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akeshavanakeshavan
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initial commit w/ dockerfile and run.py
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‎Dockerfile

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# Generated by Neurodocker version 0.4.1
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# Timestamp: 2018-09-04 17:44:34 UTC
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#
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# Thank you for using Neurodocker. If you discover any issues
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# or ways to improve this software, please submit an issue or
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# pull request on our GitHub repository:
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#
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# https://github.com/kaczmarj/neurodocker
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FROM debian:stretch
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ARG DEBIAN_FRONTEND="noninteractive"
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ENV LANG="en_US.UTF-8" \
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LC_ALL="en_US.UTF-8" \
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ND_ENTRYPOINT="/neurodocker/startup.sh"
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RUN export ND_ENTRYPOINT="/neurodocker/startup.sh" \
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&& apt-get update -qq \
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&& apt-get install -y -q --no-install-recommends \
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apt-utils \
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bzip2 \
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ca-certificates \
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curl \
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locales \
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unzip \
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&& apt-get clean \
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&& rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* \
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&& sed -i -e 's/# en_US.UTF-8 UTF-8/en_US.UTF-8 UTF-8/' /etc/locale.gen \
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&& dpkg-reconfigure --frontend=noninteractive locales \
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&& update-locale LANG="en_US.UTF-8" \
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&& chmod 777 /opt && chmod a+s /opt \
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&& mkdir -p /neurodocker \
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&& if [ ! -f "$ND_ENTRYPOINT" ]; then \
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echo '#!/usr/bin/env bash' >> "$ND_ENTRYPOINT" \
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&& echo 'set -e' >> "$ND_ENTRYPOINT" \
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&& echo 'if [ -n "$1" ]; then "$@"; else /usr/bin/env bash; fi' >> "$ND_ENTRYPOINT"; \
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fi \
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&& chmod -R 777 /neurodocker && chmod a+s /neurodocker
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ENTRYPOINT ["/neurodocker/startup.sh"]
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ENV FSLDIR="/opt/fsl-5.0.11" \
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PATH="/opt/fsl-5.0.11/bin:$PATH"
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RUN apt-get update -qq \
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&& apt-get install -y -q --no-install-recommends \
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bc \
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dc \
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file \
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libfontconfig1 \
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libfreetype6 \
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libgl1-mesa-dev \
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libglu1-mesa-dev \
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libgomp1 \
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libice6 \
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libmng1 \
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libxcursor1 \
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libxft2 \
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libxinerama1 \
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libxrandr2 \
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libxrender1 \
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libxt6 \
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wget \
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&& apt-get clean \
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&& rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* \
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&& echo "Downloading FSL ..." \
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&& mkdir -p /opt/fsl-5.0.11 \
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&& curl -fsSL --retry 5 https://fsl.fmrib.ox.ac.uk/fsldownloads/fsl-5.0.11-centos6_64.tar.gz \
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| tar -xz -C /opt/fsl-5.0.11 --strip-components 1 \
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&& sed -i '$iecho Some packages in this Docker container are non-free' $ND_ENTRYPOINT \
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&& sed -i '$iecho If you are considering commercial use of this container, please consult the relevant license:' $ND_ENTRYPOINT \
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&& sed -i '$iecho https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Licence' $ND_ENTRYPOINT \
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&& sed -i '$isource $FSLDIR/etc/fslconf/fsl.sh' $ND_ENTRYPOINT \
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&& echo "Installing FSL conda environment ..." \
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&& bash /opt/fsl-5.0.11/etc/fslconf/fslpython_install.sh -f /opt/fsl-5.0.11
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ENV CONDA_DIR="/opt/miniconda-latest" \
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PATH="/opt/miniconda-latest/bin:$PATH"
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RUN export PATH="/opt/miniconda-latest/bin:$PATH" \
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&& echo "Downloading Miniconda installer ..." \
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&& conda_installer="/tmp/miniconda.sh" \
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&& curl -fsSL --retry 5 -o "$conda_installer" https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh \
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&& bash "$conda_installer" -b -p /opt/miniconda-latest \
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&& rm -f "$conda_installer" \
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&& conda update -yq -nbase conda \
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&& conda config --system --prepend channels conda-forge \
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&& conda config --system --set auto_update_conda false \
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&& conda config --system --set show_channel_urls true \
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&& sync && conda clean -tipsy && sync \
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&& conda create -y -q --name preafq
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RUN conda install -y -q --name preafq \
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-c \
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conda-forge \
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python=3.6 \
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nipype \
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dipy \
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&& sync && conda clean -tipsy && sync
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RUN sed -i '$isource activate preafq' $ND_ENTRYPOINT
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RUN echo '{ \
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\n "pkg_manager": "apt", \
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\n "instructions": [ \
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\n [ \
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\n "base", \
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\n "debian:stretch" \
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\n ], \
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\n [ \
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\n "fsl", \
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\n { \
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\n "version": "5.0.11" \
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\n } \
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\n ], \
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\n [ \
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\n "miniconda", \
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\n { \
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\n "conda_install": [ \
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\n "-c", \
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\n "conda-forge", \
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\n "python=3.6", \
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\n "nipype", \
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\n "dipy" \
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\n ], \
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\n "create_env": "preafq", \
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\n "use_env": "preafq" \
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\n } \
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\n ] \
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\n ] \
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\n}' > /neurodocker/neurodocker_specs.json

‎run.py

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def run_preAFQ(dwi_file, bvec_file, working_dir, sink_dir):
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import nipype.interfaces.fsl as fsl
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from nipype.interfaces.fsl.utils import AvScale
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import nipype.pipeline.engine as pe
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import nipype.interfaces.utility as niu
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import nipype.interfaces.io as nio
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from nipype.workflows.dmri.fsl.epi import create_dmri_preprocessing
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from nipype.interfaces.dipy import DTI
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from nipype.utils.filemanip import fname_presuffix
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import os
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wf = create_dmri_preprocessing(name='preAFQ',
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use_fieldmap=False,
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fieldmap_registration=False)
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wf.inputs.inputnode.ref_num = 0
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wf.inputs.inputnode.in_file = dwi_file
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wf.inputs.inputnode.in_bvec = bvec_file
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dwi_filename = os.path.split(dwi_file)[1].split(".nii.gz")[0]
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bids_subject_name = dwi_filename.split("_")[0]
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assert bids_subject_name.startswith("sub-")
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inputnode = wf.get_node("inputnode")
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outputspec = wf.get_node("outputnode")
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#QC: FLIRT translation and rotation parameters
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flirt = wf.get_node("motion_correct.coregistration")
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#flirt.inputs.save_mats = True
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#wf.connect(getmotion, "motion_params", datasink, "dti.@motparams")
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def get_flirt_motion_parameters(flirt_out_mats):
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import nipype.interfaces.fsl.utils as fsl
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import os
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import numpy as np
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def get_params(A):
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"""This is a copy of spm's spm_imatrix where
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we already know the rotations and translations matrix,
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shears and zooms (as outputs from fsl FLIRT/avscale)
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Let A = the 4x4 rotation and translation matrix
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R = [ c5*c6, c5*s6, s5]
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[-s4*s5*c6-c4*s6, -s4*s5*s6+c4*c6, s4*c5]
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[-c4*s5*c6+s4*s6, -c4*s5*s6-s4*c6, c4*c5]
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"""
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import numpy as np
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def rang(b):
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a = min(max(b, -1), 1)
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return a
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Ry = np.arcsin(A[0,2])
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#Rx = np.arcsin(A[1,2]/np.cos(Ry))
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#Rz = np.arccos(A[0,1]/np.sin(Ry))
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if (abs(Ry)-np.pi/2)**2 < 1e-9:
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Rx = 0
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Rz = np.arctan2(-rang(A[1,0]), rang(-A[2,0]/A[0,2]))
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else:
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c = np.cos(Ry)
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Rx = np.arctan2(rang(A[1,2]/c), rang(A[2,2]/c))
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Rz = np.arctan2(rang(A[0,1]/c), rang(A[0,0]/c))
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rotations = [Rx, Ry, Rz]
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translations = [A[0,3], A[1,3], A[2,3]]
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return rotations, translations
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motion_params = open(os.path.abspath('motion_parameters.par'),'w')
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for mat in flirt_out_mats:
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res = fsl.AvScale(mat_file = mat).run()
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A = np.asarray(res.outputs.rotation_translation_matrix)
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rotations, translations = get_params(A)
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for i in rotations+translations:
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motion_params.write('%f '%i)
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motion_params.write('\n')
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motion_params.close()
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motion_params = os.path.abspath('motion_parameters.par')
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return motion_params
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getmotion = pe.Node(niu.Function(input_names=["flirt_out_mats"],
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output_names=["motion_params"],
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function=get_flirt_motion_parameters),
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name="get_motion_parameters",iterfield="flirt_out_mats")
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wf.connect(flirt, "out_matrix_file", getmotion, "flirt_out_mats")
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from nipype.algorithms.rapidart import ArtifactDetect
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art = pe.Node(interface=ArtifactDetect(), name="art")
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art.inputs.use_differences = [True, True]
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art.inputs.save_plot=False
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art.inputs.use_norm = True
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art.inputs.norm_threshold = 3
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art.inputs.zintensity_threshold = 9
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art.inputs.mask_type = 'spm_global'
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art.inputs.parameter_source = 'FSL'
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wf.connect(getmotion, "motion_params", art, "realignment_parameters")
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wf.connect(outputspec, "dmri_corrected", art, "realigned_files")
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datasink = pe.Node(nio.DataSink(),name="sinker")
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datasink.inputs.base_directory = sink_dir
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datasink.inputs.substitutions = [("vol0000_flirt_merged.nii.gz", dwi_filename+'_corrected.nii.gz'),
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("stats.vol0000_flirt_merged.txt", dwi_filename+".motion.txt"),
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("derivatives/dti", "derivatives/{}/dti".format(bids_subject_name))]
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wf.connect(art, "statistic_files", datasink, "dti.@artstat")
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wf.connect(outputspec, "dmri_corrected", datasink, "dti.@corrected")
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wf.connect(outputspec,"bvec_rotated", datasink, "dti.@rotated")
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wf.base_dir = working_dir
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wf.run()
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from glob import glob
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import os
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dmri_corrected = glob(os.path.join(sink_dir, 'dti', '*.nii.gz'))[0]
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bvec_rotated = glob(os.path.join(sink_dir, 'dti', '*.bvec'))[0]
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motion_outliers = glob(os.path.join(sink_dir, 'dti', '*.txt'))[0]
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return dmri_corrected, bvec_rotated, motion_outliers

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