AntoineH/smart_augmentation
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Harle, Antoine (Contracteur) 2020-01-24 14:32:37 -05:00
parent f83c73ec17
commit f507ff4741
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higher/compare_res.py
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from utils import *
if __name__ == "__main__":
#'''
files=[
"res/log/Aug_mod(Data_augV5(Mix0.8-23TFx4-Mag)-LeNet)-100 epochs (dataug:0)- 1 in_it.json",
#"res/brutus-tests/log/Aug_mod(Data_augV5(Uniform-14TFx3-MagFxSh)-LeNet)-150epochs(dataug:0)-10in_it-0.json",
#"res/brutus-tests/log/Aug_mod(Data_augV5(Uniform-14TFx3-MagFxSh)-LeNet)-150epochs(dataug:0)-10in_it-1.json",
#"res/brutus-tests/log/Aug_mod(Data_augV5(Uniform-14TFx3-MagFxSh)-LeNet)-150epochs(dataug:0)-10in_it-2.json",
#"res/log/Aug_mod(RandAugUDA(18TFx2-Mag1)-LeNet)-100 epochs (dataug:0)- 0 in_it.json",
]
for idx, file in enumerate(files):
#legend+=str(idx)+'-'+file+'\n'
with open(file) as json_file:
data = json.load(json_file)
plot_resV2(data['Log'], fig_name=file.replace('.json','').replace('log/',''), param_names=data['Param_names'])
#plot_TF_influence(data['Log'], param_names=data['Param_names'])
#'''
## Loss , Acc, Proba = f(epoch) ##
#plot_compare(filenames=files, fig_name="res/compare")
'''
## Acc, Time, Epochs = f(n_tf) ##
#fig_name="res/TF_nb_tests_compare"
fig_name="res/TF_seq_tests_compare"
inner_its = [0, 10]
dataug_epoch_starts= [0]
TF_nb = 14#[len(TF.TF_dict)] #range(10,len(TF.TF_dict)+1) #[len(TF.TF_dict)]
N_seq_TF= [1, 2, 3, 4, 6] #[1]
fig, ax = plt.subplots(ncols=3, figsize=(30, 8))
for in_it in inner_its:
for dataug in dataug_epoch_starts:
#n_tf = TF_nb
#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]
#filenames =["res/TF_nb_tests/log/Aug_mod(Data_augV4(Uniform-{} TF x {})-LeNet)-200 epochs (dataug:{})- {} in_it.json".format(n_tf, 1, dataug, in_it) for n_tf in TF_nb]
n_tf = N_seq_TF
#filenames =["res/TF_nb_tests/log/Aug_mod(Data_augV4(Uniform-{} TF x {})-LeNet)-200 epochs (dataug:{})- {} in_it.json".format(TF_nb, n_tf, dataug, in_it) for n_tf in N_seq_TF]
filenames =["res/TF_nb_tests/log/Aug_mod(Data_augV4(Uniform-{} TF x {})-LeNet)-200 epochs (dataug:{})- {} in_it.json".format(TF_nb, n_tf, dataug, in_it) for n_tf in N_seq_TF]
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)
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()
'''
#Res print
'''
nb_run=3
accs = []
times = []
files = ["res/brutus-tests/log/Aug_mod(Data_augV5(Uniform-14TFx3-Mag)-LeNet)-150epochs(dataug:0)-1in_it-%s.json"%str(run) for run in range(nb_run)]
for idx, file in enumerate(files):
#legend+=str(idx)+'-'+file+'\n'
with open(file) as json_file:
data = json.load(json_file)
accs.append(data['Accuracy'])
times.append(data['Time'][0])
print(idx, data['Accuracy'])
print(files[0], np.mean(accs), np.std(accs), np.mean(times))
'''