# drawtype="rbg" tries to draw colors on map - needs an input data with 3 vectors # drawtype="black-white" draws black-white # drawtype="networkx" graph drawing using the networkx library # drawtype="None" - default draws empty space # Also there is networkx graph drawing # labels=True or False draws labels on the map... labels are necessary... # draw_every_epoch=0 Don't draw anything # draw_every_epoch=10 draw every 10 epochs # - map1.impact_matrix labels = True drawtype = "rbg" # + # Going through a large cycle combining of number of iteration whole cycles map1.large_cycle(draw_every_epoch=100, drawtype=drawtype) # - # Drawing all the history plt.rcParams['figure.dpi'] = 150 map1.draw_all(drawtype, labels=labels) map1.draw_all(drawtype="networkx", labels=labels)
data_lables = color_names
batch_size = 2
length = 10
width = 10
number_iterations = 100
shuffle = True
learning_rate = 0.01
# + {}
# trainloader = ""
# def load_data(data, batch_size=4):
# dim = len(data[0])
# number_rows_data = len(data)
# trainloader = torch.utils.data.DataLoader(data, batch_size=batch_size, shuffle=True)
# return trainloader, dim, number_rows_data
# -
map1 = MapClass(data, length, width, learning_rate, number_iterations, matrix1,
data_lables, batch_size, shuffle)
# +
# training, dim, number_rows_data = load_data(data, batch_size)
# -
plt.rcParams['figure.dpi'] = 150
map1.large_cycle(draw_every_epoch=10, rgb=True)
# Network configuration
data = digits.data
data_lables = digits.target
batch_size = 10
length = 10
width = 10
number_iterations = 100
shuffle = True
learning_rate = 0.01
# -
map1 = MapClass(data, length, width, learning_rate, number_iterations, matrix1,
data_lables, batch_size, shuffle)
# +
# training, dim, number_rows_data = load_data(data, batch_size)
# -
plt.rcParams['figure.dpi'] = 150
map1.large_cycle(draw_every_epoch=10, rgb=False)
map1.weights.shape
for tr in map1.trainloader:
# print(tr)
for t in tr:
print(len(t))