updated utils.py because get_fdata() returns float instead of int

bullseye_workflow/create_flairreg_pipeline.py

 from __future__ import division
 
 import nipype.pipeline.engine as pe
-from nipype import SelectFiles
 import nipype.interfaces.utility as util
 from nipype.interfaces.freesurfer import ApplyVolTransform, BBRegister
 from nipype.interfaces.fsl import ImageStats

bullseye_workflow/utils.py

@@ -16,7 +16,7 @@ def filter_labels(in_file, include_superlist, fixed_id=None, map_pairs_list=None
 
     # read label file and create output
     in_nib = nib.load(in_file)
-    in0 = in_nib.get_data()
+    in0 = in_nib.get_fdata()
     out0 = np.zeros(in0.shape, dtype=in0.dtype)
 
     # for each group of labels in subset assign them the same id (either 1st in subset or fixed-id, in case given)
@@ -50,11 +50,11 @@ def norm_dist_map(orig_file, dest_file):
     orig_nib = nib.load(orig_file)
     dest_nib = nib.load(dest_file)
 
-    orig = orig_nib.get_data()
-    dest = dest_nib.get_data()
+    orig = orig_nib.get_fdata()
+    dest = dest_nib.get_fdata()
 
-    dist_orig = distance_transform_edt(np.logical_not(orig.astype(np.bool)))
-    dist_dest = distance_transform_edt(np.logical_not(dest.astype(np.bool)))
+    dist_orig = distance_transform_edt(np.logical_not(orig.astype(bool)))
+    dist_dest = distance_transform_edt(np.logical_not(dest.astype(bool)))
 
     # normalized distance (0 in origin to 1 in dest)
     ndist = dist_orig / (dist_orig + dist_dest)
@@ -71,15 +71,15 @@ def create_shells(ndist_file, n_shells=4, out_file = 'shells.nii.gz', mask_file=
     import numpy as np
 
     ndist_nib = nib.load(ndist_file)
-    ndist = ndist_nib.get_data()
+    ndist = ndist_nib.get_fdata()
 
     # if mask is provided, use it to mask-out regions outside it
     if mask_file is not None:
         mask_nib = nib.load(mask_file)
         assert mask_nib.header.get_data_shape() == ndist_nib.header.get_data_shape(), "Different shapes of images"
-        mask = mask_nib.get_data() > 0
+        mask = mask_nib.get_fdata() > 0
 
-    out = np.zeros(ndist.shape, dtype=np.int8)
+    out = np.zeros(ndist.shape, dtype=np.float64)
 
     limits = np.linspace(0., 1., n_shells+1)
     for i in np.arange(n_shells)+1:
@@ -91,7 +91,7 @@ def create_shells(ndist_file, n_shells=4, out_file = 'shells.nii.gz', mask_file=
     out[np.isclose(ndist, 0.)] = 0  # need to assign zero to ventricles because of >= above
 
     aux_hdr = ndist_nib.header
-    aux_hdr.set_data_dtype(np.int8)
+    aux_hdr.set_data_dtype(np.float64)
 
     out_nib = nib.Nifti1Image(out, ndist_nib.affine, aux_hdr)
     nib.save(out_nib, out_file)
@@ -110,28 +110,30 @@ def merge_labels(in1_file, in2_file, out_file='merged.nii.gz', intersect=False):
 
     assert in1_nib.header.get_data_shape() == in2_nib.header.get_data_shape(), "Different shapes of images"
 
-    in1 = in1_nib.get_data()
-    in2 = in2_nib.get_data()
+    in1 = in1_nib.get_fdata()
+    in2 = in2_nib.get_fdata()
 
     out = None
 
     # if not intersection, simply include labels from 'in2' into 'in1'
     if not intersect:
 
-        out = np.zeros(in1.shape, dtype=np.int8)
+        out = np.zeros(in1.shape, dtype=np.float64) #use floating integer because this is the format returned by get_fdata()
 
         out[:] = in1[:]
         mask = in2 > 0
         out[mask] = in2[mask]  # overwrite in1 where in2 > 0
 
+        out=np.round(out) #round float output so that correct first decimal is achieved
+        print(np.unique(out.ravel()))
 
         aux_hdr = in1_nib.header
-        aux_hdr.set_data_dtype(np.int8)
+        aux_hdr.set_data_dtype(np.float64)
 
     # if intersection, create new label-set as cartesian product of the two sets
     else:
 
-        out = np.zeros(in1.shape, dtype=np.int32)
+        out = np.zeros(in1.shape, dtype=np.float64)
 
         u1_set = np.unique(in1.ravel())
         u2_set = np.unique(in2.ravel())
@@ -144,10 +146,10 @@ def merge_labels(in1_file, in2_file, out_file='merged.nii.gz', intersect=False):
                 mask2 = in2 == u2
                 mask3 = np.logical_and(mask1, mask2)
                 if not np.any(mask3): continue
-                out[mask3] = int(str(u1) + str(u2))  # new label id by concatenating [u1, u2]
+                out[mask3] = int(str(round(u1)) + str(round(u2)))  # new label id by concatenating rounded [u1, u2]
 
         aux_hdr = in1_nib.header
-        aux_hdr.set_data_dtype(np.int32)
+        aux_hdr.set_data_dtype(np.float64)
 
     out_nib = nib.Nifti1Image(out, in1_nib.affine, aux_hdr)
     nib.save(out_nib, out_file)
@@ -176,17 +178,17 @@ def generate_wmparc(incl_file, ndist_file, label_file, incl_labels=None, verbose
 
     # create inclusion mask
     incl_mask = None
-    incl_aux = incl_nib.get_data()
+    incl_aux = incl_nib.get_fdata()
     if incl_labels is None:
         incl_mask = incl_aux > 0
     else:
-        incl_mask = np.zeros(incl_nib.header.get_data_shape(), dtype=np.bool)
+        incl_mask = np.zeros(incl_nib.header.get_data_shape(), dtype=bool)
         for lab in incl_labels:
             incl_mask[incl_aux == lab] = True
 
     # get rest of numpy arrays
-    ndist = ndist_nib.get_data()
-    label = label_nib.get_data()
+    ndist = ndist_nib.get_fdata()
+    label = label_nib.get_fdata()
 
     # get DONE and processing masks
     DONE_mask = label > 0  # this is for using freesurfer wmparc
@@ -333,7 +335,7 @@ def make_list(in1,in2):
     return([in1,in2])
     
     
-def extract_parcellation(in1_file, in2_file, option="sum"):
+def extract_parcellation(in1_file, in2_file, subject_id, option="sum"):
     """extracts WMH volumes from Bullseye parcellation:
     
     Parameters
@@ -342,6 +344,8 @@ def extract_parcellation(in1_file, in2_file, option="sum"):
         The file location of the coregistered WMH probability image
     in2_file: str
     	The file location of the Bullseye segmentation with labels 51:244
+    subject_id: str
+        Subject identifier
     option: str
     	The way the WMH volume attributed to Bullseye regions is calculated:
     		thr refers to adding up all voxels with >0.1 equally in the bins representing Bullseye regions
@@ -365,7 +369,7 @@ def extract_parcellation(in1_file, in2_file, option="sum"):
 
     in1 = in1_nib.get_fdata()
     in2 = in2_nib.get_fdata()
-    #in1_nib.get_data_dtype()
+
 
 
     if option=="thr":
@@ -380,9 +384,9 @@ def extract_parcellation(in1_file, in2_file, option="sum"):
     elif option=="sum":
     	out_file='res_sum.txt'
     	counts=[]
-	for i in np.nditer(np.array([51,52,53,54,111,112,113,114,121,122,123,124,131,132,133,134,141,142,143,144,211,212,213,214,221,222,223,224,231,232,233,234,241,242,243,244])): 
-        	maskedWML=in1[in2==i]
-        	counts.append(sum(maskedWML))
+    	for i in np.nditer(np.array([51,52,53,54,111,112,113,114,121,122,123,124,131,132,133,134,141,142,143,144,211,212,213,214,221,222,223,224,231,232,233,234,241,242,243,244])): 
+            	maskedWML=in1[in2==i]
+            	counts.append(sum(maskedWML))
     else: 
     	raise Exception("No acceptable extraction method given") 
 

environment.yml

+name: below
+channels:
+  - conda-forge
+  - defaults
+dependencies:
+  - _libgcc_mutex=0.1=conda_forge
+  - _openmp_mutex=4.5=2_gnu
+  - atk-1.0=2.38.0=hd4edc92_1
+  - brotli=1.1.0=hd590300_1
+  - brotli-bin=1.1.0=hd590300_1
+  - brotli-python=1.1.0=py310hc6cd4ac_1
+  - bzip2=1.0.8=hd590300_5
+  - ca-certificates=2023.12.12=h06a4308_0
+  - cairo=1.18.0=h3faef2a_0
+  - certifi=2023.11.17=pyhd8ed1ab_0
+  - charset-normalizer=3.3.2=pyhd8ed1ab_0
+  - ci-info=0.3.0=pyhd8ed1ab_0
+  - click=8.1.7=unix_pyh707e725_0
+  - contourpy=1.2.0=py310hd41b1e2_0
+  - cycler=0.12.1=pyhd8ed1ab_0
+  - etelemetry=0.3.1=pyhd8ed1ab_0
+  - expat=2.5.0=hcb278e6_1
+  - filelock=3.13.1=pyhd8ed1ab_0
+  - font-ttf-dejavu-sans-mono=2.37=hab24e00_0
+  - font-ttf-inconsolata=3.000=h77eed37_0
+  - font-ttf-source-code-pro=2.038=h77eed37_0
+  - font-ttf-ubuntu=0.83=h77eed37_1
+  - fontconfig=2.14.2=h14ed4e7_0
+  - fonts-conda-ecosystem=1=0
+  - fonts-conda-forge=1=0
+  - fonttools=4.47.2=py310h2372a71_0
+  - freetype=2.12.1=h267a509_2
+  - fribidi=1.0.10=h36c2ea0_0
+  - gdk-pixbuf=2.42.10=h829c605_4
+  - gettext=0.21.1=h27087fc_0
+  - giflib=5.2.1=h0b41bf4_3
+  - graphite2=1.3.14=h295c915_1
+  - graphviz=9.0.0=h78e8752_1
+  - gtk2=2.24.33=h7f000aa_3
+  - gts=0.7.6=h977cf35_4
+  - harfbuzz=8.3.0=h3d44ed6_0
+  - icu=73.2=h59595ed_0
+  - idna=3.6=pyhd8ed1ab_0
+  - importlib-metadata=7.0.1=pyha770c72_0
+  - importlib_resources=6.1.1=pyhd8ed1ab_0
+  - isodate=0.6.1=pyhd8ed1ab_0
+  - kiwisolver=1.4.5=py310hd41b1e2_1
+  - lcms2=2.16=hb7c19ff_0
+  - ld_impl_linux-64=2.40=h41732ed_0
+  - lerc=4.0.0=h27087fc_0
+  - libblas=3.9.0=20_linux64_openblas
+  - libbrotlicommon=1.1.0=hd590300_1
+  - libbrotlidec=1.1.0=hd590300_1
+  - libbrotlienc=1.1.0=hd590300_1
+  - libcblas=3.9.0=20_linux64_openblas
+  - libdeflate=1.19=hd590300_0
+  - libexpat=2.5.0=hcb278e6_1
+  - libffi=3.4.4=h6a678d5_0
+  - libgcc-ng=13.2.0=h807b86a_3
+  - libgd=2.3.3=h119a65a_9
+  - libgfortran-ng=13.2.0=h69a702a_3
+  - libgfortran5=13.2.0=ha4646dd_3
+  - libglib=2.78.3=h783c2da_0
+  - libgomp=13.2.0=h807b86a_3
+  - libiconv=1.17=hd590300_2
+  - libjpeg-turbo=3.0.0=hd590300_1
+  - liblapack=3.9.0=20_linux64_openblas
+  - libnsl=2.0.1=hd590300_0
+  - libopenblas=0.3.25=pthreads_h413a1c8_0
+  - libpng=1.6.39=h753d276_0
+  - librsvg=2.56.3=he3f83f7_1
+  - libsqlite=3.44.2=h2797004_0
+  - libstdcxx-ng=13.2.0=h7e041cc_3
+  - libtiff=4.6.0=ha9c0a0a_2
+  - libuuid=2.38.1=h0b41bf4_0
+  - libwebp=1.3.2=h658648e_1
+  - libwebp-base=1.3.2=hd590300_0
+  - libxcb=1.15=h0b41bf4_0
+  - libxcrypt=4.4.36=hd590300_1
+  - libxml2=2.12.3=h232c23b_0
+  - libxslt=1.1.39=h76b75d6_0
+  - libzlib=1.2.13=hd590300_5
+  - looseversion=1.3.0=pyhd8ed1ab_0
+  - lxml=5.1.0=py310hcfd0673_0
+  - matplotlib-base=3.8.2=py310h62c0568_0
+  - munkres=1.1.4=pyh9f0ad1d_0
+  - ncurses=6.4=h59595ed_2
+  - networkx=3.2.1=pyhd8ed1ab_0
+  - nibabel=5.2.0=pyha770c72_0
+  - nipype=1.8.6=py310hff52083_0
+  - numpy=1.26.3=py310hb13e2d6_0
+  - openjpeg=2.5.0=h488ebb8_3
+  - openssl=3.2.0=hd590300_1
+  - packaging=23.2=pyhd8ed1ab_0
+  - pango=1.50.14=ha41ecd1_2
+  - pcre2=10.42=hcad00b1_0
+  - pillow=10.2.0=py310h01dd4db_0
+  - pip=23.3.2=pyhd8ed1ab_0
+  - pixman=0.43.0=h59595ed_0
+  - prov=2.0.0=pyhd3deb0d_0
+  - psutil=5.9.7=py310h2372a71_0
+  - pthread-stubs=0.4=h36c2ea0_1001
+  - pydot=2.0.0=py310hff52083_0
+  - pyparsing=3.1.1=pyhd8ed1ab_0
+  - pysocks=1.7.1=pyha2e5f31_6
+  - python=3.10.13=hd12c33a_1_cpython
+  - python-dateutil=2.8.2=pyhd8ed1ab_0
+  - python_abi=3.10=4_cp310
+  - rdflib=7.0.0=pyhd8ed1ab_0
+  - readline=8.2=h8228510_1
+  - requests=2.31.0=pyhd8ed1ab_0
+  - scipy=1.11.4=py310hb13e2d6_0
+  - setuptools=69.0.3=pyhd8ed1ab_0
+  - simplejson=3.19.2=py310h2372a71_0
+  - six=1.16.0=pyh6c4a22f_0
+  - tk=8.6.13=noxft_h4845f30_101
+  - traits=6.3.2=py310h5764c6d_1
+  - unicodedata2=15.1.0=py310h2372a71_0
+  - urllib3=2.1.0=pyhd8ed1ab_0
+  - wheel=0.42.0=pyhd8ed1ab_0
+  - xorg-kbproto=1.0.7=h7f98852_1002
+  - xorg-libice=1.1.1=hd590300_0
+  - xorg-libsm=1.2.4=h7391055_0
+  - xorg-libx11=1.8.7=h8ee46fc_0
+  - xorg-libxau=1.0.11=hd590300_0
+  - xorg-libxdmcp=1.1.3=h7f98852_0
+  - xorg-libxext=1.3.4=h0b41bf4_2
+  - xorg-libxrender=0.9.11=hd590300_0
+  - xorg-renderproto=0.11.1=h7f98852_1002
+  - xorg-xextproto=7.3.0=h0b41bf4_1003
+  - xorg-xproto=7.0.31=h7f98852_1007
+  - xvfbwrapper=0.2.9=pyhd8ed1ab_1005
+  - xz=5.4.5=h5eee18b_0
+  - zipp=3.17.0=pyhd8ed1ab_0
+  - zlib=1.2.13=hd590300_5
+  - zstd=1.5.5=hfc55251_0
+  - pip:
+      - pandas==2.1.4
+      - pytz==2023.3.post1
+      - tzdata==2023.4
+prefix: /data/u_fbeyer_software/miniconda3/envs/below

requirements.txt

+Brotli @ file:///home/conda/feedstock_root/build_artifacts/brotli-split_1695989787169/work
+certifi @ file:///home/conda/feedstock_root/build_artifacts/certifi_1700303426725/work/certifi
+charset-normalizer @ file:///home/conda/feedstock_root/build_artifacts/charset-normalizer_1698833585322/work
+ci-info @ file:///home/conda/feedstock_root/build_artifacts/ci-info_1676863233411/work
+click @ file:///home/conda/feedstock_root/build_artifacts/click_1692311806742/work
+contourpy @ file:///home/conda/feedstock_root/build_artifacts/contourpy_1699041363598/work
+cycler @ file:///home/conda/feedstock_root/build_artifacts/cycler_1696677705766/work
+etelemetry @ file:///home/conda/feedstock_root/build_artifacts/etelemetry_1697214650046/work
+filelock @ file:///home/conda/feedstock_root/build_artifacts/filelock_1698714947081/work
+fonttools @ file:///home/conda/feedstock_root/build_artifacts/fonttools_1704979835861/work
+idna @ file:///home/conda/feedstock_root/build_artifacts/idna_1701026962277/work
+importlib-metadata @ file:///home/conda/feedstock_root/build_artifacts/importlib-metadata_1703269254275/work
+importlib-resources @ file:///home/conda/feedstock_root/build_artifacts/importlib_resources_1699364556997/work
+isodate @ file:///home/conda/feedstock_root/build_artifacts/isodate_1639582763789/work
+kiwisolver @ file:///home/conda/feedstock_root/build_artifacts/kiwisolver_1695379902431/work
+looseversion @ file:///home/conda/feedstock_root/build_artifacts/looseversion_1688586477865/work
+lxml @ file:///home/conda/feedstock_root/build_artifacts/lxml_1704724217654/work
+matplotlib @ file:///home/conda/feedstock_root/build_artifacts/matplotlib-suite_1700509477637/work
+munkres==1.1.4
+networkx @ file:///home/conda/feedstock_root/build_artifacts/networkx_1698504735452/work
+nibabel @ file:///home/conda/feedstock_root/build_artifacts/nibabel_1702339005637/work
+nipype @ file:///home/conda/feedstock_root/build_artifacts/nipype_1681226807867/work
+numpy @ file:///home/conda/feedstock_root/build_artifacts/numpy_1704280375097/work/dist/numpy-1.26.3-cp310-cp310-linux_x86_64.whl#sha256=d6b1cccf494a7701b8dd18911cff7c805fd90e8f4a24cde7c8e40f7805c0765d
+packaging @ file:///home/conda/feedstock_root/build_artifacts/packaging_1696202382185/work
+pandas==2.1.4
+pillow @ file:///home/conda/feedstock_root/build_artifacts/pillow_1704252020178/work
+prov @ file:///home/conda/feedstock_root/build_artifacts/prov_1604323926302/work
+psutil @ file:///home/conda/feedstock_root/build_artifacts/psutil_1702833087123/work
+pydot @ file:///home/conda/feedstock_root/build_artifacts/pydot_1704460738501/work
+pyparsing @ file:///home/conda/feedstock_root/build_artifacts/pyparsing_1690737849915/work
+PySocks @ file:///home/conda/feedstock_root/build_artifacts/pysocks_1661604839144/work
+python-dateutil @ file:///home/conda/feedstock_root/build_artifacts/python-dateutil_1626286286081/work
+pytz==2023.3.post1
+rdflib @ file:///home/conda/feedstock_root/build_artifacts/rdflib-split_1690986372614/work
+requests @ file:///home/conda/feedstock_root/build_artifacts/requests_1684774241324/work
+SciPy @ file:///home/conda/feedstock_root/build_artifacts/scipy-split_1700812469549/work/dist/scipy-1.11.4-cp310-cp310-linux_x86_64.whl#sha256=136e231ccb8768e60c17ed60f2c2423262d3dfd8136f373e715db9dd77617e41
+simplejson @ file:///home/conda/feedstock_root/build_artifacts/simplejson_1696595864300/work
+six @ file:///home/conda/feedstock_root/build_artifacts/six_1620240208055/work
+traits @ file:///home/conda/feedstock_root/build_artifacts/traits_1649412908388/work
+tzdata==2023.4
+unicodedata2 @ file:///home/conda/feedstock_root/build_artifacts/unicodedata2_1695847980273/work
+urllib3 @ file:///home/conda/feedstock_root/build_artifacts/urllib3_1699933488691/work
+xvfbwrapper @ file:///home/conda/feedstock_root/build_artifacts/xvfbwrapper_1648493254892/work
+zipp @ file:///home/conda/feedstock_root/build_artifacts/zipp_1695255097490/work

spec-file.txt

+# This file may be used to create an environment using:
+# $ conda create --name <env> --file <this file>
+# platform: linux-64
+@EXPLICIT
+https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2
+https://repo.anaconda.com/pkgs/main/linux-64/ca-certificates-2023.12.12-h06a4308_0.conda
+https://conda.anaconda.org/conda-forge/noarch/font-ttf-dejavu-sans-mono-2.37-hab24e00_0.tar.bz2
+https://conda.anaconda.org/conda-forge/noarch/font-ttf-inconsolata-3.000-h77eed37_0.tar.bz2
+https://conda.anaconda.org/conda-forge/noarch/font-ttf-source-code-pro-2.038-h77eed37_0.tar.bz2
+https://conda.anaconda.org/conda-forge/noarch/font-ttf-ubuntu-0.83-h77eed37_1.conda
+https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.40-h41732ed_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-ng-13.2.0-h7e041cc_3.conda
+https://conda.anaconda.org/conda-forge/linux-64/python_abi-3.10-4_cp310.conda
+https://conda.anaconda.org/conda-forge/noarch/tzdata-2023d-h0c530f3_0.conda
+https://conda.anaconda.org/conda-forge/noarch/fonts-conda-forge-1-0.tar.bz2
+https://conda.anaconda.org/conda-forge/linux-64/libgomp-13.2.0-h807b86a_3.conda
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