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<h1id="Helpful-Resources">Helpful Resources<aclass="anchor-link" href="#Helpful-Resources">¶</a></h1><h2id="Learn-more-about-Nipype">Learn more about Nipype<aclass="anchor-link" href="#Learn-more-about-Nipype">¶</a></h2><ul>
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<li><ahref="http://nipype.readthedocs.io/en/latest/">Nipype homepage</a>: This is the best place to learn all you need to know about Nipype. For beginner's I recommend to check out the <ahref="http://nipype.readthedocs.io/en/latest/quickstart.html">Quickstart</a> section.</li>
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<li><ahref="http://nipype.readthedocs.io/en/latest/">Nipype homepage</a>: This is the best place to learn all you need to know about Nipype. For beginner's, I recommend to check out the <ahref="http://nipype.readthedocs.io/en/latest/quickstart.html">Quickstart</a> section.</li>
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<li><ahref="http://miykael.github.io/nipype-beginner-s-guide/">Beginner's Guide</a>: This beginner's guide is an in-depth step by step tutorial to Nipype.</li>
<li><ahref="http://www.fmri4newbies.com/tutorials/">fMRI 4 Newbies</a>: A crash course in brain imaging.</li>
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<li><ahref="https://neurostars.org/">Neurostars.org</a>: If you have any questions about Neuroinformatics, this is the place to go! </li>
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<li><ahref="http://imaging.mrc-cbu.cam.ac.uk/imaging/DesignEfficiency">Design efficiency in FMRI</a>: A nice and detailed guide on how to design a good fMRI study.</li>
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</ul>
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<h2id="Open-Science-Resources">Open Science Resources<aclass="anchor-link" href="#Open-Science-Resources">¶</a></h2><p><ahref="https://twitter.com/aya_ben_yakov">Aya Ben-Yakov</a> put together a very <ahref="http://www.mrc-cbu.cam.ac.uk/openscience/resources/">nice and comprehensive list</a> of various tools and resources about open and reproducible science.</p>
<li><ahref="http://python.swaroopch.com/">A Byte of Python</a>: A very nice introduction to Python in general.</li>
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<li><ahref="http://nbviewer.jupyter.org/gist/rpmuller/5920182">A Crash Course in Python for Scientists</a>: a very good introduction to Python and scientific programming (e.g. Numpy, Scipy, Matplotlib)</li>
Copy file name to clipboardExpand all lines: notebooks/basic_data_output.ipynb
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"source": [
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"# Data Output\n",
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"\n",
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"Similarly important to data input is data output. Using a data output module allows you to restructure and rename computed output and to spatial differentiate relevant output files from the temporary computed intermediate files in the working directory. Nipype provides the following modules to handle data stream output:\n",
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"Similarly important to data input is data output. Using a data output module allows you to restructure and rename computed output and to spatially differentiate relevant output files from the temporary computed intermediate files in the working directory. Nipype provides the following modules to handle data stream output:\n",
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" DataSink\n",
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" JSONFileSink\n",
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"As we can see, there is way too much content that we might not really care about. To relocate and rename all the files that are relevant to you, you can use `DataSink`?"
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"As we can see, there is way too much content that we might not really care about. To relocate and rename all the files that are relevant to you, you can use `DataSink`."
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"cell_type": "markdown",
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"metadata": {},
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"This is already much better. But what if you want to rename the output files to represent something a bit readable. For this `DataSink` has the `substitution` input field.\n",
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"This is already much better. But what if you want to rename the output files to represent something a bit more readable. For this `DataSink` has the `substitution` input field.\n",
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"\n",
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"For example, let's assume we want to get rid of the string `'task-fingerfootlips'` and `'bold_mcf'` and that we want to rename the mean file, as well as adapt the file ending of the motion parameter file:"
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Cool, much more clearly!"
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"Cool, much clearer filenames!"
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Exercise 1\n",
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"Create a simple workflow for skullstriping with FSL, the first node should use `BET` interface and the second node will be a ``DataSink``. Test two method of connecting the nodes and check the content of the output directory."
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"Create a simple workflow for skullstriping with FSL, the first node should use `BET` interface and the second node will be a ``DataSink``. Test two methods of connecting the nodes and check the content of the output directory."
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