PhD Information: Difference between revisions

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== Essential Software ==
== Essential Software ==
See the page on [https://www.imk-tro.kit.edu/trowiki/index.php?title=Software Software]
The following is a list of essential software packages and the links to their web pages:

==== CDO ====
https://code.mpimet.mpg.de/projects/cdo/.

Note that CDO has a lot of built-in functions that are not well documented, but details about these can be usually found in their discussion forums, https://code.mpimet.mpg.de/projects/cdo/boards.

==== Python ====
Instructions on how to download and install Python for all OSs can be found at: https://www.python.org/.

It is usually recommended to use the Anaconda distribution to install Python. Details on how to do this are here: https://www.anaconda.com/

Python can be combined with a good Integrated Development Environment (IDE) of your choice. All existing IDEs have their pros and cons. Some of the most popular IDEs are the following:

*IDLE [https://docs.python.org/3/library/idle.html]
*PyCharm [https://www.jetbrains.com/pycharm/]
*Visual Studio Code[https://code.visualstudio.com/]
*Sublime Text [https://www.sublimetext.com/3]
*Jupyter [https://jupyter.org/]
*Atom [https://www.javatpoint.com/atom-python]
*Spyder [https://www.spyder-ide.org/]

Python boasts a large number of packages. Some of the most used packages for manipulating large files in NetCDF, HDF5 or CSV formats are the following:

'''Data analysis''':
*NumPy [https://numpy.org/]
*xarray [https://docs.xarray.dev/en/stable/#]
*pandas [https://pandas.pydata.org/]
*SciPy [https://scipy.org/]
'''Parallel computing, Machine learning, Deep learning etc.''':
*dask [https://www.dask.org/]
*scikit-learn [https://scikit-learn.org/stable/]
*Keras [https://keras.io/]
*PyTorch [https://pytorch.org/]
*TensorFlow [https://www.tensorflow.org/]
'''Data visualization''':
*seaborn [https://seaborn.pydata.org/]
*matplotlib [https://matplotlib.org/]
*Bokeh [https://docs.bokeh.org/en/latest/]
*plotly [https://plotly.com/]
*Geoplotlib [https://github.com/andrea-cuttone/geoplotlib]
*NcView for .nc files [https://cirrus.ucsd.edu/~pierce/software/ncview/quick_intro.html]

Most of these packages are distributed through either '''Conda''' [https://docs.conda.io/projects/conda/en/latest/user-guide/concepts/installing-with-conda.html] or '''Pip''' [https://packaging.python.org/en/latest/tutorials/installing-packages/].

On top of these, various users also create packages tuned for specific purposes. They are usually made public through '''GitHub''' [https://github.com/python].

Various forums exist for the sole purpose of clearing specific questions about coding. One such forum is '''stackoverflow'''[https://stackoverflow.com/]. '''Medium''' [https://medium.com/] is also a good source for reading up about new ideas and tools in Python and other languages.

Revision as of 10:57, 26 May 2023

This wiki hopes to cover most information regarding the admin part about doing a PhD at IMK, however there are many other places that also supply information and some are listed here.


General Information for PhD Students

A nice overview about doing a doctorate at IMK(TRO) can be found here.


PhD Council and Representatives

We have now started a PhD Council at IMK with two representatives in charge of the contact with the group leaders. We are informally in charge of adding things to this wiki as well as other projects for improving PhD life at IMK. If you are interested in joining us or you have small or big ideas send us an email at imk-phd-council@lists.kit.edu!

We are aiming at organising a bi-annual PhD Assembly to improve our networking as well as an opportunity to voice any concerns. These will hopefully be in conjunction with the semester start and will be announced in the TRO Newsletter as well through the PhD emailing lists.


Business trips

Please see the page on business trips.


On-boarding Checklist

Registering as a PhD Student

The registration procedure can be quite complicated for a new PhD student, here is the information given on the latest PhD Induction day.


Further information can be found here:

Teaching

A nice intro to teaching at the IMK can be found here.

Essential Software

See the page on Software