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"description": "**FUNPACK** - the FMRIB UKBioBank Normalisation, Parsing And Cleaning Kit\n=========================================================================\n\n\n.. image:: https://img.shields.io/pypi/v/fmrib-unpack.svg\n :target: https://pypi.python.org/pypi/fmrib-unpack/\n\n.. image:: https://anaconda.org/conda-forge/fmrib-unpack/badges/version.svg\n :target: https://anaconda.org/conda-forge/fmrib-unpack\n\n\n.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.1997626.svg\n :target: https://doi.org/10.5281/zenodo.1997626\n\n.. image:: https://git.fmrib.ox.ac.uk/fsl/funpack/badges/master/coverage.svg\n :target: https://git.fmrib.ox.ac.uk/fsl/funpack/commits/master/\n\n\n**FUNPACK** is a Python library for pre-processing of UK BioBank data.\n\n\n FUNPACK is developed at the Wellcome Centre for Integrative Neuroimaging\n (WIN@FMRIB), University of Oxford. FUNPACK is in no way endorsed,\n sanctioned, or validated by the `UK BioBank\n `_.\n\n FUNPACK comes bundled with metadata about the variables present in UK\n BioBank data sets. This metadata can be obtained from the `UK BioBank\n online data showcase `_\n\n\nInstallation\n------------\n\n\nInstall FUNPACK via pip::\n\n pip install fmrib-unpack\n\n\nOr from ``conda-forge``::\n\n conda install -c conda-forge fmrib-unpack\n\n\nThe FUNPACK source code can be found at\nhttps://git.fmrib.ox.ac.uk/fsl/funpack/.\n\n\nIntroductory notebook\n---------------------\n\n\nThe ``funpack_demo`` command will start a Jupyter Notebook which introduces\nthe main features provided by FUNPACK. A non-interactive version of this\nnotebook can be found at\nhttps://open.win.ox.ac.uk/pages/fsl/funpack/demo.html.\n\nIf you are using ``pip``, you need to install a few additional dependencies::\n\n pip install fmrib-unpack[demo]\n\n\nYou can then start the demo by running ``fmrib_unpack_demo``.\n\n\n.. note:: The introductory notebook uses ``bash``, so is unlikely to work on\n Windows.\n\n\nUsage\n-----\n\n\nGeneral usage is as follows::\n\n fmrib_unpack [options] output.tsv input1.tsv input2.tsv\n\n\nYou can get information on all of the options by typing ``fmrib_unpack --help``.\n\n The `fmrib_unpack` command was called `funpack` in older versions of\n FUNPACK, but was changed to `fmrib_unpack` in 3.0.0 to avoid a naming\n conflict with an `unrelated software package\n `_.\n\n\nOptions can be specified on the command line, and/or stored in a configuration\nfile. For example, the options in the following command line::\n\n fmrib_unpack \\\n --overwrite \\\n --write_log \\\n --icd10_map_file icd_codes.tsv \\\n --category 10 \\\n --category 11 \\\n output.tsv input1.tsv input2.tsv\n\n\nCould be stored in a configuration file ``config.txt``::\n\n overwrite\n write_log\n icd10_map_file icd_codes.tsv\n category 10\n category 11\n\n\nAnd then executed as follows::\n\n fmrib_unpack -cfg config.txt output.tsv input1.tsv input2.tsv\n\n\nFeatures\n--------\n\n\nFUNPACK allows you to perform various data sanitisation and processing steps\non your data, such as:\n\n * **NA value replacement**: Specific values for some columns can be replaced\n with NA, for example, variables where a value of -1 indicates *Do not know*.\n\n * **Categorical recoding**: Certain categorical columns can re-coded. For\n example, variables where a value of 555 represents *half* can be recoded\n so that 555 is replaced with 0.5.\n\n * **Child value replacement**: NA values within some columns which are\n dependent upon other columns may have values inserted based on the values\n of their parent columns.\n\nSee the introductory notebook for a more comprehensive overview of the features\navailable in FUNPACK.\n\n\nBuilt-in rules\n--------------\n\n\nFUNPACK contains a large number of built-in rules which have been specifically\nwritten to pre-process UK BioBank data variables. These rules are stored in\nthe following files (the `funpack/` directory is located in your Python\nenvironment directory):\n\n * ``funpack/configs/fmrib/datacodings_*.tsv``: Cleaning rules for data codings\n * ``funpack/configs/fmrib/variables_*.tsv``: Cleaning rules for individual\n variables\n * ``funpack/configs/fmrib/processing.tsv``: Processing steps\n * ``funpack/configs/fmrib/categories.tsv``: Variable categories\n\n\nYou can use these rules by using the FMRIB configuration profile::\n\n fmrib_unpack -cfg fmrib output.tsv input.tsv\n\n\nYou can customise or replace these files as you see fit. You can also pass\nyour own versions of these files to FUNPACK via the ``--variable_file``,\n``--datacoding_file``, ``--type_file``, ``--processing_file``, and\n``--category_file`` command-line options respectively. FUNPACK will load all\nvariable and datacoding files, and merge them into a single table which\ncontains the cleaning rules for each variable.\n\n\nCreating your own rule files\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\n\nTo define rules at the *data-coding* level, create one or more ``.tsv`` files\nwith an ``ID`` column containing the data-coding ID, and any of the following\ncolumns:\n\n\n - ``NAValues``: A comma-separated list of values to replace with NA\n - ``RawLevels`` A comma-separated list of values to be replaced with\n corresponding values in ``NewLevels``.\n - ``NewLevels`` A comma-separated list of replacement values for each\n of the values listed in ``RawLevels``.\n\nTo apply these rules, pass your ``.tsv`` file(s) to ``funpack`` with the\n``--datacoding_file`` option. They will be applied to all variables which\nuse the data-coding(s) listed in the file(s).\n\n\nTo define rules at the *variable* level, create one or more ``.tsv`` files\nwith an ``ID`` column containing the variable ID, and any of the following\ncolumns:\n\n\n - ``NAValues``: As above\n - ``RawLevels`` As above\n - ``NewLevels`` As above\n - ``ParentValues``: A comma-separated list of expressions on parent\n variables, defining conditions which should trigger child-value\n replacement.\n - ``ChildValues``: A comma-separated list of values to insert into the\n variable when the corresponding expression in ``ParentValues`` evaluates\n to true.\n - ``Clean``: A comma-separated list of cleaning functions to apply to the\n variable.\n\n\nOutput\n------\n\n\nThe main output of FUNPACK is a plain-text file[*]_ which contains the input\ndata, after cleaning and processing, potentially with some columns removed,\nand new columns added.\n\n\nIf you used the ``--suppress_non_numerics`` option, the main output file will\nonly contain the numeric columns. You can combine this with the\n``--write_non_numerics`` option to save non-numeric columns to a separate\nfile.\n\n\nYou can use any tool of your choice to load this output file, such as Python,\nMATLAB, or Excel. It is also possible to pass the output back into\nFUNPACK.\n\n\n.. [*] If your output file name ends with ``.csv``, the file will be\n comma-separated, and if your output file name ends with ``.tsv``, the\n file will be tab-separated.\n\n\nLoading output into MATLAB\n^^^^^^^^^^^^^^^^^^^^^^^^^^\n\n\n.. |readtable| replace:: ``readtable``\n.. _readtable: https://uk.mathworks.com/help/matlab/ref/readtable.html\n\n.. |table| replace:: ``table``\n.. _table: https://uk.mathworks.com/help/matlab/ref/table.html\n\n\nIf you are using MATLAB, you have several options for loading the FUNPACK\noutput. The best option is |readtable|_, which will load column names, and\nwill handle both non-numeric data and missing values. Use ``readtable`` like\nso (assuming that you generated a tab-separated file)::\n\n data = readtable('out.tsv', 'FileType', 'text');\n\n\nThe ``readtable`` function returns a |table|_ object, which stores each column\nas a separate vector (or cell-array for non-numeric columns). If you are only\ninterested in numeric columns, you can retrieve them as an array like this::\n\n data = data(:, vartype('numeric'));\n rawdata = data.Variables;\n\n\nThe ``readtable`` function will potentially rename the column names to ensure\nthat they are are valid MATLAB identifiers. You can retrieve the original\nnames from the ``table`` object like so::\n\n colnames = data.Properties.VariableDescriptions';\n\n\nIf you have used the ``--write_description`` or ``--description_file``\noptions, you can load in the descriptions for each column as follows::\n\n descs = readtable('out_descriptions.tsv', ...\n 'FileType', 'text', ...\n 'Delimiter', '\\t', ...\n 'ReadVariableNames',false);\n descs = [descs; {'eid', 'ID'}];\n idxs = cellfun(@(x) find(strcmp(descs.Var1, x)), colnames, ...\n 'UniformOutput', false);\n idxs = cell2mat(idxs);\n descs = descs.Var2(idxs);\n\n\nTests\n-----\n\n\nTo run the test suite, you need to install some additional dependencies::\n\n pip install fmrib-unpack[test]\n\n\nThen you can run the test suite using ``pytest``::\n\n pytest\n\n\nmacOS issues\n------------\n\n\nFUNPACK makes extensive use of the Python `multiprocessing\n`_ module to speed up\ncertain steps in its processing pipeline. FUNPACK relies on the POSIX `fork()\n`_ mechanism, so that\nworker processes may inexpensively inherit the memory space of the main\nprocess (often referred to as *copy-on-write*). This is to avoid having to\nserialise the data set being processed (stored internally as a\n``pandas.DataFrame``).\n\n\nIn python 3.8 on macOS, the default method used by the ``multiprocessing``\nmodule was changed from ``fork`` to ``spawn``, due to changes in macOS 10.13\nrestricting the use of ``fork()`` for safety reasons. Some background\ninformation on this change can be found at https://bugs.python.org/issue33725,\nand at `this blog post\n`_.\n\n\nFUNPACK therefore explicitly sets the method used by the ``multiprocessing``\nto ``fork``, to take advantage of copy-on-write semantics. Using ``fork()``\non macOS *should* be safe for single-threaded parent processes, but as FUNPACK\ncalls ``fork()`` numerous times (by creating and discarding\n``multiprocessing.Pool()`` objects on an as-needed basis), this assumption may\nnot be valid, and FUNPACK may crash with an error message resembling the\nfollowing::\n\n\n +[SomeClass initialize] may have been in progress in another thread\n when fork() was called. We cannot safely call it or ignore it in the\n fork() child process. Crashing instead.\n\n\nYou might be able to work around this error by setting an environment variable\nbefore calling FUNPACK, like so::\n\n\n export OBJC_DISABLE_INITIALIZE_FORK_SAFETY=YES\n fmrib_unpack ...\n\n\nCiting\n------\n\n\nIf you would like to cite FUNPACK, please refer to its `Zenodo page\n`_.\n\n\n",
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