Merge pull request miykael#112 from miykael/grammar_correction

ENH: corrects grammar in files [skip ci]

Author: miykael

README.md

@@ -12,12 +12,12 @@
 This is the Nipype Tutorial in Jupyter Notebook format. You can access the tutorial in two ways:
 
 1. [Nipype Tutorial Homepage](https://miykael.github.io/nipype_tutorial/): This website contains a static, read-only version of all the notebooks.
-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.
+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.
 
 
 # Feedback, Help & Support
 
-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).
+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).
 
 
 # Thanks and Acknowledgment

index.ipynb

@@ -2,7 +2,7 @@
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@@ -24,8 +24,8 @@
        "            you everything so that you can start creating your own workflows in no time. We recommend that you start with\n",
        "            the introduction section to familiarize yourself with the tools used in this tutorial and then move on to the\n",
        "            basic concepts section to learn everything you need to know for your everyday life with Nipype. The workflow\n",
-       "            examples section shows you a real example how you can use Nipype to analyze an actual dataset. For a very \n",
-       "            quick non-imaging introduction, you can check the Nipype Quickstart notebooks in the introduciton section.\n",
+       "            examples section shows you a real example of how you can use Nipype to analyze an actual dataset. For a very \n",
+       "            quick non-imaging introduction, you can check the Nipype Quickstart notebooks in the introduction section.\n",
        "            </p><p>\n",
        "            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",
        "            But if you want to have the real experience and want to go through the computations by yourself, we highly\n",
@@ -39,9 +39,9 @@
        "            with working Python 3 software (including Nipype, dipy, matplotlib, nibabel, nipy, numpy, pandas, scipy, seaborn and more),\n",
        "            FSL, ANTs and SPM12 (no license needed). We used <a href=\"https://github.com/kaczmarj/neurodocker\">Neurodocker</a> to create this docker image.\n",
        "            </p><p>\n",
-       "            If you do not want to run tutorial locally, you can also use \n",
+       "            If you do not want to run the tutorial locally, you can also use \n",
        "            <a href=\"https://mybinder.org/v2/gh/miykael/nipype_tutorial/master\">Binder service</a>. \n",
-       "            Binder automatically launch the Docker container for you and you have access to all of the notebooks. \n",
+       "            Binder automatically launches the Docker container for you and you have access to all of the notebooks. \n",
        "            Note, that Binder provides between 1G and 4G RAM memory, some notebooks from Workflow Examples might not work. \n",
        "            All notebooks from Introduction and Basic Concepts parts should work.\n",
        "           </p><p>\n",
@@ -70,7 +70,7 @@
        "        <a class=\"subject-link pure-u-1-4\" target=\"_blank\" href=\"notebooks/introduction_quickstart_non-neuroimaging.ipynb\">Nipype Quickstart (non-neuroimaging examples)</a>\n",
        "      </div>\n",
        "      <p>This section is meant as a general overview. It should give you a short introduction to the main topics that\n",
-       "          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",
+       "          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",
        "\n",
        "      <h2 class=\"domain-header color02\"><a class=\"domain-title\">Basic Concepts</a></h2>\n",
        "      <div class=\"pure-g domain-table-container color02\">\n",
@@ -105,7 +105,7 @@
        "        <a class=\"subject-link pure-u-1-4\" target=\"_blank\" href=\"notebooks/handson_preprocessing.ipynb\">Hands-on 1: Preprocessing</a>\n",
        "        <a class=\"subject-link pure-u-1-4\" target=\"_blank\" href=\"notebooks/handson_analysis.ipynb\">Hands-on 1: Analysis</a>\n",
        "      </div>\n",
-       "      <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",
+       "      <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",
        "\n",
        "      <h2 class=\"domain-header color04\"><a class=\"domain-title\">Advanced Concepts</a></h2>\n",
        "      <div class=\"pure-g domain-table-container color04\">\n",
@@ -137,7 +137,7 @@
        "        <a class=\"subject-link pure-u-1-4\" target=\"_blank\" href=\"https://www.mindboggle.info/\">Mindboggle</a>\n",
        "        <a class=\"subject-link pure-u-1-4\" target=\"_blank\" href=\"https://timvanmourik.github.io/Porcupine/\">PORcupine</a>\n",
        "      </div>\n",
-       "      <p>This section will give you helpful links and resources, so that you always know where to go to learn more.</p>\n",
+       "      <p>This section will give you helpful links and resources so that you always know where to go to learn more.</p>\n",
        "\n",
        "    </div>\n",
        "  </article>\n",
@@ -190,8 +190,8 @@
     "            you everything so that you can start creating your own workflows in no time. We recommend that you start with\n",
     "            the introduction section to familiarize yourself with the tools used in this tutorial and then move on to the\n",
     "            basic concepts section to learn everything you need to know for your everyday life with Nipype. The workflow\n",
-    "            examples section shows you a real example how you can use Nipype to analyze an actual dataset. For a very \n",
-    "            quick non-imaging introduction, you can check the Nipype Quickstart notebooks in the introduciton section.\n",
+    "            examples section shows you a real example of how you can use Nipype to analyze an actual dataset. For a very \n",
+    "            quick non-imaging introduction, you can check the Nipype Quickstart notebooks in the introduction section.\n",
     "            </p><p>\n",
     "            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",
     "            But if you want to have the real experience and want to go through the computations by yourself, we highly\n",
@@ -205,9 +205,9 @@
     "            with working Python 3 software (including Nipype, dipy, matplotlib, nibabel, nipy, numpy, pandas, scipy, seaborn and more),\n",
     "            FSL, ANTs and SPM12 (no license needed). We used <a href=\"https://github.com/kaczmarj/neurodocker\">Neurodocker</a> to create this docker image.\n",
     "            </p><p>\n",
-    "            If you do not want to run tutorial locally, you can also use \n",
+    "            If you do not want to run the tutorial locally, you can also use \n",
     "            <a href=\"https://mybinder.org/v2/gh/miykael/nipype_tutorial/master\">Binder service</a>. \n",
-    "            Binder automatically launch the Docker container for you and you have access to all of the notebooks. \n",
+    "            Binder automatically launches the Docker container for you and you have access to all of the notebooks. \n",
     "            Note, that Binder provides between 1G and 4G RAM memory, some notebooks from Workflow Examples might not work. \n",
     "            All notebooks from Introduction and Basic Concepts parts should work.\n",
     "           </p><p>\n",
@@ -236,7 +236,7 @@
     "        <a class=\"subject-link pure-u-1-4\" target=\"_blank\" href=\"notebooks/introduction_quickstart_non-neuroimaging.ipynb\">Nipype Quickstart (non-neuroimaging examples)</a>\n",
     "      </div>\n",
     "      <p>This section is meant as a general overview. It should give you a short introduction to the main topics that\n",
-    "          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",
+    "          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",
     "\n",
     "      <h2 class=\"domain-header color02\"><a class=\"domain-title\">Basic Concepts</a></h2>\n",
     "      <div class=\"pure-g domain-table-container color02\">\n",
@@ -271,7 +271,7 @@
     "        <a class=\"subject-link pure-u-1-4\" target=\"_blank\" href=\"notebooks/handson_preprocessing.ipynb\">Hands-on 1: Preprocessing</a>\n",
     "        <a class=\"subject-link pure-u-1-4\" target=\"_blank\" href=\"notebooks/handson_analysis.ipynb\">Hands-on 1: Analysis</a>\n",
     "      </div>\n",
-    "      <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",
+    "      <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",
     "\n",
     "      <h2 class=\"domain-header color04\"><a class=\"domain-title\">Advanced Concepts</a></h2>\n",
     "      <div class=\"pure-g domain-table-container color04\">\n",
@@ -303,7 +303,7 @@
     "        <a class=\"subject-link pure-u-1-4\" target=\"_blank\" href=\"https://www.mindboggle.info/\">Mindboggle</a>\n",
     "        <a class=\"subject-link pure-u-1-4\" target=\"_blank\" href=\"https://timvanmourik.github.io/Porcupine/\">PORcupine</a>\n",
     "      </div>\n",
-    "      <p>This section will give you helpful links and resources, so that you always know where to go to learn more.</p>\n",
+    "      <p>This section will give you helpful links and resources so that you always know where to go to learn more.</p>\n",
     "\n",
     "    </div>\n",
     "  </article>\n",
@@ -332,19 +332,12 @@
     "</p>\n",
     "To inspect the html code of this page, click: <form action=\"javascript:code_toggle()\"><input type=\"submit\" value=\"Show HTML code\"></form>"
    ]
-  },
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-   "cell_type": "code",
-   "execution_count": null,
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-   "source": []
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   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python [default]",
    "language": "python",
    "name": "python3"
   },
@@ -358,7 +351,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.6.5"
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  "nbformat": 4,

notebooks/advanced_create_interfaces.ipynb

@@ -218,7 +218,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Now, we have a Python object ``nipype_ls`` that is a runnable nipype interface. After execution, Nipype interface return a result object. We can retrieve the output of our ``ls`` invocation from the ``result.runtime`` property:"
+    "Now, we have a Python object ``nipype_ls`` that is a runnable nipype interface. After execution, Nipype interface returns a result object. We can retrieve the output of our ``ls`` invocation from the ``result.runtime`` property:"
    ]
   },
   {
@@ -237,7 +237,7 @@
    "source": [
     "## Create your own `CommandLine` interface\n",
     "\n",
-    "Let's create a Nipype Interface for a very simple tool called ``antsTransformInfo`` from the [ANTs](http://stnava.github.io/ANTs/) package. This tool is so simple it does not even have an usage description for bash. Using it with a file, gives us the following result: "
+    "Let's create a Nipype Interface for a very simple tool called ``antsTransformInfo`` from the [ANTs](http://stnava.github.io/ANTs/) package. This tool is so simple it does not even have a usage description for bash. Using it with a file, gives us the following result: "
    ]
   },
   {
@@ -295,7 +295,7 @@
    "source": [
     "### Specifying the inputs\n",
     "\n",
-    "However, the ``args`` argument is too generic and does not deviate much from just running it in bash, or directly using ``subprocess.Popen``. Let's define the intputs specification for the interface, extending the ``nipype.interfaces.base.CommandLineInputSpec`` class.\n",
+    "However, the ``args`` argument is too generic and does not deviate much from just running it in bash, or directly using ``subprocess.Popen``. Let's define the inputs specification for the interface, extending the ``nipype.interfaces.base.CommandLineInputSpec`` class.\n",
     "\n",
     "The inputs are implemented using the Enthought traits package. For now, we'll use the ``File`` trait extension of nipype:"
    ]
@@ -374,7 +374,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Nipype will make sure that the parameters fullfil their prescribed attributes. For instance ``in_file`` is mandatory. An error is issued if we build the command line or try to run this interface without it:"
+    "Nipype will make sure that the parameters fulfill their prescribed attributes. For instance, ``in_file`` is mandatory. An error is issued if we build the command line or try to run this interface without it:"
    ]
   },
   {
@@ -489,7 +489,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We need to complete the functionallity of the ``run()`` member of our interface to parse the standard output. This is done extending its ``_run_interface()`` member.\n",
+    "We need to complete the functionality of the ``run()`` member of our interface to parse the standard output. This is done extending its ``_run_interface()`` member.\n",
     "\n",
     "When we define outputs, generally they need to be explicitly wired in the ``_list_outputs()`` member of the core class. Let's see how we can *complete* those:"
    ]
@@ -697,7 +697,7 @@
     "\n",
     "`CommandLine` interface is great, but my tool is already in Python - can I wrap it natively?\n",
     "\n",
-    "Sure. Let's solve the following problem: Let's say we have a Python function that takes an input image and a list of three translations (x, y, z) in mm, and than writes a resampled image after the translation has been applied:"
+    "Sure. Let's solve the following problem: Let's say we have a Python function that takes an input image and a list of three translations (x, y, z) in mm, and then writes a resampled image after the translation has been applied:"
    ]
   },
   {
@@ -790,7 +790,7 @@
    "source": [
     "## Quick approach - ``Function`` interface\n",
     "\n",
-    "Don't reinvent the wheel if it's not necessary. If, like in this case, we have a well-defined function we want to run with Nipype, it is fairly easy to solve it with the ``Function`` interface:"
+    "Don't reinvent the wheel if it's not necessary. If like in this case, we have a well-defined function we want to run with Nipype, it is fairly easy to solve it with the ``Function`` interface:"
    ]
   },
   {
@@ -816,9 +816,9 @@
     "\n",
     "***Note***: The inputs and outputs do not pass any kind of conformity checking: the function node will take any kind of data type for their inputs and outputs.\n",
     "\n",
-    "There are some other limitations for the ``Function`` interface when used inside workflows. Additionally, the function must be totally self-contained, since it will run with no global context. In practice, it means that **all the imported modules and variables must be defined within the context of the function**.\n",
+    "There are some other limitations to the ``Function`` interface when used inside workflows. Additionally, the function must be totally self-contained, since it will run with no global context. In practice, it means that **all the imported modules and variables must be defined within the context of the function**.\n",
     "\n",
-    "For more, checkout the [Function Node](basic_function_nodes.ipynb) notebook."
+    "For more, check out the [Function Node](basic_function_nodes.ipynb) notebook."
    ]
   },
   {
@@ -868,7 +868,7 @@
     "\n",
     "Now, we face the problem of interfacing something different from a command line. Therefore, the ``CommandLine`` base class will not help us here. The specification of the inputs and outputs, though, will work the same way.\n",
     "\n",
-    "Let's start from that point. Our Python function takes in three inputs: (1) the input image, (2) the translation and (3) an output image.\n",
+    "Let's start from that point on. Our Python function takes in three inputs: (1) the input image, (2) the translation and (3) an output image.\n",
     "\n",
     "The specification of inputs and outputs must be familiar to you at this point. Please note that now, input specification is derived from ``BaseInterfaceInputSpec``, which is a bit thinner than ``CommandLineInputSpec``. The output specification can be derived from ``TraitedSpec`` as before:"
    ]
@@ -1116,7 +1116,7 @@
     "  total = sum(data(:) > 0)\n",
     "  ```\n",
     "  \n",
-    "The following example, uses ``scipy.io.savemat`` to convert the input image to `MATLAB` format. Once the file is loaded we can quickly extract the estimated total volume.\n",
+    "The following example uses ``scipy.io.savemat`` to convert the input image to `MATLAB` format. Once the file is loaded we can quickly extract the estimated total volume.\n",
     "\n",
     "***Note:*** For the purpose of this example, we will be using the freely available `MATLAB` alternative `Octave`. But the implementation of a `MATLAB` interface will be identical."
    ]