From eeb507ec18b7a206bac6bbf35e338d6e0e98fe11 Mon Sep 17 00:00:00 2001
From: "xiangyu.xie" <xiangyu.xie@psi.ch>
Date: Thu, 28 May 2026 16:34:17 +0200
Subject: [PATCH] Update script conventions

---
 Configs/infer_1photon.yaml | 12 +++++-------
 Configs/infer_2photon.yaml | 28 ++++++++++++++++++++++++----
 Infer_2Photon.py           |  5 +++--
 3 files changed, 32 insertions(+), 13 deletions(-)

diff --git a/Configs/infer_1photon.yaml b/Configs/infer_1photon.yaml
index e5ede71..9306a7a 100644
--- a/Configs/infer_1photon.yaml
+++ b/Configs/infer_1photon.yaml
@@ -1,6 +1,6 @@
 # configs/infer_1photon.yaml
 experiment:
-  name: "FlatField_3filters_pos0"  # options: SiemenStarLowerLeft, SiemenStarLowerRight
+  name: "FlatField_2filters"  # options: SiemenStarLowerLeft, SiemenStarLowerRight
   task: "1Photon" 
   output_base: "./InferenceResults"
 
@@ -29,7 +29,7 @@ data:
       file_pattern: "2603MaxIV_FlatField3Filters_pos0_12keV/1Photon_CS3_chunk{}.h5" ### 12 keV
       NX: 101
       NY: 101
-      file_range: [0, 48] # [0, 48)
+      file_range: [0, 16] # [0, 16)
       roi: [0, 101, 0, 101]
     KnifeEdge_2filters:
       file_pattern: "2603MaxIV_Edge2Filters_12keV/1Photon_CS3_chunk{}.h5" ### 12 keV
@@ -58,13 +58,11 @@ data:
 model:
   base_dir: "/home/xie_x1/MLXID/DeepLearning/Results/"
   # experiment_name: "260408_1ph_12keV_v251022_03"
-  # name: "singlePhoton251022_12keV_Noise0.13keV_E150_aug1.pth"
-  # experiment_name: "260511_1ph_12keV_v251022_00"
-  # name: "singlePhoton251022_12keV_Noise0.13keV_E150_aug1.pth"
+  # name: "singlePhoton251022_12keV_Noise0.13keV_E150_aug1.pth" ### std/mean = 0.033
   experiment_name: "260512_1ph_12keV_v260511_06"
-  name: "singlePhoton260511_12keV_Noise0.13keV_E300_aug1.pth"
+  name: "singlePhoton260511_12keV_Noise0.13keV_E500_aug1.pth" ### std/mean = 0.025
 
 inference:
   binning_factor: 10
   chunk_size: 16  #  
-  num_aug_ops: 8  # TTA: test-time augmentation
+  num_aug_ops: 1  # TTA: test-time augmentation
diff --git a/Configs/infer_2photon.yaml b/Configs/infer_2photon.yaml
index 4befca8..a9d8108 100644
--- a/Configs/infer_2photon.yaml
+++ b/Configs/infer_2photon.yaml
@@ -32,7 +32,28 @@ data:
       file_pattern: "2603MaxIV_FlatField3Filters_pos0_12keV/2Photon_CS7_chunk{}.h5" ### 12 keV
       NX: 101
       NY: 101
-      file_range: [0, 48] # [0, 48)
+      file_range: [0, 16] # [0, 16)
+      roi: [0, 101, 0, 101]
+      nSize: 7
+    KnifeEdge_2filters:
+      file_pattern: "2603MaxIV_Edge2Filters_12keV/2Photon_CS7_chunk{}.h5" ### 12 keV
+      NX: 101
+      NY: 101
+      file_range: [0, 16] # [0, 16)
+      roi: [0, 101, 0, 101]
+      nSize: 7
+    FlatField_2filters:
+      file_pattern: "2603MaxIV_Flat2Filters_12keV/2Photon_CS7_chunk{}.h5" ### 12 keV
+      NX: 101
+      NY: 101
+      file_range: [0, 16] # [0, 16)
+      roi: [0, 101, 0, 101]
+      nSize: 7
+    Uniformity_test:
+      file_pattern: "2603MaxIV_Flat2Filters_12keV/2Photon_CS7_chunk{}.h5" ### 12 keV
+      NX: 101
+      NY: 101
+      file_range: [0, 1]
       roi: [0, 101, 0, 101]
       nSize: 7
   
@@ -42,10 +63,9 @@ data:
   num_workers: 16
 
 model:
-  version: "251124"
   base_dir: "/home/xie_x1/MLXID/DeepLearning/Results/"
-  experiment_name: "260506_2ph_12keV_v251124_03"
-  name: "doublePhoton251124_12keV_Noise0.13keV_E150.pth"
+  experiment_name: "260511_2ph_12keV_v260507_00"
+  name: "doublePhoton260507_12keV_Noise0.13keV_E300.pth"
 
 inference:
   binning_factor: 10
diff --git a/Infer_2Photon.py b/Infer_2Photon.py
index 695a5de..5f42079 100644
--- a/Infer_2Photon.py
+++ b/Infer_2Photon.py
@@ -140,7 +140,7 @@ def save_results(ml_super_frame, count_frame, subpixel_dist,
     plt.close()
     np.save(output_dir / '2Photon_subpixel_Distribution.npy', subpixel_dist)
     std, mean = np.std(subpixel_dist), np.mean(subpixel_dist)
-    print(f"[Plotting]: Sub-pixel distribution: Std/Mean: {std/mean:.4f}")
+    print(f"[Plotting]: Sub-pixel distribution: RMS/Mean: {std/mean:.4f}, expected  value = {1/np.sqrt(mean):.4f} for uniform distribution")
 
     print(f"Results saved to: {output_dir}")
 
@@ -149,7 +149,8 @@ if __name__ == "__main__":
     output_dir = prepare_output_folder(conf)
 
     ### model loading
-    model = get_double_photon_model_class(conf.model.version)().cuda()
+    model_version = conf.model.experiment_name.split('_v')[-1][:6]
+    model = get_double_photon_model_class(model_version)().cuda()
     model.load_state_dict(torch.load(f'{conf.model.base_dir}/{conf.model.experiment_name}/Models/{conf.model.name}', weights_only=True))
     # model.eval()