tuto8 correction

tutorial/tuto_08_lpgd_split_measurements.py

@@ -89,7 +89,7 @@
 
 from spyrit.core.meas import HadamSplit
 from spyrit.core.noise import Poisson
-from spyrit.misc.sampling import meas2img2
+from spyrit.misc.sampling import meas2img
 from spyrit.misc.statistics import Cov2Var
 from spyrit.core.prep import SplitPoisson
 
@@ -106,7 +106,7 @@
 Ord_rec[n_sub:, :] = 0
 
 # Measurement and noise operators
-meas_op = HadamSplit(M, h, Ord_rec)
+meas_op = HadamSplit(M, h, torch.from_numpy(Ord_rec))
 noise_op = Poisson(meas_op, alpha)
 prep_op = SplitPoisson(alpha, meas_op)
 
@@ -119,8 +119,8 @@
 m = prep_op(y)  # preprocessed measurement vector
 
 m_plot = m.detach().numpy()
-m_plot = meas2img2(m_plot.T, Ord_rec)
-imagesc(m_plot, r"Measurements $m$")
+m_plot = meas2img(m_plot, Ord_rec)
+imagesc(m_plot[0, :, :], r"Measurements $m$")
 
 ###############################################################################
 # We define the LearnedPGD network by providing the measurement, noise and preprocessing operators,
@@ -163,15 +163,15 @@
 url_lpgd = "https://drive.google.com/file/d/1ki_cJQEwBWrpDhtE7-HoSEoY8oJUnUz5/view?usp=drive_link"
 model_net_path = os.path.join(
     model_path,
-    "lpgd_unet_imagenet_N0_10_m_hadam-split_N_128_M_4096_epo_30_lr_0.001_sss_10_sdr_0.5_bs_128_reg_1e-07_uit_3_sdec0-9",
+    "lpgd_unet_imagenet_N0_10_m_hadam-split_N_128_M_4096_epo_30_lr_0.001_sss_10_sdr_0.5_bs_128_reg_1e-07_uit_3_sdec0-9.pth",
 )
 
-try:
-    import gdown
-
-    gdown.download(url_lpgd, model_path, quiet=False, fuzzy=True)
-except:
-    print(f"Model not downloaded from {url_lpgd}!!!")
+if os.path.exists(model_net_path) is False:
+    try:
+        import gdown
+        gdown.download(url_lpgd, model_net_path, quiet=False, fuzzy=True)
+    except:
+        print(f"Model not downloaded from {url_lpgd}!!!")
 
 # Load pretrained weights to the model
 load_net(model_net_path, lpgd_net, device, strict=False)