def draw_garph_3d(node):
"""
Draw uni-directional or bi-directional graph in 3D space.
"""
nodes = serializer.graph_to_nodes_set(node)
edges = []
for node in nodes:
for neighbor in node.neighbors:
edges.append((str(node.uuid), str(neighbor.uuid)))
jgraph.draw(edges)
# In[26]:
import networkx as nx
get_ipython().magic('matplotlib inline')
results = get_ipython().magic(
'cypher MATCH p = (:Person)-[:LIKES]->(:Drink) RETURN p')
g = results.get_graph()
nx.draw(g)
# In[27]:
g.nodes(data=True)
# In[28]:
nx.degree(g)
# # jgraph
#
# `jgraph` will plot tuple lists as 3D graphs.
# In[29]:
import jgraph
jgraph.draw([(1, 2), (2, 3), (3, 4), (4, 1), (4, 5), (5, 2)])
import jgraph
graph = {'nodes': {'ft_traceroute': {}, '42_Commandements': {'color': 16755370, 'size': 2.0}, 'ft_ality': {}, 'ft_ls': {}, 'ft_ping': {}, 'RT': {}, 'mod1': {}, 'H42N42': {}, 'ft_script': {}, 'In_the_Shadows': {}, '21sh': {}, 'RainFall': {}, 'Filit': {'color': 10624845, 'size': 1.0}, 'lem_in': {'color': 10624845, 'size': 1.0}, 'Woody_Woodpacker': {}, 'Process_and_Memory': {}, 'Filesystem': {}, 'cloud_1': {}, 'Abstract_VM': {}, 'little_penguin_1': {}, 'Gomoku': {}, 'libft': {'color': 10624845, 'size': 1.0}, 'Piscine_Ruby_on_Rails': {}, 'Corewar': {'color': 10624845, 'size': 1.0}, 'Rushes': {}, 'ft_p': {}, 'Scop': {}, 'libftASM': {}, 'ft_hangouts': {}, 'Expert_System': {}, 'Hypertube': {}, 'KrpSim': {}, 'Corewar_Championship': {}, 'Savoir_Relier': {}, 'Filer': {}, 'Piscine_OCaml': {}, 'Music_Room': {}, 'Malloc': {}, 'ft_turing': {}, 'Zappy': {}, 'Camagru': {}, 'Famine': {}, 'Piscine_Swift_iOS': {}, 'Taskmaster': {}, 'ComputorV1': {}, 'Red_Tetris': {}, 'Matt_Daemon': {}, 'Open_Project_II': {}, 'Dr_Quine': {}, 'lem_ipc': {}, 'Final_Internship': {}, 'Push_swap': {'color': 10624845, 'size': 1.0}, 'Darkly': {}, 'First_Internship': {'color': 10624845, 'size': 1.0}, 'Root_me_|_Cracking': {}, 'Nm_otool': {}, 'Nibbler': {}, 'ft_printf': {'color': 10624845, 'size': 1.0}, 'Piscine_CPP': {}, 'Piscine_Reloaded': {'color': 10624845, 'size': 1.0}, 'Docker': {}, 'Piscine_Unity': {}, 'ft_linear_regression': {}, 'FdF': {}, 'XV': {}, 'Bomberman': {}, 'Wolf3d': {}, 'Root_me_|_App_Systeme': {}, 'HumanGl': {}, 'Matcha': {}, 'Snow_Crash': {}, 'Swifty_Companion': {}, '42run': {}, 'ft_nmap': {}, 'ft_select': {}, 'RTv1': {}, 'GBmu': {}, 'C_Exam___Beginner': {}, 'Open_Project_I': {}, 'Rubik': {}, "Fract'ol": {}, 'Piscine_Python_Django': {}, 'Part_time': {}, 'Particle_System': {}, '42sh': {}, 'Philosophers': {}, 'N_puzzle': {}, 'Piscine_PHP': {}, 'Get_Next_line': {'color': 10624845, 'size': 1.0}, 'Swifty_Proteins': {}, 'Drivers_and_Interrupts': {}, 'IRC': {}, 'strace': {}, 'roger_skyline_2': {}, 'roger_skyline_1': {}, 'KFS_2': {}, 'KFS_3': {}, 'KFS_1': {}, 'ft_linux': {}, 'KFS_4': {'color': 4920919, 'size': 2.0}, 'minishel': {}, 'Friends_with_Benefits': {}}, 'edges': [{'source': '42_Commandements', 'target': 'Piscine_Reloaded'}, {'source': 'Piscine_Reloaded', 'target': 'libft'}, {'source': 'libft', 'target': 'Filit'}, {'source': 'Filit', 'target': 'Get_Next_line'}, {'source': 'Get_Next_line', 'target': 'ft_printf'}, {'source': 'ft_printf', 'target': 'Push_swap'}, {'source': 'ft_printf', 'target': 'Filer'}, {'source': 'Push_swap', 'target': 'lem_in'}, {'source': 'Filer', 'target': 'lem_in'}, {'source': 'lem_in', 'target': 'Corewar'}, {'source': 'lem_in', 'target': 'mod1'}, {'source': 'Corewar', 'target': 'First_Internship'}, {'source': 'Corewar', 'target': 'Corewar_Championship'}, {'source': 'Get_Next_line', 'target': 'FdF'}, {'source': 'FdF', 'target': "Fract'ol"}, {'source': "Fract'ol", 'target': 'Wolf3d'}, {'source': "Fract'ol", 'target': 'RTv1'}, {'source': 'RTv1', 'target': 'RT'}, {'source': 'Wolf3d', 'target': 'RT'}, {'source': 'RT', 'target': 'First_Internship'}, {'source': 'Get_Next_line', 'target': 'ft_ls'}, {'source': 'ft_ls', 'target': 'minishel'}, {'source': 'minishel', 'target': 'ft_select'}, {'source': 'minishel', 'target': '21sh'}, {'source': '21sh', 'target': 'Taskmaster'}, {'source': '21sh', 'target': '42sh'}, {'source': '42sh', 'target': 'First_Internship'}, {'source': 'Piscine_PHP', 'target': 'Camagru'}, {'source': 'Camagru', 'target': 'Matcha'}, {'source': 'Matcha', 'target': 'Hypertube'}, {'source': 'Matcha', 'target': 'First_Internship'}, {'source': 'First_Internship', 'target': 'Friends_with_Benefits'}, {'source': 'First_Internship', 'target': 'Darkly'}, {'source': 'First_Internship', 'target': 'Red_Tetris'}, {'source': 'First_Internship', 'target': 'ComputorV1'}, {'source': 'First_Internship', 'target': 'N_puzzle'}, {'source': 'First_Internship', 'target': 'Expert_System'}, {'source': 'Expert_System', 'target': 'Gomoku'}, {'source': 'Expert_System', 'target': 'ft_linear_regression'}, {'source': 'Expert_System', 'target': 'KrpSim'}, {'source': 'Expert_System', 'target': 'Rubik'}, {'source': 'N_puzzle', 'target': 'Rubik'}, {'source': 'N_puzzle', 'target': 'Gomoku'}, {'source': 'N_puzzle', 'target': 'ft_linear_regression'}, {'source': 'N_puzzle', 'target': 'KrpSim'}, {'source': 'First_Internship', 'target': 'Scop'}, {'source': 'Scop', 'target': '42run'}, {'source': 'Scop', 'target': 'HumanGl'}, {'source': 'Scop', 'target': 'Particle_System'}, {'source': 'First_Internship', 'target': 'Malloc'}, {'source': 'Malloc', 'target': 'Philosophers'}, {'source': 'Malloc', 'target': 'ft_script'}, {'source': 'Malloc', 'target': 'Nm_otool'}, {'source': 'Nm_otool', 'target': 'ft_p'}, {'source': 'Nm_otool', 'target': 'IRC'}, {'source': 'IRC', 'target': 'Zappy'}, {'source': 'Nm_otool', 'target': 'Zappy'}, {'source': 'IRC', 'target': 'Matt_Daemon'}, {'source': 'Nm_otool', 'target': 'Matt_Daemon'}, {'source': 'IRC', 'target': 'lem_ipc'}, {'source': 'Nm_otool', 'target': 'lem_ipc'}, {'source': 'IRC', 'target': 'ft_ping'}, {'source': 'Nm_otool', 'target': 'ft_ping'}, {'source': 'ft_ping', 'target': 'ft_traceroute'}, {'source': 'ft_traceroute', 'target': 'ft_nmap'}, {'source': 'Nm_otool', 'target': 'libftASM'}, {'source': 'libftASM', 'target': 'strace'}, {'source': 'libftASM', 'target': 'GBmu'}, {'source': 'libftASM', 'target': 'ft_linux'}, {'source': 'ft_linux', 'target': 'little_penguin_1'}, {'source': 'little_penguin_1', 'target': 'Process_and_Memory'}, {'source': 'Process_and_Memory', 'target': 'Drivers_and_Interrupts'}, {'source': 'Drivers_and_Interrupts', 'target': 'Filesystem'}, {'source': 'Filesystem', 'target': 'KFS_1'}, {'source': 'KFS_1', 'target': 'KFS_2'}, {'source': 'KFS_2', 'target': 'KFS_3'}, {'source': 'KFS_3', 'target': 'KFS_4'}, {'source': 'libftASM', 'target': 'Snow_Crash'}, {'source': 'Snow_Crash', 'target': 'RainFall'}, {'source': 'libftASM', 'target': 'Root_me_|_App_Systeme'}, {'source': 'Root_me_|_App_Systeme', 'target': 'Root_me_|_Cracking'}, {'source': 'Famine', 'target': 'Woody_Woodpacker'}, {'source': 'Woody_Woodpacker', 'target': 'Nm_otool'}, {'source': 'Famine', 'target': 'libftASM'}, {'source': 'First_Internship', 'target': 'Dr_Quine'}, {'source': 'First_Internship', 'target': 'Piscine_Python_Django'}, {'source': 'First_Internship', 'target': 'Piscine_Ruby_on_Rails'}, {'source': 'First_Internship', 'target': 'Docker'}, {'source': 'First_Internship', 'target': 'Music_Room'}, {'source': 'First_Internship', 'target': 'Piscine_OCaml'}, {'source': 'Piscine_OCaml', 'target': 'H42N42'}, {'source': 'Piscine_OCaml', 'target': 'ft_turing'}, {'source': 'Piscine_OCaml', 'target': 'ft_ality'}, {'source': 'First_Internship', 'target': 'Piscine_Swift_iOS'}, {'source': 'First_Internship', 'target': 'Piscine_CPP'}, {'source': 'Piscine_CPP', 'target': 'Piscine_Unity'}, {'source': 'Swifty_Companion', 'target': 'Piscine_CPP'}, {'source': 'Swifty_Companion', 'target': 'Piscine_Swift_iOS'}, {'source': 'Swifty_Proteins', 'target': 'Swifty_Companion'}, {'source': 'Piscine_CPP', 'target': 'ft_hangouts'}, {'source': 'Abstract_VM', 'target': 'Piscine_CPP'}, {'source': 'Nibbler', 'target': 'Abstract_VM'}, {'source': 'Bomberman', 'target': 'Abstract_VM'}, {'source': 'Piscine_Unity', 'target': 'In_the_Shadows'}, {'source': 'In_the_Shadows', 'target': 'XV'}, {'source': 'Open_Project_I', 'target': 'First_Internship'}, {'source': 'Open_Project_II', 'target': 'First_Internship'}, {'source': 'First_Internship', 'target': 'cloud_1'}, {'source': 'First_Internship', 'target': 'roger_skyline_1'}, {'source': 'roger_skyline_1', 'target': 'roger_skyline_2'}]}
jgraph.draw(graph, z=200, size=(800, 600), directed= False, shader= "basic")
def plot_(Name, data, b_id_to_names, b_id_to_sex):
print('starting plot creating')
N = len(data['nodes'])
L = len(data['links'])
Edges = [(data['links'][k]['source'], data['links'][k]['target'])
for k in range(L)]
display(HTML(ig.draw(Edges, directed=False)))
labels = []
group = []
size_ = []
for node in data['nodes']:
labels.append(b_id_to_names[node['name']])
group.append(b_id_to_sex[node['name']])
size_.append(node['size'])
layt = ig.generate(Edges)
Xn = [layt['nodes'][k]['location'][0]
for k in range(N)] # x-coordinates of nodes
Yn = [layt['nodes'][k]['location'][1] for k in range(N)] # y-coordinates
Zn = [layt['nodes'][k]['location'][2] for k in range(N)] # z-coordinates
Xe = []
Ye = []
Ze = []
for e in Edges:
Xe += [
layt['nodes'][e[0]]['location'][0],
layt['nodes'][e[1]]['location'][0], None
] # x-coordinates of edge ends
Ye += [
layt['nodes'][e[0]]['location'][1],
layt['nodes'][e[1]]['location'][1], None
]
Ze += [
layt['nodes'][e[0]]['location'][2],
layt['nodes'][e[1]]['location'][2], None
]
trace1 = go.Scatter3d(x=Xe,
y=Ye,
z=Ze,
mode='lines',
line=dict(color='rgb(125,125,125)', width=1),
hoverinfo='none')
trace2 = go.Scatter3d(x=Xn,
y=Yn,
z=Zn,
mode='markers+text',
name='actors',
marker=dict(symbol='circle',
size=size_,
color=group,
colorscale='Viridis',
line=dict(color='rgb(50,50,50)',
width=0.5)),
text=labels,
hoverinfo='text')
axis = dict(showbackground=False,
showline=False,
zeroline=False,
showgrid=False,
showticklabels=False,
title='')
layout = go.Layout(
title="Мои друзья",
width=1000,
height=1000,
showlegend=False,
scene=dict(
xaxis=dict(axis),
yaxis=dict(axis),
zaxis=dict(axis),
),
margin=dict(t=100),
hovermode='closest',
)
data = [trace1, trace2]
fig = go.FigureWidget(data=data, layout=layout)
py.plot(fig, filename=Name + '_Friends.html')
nodes[i]['color'] = nodes[i]['node_color'].replace('#', '0x')
nodes[i].pop('node_color', None)
nodes[i].pop('node_label', None)
dict_nodes[new_key] = nodes[i]
new_edges = []
for i in range(len(edges)):
temp = edges[i]
temp['source'] = str(temp['source_id'])
temp.pop('source_id', None)
temp['target'] = str(temp['target_id'])
temp.pop('target_id', None)
temp['size'] = str(temp['weights'])
temp.pop('weights', None)
new_edges.append(temp)
graph = {'nodes': dict_nodes, 'edges': new_edges}
jgraph.draw(graph,
size=(1000, 800),
node_size=2.0,
edge_size=0.1,
shader='toon')
print("Vertrixes: ", vertrixes)
print("Edges: ", edges)
print("N_Vertrixes: ", len(vertrixes))
print("N_Edges: ", len(edges))
print("Jvertrixes:", jvertrixes)
print("Jedges:", jedges)
return {
"edges_array": edges,
"vertrix_array": vertrixes,
"nodes": jvertrixes,
"edges": jedges
}
for root, dirs, files in os.walk(paperdirectory, topdown=False):
for name in files:
if "-deep.json" in name:
with open(paperdirectory + "/" + name) as f:
d = json.load(f)
data.append(d)
gf = graphPapers(data)
import jgraph
jgraph.draw(gf)
# with open(paperdirectory+'/cross-ref-jgraph.json', 'w') as outfile:
# json.dump(gf, outfile, indent=4)
