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Mambaforge migration #680

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mathieuboudreau
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@mathieuboudreau mathieuboudreau commented Sep 14, 2022

Checklist

  • I've given this PR a concise, self-descriptive, and meaningful title
  • I've linked relevant issues in the PR body
  • I've applied the relevant labels to this PR
  • I've added relevant tests for my contribution
  • I've updated the documentation and/or added correct docstrings
  • I've assigned a reviewer
  • I've consulted ADS's internal developer documentation to ensure my contribution is in line with any relevant design decisions

Description

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#677

@mathieuboudreau mathieuboudreau marked this pull request as draft September 14, 2022 01:57
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coveralls commented Sep 15, 2022

Pull Request Test Coverage Report for Build 3394141161

  • 0 of 0 changed or added relevant lines in 0 files are covered.
  • No unchanged relevant lines lost coverage.
  • Overall coverage remained the same at 89.425%

Totals Coverage Status
Change from base Build 3380131605: 0.0%
Covered Lines: 1150
Relevant Lines: 1286

💛 - Coveralls

@mathieuboudreau
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@jcohenadad I was able to update our Github Actions file to use mamba during the CI tests, and I tested a mamba installation locally on my Mac and the tests/FSLeyes ran succesfully.

See here for full installation and test log:


Last login: Thu Sep 15 07:57:59 on ttys002
-------- freesurfer-darwin-macOS-7.2.0-20210713-aa8f76b --------
Setting up environment for FreeSurfer/FS-FAST (and FSL)
FREESURFER_HOME   /Applications/freesurfer/7.2.0
FSFAST_HOME       /Applications/freesurfer/7.2.0/fsfast
FSF_OUTPUT_FORMAT nii.gz
SUBJECTS_DIR      /Applications/freesurfer/7.2.0/subjects
MNI_DIR           /Applications/freesurfer/7.2.0/mni
FSL_DIR           /usr/local/fsl
(base) mathieuboudreau@Mathieus-MacBook-Pro ~ % cd neuropoly/github 
(base) mathieuboudreau@Mathieus-MacBook-Pro github % git clone https://github.com/neuropoly/axondeepseg.git axondeepseg_mamba
Cloning into 'axondeepseg_mamba'...
remote: Enumerating objects: 6582, done.
remote: Counting objects: 100% (565/565), done.
remote: Compressing objects: 100% (221/221), done.
remote: Total 6582 (delta 396), reused 476 (delta 337), pack-reused 6017
Receiving objects: 100% (6582/6582), 151.11 MiB | 6.98 MiB/s, done.
Resolving deltas: 100% (4521/4521), done.
(base) mathieuboudreau@Mathieus-MacBook-Pro github % cd axondeepseg_mamba 
(base) mathieuboudreau@Mathieus-MacBook-Pro axondeepseg_mamba % mamba env create -n ads_mamba
pkgs/main/noarch         [====================] (00m:00s) Done
pkgs/r/osx-64            [====================] (00m:00s) Done
pkgs/r/noarch            [====================] (00m:00s) Done
pkgs/main/osx-64         [====================] (00m:01s) Done
conda-forge/noarch       [====================] (00m:03s) Done
conda-forge/osx-64       [====================] (00m:06s) Done


Looking for: ['python=3.8', 'nibabel=3.2', 'fsleyes', 'h5py=2.10.0', 'numpy', 'scipy', 'scikit-learn=1.0.1', 'scikit-image=0.18.3', 'tabulate', 'pandas', 'matplotlib=3.3.4', 'mpld3', 'tqdm', 'requests', 'pillow!=9.0.0', 'imageio', 'pytest', 'pytest-cov', 'prettytable', 'raven', 'jupyter', 'openpyxl', 'pip']


Transaction

  Prefix: /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba

  Updating specs:

   - python==3.8
   - nibabel==3.2
   - fsleyes
   - h5py==2.10.0
   - numpy
   - scipy
   - scikit-learn==1.0.1
   - scikit-image==0.18.3
   - tabulate
   - pandas
   - matplotlib==3.3.4
   - mpld3
   - tqdm
   - requests
   - pillow !=9.0.0
   - imageio
   - pytest
   - pytest-cov
   - prettytable
   - raven
   - jupyter
   - openpyxl
   - pip


  Package                             Version  Build                   Channel                  Size
──────────────────────────────────────────────────────────────────────────────────────────────────────
  Install:
──────────────────────────────────────────────────────────────────────────────────────────────────────

  alabaster                            0.7.12  py_0                    conda-forge/noarch     Cached
  aom                                   3.4.0  hb486fe8_1              conda-forge/osx-64     Cached
  appdirs                               1.4.4  pyh9f0ad1d_0            conda-forge/noarch     Cached
  appnope                               0.1.3  pyhd8ed1ab_0            conda-forge/noarch     Cached
  argon2-cffi                          21.3.0  pyhd8ed1ab_0            conda-forge/noarch     Cached
  argon2-cffi-bindings                 21.2.0  py38hed1de0f_2          conda-forge/osx-64     Cached
  asttokens                             2.0.8  pyhd8ed1ab_0            conda-forge/noarch     Cached
  attrs                                22.1.0  pyh71513ae_1            conda-forge/noarch     Cached
  babel                                2.10.3  pyhd8ed1ab_0            conda-forge/noarch     Cached
  backcall                              0.2.0  pyh9f0ad1d_0            conda-forge/noarch     Cached
  backports                               1.0  py_2                    conda-forge/noarch     Cached
  backports.functools_lru_cache         1.6.4  pyhd8ed1ab_0            conda-forge/noarch     Cached
  beautifulsoup4                       4.11.1  pyha770c72_0            conda-forge/noarch     Cached
  bleach                                5.0.1  pyhd8ed1ab_0            conda-forge/noarch     Cached
  blosc                                1.21.1  h97e831e_3              conda-forge/osx-64     Cached
  brotli                                1.0.9  h5eb16cf_7              conda-forge/osx-64     Cached
  brotli-bin                            1.0.9  h5eb16cf_7              conda-forge/osx-64     Cached
  brotlipy                              0.7.0  py38hed1de0f_1004       conda-forge/osx-64     Cached
  brunsli                                 0.1  hb1e8313_0              conda-forge/osx-64     179 KB
  bzip2                                 1.0.8  hc929b4f_4              conda-forge/osx-64     155 KB
  c-ares                               1.18.1  h0d85af4_0              conda-forge/osx-64     Cached
  c-blosc2                              2.3.1  had5f71b_0              conda-forge/osx-64     Cached
  ca-certificates                   2022.9.14  h033912b_0              conda-forge/osx-64     Cached
  certifi                           2022.9.14  pyhd8ed1ab_0            conda-forge/noarch     Cached
  cffi                                 1.15.1  py38h86886aa_0          conda-forge/osx-64     Cached
  cfitsio                               4.1.0  h2c97ad1_0              conda-forge/osx-64     Cached
  charls                                2.3.4  he49afe7_0              conda-forge/osx-64     Cached
  charset-normalizer                    2.1.1  pyhd8ed1ab_0            conda-forge/noarch     Cached
  click                                 8.1.3  py38h50d1736_0          conda-forge/osx-64     Cached
  cloudpickle                           2.2.0  pyhd8ed1ab_0            conda-forge/noarch      25 KB
  colorama                              0.4.5  pyhd8ed1ab_0            conda-forge/noarch     Cached
  commonmark                            0.9.1  py_0                    conda-forge/noarch     Cached
  contextlib2                          21.6.0  pyhd8ed1ab_0            conda-forge/noarch     Cached
  coverage                              6.4.4  py38h35d34b1_0          conda-forge/osx-64     Cached
  cryptography                         37.0.4  py38h0f8513e_0          conda-forge/osx-64     Cached
  cycler                               0.11.0  pyhd8ed1ab_0            conda-forge/noarch     Cached
  cytoolz                              0.12.0  py38h0dd4459_0          conda-forge/osx-64     Cached
  dask-core                          2022.9.0  pyhd8ed1ab_0            conda-forge/noarch     850 KB
  dataclasses                             0.8  pyhc8e2a94_3            conda-forge/noarch     Cached
  dav1d                                 1.0.0  hac89ed1_1              conda-forge/osx-64     Cached
  dcm2niix                       1.0.20220720  h4dcc89e_0              conda-forge/osx-64     Cached
  debugpy                               1.6.3  py38hd331d03_0          conda-forge/osx-64     Cached
  decorator                             5.1.1  pyhd8ed1ab_0            conda-forge/noarch     Cached
  defusedxml                            0.7.1  pyhd8ed1ab_0            conda-forge/noarch     Cached
  dill                                0.3.5.1  pyhd8ed1ab_0            conda-forge/noarch     Cached
  docutils                             0.17.1  py38h50d1736_2          conda-forge/osx-64     761 KB
  entrypoints                             0.4  pyhd8ed1ab_0            conda-forge/noarch     Cached
  et_xmlfile                            1.0.1  py_1001                 conda-forge/noarch     Cached
  executing                             1.0.0  pyhd8ed1ab_0            conda-forge/noarch     Cached
  expat                                 2.4.8  h96cf925_0              conda-forge/osx-64     Cached
  file-tree                             1.1.0  pyhd8ed1ab_0            conda-forge/noarch     Cached
  file-tree-fsl                         0.2.1  pyhd8ed1ab_0            conda-forge/noarch     Cached
  flit-core                             3.7.1  pyhd8ed1ab_0            conda-forge/noarch     Cached
  freetype                             2.12.1  h3f81eb7_0              conda-forge/osx-64     Cached
  fsleyes                               1.5.0  py38h50d1736_0          conda-forge/osx-64     Cached
  fsleyes-props                         1.8.2  pyhd8ed1ab_0            conda-forge/noarch     Cached
  fsleyes-widgets                      0.12.3  pyhd8ed1ab_0            conda-forge/noarch     Cached
  fslpy                                3.10.0  pyhd8ed1ab_0            conda-forge/noarch     Cached
  fsspec                             2022.8.2  pyhd8ed1ab_0            conda-forge/noarch     Cached
  future                               0.18.2  py38h50d1736_5          conda-forge/osx-64     Cached
  gettext                            0.19.8.1  hd1a6beb_1008           conda-forge/osx-64     Cached
  giflib                                5.2.1  hbcb3906_2              conda-forge/osx-64     Cached
  glib                                 2.72.1  h2292cb8_0              conda-forge/osx-64     Cached
  glib-tools                           2.72.1  h2292cb8_0              conda-forge/osx-64     Cached
  gst-plugins-base                     1.20.3  h37e1711_1              conda-forge/osx-64       2 MB
  gstreamer                            1.20.3  h1d18e73_1              conda-forge/osx-64       2 MB
  h5py                                 2.10.0  nompi_py38h9a16e60_106  conda-forge/osx-64     Cached
  hdf5                                 1.10.6  nompi_hc5d9132_1114     conda-forge/osx-64     Cached
  icu                                    70.1  h96cf925_0              conda-forge/osx-64     Cached
  idna                                    3.3  pyhd8ed1ab_0            conda-forge/noarch     Cached
  imagecodecs                        2022.8.8  py38h7f92502_5          conda-forge/osx-64       2 MB
  imageio                              2.21.3  pyhfa7a67d_0            conda-forge/noarch       3 MB
  imagesize                             1.4.1  pyhd8ed1ab_0            conda-forge/noarch     Cached
  importlib-metadata                   4.11.4  py38h50d1736_0          conda-forge/osx-64     Cached
  importlib_resources                   5.9.0  pyhd8ed1ab_0            conda-forge/noarch     Cached
  indexed_gzip                          1.7.0  py38h91b5f70_0          conda-forge/osx-64     539 KB
  iniconfig                             1.1.1  pyh9f0ad1d_0            conda-forge/noarch     Cached
  ipykernel                            6.14.0  py38h60dac5d_0          conda-forge/osx-64     186 KB
  ipython                               8.4.0  py38h50d1736_0          conda-forge/osx-64     Cached
  ipython_genutils                      0.2.0  py_1                    conda-forge/noarch     Cached
  ipywidgets                            8.0.2  pyhd8ed1ab_1            conda-forge/noarch     109 KB
  isodate                               0.6.1  pyhd8ed1ab_0            conda-forge/noarch     Cached
  jedi                                 0.18.1  py38h50d1736_1          conda-forge/osx-64     Cached
  jinja2                                3.1.2  pyhd8ed1ab_1            conda-forge/noarch     Cached
  joblib                                1.1.0  pyhd8ed1ab_0            conda-forge/noarch     Cached
  jpeg                                     9e  hac89ed1_2              conda-forge/osx-64     Cached
  jsonschema                           4.16.0  pyhd8ed1ab_0            conda-forge/noarch      65 KB
  jupyter                               1.0.0  py38h50d1736_7          conda-forge/osx-64     Cached
  jupyter_client                        7.3.5  pyhd8ed1ab_0            conda-forge/noarch     Cached
  jupyter_console                       6.4.4  pyhd8ed1ab_0            conda-forge/noarch     Cached
  jupyter_core                         4.11.1  py38h50d1736_0          conda-forge/osx-64     Cached
  jupyterlab_pygments                   0.2.2  pyhd8ed1ab_0            conda-forge/noarch     Cached
  jupyterlab_widgets                    3.0.3  pyhd8ed1ab_0            conda-forge/noarch     222 KB
  jxrlib                                  1.1  h35c211d_2              conda-forge/osx-64     Cached
  kiwisolver                            1.4.4  py38hf58141a_0          conda-forge/osx-64     Cached
  krb5                                 1.19.3  hb49756b_0              conda-forge/osx-64     Cached
  lcms2                                  2.12  h577c468_0              conda-forge/osx-64     Cached
  lerc                                  4.0.0  hb486fe8_0              conda-forge/osx-64     Cached
  libaec                                1.0.6  he49afe7_0              conda-forge/osx-64     Cached
  libavif                              0.10.1  hac89ed1_1              conda-forge/osx-64     Cached
  libblas                               3.9.0  16_osx64_openblas       conda-forge/osx-64     Cached
  libbrotlicommon                       1.0.9  h5eb16cf_7              conda-forge/osx-64     Cached
  libbrotlidec                          1.0.9  h5eb16cf_7              conda-forge/osx-64     Cached
  libbrotlienc                          1.0.9  h5eb16cf_7              conda-forge/osx-64     Cached
  libcblas                              3.9.0  16_osx64_openblas       conda-forge/osx-64     Cached
  libclang                             14.0.6  default_h55ffa42_0      conda-forge/osx-64     Cached
  libclang13                           14.0.6  default_hb5731bd_0      conda-forge/osx-64     Cached
  libcurl                              7.83.1  h372c54d_0              conda-forge/osx-64     Cached
  libcxx                               14.0.6  hce7ea42_0              conda-forge/osx-64     Cached
  libdeflate                             1.14  hb7f2c08_0              conda-forge/osx-64      85 KB
  libedit                        3.1.20191231  hed1e85f_2              conda-forge/osx-64     103 KB
  libev                                  4.33  haf1e3a3_1              conda-forge/osx-64     Cached
  libffi                                3.4.2  h0d85af4_5              conda-forge/osx-64     Cached
  libgfortran                           5.0.0  11_3_0_h97931a8_25      conda-forge/osx-64     149 KB
  libgfortran5                         11.3.0  h082f757_25             conda-forge/osx-64     Cached
  libglib                              2.72.1  hfbcb929_0              conda-forge/osx-64     Cached
  libiconv                               1.16  haf1e3a3_0              conda-forge/osx-64     Cached
  liblapack                             3.9.0  16_osx64_openblas       conda-forge/osx-64     Cached
  libllvm14                            14.0.6  h41df66c_0              conda-forge/osx-64     Cached
  libnghttp2                           1.47.0  h7cbc4dc_1              conda-forge/osx-64     Cached
  libogg                                1.3.4  h35c211d_1              conda-forge/osx-64     Cached
  libopenblas                          0.3.21  openmp_h429af6e_3       conda-forge/osx-64     Cached
  libopus                               1.3.1  hc929b4f_1              conda-forge/osx-64     Cached
  libpng                               1.6.37  h5481273_4              conda-forge/osx-64     Cached
  libpq                                  14.5  h76c7896_0              conda-forge/osx-64     Cached
  libsodium                            1.0.18  hbcb3906_1              conda-forge/osx-64     Cached
  libspatialindex                       1.9.3  he49afe7_4              conda-forge/osx-64     Cached
  libsqlite                            3.39.3  ha978bb4_0              conda-forge/osx-64     871 KB
  libssh2                              1.10.0  h7535e13_3              conda-forge/osx-64     Cached
  libtiff                               4.4.0  hdb44e8a_4              conda-forge/osx-64     604 KB
  libvorbis                             1.3.7  h046ec9c_0              conda-forge/osx-64     Cached
  libwebp-base                          1.2.4  h775f41a_0              conda-forge/osx-64     Cached
  libxcb                                 1.13  h0d85af4_1004           conda-forge/osx-64     Cached
  libxml2                              2.9.14  hea49891_4              conda-forge/osx-64     Cached
  libxslt                              1.1.35  heaa0ce8_0              conda-forge/osx-64     Cached
  libzlib                              1.2.12  hfd90126_3              conda-forge/osx-64      65 KB
  libzopfli                             1.0.3  h046ec9c_0              conda-forge/osx-64     Cached
  llvm-openmp                          14.0.4  ha654fa7_0              conda-forge/osx-64     Cached
  locket                                1.0.0  pyhd8ed1ab_0            conda-forge/noarch     Cached
  lxml                                  4.9.1  py38h0dd4459_0          conda-forge/osx-64     Cached
  lz4-c                                 1.9.3  he49afe7_1              conda-forge/osx-64     Cached
  markupsafe                            2.1.1  py38hed1de0f_1          conda-forge/osx-64     Cached
  matplotlib                            3.3.4  py38h50d1736_0          conda-forge/osx-64     Cached
  matplotlib-base                       3.3.4  py38hb24f337_0          conda-forge/osx-64     Cached
  matplotlib-inline                     0.1.6  pyhd8ed1ab_0            conda-forge/noarch     Cached
  mistune                               2.0.4  pyhd8ed1ab_0            conda-forge/noarch     Cached
  mpld3                                 0.5.8  pyhd8ed1ab_0            conda-forge/noarch     Cached
  mysql-common                         8.0.30  h7ebae80_1              conda-forge/osx-64     Cached
  mysql-libs                           8.0.30  hc37e033_1              conda-forge/osx-64     Cached
  nbclient                              0.6.8  pyhd8ed1ab_0            conda-forge/noarch      65 KB
  nbconvert                             7.0.0  pyhd8ed1ab_0            conda-forge/noarch     Cached
  nbconvert-core                        7.0.0  pyhd8ed1ab_0            conda-forge/noarch     Cached
  nbconvert-pandoc                      7.0.0  pyhd8ed1ab_0            conda-forge/noarch     Cached
  nbformat                              5.5.0  pyhd8ed1ab_0            conda-forge/noarch     105 KB
  ncurses                                 6.3  h96cf925_1              conda-forge/osx-64     Cached
  nest-asyncio                          1.5.5  pyhd8ed1ab_0            conda-forge/noarch     Cached
  networkx                              2.8.6  pyhd8ed1ab_0            conda-forge/noarch     Cached
  nibabel                               3.2.2  pyhd8ed1ab_0            conda-forge/noarch     Cached
  notebook                             6.4.12  pyha770c72_0            conda-forge/noarch     Cached
  nspr                                   4.32  hcd9eead_1              conda-forge/osx-64     Cached
  nss                                    3.78  ha8197d3_0              conda-forge/osx-64     Cached
  numpy                                1.23.3  py38h4289407_0          conda-forge/osx-64       7 MB
  openjpeg                              2.5.0  h5d0d7b0_1              conda-forge/osx-64     Cached
  openpyxl                             3.0.10  py38hef030d1_1          conda-forge/osx-64     552 KB
  openssl                              1.1.1q  hfe4f2af_0              conda-forge/osx-64     Cached
  packaging                              21.3  pyhd8ed1ab_0            conda-forge/noarch     Cached
  pandas                                1.4.4  py38h5e0dbaf_0          conda-forge/osx-64     Cached
  pandoc                               2.19.2  h694c41f_0              conda-forge/osx-64     Cached
  pandocfilters                         1.5.0  pyhd8ed1ab_0            conda-forge/noarch     Cached
  parse                                1.19.0  pyh44b312d_0            conda-forge/noarch     Cached
  parso                                 0.8.3  pyhd8ed1ab_0            conda-forge/noarch     Cached
  partd                                 1.3.0  pyhd8ed1ab_0            conda-forge/noarch     Cached
  pathlib2                        2.3.7.post1  py38h50d1736_1          conda-forge/osx-64     Cached
  pcre                                   8.45  he49afe7_0              conda-forge/osx-64     Cached
  pexpect                               4.8.0  py38h32f6830_1          conda-forge/osx-64      79 KB
  pickleshare                           0.7.5  py38h32f6830_1002       conda-forge/osx-64      13 KB
  pillow                                9.2.0  py38h7bff4d5_2          conda-forge/osx-64     Cached
  pip                                  22.2.2  pyhd8ed1ab_0            conda-forge/noarch     Cached
  pkgutil-resolve-name                 1.3.10  pyhd8ed1ab_0            conda-forge/noarch     Cached
  pluggy                                1.0.0  py38h50d1736_3          conda-forge/osx-64     Cached
  ply                                    3.11  py_1                    conda-forge/noarch     Cached
  pooch                                 1.6.0  pyhd8ed1ab_0            conda-forge/noarch     Cached
  prettytable                           3.4.1  pyhd8ed1ab_0            conda-forge/noarch      27 KB
  progressbar2                          4.0.0  pyhd8ed1ab_0            conda-forge/noarch     Cached
  prometheus_client                    0.14.1  pyhd8ed1ab_0            conda-forge/noarch     Cached
  prompt-toolkit                       3.0.31  pyha770c72_0            conda-forge/noarch     254 KB
  prompt_toolkit                       3.0.31  hd8ed1ab_0              conda-forge/noarch       5 KB
  psutil                                5.9.2  py38hef030d1_0          conda-forge/osx-64     355 KB
  pthread-stubs                           0.4  hc929b4f_1001           conda-forge/osx-64     Cached
  ptyprocess                            0.7.0  pyhd3deb0d_0            conda-forge/noarch     Cached
  pure_eval                             0.2.2  pyhd8ed1ab_0            conda-forge/noarch     Cached
  py                                   1.11.0  pyh6c4a22f_0            conda-forge/noarch     Cached
  pycparser                              2.21  pyhd8ed1ab_0            conda-forge/noarch     Cached
  pydicom                               2.3.0  pyh6c4a22f_0            conda-forge/noarch     Cached
  pygments                             2.13.0  pyhd8ed1ab_0            conda-forge/noarch     Cached
  pyopengl                              3.1.6  pyhd8ed1ab_1            conda-forge/noarch     Cached
  pyopenssl                            22.0.0  pyhd8ed1ab_0            conda-forge/noarch     Cached
  pyparsing                             2.4.7  pyhd8ed1ab_1            conda-forge/noarch     Cached
  pypubsub                              4.0.3  py_0                    conda-forge/noarch     Cached
  pyqt                                 5.15.7  py38h2bdaceb_0          conda-forge/osx-64     Cached
  pyqt5-sip                           12.11.0  py38h2c8b277_0          conda-forge/osx-64     Cached
  pyrsistent                           0.18.1  py38hed1de0f_1          conda-forge/osx-64     Cached
  pysocks                               1.7.1  py38h50d1736_5          conda-forge/osx-64     Cached
  pytest                                7.1.3  py38h50d1736_0          conda-forge/osx-64     462 KB
  pytest-cov                            3.0.0  pyhd8ed1ab_0            conda-forge/noarch     Cached
  python                               3.8.13  h394c593_0_cpython      conda-forge/osx-64     Cached
  python-dateutil                       2.8.2  pyhd8ed1ab_0            conda-forge/noarch     Cached
  python-fastjsonschema                2.16.1  pyhd8ed1ab_0            conda-forge/noarch     Cached
  python-utils                          3.3.3  pyhd8ed1ab_0            conda-forge/noarch     Cached
  python.app                              1.4  py38h96a0964_0          conda-forge/osx-64     Cached
  python_abi                              3.8  2_cp38                  conda-forge/osx-64     Cached
  pytz                               2022.2.1  pyhd8ed1ab_0            conda-forge/noarch     Cached
  pywavelets                            1.3.0  py38h4277f33_1          conda-forge/osx-64     Cached
  pyyaml                                  6.0  py38hed1de0f_4          conda-forge/osx-64     Cached
  pyzmq                                23.2.1  py38hde384ec_0          conda-forge/osx-64     Cached
  qt-main                              5.15.6  he04cef1_0              conda-forge/osx-64      52 MB
  qtconsole                             5.3.2  pyhd8ed1ab_0            conda-forge/noarch     Cached
  qtconsole-base                        5.3.2  pyha770c72_0            conda-forge/noarch     Cached
  qtpy                                  2.2.0  pyhd8ed1ab_0            conda-forge/noarch     Cached
  raven                                6.10.0  py_0                    conda-forge/noarch     Cached
  readline                              8.1.2  h3899abd_0              conda-forge/osx-64     Cached
  requests                             2.28.1  pyhd8ed1ab_1            conda-forge/noarch     Cached
  rich                                 12.5.1  pyhd8ed1ab_0            conda-forge/noarch     Cached
  rtree                                 1.0.0  py38hc59ffc2_1          conda-forge/osx-64     Cached
  scikit-image                         0.18.3  py38ha53d530_1          conda-forge/osx-64     Cached
  scikit-learn                          1.0.1  py38h37f3bb3_3          conda-forge/osx-64     Cached
  scipy                                 1.9.1  py38hb5a21b1_0          conda-forge/osx-64     Cached
  send2trash                            1.8.0  pyhd8ed1ab_0            conda-forge/noarch     Cached
  setuptools                           65.3.0  py38h50d1736_0          conda-forge/osx-64       1 MB
  sip                                   6.6.2  py38h1c67a95_0          conda-forge/osx-64     Cached
  six                                  1.16.0  pyh6c4a22f_0            conda-forge/noarch     Cached
  snappy                                1.1.9  h6e38e02_1              conda-forge/osx-64     Cached
  snowballstemmer                       2.2.0  pyhd8ed1ab_0            conda-forge/noarch     Cached
  soupsieve                       2.3.2.post1  pyhd8ed1ab_0            conda-forge/noarch     Cached
  sphinx                                5.1.1  pyhd8ed1ab_1            conda-forge/noarch     Cached
  sphinx_rtd_theme                      1.0.0  pyhd8ed1ab_0            conda-forge/noarch     Cached
  sphinxcontrib-applehelp               1.0.2  py_0                    conda-forge/noarch     Cached
  sphinxcontrib-devhelp                 1.0.2  py_0                    conda-forge/noarch     Cached
  sphinxcontrib-htmlhelp                2.0.0  pyhd8ed1ab_0            conda-forge/noarch     Cached
  sphinxcontrib-jsmath                  1.0.1  py_0                    conda-forge/noarch     Cached
  sphinxcontrib-qthelp                  1.0.3  py_0                    conda-forge/noarch     Cached
  sphinxcontrib-serializinghtml         1.1.5  pyhd8ed1ab_2            conda-forge/noarch     Cached
  sqlite                               3.39.3  h9ae0607_0              conda-forge/osx-64     875 KB
  stack_data                            0.5.0  pyhd8ed1ab_0            conda-forge/noarch     Cached
  tabulate                             0.8.10  pyhd8ed1ab_0            conda-forge/noarch     Cached
  terminado                            0.15.0  py38h50d1736_0          conda-forge/osx-64     Cached
  textual                              0.1.18  pyhd8ed1ab_1            conda-forge/noarch     Cached
  threadpoolctl                         3.1.0  pyh8a188c0_0            conda-forge/noarch     Cached
  tifffile                          2022.8.12  pyhd8ed1ab_0            conda-forge/noarch     Cached
  tinycss2                              1.1.1  pyhd8ed1ab_0            conda-forge/noarch     Cached
  tk                                   8.6.12  h5dbffcc_0              conda-forge/osx-64     Cached
  toml                                 0.10.2  pyhd8ed1ab_0            conda-forge/noarch     Cached
  tomli                                 2.0.1  pyhd8ed1ab_0            conda-forge/noarch     Cached
  toolz                                0.12.0  pyhd8ed1ab_0            conda-forge/noarch     Cached
  tornado                                 6.2  py38h0dd4459_0          conda-forge/osx-64     Cached
  tqdm                                 4.64.1  pyhd8ed1ab_0            conda-forge/noarch      82 KB
  traitlets                             5.4.0  pyhd8ed1ab_0            conda-forge/noarch      85 KB
  trimesh                              3.14.1  pyh1a96a4e_0            conda-forge/noarch     527 KB
  typing-extensions                     4.3.0  hd8ed1ab_0              conda-forge/noarch     Cached
  typing_extensions                     4.3.0  pyha770c72_0            conda-forge/noarch     Cached
  urllib3                             1.26.11  pyhd8ed1ab_0            conda-forge/noarch     Cached
  wcwidth                               0.2.5  pyh9f0ad1d_2            conda-forge/noarch     Cached
  webencodings                          0.5.1  py_1                    conda-forge/noarch     Cached
  wheel                                0.37.1  pyhd8ed1ab_0            conda-forge/noarch     Cached
  widgetsnbextension                    4.0.3  pyhd8ed1ab_0            conda-forge/noarch       2 MB
  wxnatpy                               0.4.0  pyhd8ed1ab_0            conda-forge/noarch     Cached
  wxpython                              4.1.1  py38he007270_7          conda-forge/osx-64     Cached
  xarray                             2022.6.0  pyhd8ed1ab_1            conda-forge/noarch     Cached
  xnat                                  0.4.2  pyhd8ed1ab_0            conda-forge/noarch     Cached
  xorg-libxau                           1.0.9  h35c211d_0              conda-forge/osx-64     Cached
  xorg-libxdmcp                         1.1.3  h35c211d_0              conda-forge/osx-64     Cached
  xz                                    5.2.6  h775f41a_0              conda-forge/osx-64     Cached
  yaml                                  0.2.5  h0d85af4_2              conda-forge/osx-64     Cached
  zeromq                                4.3.4  he49afe7_1              conda-forge/osx-64     Cached
  zfp                                   1.0.0  hb9aa9fd_1              conda-forge/osx-64     Cached
  zipp                                  3.8.1  pyhd8ed1ab_0            conda-forge/noarch     Cached
  zlib                                 1.2.12  hfd90126_3              conda-forge/osx-64      95 KB
  zlib-ng                               2.0.6  hac89ed1_0              conda-forge/osx-64     Cached
  zstd                                  1.5.2  hfa58983_4              conda-forge/osx-64     Cached

  Summary:

  Install: 279 packages

  Total download: 80 MB

──────────────────────────────────────────────────────────────────────────────────────────────────────


Downloading and Extracting Packages
brunsli-0.1          | 179 KB    | ############################################################################# | 100% 
numpy-1.23.3         | 6.8 MB    | ############################################################################# | 100% 
widgetsnbextension-4 | 1.6 MB    | ############################################################################# | 100% 
libtiff-4.4.0        | 604 KB    | ############################################################################# | 100% 
trimesh-3.14.1       | 527 KB    | ############################################################################# | 100% 
libgfortran-5.0.0    | 149 KB    | ############################################################################# | 100% 
nbclient-0.6.8       | 65 KB     | ############################################################################# | 100% 
gstreamer-1.20.3     | 1.8 MB    | ############################################################################# | 100% 
bzip2-1.0.8          | 155 KB    | ############################################################################# | 100% 
ipywidgets-8.0.2     | 109 KB    | ############################################################################# | 100% 
jsonschema-4.16.0    | 65 KB     | ############################################################################# | 100% 
pytest-7.1.3         | 462 KB    | ############################################################################# | 100% 
zlib-1.2.12          | 95 KB     | ############################################################################# | 100% 
nbformat-5.5.0       | 105 KB    | ############################################################################# | 100% 
libdeflate-1.14      | 85 KB     | ############################################################################# | 100% 
libsqlite-3.39.3     | 871 KB    | ############################################################################# | 100% 
traitlets-5.4.0      | 85 KB     | ############################################################################# | 100% 
gst-plugins-base-1.2 | 2.5 MB    | ############################################################################# | 100% 
psutil-5.9.2         | 355 KB    | ############################################################################# | 100% 
pickleshare-0.7.5    | 13 KB     | ############################################################################# | 100% 
pexpect-4.8.0        | 79 KB     | ############################################################################# | 100% 
cloudpickle-2.2.0    | 25 KB     | ############################################################################# | 100% 
dask-core-2022.9.0   | 850 KB    | ############################################################################# | 100% 
prompt_toolkit-3.0.3 | 5 KB      | ############################################################################# | 100% 
sqlite-3.39.3        | 875 KB    | ############################################################################# | 100% 
qt-main-5.15.6       | 51.8 MB   | ############################################################################# | 100% 
libedit-3.1.20191231 | 103 KB    | ############################################################################# | 100% 
prettytable-3.4.1    | 27 KB     | ############################################################################# | 100% 
imagecodecs-2022.8.8 | 2.2 MB    | ############################################################################# | 100% 
docutils-0.17.1      | 761 KB    | ############################################################################# | 100% 
ipykernel-6.14.0     | 186 KB    | ############################################################################# | 100% 
libzlib-1.2.12       | 65 KB     | ############################################################################# | 100% 
imageio-2.21.3       | 3.2 MB    | ############################################################################# | 100% 
jupyterlab_widgets-3 | 222 KB    | ############################################################################# | 100% 
setuptools-65.3.0    | 1.4 MB    | ############################################################################# | 100% 
openpyxl-3.0.10      | 552 KB    | ############################################################################# | 100% 
prompt-toolkit-3.0.3 | 254 KB    | ############################################################################# | 100% 
tqdm-4.64.1          | 82 KB     | ############################################################################# | 100% 
indexed_gzip-1.7.0   | 539 KB    | ############################################################################# | 100% 
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
Installing pip dependencies: - Ran pip subprocess with arguments:
['/Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/bin/python', '-m', 'pip', 'install', '-U', '-r', '/Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/condaenv.lk0bemse.requirements.txt']
Pip subprocess output:
Collecting opencv-contrib-python
  Using cached opencv_contrib_python-4.6.0.66-cp36-abi3-macosx_10_15_x86_64.whl (56.1 MB)
Collecting opencv-python-headless
  Using cached opencv_python_headless-4.6.0.66-cp36-abi3-macosx_10_15_x86_64.whl (46.4 MB)
Collecting protobuf==3.20.1
  Using cached protobuf-3.20.1-cp38-cp38-macosx_10_9_x86_64.whl (962 kB)
Collecting ivadomed~=2.9.6
  Using cached ivadomed-2.9.6-py3-none-any.whl (225 kB)
Requirement already satisfied: numpy>=1.14.5 in /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages (from opencv-contrib-python->-r /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/condaenv.lk0bemse.requirements.txt (line 1)) (1.23.3)
Collecting torch~=1.8.1
  Using cached torch-1.8.1-cp38-none-macosx_10_9_x86_64.whl (119.6 MB)
Requirement already satisfied: pyparsing<3,>=2.0.2 in /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages (from ivadomed~=2.9.6->-r /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/condaenv.lk0bemse.requirements.txt (line 4)) (2.4.7)
Requirement already satisfied: pillow>=7.0.0 in /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages (from ivadomed~=2.9.6->-r /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/condaenv.lk0bemse.requirements.txt (line 4)) (9.2.0)
Requirement already satisfied: scikit-image~=0.17 in /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages (from ivadomed~=2.9.6->-r /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/condaenv.lk0bemse.requirements.txt (line 4)) (0.18.3)
Requirement already satisfied: joblib~=1.0 in /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages (from ivadomed~=2.9.6->-r /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/condaenv.lk0bemse.requirements.txt (line 4)) (1.1.0)
Collecting tensorboard>=1.15.0
  Using cached tensorboard-2.10.0-py3-none-any.whl (5.9 MB)
Collecting torchvision~=0.9.1
  Using cached torchvision-0.9.1-cp38-cp38-macosx_10_9_x86_64.whl (13.2 MB)
Collecting pybids>=0.14.0
  Downloading pybids-0.15.3-py3-none-any.whl (14.9 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 14.9/14.9 MB 8.4 MB/s eta 0:00:00
Requirement already satisfied: scipy in /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages (from ivadomed~=2.9.6->-r /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/condaenv.lk0bemse.requirements.txt (line 4)) (1.9.1)
Requirement already satisfied: tqdm>=4.30 in /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages (from ivadomed~=2.9.6->-r /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/condaenv.lk0bemse.requirements.txt (line 4)) (4.64.1)
Collecting loguru~=0.5
  Using cached loguru-0.6.0-py3-none-any.whl (58 kB)
Collecting seaborn~=0.11
  Downloading seaborn-0.12.0-py3-none-any.whl (285 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 285.1/285.1 kB 6.8 MB/s eta 0:00:00
Collecting csv-diff>=1.0
  Using cached csv_diff-1.1-py3-none-any.whl (12 kB)
Requirement already satisfied: pandas~=1.1 in /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages (from ivadomed~=2.9.6->-r /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/condaenv.lk0bemse.requirements.txt (line 4)) (1.4.4)
Collecting wandb>=0.12.11
  Downloading wandb-0.13.3-py2.py3-none-any.whl (1.8 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.8/1.8 MB 7.8 MB/s eta 0:00:00
Requirement already satisfied: scikit-learn>=0.20.3 in /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages (from ivadomed~=2.9.6->-r /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/condaenv.lk0bemse.requirements.txt (line 4)) (1.0.1)
Collecting onnxruntime==1.7.0
  Using cached onnxruntime-1.7.0-cp38-cp38-macosx_10_12_x86_64.whl (4.7 MB)
Collecting torchio>=0.18.68
  Using cached torchio-0.18.84-py2.py3-none-any.whl (172 kB)
Requirement already satisfied: nibabel~=3.2 in /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages (from ivadomed~=2.9.6->-r /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/condaenv.lk0bemse.requirements.txt (line 4)) (3.2.2)
Requirement already satisfied: matplotlib>=3.3.0 in /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages (from ivadomed~=2.9.6->-r /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/condaenv.lk0bemse.requirements.txt (line 4)) (3.3.4)
Collecting dictdiffer
  Using cached dictdiffer-0.9.0-py2.py3-none-any.whl (16 kB)
Requirement already satisfied: click in /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages (from csv-diff>=1.0->ivadomed~=2.9.6->-r /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/condaenv.lk0bemse.requirements.txt (line 4)) (8.1.3)
Requirement already satisfied: cycler>=0.10 in /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages (from matplotlib>=3.3.0->ivadomed~=2.9.6->-r /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/condaenv.lk0bemse.requirements.txt (line 4)) (0.11.0)
Requirement already satisfied: kiwisolver>=1.0.1 in /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages (from matplotlib>=3.3.0->ivadomed~=2.9.6->-r /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/condaenv.lk0bemse.requirements.txt (line 4)) (1.4.4)
Requirement already satisfied: python-dateutil>=2.1 in /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages (from matplotlib>=3.3.0->ivadomed~=2.9.6->-r /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/condaenv.lk0bemse.requirements.txt (line 4)) (2.8.2)
Requirement already satisfied: setuptools in /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages (from nibabel~=3.2->ivadomed~=2.9.6->-r /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/condaenv.lk0bemse.requirements.txt (line 4)) (65.3.0)
Requirement already satisfied: packaging>=14.3 in /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages (from nibabel~=3.2->ivadomed~=2.9.6->-r /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/condaenv.lk0bemse.requirements.txt (line 4)) (21.3)
Requirement already satisfied: pytz>=2020.1 in /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages (from pandas~=1.1->ivadomed~=2.9.6->-r /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/condaenv.lk0bemse.requirements.txt (line 4)) (2022.2.1)
Collecting sqlalchemy<1.4.0.dev0
  Using cached SQLAlchemy-1.3.24-cp38-cp38-macosx_10_14_x86_64.whl (1.2 MB)
Collecting bids-validator
  Using cached bids_validator-1.9.8-py2.py3-none-any.whl (21 kB)
Collecting formulaic<0.4,>=0.2.4
  Using cached formulaic-0.3.4-py3-none-any.whl (68 kB)
Collecting num2words
  Using cached num2words-0.5.12-py3-none-any.whl (125 kB)
Requirement already satisfied: PyWavelets>=1.1.1 in /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages (from scikit-image~=0.17->ivadomed~=2.9.6->-r /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/condaenv.lk0bemse.requirements.txt (line 4)) (1.3.0)
Requirement already satisfied: imageio>=2.3.0 in /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages (from scikit-image~=0.17->ivadomed~=2.9.6->-r /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/condaenv.lk0bemse.requirements.txt (line 4)) (2.21.3)
Requirement already satisfied: networkx>=2.0 in /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages (from scikit-image~=0.17->ivadomed~=2.9.6->-r /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/condaenv.lk0bemse.requirements.txt (line 4)) (2.8.6)
Requirement already satisfied: tifffile>=2019.7.26 in /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages (from scikit-image~=0.17->ivadomed~=2.9.6->-r /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/condaenv.lk0bemse.requirements.txt (line 4)) (2022.8.12)
Requirement already satisfied: threadpoolctl>=2.0.0 in /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages (from scikit-learn>=0.20.3->ivadomed~=2.9.6->-r /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/condaenv.lk0bemse.requirements.txt (line 4)) (3.1.0)
Collecting grpcio>=1.24.3
  Using cached grpcio-1.48.1-cp38-cp38-macosx_10_10_x86_64.whl (4.5 MB)
Collecting markdown>=2.6.8
  Using cached Markdown-3.4.1-py3-none-any.whl (93 kB)
Collecting google-auth<3,>=1.6.3
  Using cached google_auth-2.11.0-py2.py3-none-any.whl (167 kB)
Collecting tensorboard-plugin-wit>=1.6.0
  Using cached tensorboard_plugin_wit-1.8.1-py3-none-any.whl (781 kB)
Collecting werkzeug>=1.0.1
  Using cached Werkzeug-2.2.2-py3-none-any.whl (232 kB)
Collecting absl-py>=0.4
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Installing collected packages: tensorboard-plugin-wit, SimpleITK, pyasn1, pathtools, docopt, dictdiffer, bids-validator, wrapt, werkzeug, torch, tensorboard-data-server, sqlalchemy, smmap, shortuuid, setproctitle, sentry-sdk, rsa, pyasn1-modules, protobuf, promise, opencv-python-headless, opencv-contrib-python, oauthlib, num2words, loguru, interface-meta, humanize, grpcio, docker-pycreds, csv-diff, cachetools, astor, absl-py, torchvision, requests-oauthlib, onnxruntime, markdown, google-auth, gitdb, Deprecated, torchio, seaborn, google-auth-oauthlib, GitPython, formulaic, wandb, tensorboard, pybids, ivadomed
Successfully installed Deprecated-1.2.13 GitPython-3.1.27 SimpleITK-2.2.0 absl-py-1.2.0 astor-0.8.1 bids-validator-1.9.8 cachetools-5.2.0 csv-diff-1.1 dictdiffer-0.9.0 docker-pycreds-0.4.0 docopt-0.6.2 formulaic-0.3.4 gitdb-4.0.9 google-auth-2.11.0 google-auth-oauthlib-0.4.6 grpcio-1.48.1 humanize-4.3.0 interface-meta-1.3.0 ivadomed-2.9.6 loguru-0.6.0 markdown-3.4.1 num2words-0.5.12 oauthlib-3.2.1 onnxruntime-1.7.0 opencv-contrib-python-4.6.0.66 opencv-python-headless-4.6.0.66 pathtools-0.1.2 promise-2.3 protobuf-3.20.1 pyasn1-0.4.8 pyasn1-modules-0.2.8 pybids-0.15.3 requests-oauthlib-1.3.1 rsa-4.9 seaborn-0.12.0 sentry-sdk-1.9.8 setproctitle-1.3.2 shortuuid-1.0.9 smmap-5.0.0 sqlalchemy-1.3.24 tensorboard-2.9.0 tensorboard-data-server-0.6.1 tensorboard-plugin-wit-1.8.1 torch-1.8.1 torchio-0.18.84 torchvision-0.9.1 wandb-0.13.3 werkzeug-2.2.2 wrapt-1.14.1
\ 
done
#
# To activate this environment, use
#
#     $ conda activate ads_mamba
#
# To deactivate an active environment, use
#
#     $ conda deactivate

(base) mathieuboudreau@Mathieus-MacBook-Pro axondeepseg_mamba % mamba activate ads_mamba
Use conda to activate / deactivate the environment.

    $ conda activate ads_mamba

(base) mathieuboudreau@Mathieus-MacBook-Pro axondeepseg_mamba % conda activate ads_mamba
(ads_mamba) mathieuboudreau@Mathieus-MacBook-Pro axondeepseg_mamba % pip install -e .
Obtaining file:https:///Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba
  Preparing metadata (setup.py) ... done
Installing collected packages: AxonDeepSeg
  Running setup.py develop for AxonDeepSeg
Successfully installed AxonDeepSeg-4.0.0
(ads_mamba) mathieuboudreau@Mathieus-MacBook-Pro axondeepseg_mamba % axondeepseg_test        

Computing the segmentation of axon and myelin on test image.
2022-09-15 08:52:10.577 | INFO     | ivadomed.config_manager:_display_differing_keys:153 - Adding the following keys to the configuration file
2022-09-15 08:52:10.579 | INFO     | ivadomed.config_manager:deep_dict_compare:44 -     wandb: {'wandb_api_key': '', 'project_name': 'my_project', 'group_name': 'my_group', 'run_name': 'run-1', 'log_grads_every': 100}
2022-09-15 08:52:10.579 | INFO     | ivadomed.config_manager:deep_dict_compare:44 -     loader_parameters: patch_filter_params: {'filter_empty_mask': False, 'filter_empty_input': False}
2022-09-15 08:52:10.579 | INFO     | ivadomed.config_manager:deep_dict_compare:44 -     lr_scheduler: base_lr: 1e-05
2022-09-15 08:52:10.579 | INFO     | ivadomed.config_manager:deep_dict_compare:44 -     lr_scheduler: max_lr: 0.01
2022-09-15 08:52:10.582 | INFO     | ivadomed.config_manager:_display_differing_keys:155 - 

2022-09-15 08:52:10.582 | WARNING  | ivadomed.inference:segment_volume:403 - fname_roi has not been specified, then the entire volume is processed.
2022-09-15 08:52:11.065 | INFO     | ivadomed.inference:segment_volume:451 - Loaded 35 axial patches of shape [256, 256].
2022-09-15 08:52:11.131 | INFO     | ivadomed.utils:define_device:157 - Cuda is not available.
2022-09-15 08:52:11.131 | INFO     | ivadomed.utils:define_device:158 - Working on cpu.
2022-09-15 08:52:11.131 | DEBUG    | ivadomed.inference:get_preds:88 - Likely ONNX model detected at: /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/AxonDeepSeg/models/model_seg_rat_axon-myelin_sem/model_seg_rat_axon-myelin_sem.onnx
2022-09-15 08:52:11.131 | DEBUG    | ivadomed.inference:get_preds:89 - Conduct ONNX model inference... 
2022-09-15 08:52:15.503 | DEBUG    | ivadomed.inference:get_preds:92 - Sending predictions to CPU
2022-09-15 08:52:15.535 | INFO     | ivadomed.utils:define_device:157 - Cuda is not available.
2022-09-15 08:52:15.535 | INFO     | ivadomed.utils:define_device:158 - Working on cpu.
2022-09-15 08:52:15.535 | DEBUG    | ivadomed.inference:get_preds:88 - Likely ONNX model detected at: /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/AxonDeepSeg/models/model_seg_rat_axon-myelin_sem/model_seg_rat_axon-myelin_sem.onnx
2022-09-15 08:52:15.535 | DEBUG    | ivadomed.inference:get_preds:89 - Conduct ONNX model inference... 
2022-09-15 08:52:19.826 | DEBUG    | ivadomed.inference:get_preds:92 - Sending predictions to CPU
2022-09-15 08:52:19.854 | INFO     | ivadomed.utils:define_device:157 - Cuda is not available.
2022-09-15 08:52:19.855 | INFO     | ivadomed.utils:define_device:158 - Working on cpu.
2022-09-15 08:52:19.855 | DEBUG    | ivadomed.inference:get_preds:88 - Likely ONNX model detected at: /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/AxonDeepSeg/models/model_seg_rat_axon-myelin_sem/model_seg_rat_axon-myelin_sem.onnx
2022-09-15 08:52:19.855 | DEBUG    | ivadomed.inference:get_preds:89 - Conduct ONNX model inference... 
2022-09-15 08:52:23.864 | DEBUG    | ivadomed.inference:get_preds:92 - Sending predictions to CPU
2022-09-15 08:52:23.884 | INFO     | ivadomed.utils:define_device:157 - Cuda is not available.
2022-09-15 08:52:23.884 | INFO     | ivadomed.utils:define_device:158 - Working on cpu.
2022-09-15 08:52:23.884 | DEBUG    | ivadomed.inference:get_preds:88 - Likely ONNX model detected at: /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/AxonDeepSeg/models/model_seg_rat_axon-myelin_sem/model_seg_rat_axon-myelin_sem.onnx
2022-09-15 08:52:23.884 | DEBUG    | ivadomed.inference:get_preds:89 - Conduct ONNX model inference... 
2022-09-15 08:52:27.604 | DEBUG    | ivadomed.inference:get_preds:92 - Sending predictions to CPU
2022-09-15 08:52:27.627 | INFO     | ivadomed.utils:define_device:157 - Cuda is not available.
2022-09-15 08:52:27.628 | INFO     | ivadomed.utils:define_device:158 - Working on cpu.
2022-09-15 08:52:27.628 | DEBUG    | ivadomed.inference:get_preds:88 - Likely ONNX model detected at: /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/AxonDeepSeg/models/model_seg_rat_axon-myelin_sem/model_seg_rat_axon-myelin_sem.onnx
2022-09-15 08:52:27.628 | DEBUG    | ivadomed.inference:get_preds:89 - Conduct ONNX model inference... 
2022-09-15 08:52:32.787 | DEBUG    | ivadomed.inference:get_preds:92 - Sending predictions to CPU
2022-09-15 08:52:32.828 | INFO     | ivadomed.utils:define_device:157 - Cuda is not available.
2022-09-15 08:52:32.828 | INFO     | ivadomed.utils:define_device:158 - Working on cpu.
2022-09-15 08:52:32.828 | DEBUG    | ivadomed.inference:get_preds:88 - Likely ONNX model detected at: /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/AxonDeepSeg/models/model_seg_rat_axon-myelin_sem/model_seg_rat_axon-myelin_sem.onnx
2022-09-15 08:52:32.828 | DEBUG    | ivadomed.inference:get_preds:89 - Conduct ONNX model inference... 
2022-09-15 08:52:36.778 | DEBUG    | ivadomed.inference:get_preds:92 - Sending predictions to CPU
2022-09-15 08:52:36.807 | INFO     | ivadomed.utils:define_device:157 - Cuda is not available.
2022-09-15 08:52:36.808 | INFO     | ivadomed.utils:define_device:158 - Working on cpu.
2022-09-15 08:52:36.808 | DEBUG    | ivadomed.inference:get_preds:88 - Likely ONNX model detected at: /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/AxonDeepSeg/models/model_seg_rat_axon-myelin_sem/model_seg_rat_axon-myelin_sem.onnx
2022-09-15 08:52:36.808 | DEBUG    | ivadomed.inference:get_preds:89 - Conduct ONNX model inference... 
2022-09-15 08:52:40.878 | DEBUG    | ivadomed.inference:get_preds:92 - Sending predictions to CPU
2022-09-15 08:52:40.923 | INFO     | ivadomed.utils:define_device:157 - Cuda is not available.
2022-09-15 08:52:40.923 | INFO     | ivadomed.utils:define_device:158 - Working on cpu.
2022-09-15 08:52:40.925 | DEBUG    | ivadomed.inference:get_preds:88 - Likely ONNX model detected at: /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/AxonDeepSeg/models/model_seg_rat_axon-myelin_sem/model_seg_rat_axon-myelin_sem.onnx
2022-09-15 08:52:40.926 | DEBUG    | ivadomed.inference:get_preds:89 - Conduct ONNX model inference... 
2022-09-15 08:52:47.535 | DEBUG    | ivadomed.inference:get_preds:92 - Sending predictions to CPU
2022-09-15 08:52:47.607 | INFO     | ivadomed.utils:define_device:157 - Cuda is not available.
2022-09-15 08:52:47.608 | INFO     | ivadomed.utils:define_device:158 - Working on cpu.
2022-09-15 08:52:47.608 | DEBUG    | ivadomed.inference:get_preds:88 - Likely ONNX model detected at: /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/AxonDeepSeg/models/model_seg_rat_axon-myelin_sem/model_seg_rat_axon-myelin_sem.onnx
2022-09-15 08:52:47.608 | DEBUG    | ivadomed.inference:get_preds:89 - Conduct ONNX model inference... 
2022-09-15 08:52:51.343 | DEBUG    | ivadomed.inference:get_preds:92 - Sending predictions to CPU
Lossy conversion from float64 to uint8. Range [0, 1]. Convert image to uint8 prior to saving to suppress this warning.
Lossy conversion from float64 to uint8. Range [0, 1]. Convert image to uint8 prior to saving to suppress this warning.
Lossy conversion from float64 to uint8. Range [0.0, 255.0]. Convert image to uint8 prior to saving to suppress this warning.
Generating axon and myelin segmentation masks and saving.
* * * Integrity test passed. AxonDeepSeg is correctly installed. * * * 
(ads_mamba) mathieuboudreau@Mathieus-MacBook-Pro axondeepseg_mamba % 
(ads_mamba) mathieuboudreau@Mathieus-MacBook-Pro axondeepseg_mamba % pytest .
================================================= test session starts ==================================================
platform darwin -- Python 3.8.13, pytest-7.1.3, pluggy-1.0.0
rootdir: /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba, configfile: pytest.ini
plugins: cov-3.0.0
collected 130 items                                                                                                    

test/test_ads_utils.py ............                                                                              [  9%]
test/test_download_models.py .F                                                                                  [ 10%]
test/test_download_tests.py ^C^X^Z
zsh: suspended  pytest .
(ads_mamba) mathieuboudreau@Mathieus-MacBook-Pro axondeepseg_mamba % pytest .        
================================================= test session starts ==================================================
platform darwin -- Python 3.8.13, pytest-7.1.3, pluggy-1.0.0
rootdir: /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba, configfile: pytest.ini
plugins: cov-3.0.0
collected 130 items                                                                                                    

test/test_ads_utils.py ............                                                                              [  9%]
test/test_download_models.py ..                                                                                  [ 10%]
test/test_download_tests.py ..                                                                                   [ 12%]
test/test_integrity_test.py .                                                                                    [ 13%]
test/test_params.py ....                                                                                         [ 16%]
test/test_postprocessing.py ........                                                                             [ 22%]
test/test_segment.py .....................                                                                       [ 38%]
test/morphometrics/test_compute_morphometrics.py ....................................                            [ 66%]
test/morphometrics/test_launch_morphometrics_computation.py .................                                    [ 79%]
test/testing/test_launch_performance_metrics.py .                                                                [ 80%]
test/testing/test_noise_simulation.py ...                                                                        [ 82%]
test/testing/test_segmentation_scoring.py ........                                                               [ 88%]
test/visualization/test_colorization.py ..                                                                       [ 90%]
test/visualization/test_generate_axons_from_myelin.py .                                                          [ 90%]
test/visualization/test_get_masks.py .....                                                                       [ 94%]
test/visualization/test_merge_masks.py .                                                                         [ 95%]
test/visualization/test_simulate_axons.py ......                                                                 [100%]

=================================================== warnings summary ===================================================
../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/skimage/data/__init__.py:121
../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/skimage/data/__init__.py:121
  /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/skimage/data/__init__.py:121: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
    if LooseVersion(pooch_version) < LooseVersion('1.3.0'):

../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/skimage/restoration/inpaint.py:6
  /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/skimage/restoration/inpaint.py:6: DeprecationWarning: Please use `laplace` from the `scipy.ndimage` namespace, the `scipy.ndimage.filters` namespace is deprecated.
    from scipy.ndimage.filters import laplace

../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/skimage/feature/_orb_descriptor_positions.py:8
  /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/skimage/feature/_orb_descriptor_positions.py:8: DeprecationWarning: loadtxt(): Parsing an integer via a float is deprecated.  To avoid this warning, you can:
      * make sure the original data is stored as integers.
      * use the `converters=` keyword argument.  If you only use
        NumPy 1.23 or later, `converters=float` will normally work.
      * Use `np.loadtxt(...).astype(np.int64)` parsing the file as
        floating point and then convert it.  (On all NumPy versions.)
    (Deprecated NumPy 1.23)
    POS = np.loadtxt(os.path.join(this_dir, "orb_descriptor_positions.txt"),

../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/skimage/filters/_unsharp_mask.py:2
  /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/skimage/filters/_unsharp_mask.py:2: DeprecationWarning: Please use `gaussian_filter` from the `scipy.ndimage` namespace, the `scipy.ndimage.filters` namespace is deprecated.
    from scipy.ndimage.filters import gaussian_filter

../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/matplotlib/__init__.py:169
../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/matplotlib/__init__.py:169
../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/matplotlib/__init__.py:169
../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/matplotlib/__init__.py:169
../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/matplotlib/__init__.py:169
  /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/matplotlib/__init__.py:169: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
    if LooseVersion(module.__version__) < minver:

../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/setuptools/_distutils/version.py:346
../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/setuptools/_distutils/version.py:346
../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/setuptools/_distutils/version.py:346
../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/setuptools/_distutils/version.py:346
../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/setuptools/_distutils/version.py:346
  /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/setuptools/_distutils/version.py:346: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
    other = LooseVersion(other)

../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/h5py/__init__.py:46
  /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/h5py/__init__.py:46: DeprecationWarning: `np.typeDict` is a deprecated alias for `np.sctypeDict`.
    from ._conv import register_converters as _register_converters

../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/nibabel/openers.py:26
../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/nibabel/openers.py:26
  /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/nibabel/openers.py:26: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
    if StrictVersion(version) < StrictVersion('0.7.0'):

../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/nibabel/openers.py:30
../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/nibabel/openers.py:30
  /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/nibabel/openers.py:30: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
    elif StrictVersion(version) < StrictVersion('0.8.0'):

../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/torchvision/transforms/functional_pil.py:207
  /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/torchvision/transforms/functional_pil.py:207: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.
    def resize(img, size, interpolation=Image.BILINEAR):

../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/torchvision/transforms/functional_pil.py:280
  /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/torchvision/transforms/functional_pil.py:280: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.
    def perspective(img, perspective_coeffs, interpolation=Image.BICUBIC, fill=None):

../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/sklearn/utils/multiclass.py:14
  /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/sklearn/utils/multiclass.py:14: DeprecationWarning: Please use `spmatrix` from the `scipy.sparse` namespace, the `scipy.sparse.base` namespace is deprecated.
    from scipy.sparse.base import spmatrix

../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/sklearn/utils/optimize.py:18
  /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/sklearn/utils/optimize.py:18: DeprecationWarning: Please use `line_search_wolfe2` from the `scipy.optimize` namespace, the `scipy.optimize.linesearch` namespace is deprecated.
    from scipy.optimize.linesearch import line_search_wolfe2, line_search_wolfe1

../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/sklearn/utils/optimize.py:18
  /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/sklearn/utils/optimize.py:18: DeprecationWarning: Please use `line_search_wolfe1` from the `scipy.optimize` namespace, the `scipy.optimize.linesearch` namespace is deprecated.
    from scipy.optimize.linesearch import line_search_wolfe2, line_search_wolfe1

../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/torch/utils/tensorboard/__init__.py:3
../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/torch/utils/tensorboard/__init__.py:3
  /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/torch/utils/tensorboard/__init__.py:3: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
    if not hasattr(tensorboard, '__version__') or LooseVersion(tensorboard.__version__) < LooseVersion('1.15'):

../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/skimage/segmentation/random_walker_segmentation.py:49
../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/skimage/segmentation/random_walker_segmentation.py:49
  /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/skimage/segmentation/random_walker_segmentation.py:49: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
    if Version(scipy.__version__) >= Version('1.1'):

../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/skimage/io/collection.py:15
../../../opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/skimage/io/collection.py:15
  /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/skimage/io/collection.py:15: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
    if LooseVersion(pil_version) < LooseVersion('7.1.0'):

test/morphometrics/test_launch_morphometrics_computation.py:286
  /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/test/morphometrics/test_launch_morphometrics_computation.py:286: PytestUnknownMarkWarning: Unknown pytest.mark.single - is this a typo?  You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/how-to/mark.html
    @pytest.mark.single

test/test_integrity_test.py: 2 warnings
test/test_segment.py: 44 warnings
  /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/ivadomed/loader/segmentation_pair.py:318: DeprecationWarning: Starting with ImageIO v3 the behavior of this function will switch to that of iio.v3.imread. To keep the current behavior (and make this warning disappear) use `import imageio.v2 as imageio` or call `imageio.v2.imread` directly.
    img = np.expand_dims(imageio.imread(filename, as_gray=True), axis=-1).astype(np.uint8)

test/test_integrity_test.py: 4 warnings
test/test_postprocessing.py: 28 warnings
test/test_segment.py: 99 warnings
test/morphometrics/test_compute_morphometrics.py: 159 warnings
test/morphometrics/test_launch_morphometrics_computation.py: 6 warnings
test/testing/test_launch_performance_metrics.py: 2 warnings
test/visualization/test_colorization.py: 1 warning
test/visualization/test_generate_axons_from_myelin.py: 2 warnings
test/visualization/test_get_masks.py: 2 warnings
test/visualization/test_merge_masks.py: 2 warnings
  /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/AxonDeepSeg/ads_utils.py:279: DeprecationWarning: Starting with ImageIO v3 the behavior of this function will switch to that of iio.v3.imread. To keep the current behavior (and make this warning disappear) use `import imageio.v2 as imageio` or call `imageio.v2.imread` directly.
    raw_img = imageio.imread(filename)

test/test_postprocessing.py: 24 warnings
test/test_segment.py: 39 warnings
test/morphometrics/test_compute_morphometrics.py: 73 warnings
test/testing/test_launch_performance_metrics.py: 1 warning
  /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/AxonDeepSeg/ads_utils.py:281: DeprecationWarning: Starting with ImageIO v3 the behavior of this function will switch to that of iio.v3.imread. To keep the current behavior (and make this warning disappear) use `import imageio.v2 as imageio` or call `imageio.v2.imread` directly.
    raw_img = imageio.imread(filename, as_gray=True)

test/test_postprocessing.py::TestCore::test_fill_myelin_holes_returns_expected_arrays
  /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/AxonDeepSeg/postprocessing.py:80: DeprecationWarning: `np.bool` is a deprecated alias for the builtin `bool`. To silence this warning, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here.
  Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
    filled_array = morphology.remove_small_holes(myelin_array.astype(np.bool), area_threshold=maximum_axon_area)

test/test_segment.py::TestCore::test_segment_image_creates_runs_successfully_for_16bit_TIF_gray_file
  /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/AxonDeepSeg/ads_utils.py:275: DeprecationWarning: Starting with ImageIO v3 the behavior of this function will switch to that of iio.v3.imread. To keep the current behavior (and make this warning disappear) use `import imageio.v2 as imageio` or call `imageio.v2.imread` directly.
    raw_img = imageio.imread(filename, format='tiff-pil')

test/test_segment.py::TestCore::test_segment_image_creates_runs_successfully_for_16bit_TIF_gray_file
test/test_segment.py::TestCore::test_segment_image_creates_runs_successfully_for_16bit_TIF_gray_file
  /Users/mathieuboudreau/opt/anaconda3/envs/ads_mamba/lib/python3.8/site-packages/ivadomed/loader/segmentation_pair.py:314: DeprecationWarning: Starting with ImageIO v3 the behavior of this function will switch to that of iio.v3.imread. To keep the current behavior (and make this warning disappear) use `import imageio.v2 as imageio` or call `imageio.v2.imread` directly.
    img = np.expand_dims(imageio.imread(filename, format='tiff-pil'), axis=-1).astype(np.uint8)

test/testing/test_noise_simulation.py::TestCore::test_add_additive_gaussian_noise_returns_expected_std_diff
test/testing/test_noise_simulation.py::TestCore::test_add_multiplicative_gaussian_noise_returns_different_image
test/testing/test_noise_simulation.py::TestCore::test_change_brightness
  /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/test/testing/test_noise_simulation.py:21: DeprecationWarning: Starting with ImageIO v3 the behavior of this function will switch to that of iio.v3.imread. To keep the current behavior (and make this warning disappear) use `import imageio.v2 as imageio` or call `imageio.v2.imread` directly.
    self.image = imread(self.folderPath / 'image.png', as_gray=True)

test/testing/test_segmentation_scoring.py::TestCore::test_score_analysis_returns_nonzero_outputs_diff_masks
test/testing/test_segmentation_scoring.py::TestCore::test_score_analysis_returns_expected_outputs_for_same_masks
test/testing/test_segmentation_scoring.py::TestCore::test_score_analysis_runs_successfully_with_visualization_on
test/testing/test_segmentation_scoring.py::TestCore::test_dice_returns_nonempty_pandas_dataframe
test/testing/test_segmentation_scoring.py::TestCore::test_pwdice_returns_nonzero_value_for_diff_masks
test/testing/test_segmentation_scoring.py::TestCore::test_pwdice_returns_1_for_identical_masks
test/testing/test_segmentation_scoring.py::TestCore::test_Metrics_calculator_class_return_nonzeros_for_diff_masks
test/testing/test_segmentation_scoring.py::TestCore::test_Metrics_calculator_class_same_masks_returns_expected_values
  /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/test/testing/test_segmentation_scoring.py:24: DeprecationWarning: Starting with ImageIO v3 the behavior of this function will switch to that of iio.v3.imread. To keep the current behavior (and make this warning disappear) use `import imageio.v2 as imageio` or call `imageio.v2.imread` directly.
    self.img = imread(self.folderPath / 'image.png', as_gray=True)

test/testing/test_segmentation_scoring.py::TestCore::test_score_analysis_returns_nonzero_outputs_diff_masks
test/testing/test_segmentation_scoring.py::TestCore::test_score_analysis_returns_expected_outputs_for_same_masks
test/testing/test_segmentation_scoring.py::TestCore::test_score_analysis_runs_successfully_with_visualization_on
test/testing/test_segmentation_scoring.py::TestCore::test_dice_returns_nonempty_pandas_dataframe
test/testing/test_segmentation_scoring.py::TestCore::test_pwdice_returns_nonzero_value_for_diff_masks
test/testing/test_segmentation_scoring.py::TestCore::test_pwdice_returns_1_for_identical_masks
test/testing/test_segmentation_scoring.py::TestCore::test_Metrics_calculator_class_return_nonzeros_for_diff_masks
test/testing/test_segmentation_scoring.py::TestCore::test_Metrics_calculator_class_same_masks_returns_expected_values
  /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/test/testing/test_segmentation_scoring.py:26: DeprecationWarning: Starting with ImageIO v3 the behavior of this function will switch to that of iio.v3.imread. To keep the current behavior (and make this warning disappear) use `import imageio.v2 as imageio` or call `imageio.v2.imread` directly.
    self.groundtruth = imread(self.folderPath / 'mask.png', as_gray=True)

test/testing/test_segmentation_scoring.py::TestCore::test_score_analysis_returns_nonzero_outputs_diff_masks
test/testing/test_segmentation_scoring.py::TestCore::test_score_analysis_returns_expected_outputs_for_same_masks
test/testing/test_segmentation_scoring.py::TestCore::test_score_analysis_runs_successfully_with_visualization_on
test/testing/test_segmentation_scoring.py::TestCore::test_dice_returns_nonempty_pandas_dataframe
test/testing/test_segmentation_scoring.py::TestCore::test_pwdice_returns_nonzero_value_for_diff_masks
test/testing/test_segmentation_scoring.py::TestCore::test_pwdice_returns_1_for_identical_masks
test/testing/test_segmentation_scoring.py::TestCore::test_Metrics_calculator_class_return_nonzeros_for_diff_masks
test/testing/test_segmentation_scoring.py::TestCore::test_Metrics_calculator_class_same_masks_returns_expected_values
  /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/test/testing/test_segmentation_scoring.py:28: DeprecationWarning: Starting with ImageIO v3 the behavior of this function will switch to that of iio.v3.imread. To keep the current behavior (and make this warning disappear) use `import imageio.v2 as imageio` or call `imageio.v2.imread` directly.
    self.prediction = imread(

test/visualization/test_get_masks.py::TestCore::test_rgb_rendering_of_mask_returns_array_with_extra_dim_of_len_3
  /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/test/visualization/test_get_masks.py:55: DeprecationWarning: Starting with ImageIO v3 the behavior of this function will switch to that of iio.v3.imread. To keep the current behavior (and make this warning disappear) use `import imageio.v2 as imageio` or call `imageio.v2.imread` directly.
    pred_img = imageio.imread(self.path_folder / ('image' + str(axonmyelin_suffix)))

test/visualization/test_get_masks.py::TestCore::test_rgb_rendering_of_mask_writes_expected_files
  /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/test/visualization/test_get_masks.py:67: DeprecationWarning: Starting with ImageIO v3 the behavior of this function will switch to that of iio.v3.imread. To keep the current behavior (and make this warning disappear) use `import imageio.v2 as imageio` or call `imageio.v2.imread` directly.
    pred_img = imageio.imread(self.path_folder / ('image' + str(axonmyelin_suffix)))

test/visualization/test_get_masks.py::TestCore::test_rgb_rendering_of_mask_writes_expected_files
  /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/test/visualization/test_get_masks.py:77: DeprecationWarning: Starting with ImageIO v3 the behavior of this function will switch to that of iio.v3.imread. To keep the current behavior (and make this warning disappear) use `import imageio.v2 as imageio` or call `imageio.v2.imread` directly.
    assert np.array_equal(rgb_mask, imageio.imread(rgbFile))

test/visualization/test_get_masks.py::TestCore::test_get_image_properties_returns_expeception_for_unexpected_number_of_unique_values
  /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/test/visualization/test_get_masks.py:99: DeprecationWarning: Starting with ImageIO v3 the behavior of this function will switch to that of iio.v3.imread. To keep the current behavior (and make this warning disappear) use `import imageio.v2 as imageio` or call `imageio.v2.imread` directly.
    loaded_image = imageio.imread(pred_img)

test/visualization/test_merge_masks.py::TestCore::test_merge_masks_outputs_expected_volume_and_writes_files
  /Users/mathieuboudreau/neuropoly/github/axondeepseg_mamba/test/visualization/test_merge_masks.py:46: DeprecationWarning: Starting with ImageIO v3 the behavior of this function will switch to that of iio.v3.imread. To keep the current behavior (and make this warning disappear) use `import imageio.v2 as imageio` or call `imageio.v2.imread` directly.
    assert np.array_equal(both, imageio.imread(expectedFilePath))

-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
==================================== 130 passed, 556 warnings in 1513.29s (0:25:13) ====================================
(ads_mamba) mathieuboudreau@Mathieus-MacBook-Pro axondeepseg_mamba % 

So I think there wouldn't be too much issue migrating to Mambaforge. There's different ways of installating it, however I think my preferred way to document it for users is to suggest installation through conda , instead of forcing them to use MiniForge like is being done in Shimming Toolbox here shimming-toolbox/shimming-toolbox#403. This is because they have an automated installation script to handle their environment (eg where they install miniforge automatically), whereas we don't and some of our users might not know how to manually manage both a prior Anaconda/Miniconda installation and a new Miniforge installation (i.e. they might complain they lost their old conda envs). Essentially, we would just need to add the instruction under "Existing conda install" described here, https://mamba.readthedocs.io/en/latest/installation.html, and then make them install the ADS venv with mamba instead of conda. Activating the env is still used with conda afterwards though (which might get confusing, but it is what it is).

@mathieuboudreau mathieuboudreau self-assigned this Sep 15, 2022
@mathieuboudreau mathieuboudreau added the installation category: the change alters the installation of AxonDeepSeg label Sep 15, 2022
@hermancollin
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@mathieuboudreau not sure why I never reviewed this, sorry about that. I like this PR a lot and would like to revive it. We should merge this during/after the nnunet migration #800. Maybe we'll need a new PR because this one is pretty old.

I had to re-install the venv to test new dependencies and conda was excruciatingly slow. mamba is faster and IIUC it can be used as a direct replacement.

@mathieuboudreau
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@mathieuboudreau not sure why I never reviewed this, sorry about that. I like this PR a lot and would like to revive it. We should merge this during/after the nnunet migration #800. Maybe we'll need a new PR because this one is pretty old.

I had to re-install the venv to test new dependencies and conda was excruciatingly slow. mamba is faster and IIUC it can be used as a direct replacement.

I agree - and it's (conda) been quite excruciatingly slow for me too lately. This PR wasn't ready for review, we need to write up instructions for the users in the documentation, note how in one of my prior comments I thought it may be wiser to first ask the users to install miniconda, and install mambaforge using that instead of going the route SCT does (since they have a different installation procedure )

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