Adding row_col_swap.py

dtiprep.py

@@ -4,14 +4,17 @@
 import sys
 import argparse
 import glob
-from scai_utils import saydo
+from scai_utils import *
 
 DATA_DIR = "/users/cais/STUT/DATA"
+DATA_DIR_RHY = "/users/cais/RHY/DATA"
 FSDATA_DIR = "/users/cais/STUT/FSDATA"
-DTIPREP_PATH = "/software/DTIPrep/1.1.6"
+# DTIPREP_PATH = "/software/DTIPrep/1.1.6"
+DTIPREP_PATH = "/software/DTIPrep/130630"
 OUTPUT_DIR = "/users/cais/STUT/analysis/dti"
+OUTPUT_DIR_RHY = "/users/cais/RHY/analysis/dwi"
 NRRD2NIFTI_BIN = "/software/DTIPrep/dev/DWI_NiftiNrrdConversion"
-DWICONVERT_BIN = "/software/DTIPrep/dev/DWIConvert"
+DWICONVERT_BIN = "/software/DTIPrep/3f0a2b4/DWIConvert"
 
 if __name__ == "__main__":
     parser = argparse.ArgumentParser(description="Run DTIPrep on STUT data")
@@ -58,11 +61,12 @@
         if not os.path.isfile(bve):
             raise Exception, "Cannot find bvecs file: %s"%(bve)
 
-    else: # MIT STUT study
+    elif len(sID) == 3 and sID.startswith("S"): # MIT STUT study
         rawdifdir = os.path.join(DATA_DIR, sID, "diffusion");
         if not os.path.isdir(rawdifdir):
             raise Exception, "Cannot find raw NIFTI diffusion data directory: %s"\
                              %(rawdifdir)
+
         bva = glob.glob(os.path.join(rawdifdir, "%s_*.mghdti.bvals"%(sID)))
         if len(bva) == 0:
             raise Exception, "Found no DTI volumes in raw data directory: %s"\
@@ -82,6 +86,29 @@
             raise Exception, "Cannot find raw 4D DTI series: %s"%(raw4d)
         if not os.path.isfile(bve):
             raise Exception, "Cannot find bvecs file: %s"%(bve)
+    else:
+        DATA_DIR = DATA_DIR_RHY
+        OUTPUT_DIR = OUTPUT_DIR_RHY
+        rawdifdir = os.path.join(DATA_DIR, sID, "diffusion")
+
+        if not os.path.isdir(rawdifdir):
+            raise Exception, "Cannot find raw NIFTI diffusion data directory: %s"\
+                             %(rawdifdir)
+
+        bva = glob.glob(os.path.join(rawdifdir, "%s_diffusion_*.bval" % sID))
+        if len(bva) == 0:
+            raise Exception, "Found no DTI volumes in raw data directory: %s"\
+                             %(rawdifdir)
+
+        bva = bva[-1]
+        rootname = os.path.split(bva)[1].replace('.bval', '')
+        print("INFO: rootname = %s"%(rootname))
+
+        raw4d = os.path.join(rawdifdir, "%s.nii.gz"%(rootname))
+        check_file(raw4d)
+
+        bve = os.path.join(rawdifdir, "%s.bvec"%(rootname))
+        check_file(bve)
 
     print("INFO: raw4d = %s"%(raw4d))
     print("INFO: bva = %s"%(bva))
@@ -112,7 +139,7 @@
             print("INFO: nifti-to-nrrd conversion done: output = %s\n"%(nrrdfn))
 
     if bConvertOnly:
-        sys.exit(0)    
+        sys.exit(0)
 
     # ------- Convert to Nrrd ------ #
     # Find the diffusion_dcm directory
@@ -161,6 +188,8 @@
         if not os.path.isfile(qced_nrrd):
             raise Exception,  "It appears that DTIPrep has failed: cannot find series: %s"%(qced_nrrd)
 
+    sys.exit(0)
+
     # ------ Convert QCed back to nifti ------ #
     qced_ngz = os.path.join(qcDir, "%s_QCed.nii.gz"%(sID))
 

row_col_swap.py

@@ -0,0 +1,55 @@
+#!/usr/bin/python
+
+import os
+import sys
+import numpy as np
+import argparse
+
+from scai_utils import *
+
+if __name__ == "__main__":
+    ap = argparse.ArgumentParser(description="Swap rows and columns in an ASCII data file of numbers (e.g., diffusion-weighted MRI gradient orientation vectors")
+    ap.add_argument("inFN", help="Input file name")
+    ap.add_argument("outFN", help="Output file name")
+
+    if len(sys.argv) == 1:
+        ap.print_help()
+        sys.exit(0)
+
+    args = ap.parse_args()
+    check_file(args.inFN)
+
+    f = open(args.inFN, "rt")
+    txt = remove_empty_strings(f.read().split("\n"))
+    f.close()
+
+    nrows = len(txt)
+
+    a_ncols = np.zeros(nrows)
+    for (i0, tline) in enumerate(txt):
+        items = remove_empty_strings(tline.split(" "))
+        a_ncols[i0] = len(items)
+
+    assert(len(np.unique(a_ncols)) == 1)
+
+    ncols = int(a_ncols[0])
+    dat = np.zeros([nrows, ncols])
+
+    for (i0, tline) in enumerate(txt):
+        items = remove_empty_strings(tline.split(" "))
+
+        for (i1, t_item) in enumerate(items):
+            dat[i0, i1] = float(t_item)
+
+
+    dat = np.transpose(dat)
+
+
+    f = open(args.outFN, "wt")
+    for i0 in range(ncols):
+        for i1 in range(nrows):
+            f.write("%.14f " % dat[i0, i1])
+        f.write("\n")
+
+    f.close()
+    check_file(args.outFN)