Exemplo n.º 1
0
# Graph setup
# -

# for now amount_verticies has to be a multiplication of length and width
amount_nodes = 400
percent_edges = 0.5

# +
# using graph class to generate matrix

graph1 = Graph()

# +
# matrix genaration

matrix1 = graph1.create_matrix(amount_nodes)
edges1 = graph1.generate_edges(amount_nodes, percent_edges)
matrix1 = graph1.add_edges(matrix1, edges1)
list_edges = graph1.make_list_edges_distances(matrix1)
netxgraph1 = graph1.build_networkx_graph(list_edges)

# +
# matrix1
# -

# This initializes regular SOM grid matrix, it needs to be passes instead of matrix1 for it to work
# Also one needs to experiment with sigma to achieve good results learning rate
matrix2 = graph1.standard_som_distance_matrix(length, width)
matrix2

map1 = MapClass(data, length, width, learning_rate, number_epochs, matrix2,
Exemplo n.º 2
0
color_names = \
    ['black', 'blue', 'darkblue', 'skyblue',
     'greyblue', 'lilac', 'green', 'red',
     'cyan', 'violet', 'yellow', 'white',
     'darkgrey', 'mediumgrey', 'lightgrey']

# +
# Graph setup
# -

amount_vertecies = 100
percent_edges = 0.5

graph1 = Graph()

matrix1 = graph1.create_matrix(amount_vertecies)

edges1 = graph1.generate_edges(amount_vertecies, percent_edges)

matrix1 = graph1.add_edges(matrix1, edges1)

# +
# Network configuration

data = rgb_colors
data_lables = color_names
batch_size = 2

length = 10
width = 10
number_iterations = 100
Exemplo n.º 3
0
# Graph setup
# -

# for now amount_verticies has to be a multiplication of length and width
amount_nodes = 100
percent_edges = 0.2

# +
# using graph class to generate matrix

graph1 = Graph()

# +
# matrix genaration

matrix1 = graph1.create_matrix(amount_nodes)
edges1 = graph1.generate_edges(amount_nodes, percent_edges)
matrix1 = graph1.add_edges(matrix1, edges1)
list_edges = graph1.make_list_edges_distances(matrix1)
netxgraph1 = graph1.build_networkx_graph(list_edges)
# -

# +
# matrix1

# +
# This initializes regular SOM grid matrix, it needs to be passes instead of matrix1 for it to work
# Also one needs to experiment with sigma to achieve good results learning rate
# matrix2 = graph1.standard_som_distance_matrix(length, width)
# matrix2
# -