[ENH] Add try/except block to interfaces tracking

Author: dPys

Dockerfile

@@ -48,6 +48,7 @@ RUN apt-get update -qq \
         libglu1-mesa-dev \
         libglib2.0-0 \
         libglw1-mesa \
+        libxkbcommon-x11-0 \
 	liblapack-dev \
 	libopenblas-base \
 	sqlite3 \
@@ -190,6 +191,7 @@ ENV PATH="/opt/conda/bin":$PATH
 ENV OPENBLAS_NUM_THREADS=4 \
     GOTO_NUM_THREADS=4 \
     OMP_NUM_THREADS=4
+ENV QT_QPA_PLATFORM=offscreen
 
 # and add it as an entrypoint
 #ENTRYPOINT ["pynets"]

pynets/core/interfaces.py

@@ -1154,6 +1154,7 @@ def _run_interface(self, runtime):
         import gc
         import time
         import glob
+        import os
         import os.path as op
         from pynets.registration import register
         from nipype.utils.filemanip import fname_presuffix, copyfile
@@ -1347,6 +1348,22 @@ def _run_interface(self, runtime):
         self._results["t1w2dwi_xfm"] = reg.t1w2dwi_xfm
         self._results["wm_gm_int_in_dwi"] = reg.wm_gm_int_in_dwi
 
+        reg_tmp = [
+            fa_tmp_path,
+            mask_tmp_path,
+            reg.warp_t1w2mni,
+            reg.t1w_head,
+            reg.wm_edge,
+            reg.vent_mask_dwi,
+            reg.vent_mask_t1w,
+            reg.corpuscallosum_mask_t1w,
+            reg.corpuscallosum_dwi
+        ]
+        for j in reg_tmp:
+            if j is not None:
+                if os.path.isfile(j):
+                    os.system(f"rm -f {j} &")
+
         gc.collect()
 
         return runtime
@@ -1745,6 +1762,8 @@ def _run_interface(self, runtime):
             t1w2dwi_bbr_xfm_tmp_path,
             t1w2dwi_xfm_tmp_path,
             wm_gm_int_in_dwi_tmp_path,
+            aligned_atlas_skull,
+            t1w_brain_tmp_path
         ]
         for j in reg_tmp:
             if j is not None:
@@ -1922,6 +1941,9 @@ def _run_interface(self, runtime):
             mni2t1w_warp_tmp_path,
             t1wtissue2dwi_xfm_tmp_path,
             mni2t1_xfm_tmp_path,
+            template_tmp_path,
+            roi_in_t1w,
+            roi_file_tmp_path
         ]
         for j in reg_tmp:
             if j is not None:
@@ -2238,6 +2260,8 @@ def _run_interface(self, runtime):
             uatlas_tmp_path,
             template_tmp_path,
             t1w2mni_xfm_tmp_path,
+            t1w2mni_warp_tmp_path,
+            template_mask_tmp_path
         ]
 
         for j in reg_tmp:
@@ -2612,6 +2636,7 @@ def _run_interface(self, runtime):
             mni2t1w_warp_tmp_path,
             mni2t1_xfm_tmp_path,
             roi_file_tmp_path,
+            template_tmp_path
         ]
         for j in reg_tmp:
             if j is not None:
@@ -3036,35 +3061,37 @@ def _run_interface(self, runtime):
             print(Style.RESET_ALL)
 
             # Commence Ensemble Tractography
-            streamlines = track_ensemble(
-                self.inputs.target_samples,
-                labels_im_file_tmp_path_wm_gm_int,
-                labels_im_file_tmp_path,
-                recon_path,
-                get_sphere(sphere),
-                self.inputs.directget,
-                self.inputs.curv_thr_list,
-                self.inputs.step_list,
-                self.inputs.track_type,
-                self.inputs.maxcrossing,
-                int(roi_neighborhood_tol),
-                self.inputs.min_length,
-                waymask_tmp_path,
-                B0_mask_tmp_path,
-                t1w2dwi_tmp_path, gm_in_dwi_tmp_path,
-                vent_csf_in_dwi_tmp_path, wm_in_dwi_tmp_path,
-                self.inputs.tiss_class,
-                runtime.cwd
-            )
-
-            gc.collect()
+            try:
+                streamlines = track_ensemble(
+                    self.inputs.target_samples,
+                    labels_im_file_tmp_path_wm_gm_int,
+                    labels_im_file_tmp_path,
+                    recon_path,
+                    get_sphere(sphere),
+                    self.inputs.directget,
+                    self.inputs.curv_thr_list,
+                    self.inputs.step_list,
+                    self.inputs.track_type,
+                    self.inputs.maxcrossing,
+                    int(roi_neighborhood_tol),
+                    self.inputs.min_length,
+                    waymask_tmp_path,
+                    B0_mask_tmp_path,
+                    t1w2dwi_tmp_path, gm_in_dwi_tmp_path,
+                    vent_csf_in_dwi_tmp_path, wm_in_dwi_tmp_path,
+                    self.inputs.tiss_class,
+                    runtime.cwd
+                )
+                gc.collect()
+            except BaseException:
+                print(UserWarning("Tractography failed..."))
+                streamlines = None
 
             if streamlines is not None:
                 # import multiprocessing
                 # from pynets.core.utils import kill_process_family
                 # return kill_process_family(int(multiprocessing.current_process().pid))
 
-
                 # Linear Fascicle Evaluation (LiFE)
                 if use_life is True:
                     print('Using LiFE to evaluate streamline plausibility...')

pynets/core/nodemaker.py

@@ -1203,7 +1203,7 @@ def gen_network_parcels(uatlas, network, labels, dir_path):
     )
     out_path = f"{dir_path}" \
                f"/{op.basename(uatlas).split(op.splitext(uatlas)[1])[0]}_" \
-               f"{network}{'_parcels.nii.gz'}"
+               f"{network}_parcels.nii.gz"
     nib.save(nib.Nifti1Image(net_parcels_sum, affine=np.eye(4)), out_path)
     del net_parcels_concatted, img_list
     gc.collect()

pynets/dmri/estimation.py

@@ -553,7 +553,7 @@ def streams2graph(
     overlap_thr = hardcoded_params[
         "StructuralNetworkWeighting"]["overlap_thr"][0]
     roi_neighborhood_tol = \
-    hardcoded_params['tracking']["roi_neighborhood_tol"][0]
+        hardcoded_params['tracking']["roi_neighborhood_tol"][0]
 
     start = time.time()
 
@@ -709,7 +709,7 @@ def streams2graph(
         # Adapted from the nnormalized fiber-density estimation routines of
         # Sebastian Tourbier.
         if fiber_density is True:
-            print("Weighting edges by fiber density...")
+            print("Redefining edges on the basis of fiber density...")
             # Summarize total fibers and total label volumes
             total_fibers = 0
             total_volume = 0
@@ -736,7 +736,7 @@ def streams2graph(
                 ix += 1
 
         if fa_wei is True:
-            print("Weighting edges by FA...")
+            print("Re-weighting edges by FA...")
             # Add FA attributes for each edge
             ix = 0
             for u, v, d in g.edges(data=True):
@@ -815,12 +815,6 @@ def streams2graph(
         ),
     )
 
-    tmp_files = [streams, warped_fa]
-    for j in tmp_files:
-        if j is not None:
-            if os.path.isfile(j):
-                os.system(f"rm -f {j} &")
-
     return (
         atlas_mni,
         streams,

pynets/dmri/track.py

@@ -480,7 +480,7 @@ def track_ensemble(
         while float(stream_counter) < float(target_samples) and float(ix) < 0.50*float(len(all_combs)):
             with Parallel(n_jobs=nthreads, backend='loky',
                           mmap_mode='r+', temp_folder=joblib_dir,
-                          verbose=2, max_nbytes='50000M',
+                          verbose=2, max_nbytes='25000M',
                           timeout=timeout) as parallel:
                 out_streams = parallel(
                     delayed(run_tracking)(

pynets/stats/benchmarking.py

@@ -562,7 +562,6 @@ def benchmark_reproducibility(comb, modality, alg, par_dict, disc,
                 print('Empty dataframe!')
                 return df_summary
 
-
             shapes = []
             for ix, i in enumerate(vect_all):
                 shapes.append(i.shape[0] * [list(ids)[ix]])
@@ -594,23 +593,23 @@ def benchmark_reproducibility(comb, modality, alg, par_dict, disc,
 if __name__ == "__main__":
     __spec__ = "ModuleSpec(name='builtins', loader=<class '_" \
                "frozen_importlib.BuiltinImporter'>)"
-    #base_dir = '/scratch/04171/dpisner/HNU/HNU_outs/triple'
-    base_dir = '/scratch/04171/dpisner/HNU/HNU_outs/outputs_language'
+    base_dir = '/scratch/04171/dpisner/HNU/HNU_outs/triple'
+    #base_dir = '/scratch/04171/dpisner/HNU/HNU_outs/outputs_language'
     thr_type = "MST"
-    icc = True
+    icc = False
     disc = True
-    int_consist = True
-    target_modality = 'func'
+    int_consist = False
+    target_modality = 'dwi'
 
     #embedding_types = ['ASE']
-    embedding_types = ['topology']
+    #embedding_types = ['topology']
     #embedding_types = ['OMNI']
-    #embedding_types = ['OMNI', 'ASE']
+    embedding_types = ['OMNI', 'ASE']
     modalities = ['func', 'dwi']
-    #rsns = ['triple', 'kmeans']
-    rsns = ['language']
-    template = 'CN200'
-    #template = 'MNI152_T1'
+    rsns = ['kmeans']
+    #rsns = ['language']
+    #template = 'CN200'
+    template = 'MNI152_T1'
     mets = ["global_efficiency",
             "average_shortest_path_length",
             "degree_assortativity_coefficient",
@@ -686,10 +685,6 @@ def tuple_insert(tup, pos, ele):
         tup = tup[:pos] + (ele,) + tup[pos:]
         return tup
 
-    # rsns = ['SalVentAttnA', 'DefaultA', 'ContB']
-    #rsns = ["triple", "kmeans"]
-    rsns = ["language"]
-
     for modality in modalities:
         print(f"MODALITY: {modality}")
         hyperparams = eval(f"hyperparams_{modality}")