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1 | .. _kernel_install: | |
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2 | ||
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3 | Kernel Installation | |
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4 | ------------------- | |
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5 | ||
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6 | IPython can be installed (different python versions, virtualenv or conda environments) can | |
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7 | be installed as a kernel by following these steps: | |
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8 | ||
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9 | * make sure that the desired python installation is active (e.g. activate the environment) | |
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10 | and ipython is installed | |
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11 | * run once ``ipython kernelspec install-self --user`` (or ``ipython2 ...`` or ``ipython3 ...`` | |
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12 | if you want to install specific python versions) | |
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13 | ||
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14 | The last command installs a kernel spec file for the current python installation in | |
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15 | ``~/.jupyter/kernels/``. Kernel spec files are JSON files, which can be viewed and changed with a | |
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16 | normal text editor. |
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1 | .. _plotting: | |
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2 | ||
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3 | Plotting | |
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4 | -------- | |
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5 | One major feature of the Jupyter notebook is the ability to display plots that | |
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6 | are the output of running code cells. The IPython kernel is designed to work | |
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7 | seamlessly with the matplotlib_ plotting library to provide this functionality. | |
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8 | ||
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9 | To set this up, before any plotting is performed you must execute the | |
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10 | ``%matplotlib`` :ref:`magic command <magics_explained>`. This performs the | |
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11 | necessary behind-the-scenes setup for IPython to work correctly hand in hand | |
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12 | with ``matplotlib``; it does *not*, however, actually execute any Python | |
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13 | ``import`` commands, that is, no names are added to the namespace. | |
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14 | ||
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15 | If the ``%matplotlib`` magic is called without an argument, the | |
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16 | output of a plotting command is displayed using the default ``matplotlib`` | |
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17 | backend in a separate window. Alternatively, the backend can be explicitly | |
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18 | requested using, for example:: | |
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19 | ||
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20 | %matplotlib gtk | |
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21 | ||
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22 | A particularly interesting backend, provided by IPython, is the ``inline`` | |
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23 | backend. This is available only for the Jupyter Notebook and the | |
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24 | :ref:`IPython QtConsole <qtconsole>`. It can be invoked as follows:: | |
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25 | ||
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26 | %matplotlib inline | |
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27 | ||
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28 | With this backend, the output of plotting commands is displayed *inline* | |
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29 | within the notebook, directly below the code cell that produced it. The | |
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30 | resulting plots will then also be stored in the notebook document. | |
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31 | ||
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32 | .. seealso:: | |
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33 | ||
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34 | `Plotting with Matplotlib`_ example notebook |
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