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README.md

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This is the Nipype Tutorial in Jupyter Notebook format. You can access the tutorial in two ways:
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1. [Nipype Tutorial Homepage](https://miykael.github.io/nipype_tutorial/): This website contains a static, read-only version of all the notebooks.
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2. [Nipype Tutorial Docker Image](https://miykael.github.io/nipype_tutorial/notebooks/introduction_docker.html): This guide explains how to use docker to run the notebooks interactively on your own computer. The nipype tutorial docker image is the best interactive way to learn Nipype.
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2. [Nipype Tutorial Docker Image](https://miykael.github.io/nipype_tutorial/notebooks/introduction_docker.html): This guide explains how to use Docker to run the notebooks interactively on your own computer. The nipype tutorial docker image is the best interactive way to learn Nipype.
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# Feedback, Help & Support
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If you want to help with this tutorial or have any questions, fell free to fork the repo of the [Notebooks](https://github.com/miykael/nipype_tutorial) or interact with other contributors on the slack channel [brainhack.slack.com/messages/nipype/](https://brainhack.slack.com/messages/nipype/). If you have any questions or found a problem, open a new [issue on github](https://github.com/miykael/nipype_tutorial/issues).
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If you want to help with this tutorial or have any questions, feel free to fork the repo of the [Notebooks](https://github.com/miykael/nipype_tutorial) or interact with other contributors on the slack channel [brainhack.slack.com/messages/nipype/](https://brainhack.slack.com/messages/nipype/). If you have any questions or found a problem, open a new [issue on github](https://github.com/miykael/nipype_tutorial/issues).
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# Thanks and Acknowledgment

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" you everything so that you can start creating your own workflows in no time. We recommend that you start with\n",
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" the introduction section to familiarize yourself with the tools used in this tutorial and then move on to the\n",
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" basic concepts section to learn everything you need to know for your everyday life with Nipype. The workflow\n",
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" examples section shows you a real example how you can use Nipype to analyze an actual dataset. For a very \n",
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" quick non-imaging introduction, you can check the Nipype Quickstart notebooks in the introduciton section.\n",
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" examples section shows you a real example of how you can use Nipype to analyze an actual dataset. For a very \n",
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" quick non-imaging introduction, you can check the Nipype Quickstart notebooks in the introduction section.\n",
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" </p><p>\n",
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" All of the notebooks used in this tutorial can be found on <a href=\"https://github.com/miykael/nipype_tutorial\">github.com/miykael/nipype_tutorial</a>.\n",
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" But if you want to have the real experience and want to go through the computations by yourself, we highly\n",
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" This docker container gives you the opportunity to adapt the commands to your liking and discover the flexibility and real power of\n",
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" Nipype yourself.\n",
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" </p><p>\n",
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" To run the tutorial locally on your system, we will use a <a href=\"http://www.docker.com/\">Docker</a> container. For this you\n",
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" To run the tutorial locally on your system, we will use a <a href=\"http://www.docker.lcom/\">Docker</a> container. For this you\n",
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" need to install Docker and download a docker image that provides you a neuroimaging environment based on a Debian system,\n",
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" with working Python 3 software (including Nipype, dipy, matplotlib, nibabel, nipy, numpy, pandas, scipy, seaborn and more),\n",
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" FSL, ANTs and SPM12 (no license needed). We used <a href=\"https://github.com/kaczmarj/neurodocker\">Neurodocker</a> to create this docker image.\n",
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" </p><p>\n",
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" If you do not want to run tutorial locally, you can also use \n",
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" If you do not want to run the tutorial locally, you can also use \n",
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" <a href=\"https://mybinder.org/v2/gh/miykael/nipype_tutorial/master\">Binder service</a>. \n",
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" Binder automatically launch the Docker container for you and you have access to all of the notebooks. \n",
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" Binder automatically launches the Docker container for you and you have access to all of the notebooks. \n",
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" Note, that Binder provides between 1G and 4G RAM memory, some notebooks from Workflow Examples might not work. \n",
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" All notebooks from Introduction and Basic Concepts parts should work.\n",
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" </p><p>\n",
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" <a class=\"subject-link pure-u-1-4\" target=\"_blank\" href=\"notebooks/introduction_quickstart_non-neuroimaging.ipynb\">Nipype Quickstart (non-neuroimaging examples)</a>\n",
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" </div>\n",
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" <p>This section is meant as a general overview. It should give you a short introduction to the main topics that\n",
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" you need to understand to use Nipype and this tutorial. The section also contains a very short neuroimaging showcase, as well as as quick non-imaging introduction to Nipype workflows.</p>\n",
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" you need to understand to use Nipype and this tutorial. The section also contains a very short neuroimaging showcase, as well as quick non-imaging introduction to Nipype workflows.</p>\n",
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"\n",
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" <h2 class=\"domain-header color02\"><a class=\"domain-title\">Basic Concepts</a></h2>\n",
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" <div class=\"pure-g domain-table-container color02\">\n",
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" <a class=\"subject-link pure-u-1-4\" target=\"_blank\" href=\"notebooks/handson_preprocessing.ipynb\">Hands-on 1: Preprocessing</a>\n",
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" <a class=\"subject-link pure-u-1-4\" target=\"_blank\" href=\"notebooks/handson_analysis.ipynb\">Hands-on 1: Analysis</a>\n",
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" </div>\n",
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" <p>In this section you will find some practical examples and hands-on that show you how to use Nipype in a \"real world\" scenario.</p>\n",
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" <p>In this section, you will find some practical examples and hands-on that show you how to use Nipype in a \"real world\" scenario.</p>\n",
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"\n",
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" <h2 class=\"domain-header color04\"><a class=\"domain-title\">Advanced Concepts</a></h2>\n",
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" <div class=\"pure-g domain-table-container color04\">\n",
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" <a class=\"subject-link pure-u-1-4\" target=\"_blank\" href=\"https://www.mindboggle.info/\">Mindboggle</a>\n",
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" <a class=\"subject-link pure-u-1-4\" target=\"_blank\" href=\"https://timvanmourik.github.io/Porcupine/\">PORcupine</a>\n",
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" </div>\n",
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" <p>This section will give you helpful links and resources, so that you always know where to go to learn more.</p>\n",
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" <p>This section will give you helpful links and resources so that you always know where to go to learn more.</p>\n",
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"\n",
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" </div>\n",
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" </article>\n",
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" you everything so that you can start creating your own workflows in no time. We recommend that you start with\n",
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" the introduction section to familiarize yourself with the tools used in this tutorial and then move on to the\n",
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" basic concepts section to learn everything you need to know for your everyday life with Nipype. The workflow\n",
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" examples section shows you a real example how you can use Nipype to analyze an actual dataset. For a very \n",
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" quick non-imaging introduction, you can check the Nipype Quickstart notebooks in the introduciton section.\n",
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" examples section shows you a real example of how you can use Nipype to analyze an actual dataset. For a very \n",
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" quick non-imaging introduction, you can check the Nipype Quickstart notebooks in the introduction section.\n",
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" </p><p>\n",
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" All of the notebooks used in this tutorial can be found on <a href=\"https://github.com/miykael/nipype_tutorial\">github.com/miykael/nipype_tutorial</a>.\n",
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" But if you want to have the real experience and want to go through the computations by yourself, we highly\n",
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" This docker container gives you the opportunity to adapt the commands to your liking and discover the flexibility and real power of\n",
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" Nipype yourself.\n",
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" </p><p>\n",
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" To run the tutorial locally on your system, we will use a <a href=\"http://www.docker.com/\">Docker</a> container. For this you\n",
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" To run the tutorial locally on your system, we will use a <a href=\"http://www.docker.lcom/\">Docker</a> container. For this you\n",
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" need to install Docker and download a docker image that provides you a neuroimaging environment based on a Debian system,\n",
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" with working Python 3 software (including Nipype, dipy, matplotlib, nibabel, nipy, numpy, pandas, scipy, seaborn and more),\n",
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" FSL, ANTs and SPM12 (no license needed). We used <a href=\"https://github.com/kaczmarj/neurodocker\">Neurodocker</a> to create this docker image.\n",
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" </p><p>\n",
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" If you do not want to run tutorial locally, you can also use \n",
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" If you do not want to run the tutorial locally, you can also use \n",
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" <a href=\"https://mybinder.org/v2/gh/miykael/nipype_tutorial/master\">Binder service</a>. \n",
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" Binder automatically launch the Docker container for you and you have access to all of the notebooks. \n",
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" Binder automatically launches the Docker container for you and you have access to all of the notebooks. \n",
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" Note, that Binder provides between 1G and 4G RAM memory, some notebooks from Workflow Examples might not work. \n",
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" All notebooks from Introduction and Basic Concepts parts should work.\n",
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" </p><p>\n",
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" <a class=\"subject-link pure-u-1-4\" target=\"_blank\" href=\"notebooks/introduction_quickstart_non-neuroimaging.ipynb\">Nipype Quickstart (non-neuroimaging examples)</a>\n",
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" </div>\n",
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" <p>This section is meant as a general overview. It should give you a short introduction to the main topics that\n",
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" you need to understand to use Nipype and this tutorial. The section also contains a very short neuroimaging showcase, as well as as quick non-imaging introduction to Nipype workflows.</p>\n",
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" you need to understand to use Nipype and this tutorial. The section also contains a very short neuroimaging showcase, as well as quick non-imaging introduction to Nipype workflows.</p>\n",
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"\n",
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" <h2 class=\"domain-header color02\"><a class=\"domain-title\">Basic Concepts</a></h2>\n",
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" <div class=\"pure-g domain-table-container color02\">\n",
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" <a class=\"subject-link pure-u-1-4\" target=\"_blank\" href=\"notebooks/handson_preprocessing.ipynb\">Hands-on 1: Preprocessing</a>\n",
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" <a class=\"subject-link pure-u-1-4\" target=\"_blank\" href=\"notebooks/handson_analysis.ipynb\">Hands-on 1: Analysis</a>\n",
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" </div>\n",
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" <p>In this section you will find some practical examples and hands-on that show you how to use Nipype in a \"real world\" scenario.</p>\n",
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" <p>In this section, you will find some practical examples and hands-on that show you how to use Nipype in a \"real world\" scenario.</p>\n",
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"\n",
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" <h2 class=\"domain-header color04\"><a class=\"domain-title\">Advanced Concepts</a></h2>\n",
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" <div class=\"pure-g domain-table-container color04\">\n",
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" <a class=\"subject-link pure-u-1-4\" target=\"_blank\" href=\"https://www.mindboggle.info/\">Mindboggle</a>\n",
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" <a class=\"subject-link pure-u-1-4\" target=\"_blank\" href=\"https://timvanmourik.github.io/Porcupine/\">PORcupine</a>\n",
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" </div>\n",
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" <p>This section will give you helpful links and resources, so that you always know where to go to learn more.</p>\n",
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" <p>This section will give you helpful links and resources so that you always know where to go to learn more.</p>\n",
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"\n",
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" </div>\n",
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" </article>\n",
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