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Harle, Antoine (Contracteur) 2019-11-11 14:36:37 -05:00
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from utils import *
if __name__ == "__main__":
#### Comparison ####
## Loss , Acc, Proba = f(epoch) ##
files=[
#"res/log/LeNet-100 epochs.json",
#"res/log/Aug_mod(Data_augV4(Uniform-4 TF)-LeNet)-100 epochs (dataug:0)- 0 in_it.json",
#"res/log/Aug_mod(Data_augV4(Uniform-4 TF)-LeNet)-100 epochs (dataug:50)- 0 in_it.json",
#"res/log/Aug_mod(Data_augV4(Uniform-3 TF)-LeNet)-100 epochs (dataug:0)- 0 in_it.json",
#"res/log/Aug_mod(Data_augV3(Uniform-3 TF)-LeNet)-100 epochs (dataug:50)- 10 in_it.json",
#"res/log/Aug_mod(Data_augV4(Mix 0,5-3 TF)-LeNet)-100 epochs (dataug:0)- 1 in_it.json",
#"res/log/Aug_mod(Data_augV4(Mix 0.5-3 TF)-LeNet)-100 epochs (dataug:50)- 10 in_it.json",
#"res/log/Aug_mod(Data_augV4(Uniform-3 TF)-LeNet)-100 epochs (dataug:0)- 10 in_it.json",
#"res/log/Aug_mod(Data_augV4(Uniform-10 TF)-LeNet)-100 epochs (dataug:50)- 10 in_it.json",
#"res/log/Aug_mod(Data_augV4(Uniform-10 TF)-LeNet)-100 epochs (dataug:50)- 0 in_it.json",
]
#plot_compare(filenames=files, fig_name="res/compare")
## Acc, Time, Epochs = f(n_tf) ##
fig_name="res/TF_nb_tests_compare"
inner_its = [0, 10]
dataug_epoch_starts= [0, -1]
TF_nb = range(1,14+1)
fig, ax = plt.subplots(ncols=3, figsize=(30, 8))
for in_it in inner_its:
for dataug in dataug_epoch_starts:
filenames =["res/TF_nb_tests/log/Aug_mod(Data_augV4(Uniform-{} TF)-LeNet)-200 epochs (dataug:{})- {} in_it.json".format(n_tf, dataug, in_it) for n_tf in TF_nb]
all_data=[]
#legend=""
for idx, file in enumerate(filenames):
#legend+=str(idx)+'-'+file+'\n'
with open(file) as json_file:
data = json.load(json_file)
all_data.append(data)
n_tf = [len(x["Param_names"]) for x in all_data]
acc = [x["Accuracy"] for x in all_data]
epochs = [len(x["Log"]) for x in all_data]
time = [x["Time"][0] for x in all_data]
#for i in range(len(time)): time[i] *= epochs[i] #Estimation temps total
ax[0].plot(n_tf, acc, label="{} in_it/{} dataug".format(in_it,dataug))
ax[1].plot(n_tf, time, label="{} in_it/{} dataug".format(in_it,dataug))
ax[2].plot(n_tf, epochs, label="{} in_it/{} dataug".format(in_it,dataug))
#for data in all_data:
#print(np.mean([x["param"] for x in data["Log"]], axis=0))
# print(len(data["Param_names"]), np.argsort(np.argsort(np.mean([x["param"] for x in data["Log"]], axis=0))))
ax[0].set_title('Acc')
ax[1].set_title('Time')
ax[2].set_title('Epochs')
for a in ax: a.legend()
fig_name = fig_name.replace('.',',')
plt.savefig(fig_name, bbox_inches='tight')
plt.close()