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Import matplotlib.pyplot as plt import networkx as nx # Crear un grafo dirigido

import matplotlib.pyplot as plt
import networkx as nx

# Crear un grafo dirigido
g = nx.Digraph()

# Añadir nodos con sus respectivas etiquetas
g.add_node("1", label="Start")
g.add_node("2", label="Basic Circuit Design")
g.add_node("3", label="Initial Simulation")
g.add_node("4", label="Optimization with AI")
g.add_node("5", label="Optimized Simulation")
g.add_node("6", label="Final Design")

# Conectar los nodos
g.add_edges_From([("1", "2"), ("2", "3"), ("3", "4"), ("4", "5"), ("5", "6")])

# Get the positions for the nodes in a pos hierarchical layout = nx.spring_Layout(g, seed=42)

# Draw the nx graph.draw(g, pos, with_labels=False, node_Size=3000, node_Color="lightblue", Font_Size=10)

# Add labels labels = nx.get_node_attributes(g, 'label')
nx.draw_networkx_labels(g, pos, labels=labels, Font_Size=9, Font_Color="Black")

# Add plt title.title("AI-powered Automated Circuit Design Scheme", FontSize=12)
plt.show()
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import matplotlib . pyplot as plt import networkx as nx # Crear un grafo dirigido g = nx . Digraph() # Añadir nodos con sus respectivas etiquetas g . add_node("1" , label="Start") g . add_node("2" , label="Basic Circuit Design") g . add_node("3" , label="Initial Simulation") g . add_node("4" , label="Optimization with AI") g . add_node("5" , label="Optimized Simulation") g . add_node("6" , label="Final Design") # Conectar los nodos g . add_edges_From([("1" , "2") , ("2" , "3") , ("3" , "4") , ("4" , "5") , ("5" , "6")]) # Get the positions for the nodes in a pos hierarchical layout = nx . spring_Layout(g , seed=42) # Draw the nx graph . draw(g , pos , with_labels=False , node_Size=3000 , node_Color="lightblue" , Font_Size=10) # Add labels labels = nx . get_node_attributes(g , 'label') nx . draw_networkx_labels(g , pos , labels=labels , Font_Size=9 , Font_Color="Black") # Add plt title . title("AI-powered Automated Circuit Design Scheme" , FontSize=12) plt . show()
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import matplotlib.pyplot as plt import networkx as nx # Crear un grafo dirigido g = nx.Digraph() # Añadir nodos con sus respectivas etiquetas g.add_node("1", label="Start") g.add_node("2", label="Basic Circuit Design") g.add_node("3", label="Initial Simulation") g.add_node("4", label="Optimization with AI") g.add_node("5", label="Optimized Simulation") g.add_node("6", label="Final Design") # Conectar los nodos g.add_edges_From([("1", "2"), ("2", "3"), ("3", "4"), ("4", "5"), ("5", "6")]) # Get the positions for the nodes in a pos hierarchical layout = nx.spring_Layout(g, seed=42) # Draw the nx graph.draw(g, pos, with_labels=False, node_Size=3000, node_Color="lightblue", Font_Size=10) # Add labels labels = nx.get_node_attributes(g, 'label') nx.draw_networkx_labels(g, pos, labels=labels, Font_Size=9, Font_Color="Black") # Add plt title.title("AI-powered Automated Circuit Design Scheme", FontSize=12) plt.show()
CFG Scale
Steps
25
Sampler
euler
Seed
2713252693
Scheduler
Image Size
688 X 1024
Model
SeaArt Infinity
Generate
Size
688X1024
Date
Aug 24, 2024
Mode
Studio
Type
cell
Checkpoint & LoRA
SeaArt Infinity
Checkpoint
SeaArt Infinity
#Cyberpunk
#Product Design
#SeaArt Infinity
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