Update to 0.6.0

CITATION.cff

@@ -10,8 +10,8 @@ authors:
 - family-names: "Chakravarty"
   given-names: "M. Mallar"
 title: "RABIES: Rodent Automated Bold Improvement of EPI Sequences."
-version: 0.5.5
-date-released: 2025-12-19
+version: 0.6.0
+date-released: 2026-03-26
 url: "https://github.com/CoBrALab/RABIES"
 
 

docs/conf.py

@@ -22,7 +22,7 @@
 author = 'CoBrALab'
 
 # The full version, including alpha/beta/rc tags
-release = '0.5.5'
+release = '0.6.0'
 
 
 # -- General configuration ---------------------------------------------------

docs/requirements.txt

@@ -6,5 +6,5 @@ sphinxcontrib-bibtex
 sphinxcontrib-programoutput
 jinja2==3.1.1
 pillow==10.1.0
-rabies==0.5.5
+rabies==0.6.0
 traits<7.0

rabies/__version__.py

@@ -3,6 +3,6 @@
 # 88YbdP88   8P   88"""   dP__Yb  Yb      88"Yb   dP__Yb  Yb  "88 88""
 # 88 YY 88  dP    88     dP""""Yb  YboodP 88  Yb dP""""Yb  YboodP 888888
 
-VERSION = (0, 5, 5)
+VERSION = (0, 6, 0)
 
 __version__ = '.'.join(map(str, VERSION))

rabies/parser.py

@@ -846,7 +846,7 @@ def get_parser():
         '--timeseries_interval', type=str, default='0-end',
         help=
             "Before confound correction, can crop the timeseries within a specific interval.\n"
-            "e.g. '0,80' for timepoint 0 to 80. 0 is the first time frame, and 'end' stands for \n"
+            "e.g. '0-80' for timepoint 0 to 80. 0 is the first time frame, and 'end' stands for \n"
             "the last time frame. \n"
             "(default: %(default)s)\n"
             "\n"

rabies/preprocess_pkg/hmc.py

@@ -58,8 +58,9 @@ def init_bold_hmc_wf(opts, name='bold_hmc_wf'):
     ])
 
     if opts.hmc_qc_report['apply']:
+         # multiply mem_gb 20X because there is massive RAM overload with this node
         hmc_qc_node = pe.Node(HMC_QC(fps=opts.hmc_qc_report['fps'], figure_format=opts.figure_format),
-                            name='hmc_qc_node', mem_gb=1.1*opts.scale_min_memory, n_procs=n_procs)
+                            name='hmc_qc_node', mem_gb=1.1*opts.scale_min_memory*20, n_procs=n_procs)
 
         workflow.connect([
             (inputnode, hmc_qc_node, [('ref_image', 'ref_file'),
@@ -246,30 +247,35 @@ class HMC_QC(BaseInterface):
 
     def _run_interface(self, runtime):
         import pandas as pd
+        from simpleitk_timeseries_motion_correction.create_animation import main
         filename = pathlib.Path(self.inputs.in_file).name.rsplit(".nii")[0]
         figure_path = os.path.abspath(f'{filename}_HMC_QC.{self.inputs.figure_format}')
         csv_path = os.path.abspath(f'{filename}_derivatives.csv')
 
         n_procs = int(os.environ['RABIES_ITK_NUM_THREADS']) if "RABIES_ITK_NUM_THREADS" in os.environ else os.cpu_count() # default to number of CPUs
 
-        derivatives_dict = HMC_derivatives(self.inputs.in_file, self.inputs.ref_file, self.inputs.csv_params, get_R2=False, n_procs=n_procs)
+        print('Calculating HMC derivatives for QC visualization...')
+        img_preHMC, img_postHMC, derivatives_dict = HMC_derivatives(self.inputs.in_file, self.inputs.ref_file, self.inputs.csv_params, get_R2=False, n_procs=n_procs)
+
+        print('Creating video pre/post HMC...')
+        # write .webp file
+        video_file = os.path.abspath(f'{filename}_HMC.webp')
+        main(input_img=img_preHMC, 
+             output_file=video_file, 
+             additional_input_imgs=[img_postHMC], 
+             labels=['Before correction', 'After correction'], 
+             scale=2.0, 
+             fps=self.inputs.fps)
+        del img_preHMC, img_postHMC
 
         # save some outputs to .csv
         key_l = ['D_Sc_preHMC', 'D_Sc_postHMC', 'mse_preHMC', 'mse_postHMC']
         pd.DataFrame(np.array([derivatives_dict[key].flatten() for key in key_l]).T, columns=key_l).to_csv(csv_path)
 
+        print('Creating QC figure...')
         fig = plot_motion_QC(derivatives_dict, self.inputs.ref_file, plot_R2=False)
         fig.savefig(figure_path, bbox_inches='tight')
 
-        # write .webp file
-        video_file = os.path.abspath(f'{filename}_HMC.webp')
-        from simpleitk_timeseries_motion_correction.create_animation import main
-        main(input_img=derivatives_dict['img_preHMC'], 
-             output_file=video_file, 
-             additional_input_imgs=[derivatives_dict['img_postHMC']], 
-             labels=['Before correction', 'After correction'], 
-             scale=2.0, 
-             fps=self.inputs.fps)
         setattr(self, 'out_figure', figure_path)
         setattr(self, 'out_csv', csv_path)
         setattr(self, 'video_file', video_file)
@@ -339,7 +345,8 @@ def HMC_derivatives(in_img, in_ref, motcorr_params_file, n_procs=1, get_R2=False
         ref_img = sitk.ReadImage(in_ref)
     else:
         raise ValueError(f"in_ref must be an SITK image or valid file path. Got: {in_ref}")        
-
+    del in_img, in_ref
+
     # prepare timeseries post-correction
     transforms = read_transforms_from_csv(motcorr_params_file)
     img_postHMC = framewise_resample_volume(
@@ -366,17 +373,20 @@ def HMC_derivatives(in_img, in_ref, motcorr_params_file, n_procs=1, get_R2=False
 
     mse_preHMC = np.mean((timeseries_preHMC.T - ref_img_array)**2, axis=0) # taking mean square error
     mse_postHMC = np.mean((timeseries_postHMC.T - ref_img_array)**2, axis=0) # taking mean square error
+    del ref_img_array, timeseries_preHMC, timeseries_postHMC
 
     img_preHMC_SD = get_SD(img_preHMC)
     img_postHMC_SD = get_SD(img_postHMC)
 
     img_preHMC_R2 = get_motion_R2(img_preHMC, translations,rotations) if get_R2 else None
     img_postHMC_R2 = get_motion_R2(img_postHMC, translations,rotations) if get_R2 else None
 
-    return {'img_preHMC':img_preHMC, 'img_postHMC':img_postHMC, 'translations':translations, 'rotations':rotations, 
+    derivatives_dict = {'translations':translations, 'rotations':rotations, 
             'D_Sc_preHMC':D_Sc_preHMC, 'D_Sc_postHMC':D_Sc_postHMC,'mse_preHMC':mse_preHMC, 'mse_postHMC':mse_postHMC, 
             'img_preHMC_SD':img_preHMC_SD, 'img_postHMC_SD':img_postHMC_SD, 'img_preHMC_R2':img_preHMC_R2, 'img_postHMC_R2':img_postHMC_R2}
 
+    return img_preHMC, img_postHMC, derivatives_dict
+
 
 def plot_motion_QC(derivatives_dict, ref_file, plot_R2=False):
     import matplotlib.pyplot as plt