.seed(7)
edge_labels = np.random.rand(8)

nodes = hv.Nodes((x, y, node_indices, node_labels), vdims='Type')
graph = hv.Graph(((source, target, edge_labels), nodes, paths), vdims='Weight').redim.range(**padding)
graph + graph.options(inspection_policy='edges')

%%opts Graph [color_index='Label'] (cmap='Set1')
node_info = hv.Dataset(node_labels, vdims='Label')
hv.Graph(((source, target), node_info)).redim.range(**padding)

%%opts Graph [tools=['hover']]
G = nx.karate_club_graph()
hv.Graph.from_networkx(G, nx.layout.circular_layout).redim.range(**padding)

%%opts Graph
G = nx.karate_club_graph()

def get_graph(iteration):
    np.random.seed(10)
    return hv.Graph.from_networkx(G, nx.spring_layout, iterations=iteration)

hv.HoloMap({i: get_graph(i) for i in range(5, 30, 5)},
           kdims='Iterations').redim.range(x=(-1.2, 1.2), y=(-1.2, 1.2))

%opts Nodes Graph [width=800 height=800 xaxis=None yaxis=None]

%%opts Graph [color_index='circle']
%%opts Graph (node_size=10 edge_line_width=1)
colors = ['#000000']+hv.Cycle('Category20').values
edges_df = pd.read_csv('../assets/fb_edges.csv')
fb_nodes = hv.Nodes(pd.read_csv('../assets/fb_nodes.csv')).sort()
fb_graph = hv.Graph((edges_df, fb_nodes), label='Facebook Circles')
fb_graph = fb_graph.redim.range(x=(-0.05, 1.05), y=(-0.05, 1.05)).options(cmap=colors)
fb_graph

from holoviews.operation.datashader import datashade, bundle_graph
bundled = bundle_graph(fb_graph)
bundled

%%opts Nodes [color_index='circle'] (size=10 cmap=colors) Overlay [show_legend=False]
datashade(bundled, normalization='linear', width=800, height=800) * bundled.nodes

%%opts Graph (node_fill_color='white')
datashade(bundle_graph(fb_graph), normalization='linear', width=800, height=800) *\
bundled.select(circle='circle15')

bundled.select(circle='circle15', selection_mode='nodes')