Adding new IDP generation scripts

bip/pipelines/IDPs_gen/IDP_T1_GM_parcellation.py

+#!/usr/bin/env python
+#
+# IDP_T1_GM_parcellation.py - Generating IDP file with GM parcellation metrics
+#
+# Author: Fidel Alfaro Almagro <fidel.alfaroalmagro@ndcn.ox.ac.uk>
+# Author: Paul McCarthy <pauldmccarthy@gmail.com>
+# Author: Michiel Cottaar <michiel.cottaar@ndcn.ox.ac.uk>
+#
+# pylint: disable=C0103,E0602,C0114,C0115,C0116,R0913,R0914,R0915
+#
+
+import os
+import json
+import logging
+from fsl import wrappers
+from pipe_tree import In, Out, Ref
+from bip.utils.log_utils import redirect_logging, tempdir
+
+log = logging.getLogger(__name__)
+
+def run(ctx,
+        T1:                      In,
+        T1_to_MNI_warp_coef_inv: In,
+        T1_fast_pve_1:           In,
+        logs_dir:                Ref,
+        IDP_T1_GM_parcellation:  Out):
+    
+    with redirect_logging('IDP_T1_GM_parcellation', outdir=logs_dir),\
+        tempdir(tmp_dir):
+        result = ("NaN " * 139).strip()
+
+        GMatlas_to_T1 = tmp_dir + '/GMatlas_to_T1.nii.gz'
+        GMatlas = ctx.get_data("IDPs/GMatlas/GMatlas.nii.gz")
+       
+        wrappers.applywarp(src=GMatlas, ref=T1, w=T1_to_MNI_warp_coef_inv,
+                           out=GMatlas_to_T1, interp='nn')
+
+        wrappers.fslstats(fMRI_SNR).l(0.1).p(50).run()
+        vals = wrappers.fslstats(T1_brain_pve_1, K=GMatlas_to_T1).m.v.run()
+        result = " ".join([str(x) for x in vals[:,0] * vals[:,1]])
+
+        with open(IDP_T1_GM_parcellation, 'wt', encoding="utf-8") as f:
+            f.write(f'{result}\n')

bip/pipelines/IDPs_gen/IDP_func_TSNR.py

@@ -38,10 +38,7 @@ def run(ctx,
             if os.path.exists(file_name):
                 wrappers.fslmaths(file_name).Tstd().run(fMRI_SNR)
                 wrappers.fslmaths(file_name).Tmean().div(fMRI_SNR).run(fMRI_SNR)
-                v=wrappers.fslstats(fMRI_SNR).l(0.1).p(50).run()
-                print(v)
-                v = 1/v
-                print(v)
+                v = 1 / wrappers.fslstats(fMRI_SNR).l(0.1).p(50).run()
                 result += f"{v} "
             else:
                 result += "NaN "