{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "\"logo\"\n", "\n", "# Boutiques tutorial\n", "\n", "\n", "This tutorial will walk you through the main features of [Boutiques](http://boutiques.github.io). Boutiques is a framework to make tools Findable Accessible Interoperable and Reusable (FAIR). An overview of the framework and its capabilities is available [here](https://figshare.com/articles/fair-pipelines-poster_pdf/8143241), and a more complete description is [here](https://academic.oup.com/gigascience/article/7/5/giy016/4951979). The entry point for our documentation is http://github.com/boutiques." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Getting Started\n", "\n", "Boutiques is available as a Python module on `pip` and can be installed by simply typing `pip install boutiques`. Once Boutiques is installed, its Python and command-line APIs can be accessed through your new favourite command, _bosh_ (BOutiques SHell). _bosh_ provides an access point to all of the tools wrapped within Boutiques and has some --help text to keep you moving forward if you feel like you're getting stuck. You can check that it's correctly installed by simply typing `bosh version` in a command line:" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.5.20.post1\n" ] } ], "source": [ "%%bash\n", "bosh version" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Help is available through `--help`:" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "usage: bosh [--help]\n", " [{create,data,evaluate,example,exec,export,import,invocation,pprint,publish,pull,search,test,validate,version}]\n", "\n", "positional arguments:\n", " {create,data,evaluate,example,exec,export,import,invocation,pprint,publish,pull,search,test,validate,version}\n", " \n", " BOUTIQUES COMMANDS\n", " \n", " TOOL CREATION\n", " * create: create a Boutiques descriptor from scratch.\n", " * export: export a descriptor to other formats.\n", " * import: create a descriptor for a BIDS app or update a descriptor from \\\n", " an older version of the schema.\n", " * validate: validate an existing boutiques descriptor.\n", " \n", " TOOL USAGE & EXECUTION\n", " * example: generate example command-line for descriptor.\n", " * pprint: generate pretty help text from a descriptor.\n", " * exec: launch or simulate an execution given a descriptor and a set of inputs.\n", " * test: run pytest on a descriptor detailing tests.\n", " \n", " TOOL SEARCH & PUBLICATION\n", " * publish: create an entry in Zenodo for the descriptor and adds the DOI \\\n", " created by Zenodo to the descriptor.\n", " * pull: download a descriptor from Zenodo.\n", " * search: search Zenodo for descriptors.\n", " \n", " DATA COLLECTION\n", " * data: manage execution data collection.\n", " \n", " OTHER\n", " * evaluate: given an invocation and a descriptor,queries execution properties.\n", " * invocation: generate or validate inputs against the invocation schema\n", " * for a given descriptor.\n", " * version: print the Boutiques version.\n", "\n", "optional arguments:\n", " --help, -h show this help message and exit\n" ] } ], "source": [ "%%bash\n", "bosh --help" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "_bosh_ commands are also available as a Python API, where the same parameters as in the command line are passed as a list to function _bosh_:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'0.5.20.post1'" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from boutiques import bosh\n", "bosh([\"version\"])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This tutorial mostly uses the command line API. In case you are not familiar with the command line syntax, more specifically that of the [bash](https://www.gnu.org/software/bash) shell, you are encouraged to first follow the tutorial [here](https://www.shellscript.sh). We will also try to explain the command-line syntax throughout the tutorial as much as possible (pay attention to the comment strings in the code cells!). All the `bosh` commands are also available from a Python API that we will occasionally mention. If you need help with Python, a good intro for scientific programing is available [here](https://github.com/neurohackweek/python-for-scientists). You may also want to check Python's [getting started guide](https://www.python.org/about/gettingstarted).\n", "\n", "## Tutorial outline\n", "\n", "We will use brain extraction (BET) as a running example to illustrate Boutiques features. More specifically, we will go through the following steps:\n", "* [Finding tools](#finding_tools)\n", "* [Reusing tools](#reusing_tools)\n", "* [Publishing tools](#publishing_tools) (including how to write a Boutiques descriptor)\n", "* [Advanced features](#advanced_features)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Finding tools\n", "\n", "\n", "Perhaps someone has already described the tool you are looking for and you could reuse their work. For instance, if you are looking for a tool that does brain extraction (BET), try:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[ INFO ] Showing 1 of 1 results.\n", "ID TITLE DESCRIPTION DOWNLOADS\n", "zenodo.1482743 fsl_bet Automated brain extraction tool for FSL 38\n" ] } ], "source": [ "%%bash\n", "bosh search bet" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The _search_ command returns a list of identifiers for tools matching your query. You can use these identifiers in any bosh command transparently. Even better, these identifiers are [Digital Object Identifiers](https://www.doi.org) hosted on [Zenodo](http://zenodo.org), they will never change and can't be deleted!\n", "\n", "Once you have identified candidate tools for your task, you can get more details about how they work using bosh _pprint_:" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "================================================================================\n", "\n", "Tool name: fsl_bet (ver: 1.0.0)\n", "Tool description: Automated brain extraction tool for FSL\n", "Tags: domain: neuroinformatics, mri\n", "\n", "Command-line:\n", " bet [INPUT_FILE] [MASK] [FRACTIONAL_INTENSITY] [VERTICAL_GRADIENT]\n", " [CENTER_OF_GRAVITY] [OVERLAY_FLAG] [BINARY_MASK_FLAG]\n", " [APPROX_SKULL_FLAG] [NO_SEG_OUTPUT_FLAG] [VTK_VIEW_FLAG]\n" ] } ], "source": [ "%%bash\n", "bosh pprint zenodo.1482743 | head\n", "# The `|` operator, pronounced \"pipe\", is a bash operator to link two commands.\n", "# Here we use it to redirect the output of `bosh pprint` to the input of `head`, \n", "# a handy command to display only the first lines of a long text." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Behind the scene, _bosh_ has downloaded the tool descriptor from Zenodo and has stored it in `~/.cache/boutiques` on your computer:" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{\n", " \"tool-version\": \"1.0.0\", \n", " \"name\": \"fsl_bet\", \n", " \"author\": \"Oxford Centre for Functional MRI of the Brain (FMRIB)\",\n", " \"descriptor-url\": \"https://github.com/aces/cbrain-plugins-neuro/blob/master/cbrain_task_descriptors/fsl_bet.json\",\n", " \"command-line\": \"bet [INPUT_FILE] [MASK] [FRACTIONAL_INTENSITY] [VERTICAL_GRADIENT] [CENTER_OF_GRAVITY] [OVERLAY_FLAG] [BINARY_MASK_FLAG] [APPROX_SKULL_FLAG] [NO_SEG_OUTPUT_FLAG] [VTK_VIEW_FLAG] [HEAD_RADIUS] [THRESHOLDING_FLAG] [ROBUST_ITERS_FLAG] [RES_OPTIC_CLEANUP_FLAG] [REDUCE_BIAS_FLAG] [SLICE_PADDING_FLAG] [MASK_WHOLE_SET_FLAG] [ADD_SURFACES_FLAG] [ADD_SURFACES_T2] [VERBOSE_FLAG] [DEBUG_FLAG]\", \n", " \"inputs\": [\n", " {\n", " \"description\": \"Input image (e.g. img.nii.gz)\", \n", " \"value-key\": \"[INPUT_FILE]\", \n" ] } ], "source": [ "%%bash\n", "head ~/.cache/boutiques/zenodo-1482743.json" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You can use file paths or Zenodo IDs indifferently in all _bosh_ commands. This can be useful when you work offline. For instance:" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "================================================================================\n", "\n", "Tool name: fsl_bet (ver: 1.0.0)\n", "Tool description: Automated brain extraction tool for FSL\n", "Tags: domain: neuroinformatics, mri\n", "\n", "Command-line:\n", " bet [INPUT_FILE] [MASK] [FRACTIONAL_INTENSITY] [VERTICAL_GRADIENT]\n", " [CENTER_OF_GRAVITY] [OVERLAY_FLAG] [BINARY_MASK_FLAG]\n", " [APPROX_SKULL_FLAG] [NO_SEG_OUTPUT_FLAG] [VTK_VIEW_FLAG]\n" ] } ], "source": [ "%%bash\n", "bosh pprint ~/.cache/boutiques/zenodo-1482743.json | head" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Reusing tools\n", "\n", "\n", "It looks like we have found a tool that suits our needs -- now it's time to put it to work! The first step is to create an _invocation_ with your input values. We will use the test data in [data](./data), a sample from the [CoRR](http://fcon_1000.projects.nitrc.org/indi/CoRR/html) dataset. You can visualize the dataset as follows. Note that upon first invocation, NiftiWidget might raise a `FutureWarning` exception: re-runing the cell should make it disappear." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from niwidgets import NiftiWidget\n", "my_widget = NiftiWidget('./data/test.nii.gz')\n", "my_widget.nifti_plotter(colormap='gray')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The _example_ command will create a first minimal invocation so that you don't have to start from scratch:" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{\n", " \"infile\": \"f_infile_97.tex\",\n", " \"maskfile\": \"str_maskfile_jD\"\n", "}\n" ] } ], "source": [ "%%bash\n", "bosh example zenodo.1482743" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If you feel like starting with a more complete set of options, you can pass `--complete` to the _example_ command:" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{\n", " \"approx_skull_flag\": true,\n", " \"binary_mask_flag\": true,\n", " \"center_of_gravity\": [\n", " -6.146,\n", " -46.492,\n", " -10.684\n", " ],\n", " \"debug_flag\": false,\n", " \"fractional_intensity\": 0.991,\n", " \"head_radius\": -2.001,\n", " \"infile\": \"f_infile_98.csv\",\n", " \"maskfile\": \"str_maskfile_rH\",\n", " \"no_seg_output_flag\": false,\n", " \"overlay_flag\": false,\n", " \"robust_iters_flag\": false,\n", " \"thresholding_flag\": true,\n", " \"verbose_flag\": true,\n", " \"vg_fractional_intensity\": -0.195,\n", " \"vtk_mesh\": true\n", "}\n" ] } ], "source": [ "%%bash\n", "bosh example --complete zenodo.1482743" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You can now edit the example invocation to add your input values:" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{\n", "\t\"infile\": \"./data/test.nii.gz\",\n", " \"maskfile\": \"test_brain.nii.gz\"\n", "}\n" ] } ], "source": [ "%%bash\n", "cat example_invocation.json\n", "# The cat command prints the content of a file." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You are now all set to use the _exec_ command to launch an analysis. One catch: we assume you have Docker or Singularity installed. A fair assumption, nowadays? We hope so:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "%%bash\n", "bosh exec launch -s zenodo.1482743 ./example_invocation.json" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You can check that the output file was created as expected:" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from niwidgets import NiftiWidget\n", "my_widget = NiftiWidget('./test_brain.nii.gz')\n", "my_widget.nifti_plotter(colormap='gray')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This can also be reproduced with the Python API, by using function `bosh` from the `boutiques` module. This function accepts the same arguments as the command-line, in the form of a list. For instance:" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{\n", " \"infile\": \"f_infile_98.tex\",\n", " \"maskfile\": \"str_maskfile_eN\"\n", "}\n" ] } ], "source": [ "from boutiques import bosh\n", "out = bosh([\"example\", \"zenodo.1482743\"])\n", "print(out)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And to integrate with Python programs even better, you may want to use function `function` from module `boutiques.descriptor2func`. This will generate a Python function from a Boutiques descriptor, that you could use in any Python program. Here is an example that will run our BET tool:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from boutiques.descriptor2func import function\n", "fslbet = function(\"zenodo.1482743\")\n", "out = fslbet(infile=\"./data/test.nii.gz\", maskfile=\"test_brain.nii.gz\")\n", "print(out)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You now have a Python API for Boutiques tools, regardless of their original programming language!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Chaining tools\n", "\n", "Boutiques doesn't prescribe any pipeline language or engine. Feel free to use whichever you want! In its simplest form, `descriptor2func` makes it easy to chain tools in a Python program:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from boutiques.descriptor2func import function\n", "fslbet = function(\"zenodo.1482743\")\n", "fslstats = function(\"zenodo.3240521\")\n", "bet_out = fslbet(infile=\"./data/test.nii.gz\", maskfile=\"test_brain.nii.gz\")\n", "stats_out = fslstats(input_file=\"test_brain.nii.gz\", v=True)\n", "! cat output.txt" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Publishing your own tool\n", "\n", "\n", "So far we have been referring to Boutiques tools through their IDs/DOIs. Tools are described in a structured format where the tool interface and installation are specified. A Boutiques tool descriptor is a JSON file that fully describes the input and output parameters and files for a given command line call (or calls, as you can include pipes(`|`) and ampersands (`&`)). To help you describe and publish your tool, we will walk through the process of making a tool descriptor for [FSL's BET](http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/BET). The finished product is the one we used in the previous section (tool id: `zenodo.1482743`, also available as [fsl-bet-final.json](./fsl-bet-final.json))." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 0: Tool containerization\n", "\n", "A useful feature of Boutiques is its ability to refer to container images so that tools can be deployed transparently on multiple platforms. Although Boutiques can technically describe uncontainerized tools, we strongly recommend that you find or build a container image where your tool is available. Containers will make your work more reusable! \n", "\n", "In this tutorial, however, we won't be able to use containers as this notebook runs in Binder and Binder doesn't support running containers from notebooks." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 1: Describing the command line\n", "\n", "The first step in creating a tool descriptor for your command line call is creating a fully descriptive list of your command line options. If your tool was written in Python and you use the `argparse` library, then this is already done for you in large part. For many tools (bash, Python, or otherwise) this can be obtained by executing it with the `-h` flag. In the case of FSL BET, we get the following from our container image:" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Usage: bet [options]\n", "\n", "Main bet2 options:\n", " -o generate brain surface outline overlaid onto original image\n", " -m generate binary brain mask\n", " -s generate approximate skull image\n", " -n don't generate segmented brain image output\n", " -f fractional intensity threshold (0->1); default=0.5; smaller values give larger brain outline estimates\n", " -g vertical gradient in fractional intensity threshold (-1->1); default=0; positive values give larger brain outline at bottom, smaller at top\n", " -r head radius (mm not voxels); initial surface sphere is set to half of this\n", " -c centre-of-gravity (voxels not mm) of initial mesh surface.\n", " -t apply thresholding to segmented brain image and mask\n", " -e generates brain surface as mesh in .vtk format\n", "\n", "Variations on default bet2 functionality (mutually exclusive options):\n", " (default) just run bet2\n", " -R robust brain centre estimation (iterates BET several times)\n", " -S eye & optic nerve cleanup (can be useful in SIENA)\n", " -B bias field & neck cleanup (can be useful in SIENA)\n", " -Z improve BET if FOV is very small in Z (by temporarily padding end slices)\n", " -F apply to 4D FMRI data (uses -f 0.3 and dilates brain mask slightly)\n", " -A run bet2 and then betsurf to get additional skull and scalp surfaces (includes registrations)\n", " -A2 as with -A, when also feeding in non-brain-extracted T2 (includes registrations)\n", "\n", "Miscellaneous options:\n", " -v verbose (switch on diagnostic messages)\n", " -h display this help, then exits\n", " -d debug (don't delete temporary intermediate images)\n", "\n" ] } ], "source": [ "%%bash\n", "bet -h || true\n", "# \"|| true\" is just a trick to improve display in this notebook" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Looking at all of these flags, we see a list of options which can be summarized by:\n", "```\n", "bet [INPUT_FILE] [MASK] [FRACTIONAL_INTENSITY] [VERTICAL_GRADIENT] [CENTER_OF_GRAVITY] [OVERLAY_FLAG] [BINARY_MASK_FLAG] [APPROX_SKULL_FLAG] [NO_SEG_OUTPUT_FLAG] [VTK_VIEW_FLAG] [HEAD_RADIUS] [THRESHOLDING_FLAG] [ROBUST_ITERS_FLAG] [RES_OPTIC_CLEANUP_FLAG] [REDUCE_BIAS_FLAG] [SLICE_PADDING_FLAG] [MASK_WHOLE_SET_FLAG] [ADD_SURFACES_FLAG] [ADD_SURFACES_T2] [VERBOSE_FLAG] [DEBUG_FLAG]\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now that we have summarized all command line options for our tool - some of which describe inputs and others, outputs - we can begin to craft our JSON Boutiques tool descriptor." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 2: Understanding Boutiques + JSON\n", "\n", "For those unfamiliar with JSON, we recommend following this [3 minute JSON tutorial](http://www.secretgeek.net/json_3mins) to get you up to speed. In short, a JSON file is a dictionary object which contains *keys* and associated *values*. A *key* informs us what is being described, and a *value* is the description (which, importantly, can be arbitrarily typed). The Boutiques tool descriptor is a JSON file which requires the following keys, or, properties:\n", "- `name`\n", "- `description`\n", "- `tool-version`\n", "- `schema-version`\n", "- `command-line`\n", "- `inputs`\n", "\n", "Some additional, optional, properties that Boutiques will recognize are:\n", "- `groups`\n", "- `tool-version`\n", "- `suggested-resources`\n", "- `container-image`:\n", " - `type`\n", " - `image`\n", " - `index`\n", "\n", "The complete list of properties and their description is available [here](https://github.com/boutiques/boutiques/tree/master/schema).\n", "In the case of BET, we will of course populate the required elements, but will also include `groups` and `tags`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 3: Populating the tool descriptor\n", "\n", "bosh command _create_ will help you start with a minimal descriptor:" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": [ "%%bash\n", "bosh create fsl-bet.json" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This produced a template descriptor in [fsl-bet.json](./fsl-bet.json):" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{\n", " \"command-line\": \"echo [PARAM1] [PARAM2] [FLAG1] > [OUTPUT1]\",\n", " \"container-image\": {\n", " \"image\": \"user/image\",\n", " \"index\": \"docker://\",\n", " \"type\": \"singularity\"\n", " },\n", " \"description\": \"tool description\",\n", " \"error-codes\": [\n", " {\n" ] } ], "source": [ "%%bash\n", "head fsl-bet.json" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We will break-up populating the tool descriptor into two sections: adding meta-parameters (such as `name`, `description`, `schema-version`, `command-line`, and `tool-version`) and adding i/o-parameters (such as `inputs`, `output-files`, and `groups`)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Step 3.1: Adding meta-parameters\n", "\n", "Many of the meta-parameters will be obvious to you if you're familiar with the tool, or extractable from the message received earlier when you passed the `-h` flag into your program. We can update properties `name`, `tool-version`, `description`, `container-image` and `command-line` in our JSON (see current descriptor in [fsl-bet-metadata.json](fsl-bet-metadata.json)):" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " \"command-line\": \"bet [INPUT_FILE] [MASK] [FRACTIONAL_INTENSITY] [VERTICAL_GRADIENT] [CENTER_OF_GRAVITY] [OVERLAY_FLAG] [BINARY_MASK_FLAG] [APPROX_SKULL_FLAG] [NO_SEG_OUTPUT_FLAG] [VTK_VIEW_FLAG] [HEAD_RADIUS] [THRESHOLDING_FLAG] [ROBUST_ITERS_FLAG] [RES_OPTIC_CLEANUP_FLAG] [REDUCE_BIAS_FLAG] [SLICE_PADDING_FLAG] [MASK_WHOLE_SET_FLAG] [ADD_SURFACES_FLAG] [ADD_SURFACES_T2] [VERBOSE_FLAG] [DEBUG_FLAG]\",\n", " \"description\": \"Automated brain extraction tool for FSL\",\n", " \"command-line-flag\": \"-f\",\n", " \"name\": \"fsl_bet\",\n", " \"tool-version\": \"1.0.0\"\n" ] } ], "source": [ "%%bash\n", "grep -P \"fsl_bet|tool-version|Automated|command-line|image\" fsl-bet-metadata.json\n", "# grep is a useful command to find the lines in a text files that contain\n", "# specific patters, here \"fsl_bet\" or \"too-version\" ... \n", "# Here we use it to show the relevant lines of file fsl-bet-metadata.json" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Step 3.2: Adding i/o parameters\n", "\n", "Inputs and outputs of many applications are complicated - outputs can be dependent upon input flags, flags can be mutually exclusive or require at least one option, etc. The way Boutiques handles this is with a detailed schema which consists of options for inputs and outputs, as well as optionally specifying groups of inputs which may add additional layers of input complexity.\n", "\n", "As you have surely noted, tools may have many input and output parameters. This means that inputs, outputs, and groups, will be described as a list. Each element of these lists will be a dictionary following the input, output, or group schema, respectively. \n", "\n", "In the following sections, we will show you the dictionaries responsible for output, input, and group entries. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Step 3.2.1: Specifying inputs\n", "\n", "The input schema contains several options, many of which can be ignored in this first example with the exception of `id`, `name`, and `type`. For BET, there are several input values we can choose to demonstrate this for you. We have chosen four with considerably different functionality and therefore schemas. In particular:\n", "- `[INPUT_FILE]`\n", "- `[MASK]`\n", "- `[FRACTIONAL_INTENSITY]`\n", "- `[CENTER_OF_GRAVITY]`\n", "\n", "**`[INPUT_FILE]`** The simplest of these is the `[INPUT_FILE]` which is a required parameter that simply expects a qualified path to a file. The dictionary entry is:\n", "```\n", "{\n", " \"id\" : \"infile\",\n", " \"name\" : \"Input file\",\n", " \"type\" : \"File\",\n", " \"description\" : \"Input image (e.g. img.nii.gz)\",\n", " \"value-key\" : \"[INPUT_FILE]\"\n", "}\n", "```\n", "\n", "**`[MASK]`** This parameter is a string from which the output mask file name will be defined. The dictionary entry is:\n", "```\n", "{\n", " \"description\": \"Output brain mask (e.g. img_bet.nii.gz)\", \n", " \"value-key\": \"[MASK]\", \n", " \"type\": \"String\", \n", " \"optional\": false, \n", " \"id\": \"maskfile\", \n", " \"name\": \"Mask file\"\n", "}\n", "```\n", "\n", "**`[FRACTIONAL_INTENSITY]`** This parameter documents an optional flag that can be passed to the executable. Along with the flag, when it is passed, is a floating point value that can range from 0 to 1. We are able to validate at the level of Boutiques whether or not a valid input is passed, so that jobs are not submitted to the execution engine which will error, but they get flagged upon validation of inputs. This dictionary is:\n", "```\n", "{\n", " \"id\" : \"fractional_intensity\",\n", " \"name\" : \"Fractional intensity threshold\",\n", " \"type\" : \"Number\",\n", " \"description\" : \"Fractional intensity threshold (0->1); default=0.5; smaller values give larger brain outline estimates\",\n", " \"command-line-flag\": \"-f\",\n", " \"optional\": true,\n", " \"value-key\" : \"[FRACTIONAL_INTENSITY]\",\n", " \"minimum\" : 0,\n", " \"maximum\" : 1\n", "}\n", "```\n", "\n", "**`[CENTER_OF_GRAVITY]`** The center of gravity value expects a triple (i.e. [X, Y, Z] position) if the flag is specified. Here we are able to set the condition that the length of the list received after this flag is 3, by specifying that the input is a list that has both a minimum and maximum length.\n", "```\n", "{\n", " \"id\" : \"center_of_gravity\",\n", " \"name\" : \"Center of gravity vector\",\n", " \"type\" : \"Number\",\n", " \"description\" : \"The xyz coordinates of the center of gravity (voxels, not mm) of initial mesh surface. Must have exactly three numerical entries in the list (3-vector).\",\n", " \"command-line-flag\": \"-c\",\n", " \"optional\": true,\n", " \"value-key\" : \"[CENTER_OF_GRAVITY]\",\n", " \"list\" : true,\n", " \"min-list-entries\" : 3,\n", " \"max-list-entries\" : 3\n", "}\n", "```\n", "\n", "For further examples of different types of inputs, feel free to explore [more examples](https://github.com/aces/cbrain-plugins-neuro/tree/master/cbrain_task_descriptors)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Step 3.2.2: Specifying outputs\n", "\n", "The output schema also contains several options, with the only mandatory ones being `id`, `name`, and `path-template`. We again demonstrate an example from BET:\n", "- `outfile`\n", "\n", "**`outfile`** All of the output parameters in BET are similarly structured, and exploit the same core functionality of basing the output file, described by `path-template`, as a function of an input value on the command line, here given by `[MASK]`. The `optional` flag also describes whether or not a derivative should always be produced, and whether Boutiques should indicate an error if a file isn't found. The output descriptor is thus:\n", "\n", "```\n", "{\n", " \"id\" : \"outfile\",\n", " \"name\" : \"Output mask file\",\n", " \"description\" : \"Main default mask output of BET\",\n", " \"path-template\" : \"[MASK].nii.gz\",\n", " \"optional\" : true\n", "}\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Step 3.2.3: Specifying groups\n", "\n", "The group schema provides an additional layer of complexity when considering the relationships between inputs. For instance, if multiple inputs within a set are mutually exclusive, they may be grouped and a flag set indicating that only one can be selected. Alternatively, if at least one option within a group must be specified, the user can also set a flag indicating such. The following group from the BET implementation is used to illustrate this:\n", "- `variational_params_group`\n", "\n", "**`variational_params_group`** Many flags exist in BET, and each of them is represented in the command line we specified earlier. However, as you may have noticed when reading the output of `bet -h`, several of these options are mutually exclusive to one another. In order to again prevent jobs from being submitted to a scheduler and failing there, Boutiques enables grouping of inputs and forcing such mutual exclusivity so that the invalid inputs are flagged in the validation stage. This group dictionary is:\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```\n", "{\n", " \"id\" : \"variational_params_group\",\n", " \"name\" : \"Variations on Default Functionality\",\n", " \"description\" : \"Mutually exclusive options that specify variations on how BET should be run.\",\n", " \"members\" : [\"robust_iters_flag\", \"residual_optic_cleanup_flag\", \"reduce_bias_flag\", \"slice_padding_flag\", \"whole_set_mask_flag\", \"additional_surfaces_flag\", \"additional_surfaces_t2\"],\n", " \"mutually-exclusive\" : true\n", "}\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Step 3.3: Specifying tags (optional)\n", "\n", "You can also specify tags to help others find your tool once it's published:\n", "```\n", "\"tags\": {\n", " \"domain\": [ \"neuroimaging\", \"mri\" ]\n", " \"toolbox\": \"fsl\",\n", " \"brain extraction\": true\n", " }\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Step 3.4: Extending the tool descriptor (optional) \n", "\n", "Now that the basic implementation of this tool has been done, you can check out the [schema](https://github.com/boutiques/boutiques/tree/master/schema) to explore deeper functionality of Boutiques. For instance, you can specify `suggested-resources` to help platforms run your tool on HPC clusters or clouds." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Alternate path: Creating descriptors from Python scripts\n", "\n", "If you want a bit more of a head start and your tool is built in Python using the argparse library, you don't have to write your descriptor by hand! In the Python script with your argparser defined, simply add the following lines to get yourself a minimal corresponding descriptor:\n", "\n", "```\n", "import boutiques.creator as bc\n", "newDescriptor = bc.CreateDescriptor(myparser, execname=\"/command/to/run/exec\")\n", "newDescriptor.save(\"my-new-descriptor.json\")\n", "```\n", "\n", "There are additional custom arguments which can be supplied to this script, such as tags for your tool. It is also worth noting that no interpretation of output files is attempted by this tool, so your descriptor could certainly be enhanced by addind these and other features available through Boutiques, such as tests, tags, error codes, groups, and container images.\n", "\n", "Once you've created your descriptor this way you can translate your arguments to a Boutiques-style invocation using the following code block:\n", "\n", "```\n", "args = myparser.parse_args()\n", "invoc = newDescriptor.createInvocation(args)\n", "\n", "# Then, if you want to save them to a file...\n", "import json\n", "with open('my-inputs.json', 'w') as fhandle:\n", " fhandle.write(json.dumps(invoc, indent=4))\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 4: Validating the tool descriptor\n", "\n", "You just created a Boutiques descriptor - Congratulations! \n", "Now, you need to quickly validate it to make sure that you didn't accidentally break any rules in this definition (like requiring a \"flag\" input). You can validate your schema like this" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "OK\n" ] } ], "source": [ "%%bash\n", "# Here we use the final product of the FSL BET descriptor\n", "bosh validate fsl-bet-final.json" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Depending on the status of your descriptor, bosh will either tell you it's A-OK or tell you where the problems are and what you should fix. If you want to know more about some extra options packed into this validator, you can check them with `bosh validate -h`, as one may expect." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 5: Checking the descriptor\n", "\n", "You now have a valid tool descriptor, congratulations! It doesn't mean that it will do what you expect though. The _simulate_ command will help you check that the tool will generate meaningful command lines:" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Generated Command:\n", "bet f_infile_66.csv str_maskfile_7g \n" ] } ], "source": [ "%%bash\n", "# Command line without options\n", "bosh exec simulate fsl-bet-final.json" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Generated Command:\n", "bet f_infile_08.j str_maskfile_lT -f 0.64 -g 0.271 -c -13.316 32.532 42.799 -o -n -r -37.005 -t -R -d\n" ] } ], "source": [ "%%bash\n", "# Command line with all options\n", "bosh exec simulate -c fsl-bet-final.json" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The filenames and parameters were generated randomly within the valid ranges specified in the descriptor. This specific command line may not run, but you should check that it corresponds to what you had in mind. If anything seems fishy, you can update your descriptor and ensure you're describing the command-line you want. If you had a particular set of inputs in mind, you could pass them in with the `-i` flag. Again, as I'm sure you've guessed, you can learn more here with `bosh exec simulate -h`.\n", "\n", "You could now try to run the tool on actual data, as explained in Section [Reusing tools](#reusing_tools). " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 6: Publishing the descriptor\n", "\n", "Now that you have checked that your descriptor works as intended, it's time to publish it so that others can reuse it. To do that, you will first have to create an account on [Zenodo](http://zenodo.org), the publishing platform used by Boutiques. Once your Zenodo account is created, you should create an application token in the \"Applications\" menu so that _bosh_ can publish descriptors under your name:\n", "\n", "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Write down the access token that you have created, you will need it during publication.\n", "\n", "You are now all set to publish your descriptor! Be careful though: once it's published, there won't be any way to remove it, although you will be able to update it. If you want to try a dry-run publication, you can use option `--sandbox` of the _publish_ command. It will require that you create an account on Zenodo's [sandbox](https://sandbox.zenodo.org) and create an access token for it.\n", "\n", "In the example below, we use a common sandbox token:" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "10.5072/zenodo.295262\n" ] } ], "source": [ "%%bash\n", "# Assuming you have saved your tool in fsl-bet-final.json\n", "# Option -y answers 'yes' to all questions asked during publication\n", "bosh publish --sandbox -y --zenodo-token 5EvAz78stQAb3uGn28IyC6Ovjer0GsHpLfd2aumJVuIReGmed3Mo0YjAgntr fsl-bet-final.json" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Hooray, your tool is now published! It is now being shared in a packaged and fully described fashion, making it easier than ever to reproduce and extend your work! As always, learn more about this feature with `bosh publish -h`.\n", "\n", "You can find your tool the usual way:" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[ INFO ] Showing 10 of 12 results.\n", "ID TITLE DESCRIPTION DOWNLOADS\n", "zenodo.246085 PreFreeSurferPipelineBatch PreFreeSurferPipelineBatch HCP pipeline 0\n", "zenodo.264108 FNIRT FNIRT, as implemented in Nipype (module:... 0\n", "zenodo.265109 fsl_fast FAST (FMRIB's Automated Segmentation Too... 0\n", "zenodo.295207 tool name tool description 0\n", "zenodo.295262 fsl_bet-test Automated brain extraction tool for FSL 0\n", "zenodo.242580 Example Boutiques Tool This property describes the tool or appl... 0\n", "zenodo.252521 fsl_first FIRST is a model-based segmentation and ... 0\n", "zenodo.246081 fsl_probtrackx2 probabilistic tracking with crossing fib... 0\n", "zenodo.263338 FLIRT FLIRT, as implemented in Nipype (module:... 0\n", "zenodo.295213 tool name 1 tool description 0\n" ] } ], "source": [ "%%bash\n", "bosh search --sandbox fsl" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Check that your tool DOI shows in the list." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Advanced features\n", "\n", "\n", "### Evaluate Your Usage\n", "\n", "If you've been using your tool and forget what exactly that output file will be named, or if it's optional, but find re-reading the descriptor a bit cumbersome, you should just evaluate your invocation. If we wanted to check the location of our output corresponding to the id `outfile`, we could do the following query:" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{'outfile': 'test_brain.nii.gz.nii.gz'}\n" ] } ], "source": [ "%%bash\n", "bosh evaluate zenodo.1482743 ./example_invocation.json output-files/id=outfile" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Execution Records\n", "\n", "Want to check up on what happened during a previous analysis? The details of each execution are captured and recorded in a publicly safe format so that you can review past analysis runs. These records are stored in the Boutiques cache and capture each executions' descriptor, invocation and output results. Input and output file hashes are included to easily compare results between different analyses. `bosh data` is the command to interact and publish execution records. For instance, here is the record for one of your runs:" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{\n", " \"summary\": {\n", " \"name\": \"fsl_bet\",\n", " \"descriptor-doi\": \"10.5281/zenodo.1482743\",\n", " \"date-time\": \"2019-06-09T10:52:45.250677\"\n", " },\n", " \"public-invocation\": {\n", " \"infile\": {\n", " \"file-name\": \"test.nii.gz\",\n", " \"md5sum\": \"9daa5cff15e633a044b0df44a626abe1\"\n", " },\n", " \"maskfile\": \"test_brain.nii.gz\"\n", " },\n", " \"public-output\": {\n", " \"stdout\": null,\n", " \"stderr\": null,\n", " \"exit-code\": 127,\n", " \"error-message\": \"\",\n", " \"shell-command\": \"bet ./data/test.nii.gz test_brain.nii.gz \",\n", " \"missing-files\": {},\n", " \"output-files\": {}\n", " }\n", "}\n", "OK\n" ] } ], "source": [ "%%bash\n", "bosh data inspect -e" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Don't worry though, nothing gets public until you explicitly do so by running `bosh data publish`:" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[ INFO ] File fsl_bet_2019-06-09T10:52:45.250677.json has been removed from the data cache\n", "[ INFO ] File fsl_bet_2019-06-09T04:47:05.050745.json has been removed from the data cache\n", "[ INFO ] File fsl_bet_2019-06-09T10:52:04.202341.json has been removed from the data cache\n", "OK\n" ] } ], "source": [ "%%bash\n", "bosh data publish --sandbox -y" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Epilogue\n", "\n", "That's the end of this tutorial, we hope you enjoyed it. Don't hesitate to leave us feedback by submitting an issue at https://github.com/boutiques/boutiques-tutorial, we'd love to improve this material!\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.3" } }, "nbformat": 4, "nbformat_minor": 2 }