General purpose neuroimaging conda environment

neuro_jupyter.yml

name: neuro
channels:
  - conda-forge
  - defaults
dependencies:
  - ca-certificates=2019.9.11=hecc5488_0
  - certifi=2019.9.11=py37_0
  - dbus=1.13.6=he372182_0
  - dcm2niix=1.0.20190902=hc9558a2_0
  - fontconfig=2.13.1=h86ecdb6_1001
  - gettext=0.19.8.1=hc5be6a0_1002
  - glib=2.58.3=h6f030ca_1002
  - gst-plugins-base=1.14.5=h0935bb2_0
  - gstreamer=1.14.5=h36ae1b5_0
  - icu=64.2=he1b5a44_1
  - jpeg=9c=h14c3975_1001
  - libiconv=1.15=h516909a_1005
  - libuuid=2.32.1=h14c3975_1000
  - libuv=1.33.1=h516909a_0
  - matplotlib=3.1.1=py37_1
  - matplotlib-base=3.1.1=py37he7580a8_1
  - nodejs=12.13.0=h10a4023_0
  - openssl=1.1.1c=h516909a_0
  - qt=5.9.7=h0c104cb_3
  - tk=8.6.9=hed695b0_1003
  - _libgcc_mutex=0.1=main
  - atomicwrites=1.3.0=py37_1
  - attrs=19.3.0=py_0
  - backcall=0.1.0=py37_0
  - blas=1.0=mkl
  - bleach=3.1.0=py37_0
  - cloudpickle=1.2.2=py_0
  - cycler=0.10.0=py37_0
  - cytoolz=0.10.0=py37h7b6447c_0
  - dask-core=2.6.0=py_0
  - decorator=4.4.0=py37_1
  - defusedxml=0.6.0=py_0
  - entrypoints=0.3=py37_0
  - expat=2.2.6=he6710b0_0
  - freetype=2.9.1=h8a8886c_1
  - gmp=6.1.2=h6c8ec71_1
  - imageio=2.6.1=py37_0
  - importlib_metadata=0.23=py37_0
  - intel-openmp=2019.4=243
  - ipykernel=5.1.2=py37h39e3cac_0
  - ipython=7.8.0=py37h39e3cac_0
  - ipython_genutils=0.2.0=py37_0
  - jedi=0.15.1=py37_0
  - jinja2=2.10.3=py_0
  - joblib=0.13.2=py37_0
  - json5=0.8.5=py_0
  - jsonschema=3.1.1=py37_0
  - jupyter_client=5.3.4=py37_0
  - jupyter_core=4.6.0=py37_0
  - jupyterlab=1.1.4=pyhf63ae98_0
  - jupyterlab_server=1.0.6=py_0
  - kiwisolver=1.1.0=py37he6710b0_0
  - libedit=3.1.20181209=hc058e9b_0
  - libffi=3.2.1=hd88cf55_4
  - libgcc-ng=9.1.0=hdf63c60_0
  - libgfortran-ng=7.3.0=hdf63c60_0
  - libpng=1.6.37=hbc83047_0
  - libsodium=1.0.16=h1bed415_0
  - libstdcxx-ng=9.1.0=hdf63c60_0
  - libtiff=4.0.10=h2733197_2
  - libxcb=1.13=h1bed415_1
  - libxml2=2.9.9=hea5a465_1
  - markupsafe=1.1.1=py37h7b6447c_0
  - mistune=0.8.4=py37h7b6447c_0
  - mkl=2019.4=243
  - mkl-service=2.3.0=py37he904b0f_0
  - mkl_fft=1.0.14=py37ha843d7b_0
  - mkl_random=1.1.0=py37hd6b4f25_0
  - more-itertools=7.2.0=py37_0
  - nb_conda=2.2.1=py37_0
  - nb_conda_kernels=2.2.2=py37_0
  - nbconvert=5.6.0=py37_1
  - nbformat=4.4.0=py37_0
  - ncurses=6.1=he6710b0_1
  - networkx=2.4=py_0
  - notebook=6.0.1=py37_0
  - numpy=1.17.2=py37haad9e8e_0
  - numpy-base=1.17.2=py37hde5b4d6_0
  - olefile=0.46=py37_0
  - packaging=19.2=py_0
  - pandas=0.25.2=py37he6710b0_0
  - pandoc=2.2.3.2=0
  - pandocfilters=1.4.2=py37_1
  - parso=0.5.1=py_0
  - patsy=0.5.1=py37_0
  - pcre=8.43=he6710b0_0
  - pexpect=4.7.0=py37_0
  - pickleshare=0.7.5=py37_0
  - pillow=6.2.0=py37h34e0f95_0
  - pip=19.3.1=py37_0
  - pluggy=0.13.0=py37_0
  - prometheus_client=0.7.1=py_0
  - prompt_toolkit=2.0.10=py_0
  - ptyprocess=0.6.0=py37_0
  - py=1.8.0=py37_0
  - pygments=2.4.2=py_0
  - pyparsing=2.4.2=py_0
  - pyqt=5.9.2=py37h05f1152_2
  - pyrsistent=0.15.4=py37h7b6447c_0
  - pytest=5.0.1=py37_0
  - python=3.7.4=h265db76_1
  - python-dateutil=2.8.0=py37_0
  - pytz=2019.3=py_0
  - pywavelets=1.1.1=py37h7b6447c_0
  - pyzmq=18.1.0=py37he6710b0_0
  - readline=7.0=h7b6447c_5
  - scikit-image=0.15.0=py37he6710b0_0
  - scikit-learn=0.21.3=py37hd81dba3_0
  - scipy=1.3.1=py37h7c811a0_0
  - seaborn=0.9.0=py37_0
  - send2trash=1.5.0=py37_0
  - setuptools=41.4.0=py37_0
  - sip=4.19.8=py37hf484d3e_0
  - six=1.12.0=py37_0
  - sqlite=3.30.1=h7b6447c_0
  - statsmodels=0.10.1=py37hdd07704_0
  - terminado=0.8.2=py37_0
  - testpath=0.4.2=py37_0
  - toolz=0.10.0=py_0
  - tornado=6.0.3=py37h7b6447c_0
  - traitlets=4.3.3=py37_0
  - wcwidth=0.1.7=py37_0
  - webencodings=0.5.1=py37_1
  - wheel=0.33.6=py37_0
  - xz=5.2.4=h14c3975_4
  - zeromq=4.3.1=he6710b0_3
  - zipp=0.6.0=py_0
  - zlib=1.2.11=h7b6447c_3
  - zstd=1.3.7=h0b5b093_0
  -pip:
    - heudiconv==0.5.4
    - nibabel==2.5.1      
    - nilearn==0.5.2  
    - pybids==0.9.4