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Add 'matplotlib.use('Agg')'; update output path

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xie_x1
2026-06-10 16:14:07 +02:00
parent 2ef6f79480
commit fd76272157
6 changed files with 31 additions and 9 deletions
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Infer_1Photon.py
+3
View File
@@ -1,5 +1,8 @@
import sys
sys.path.append('./src')
import matplotlib
matplotlib.use('Agg')
from pathlib import Path
from omegaconf import OmegaConf
import torch
Infer_2Photon.py
+3
View File
@@ -1,5 +1,8 @@
import sys
sys.path.append('./src')
import matplotlib
matplotlib.use('Agg')
from pathlib import Path
from omegaconf import OmegaConf
import torch
Infer_3Photon.py
+3
View File
@@ -1,5 +1,8 @@
import sys
sys.path.append('./src')
import matplotlib
matplotlib.use('Agg')
from pathlib import Path
from omegaconf import OmegaConf
import torch
Train_1Photon.py
+5
View File
@@ -1,5 +1,8 @@
import sys
sys.path.append('./src')
import matplotlib
matplotlib.use('Agg')
from omegaconf import OmegaConf ### for yaml config parsing
import torch
import numpy as np
@@ -173,6 +176,7 @@ def plot_loss_curve(train_losses, val_losses, test_loss, exp_name, conf):
if conf.data.normalize:
plotName += '_normalized'
plt.savefig(f'Results/{exp_name}/Plots/{plotName}.png')
plt.close()
def plot_rms_curve(train_rms_x, train_rms_y, val_rms_x, val_rms_y, test_rms_x, test_rms_y, exp_name, conf):
import matplotlib.pyplot as plt
@@ -192,6 +196,7 @@ def plot_rms_curve(train_rms_x, train_rms_y, val_rms_x, val_rms_y, test_rms_x, t
if conf.data.normalize:
plotName += '_normalized'
plt.savefig(f'Results/{exp_name}/Plots/{plotName}.png')
plt.close()
def get_model_name(epoch, conf):
modelName = f'singlePhoton{conf.model.version}_{conf.data.energy}keV_Noise{conf.data.noise_keV}keV_E{epoch}_aug{conf.data.num_aug_ops}'
Train_2Photon.py
+13 -9
View File
@@ -1,5 +1,8 @@
import sys
sys.path.append('./src')
import matplotlib
matplotlib.use('Agg')
from omegaconf import OmegaConf ### for yaml config parsing
import torch
from torch import nn
@@ -27,14 +30,14 @@ def prepare_output_folder(conf):
# find the next index for experiment name
exp_index = 0
while True:
exp_name = f'{date}_2ph_{conf.data.energy}keV_v{conf.model.version}_{exp_index:02d}'
if not Path(f'Results/{exp_name}').exists():
exp_name = f'{date}_{conf.data.energy}keV_v{conf.model.version}_{exp_index:02d}'
if not Path(f'Results/2ph/{exp_name}').exists():
break
exp_index += 1
Path(f'Results/{exp_name}').mkdir(parents=True, exist_ok=True)
Path(f'Results/{exp_name}/Models').mkdir(parents=True, exist_ok=True)
Path(f'Results/{exp_name}/Plots').mkdir(parents=True, exist_ok=True)
OmegaConf.save(conf, f'Results/{exp_name}/config.yaml')
Path(f'Results/2ph/{exp_name}').mkdir(parents=True, exist_ok=True)
Path(f'Results/2ph/{exp_name}/Models').mkdir(parents=True, exist_ok=True)
Path(f'Results/2ph/{exp_name}/Plots').mkdir(parents=True, exist_ok=True)
OmegaConf.save(conf, f'Results/2ph/{exp_name}/config.yaml')
return exp_name
def get_loss_function(conf):
@@ -208,7 +211,7 @@ def plot_loss_curves(train_losses, val_losses, test_loss, exp_name, conf):
plt.legend()
plt.grid()
plotName = f'loss_curve_doublePhoton_{conf.model.version}.png'
plt.savefig(f'Results/{exp_name}/Plots/{plotName}')
plt.savefig(f'Results/2ph/{exp_name}/Plots/{plotName}')
plt.close()
def plot_rms_curve(train_rms_x, train_rms_y, val_rms_x, val_rms_y, test_rms_x, test_rms_y, exp_name, conf):
@@ -226,7 +229,8 @@ def plot_rms_curve(train_rms_x, train_rms_y, val_rms_x, val_rms_y, test_rms_x, t
plt.legend()
plt.grid()
plotName = f'rms_curve_doublePhoton_{conf.model.version}'
plt.savefig(f'Results/{exp_name}/Plots/{plotName}.png')
plt.savefig(f'Results/2ph/{exp_name}/Plots/{plotName}.png')
plt.close()
def get_model_name(conf):
modelName = f'doublePhoton{conf.model.version}_{conf.data.energy}keV_Noise{conf.data.noise_keV}keV'
@@ -260,7 +264,7 @@ if __name__ == "__main__":
print(f"Learning Rate: {optimizer.param_groups[0]['lr']:.2e}")
if epoch in conf.training.checkpoint_epochs or epoch == conf.training.epochs:
modelName = get_model_name(conf)
torch.save(model.state_dict(), f'Results/{exp_name}/Models/{modelName}_E{epoch}.pth')
torch.save(model.state_dict(), f'Results/2ph/{exp_name}/Models/{modelName}_E{epoch}.pth')
print(f"Saved model checkpoint: {modelName}_E{epoch}.pth")
plot_loss_curves(TrainLosses, ValLosses, test_loss=-1, exp_name=exp_name, conf=conf)
plot_rms_curve(train_rms_xs, train_rms_ys, val_rms_xs, val_rms_ys, test_rms_x = -1, test_rms_y = -1, exp_name=exp_name, conf=conf)
Train_3Photon.py
+4
View File
@@ -1,5 +1,8 @@
import sys
sys.path.append('./src')
import matplotlib
matplotlib.use('Agg')
from omegaconf import OmegaConf ### for yaml config parsing
import torch
import numpy as np
@@ -134,6 +137,7 @@ def plot_loss_curves(train_losses, val_losses, test_loss, exp_name, conf):
plt.grid()
plotName = f'loss_curve_triplePhoton_{conf.model.version}.png'
plt.savefig(f'Results/{exp_name}/Plots/{plotName}')
plt.close()
def get_model_name(conf):
modelName = f'triplePhoton{conf.model.version}_{conf.data.energy}keV'