Create labhacks.md

Author: Patrick Beukema

labhacks.md

@@ -18,20 +18,24 @@ Use it for writing experimental code, scanner code, bash scripts and so on.
 
 * Use [jupyter notebooks](http://jupyter.readthedocs.io/en/latest/index.html) for development and for analysis pipelines. Install [Kyle Dunovan's](https://github.com/dunovank) [jupyter themes](https://github.com/dunovank/jupyter-themes) to make your notebooks pretty and work faster. 
 
-* Make an "autopilot" script for your analyses, so that figures (and even posters if you are feeling ambitious) are updated in real time while the data is collected. Write a [cron job](http://www.adminschoice.com/crontab-quick-reference) to execute an autopilot.py script that updates imaging and behavioral analyses and then sends an email with your figures automatically. You can find some autpilot examples [here](https://github.com/pbeukema/rsaRemap/blob/master/modmap_autopilot.py). 
+* Make an "autopilot" script for your analyses, so that figures (and even posters if you are feeling ambitious) are updated in real time while the data is collected. Write a [cron job](http://www.adminschoice.com/crontab-quick-reference) to execute an autopilot script that integrates newly collected data and updates analyses perhaps with an email summarizing the results sent to you or your advisor. You can find some autpilot examples [here](https://github.com/pbeukema/rsaRemap/blob/master/modmap_autopilot.py). 
 
 * Make a startup file for your jupyter notebooks that preloads modules like numpy and scipy to save you time and also so that your figures are always publication quality, from the get go, without modification. The config file can specify font sizes, legends, color themes etc.
 
 ##  Programming 
 * Start using github. It is excellent for version control and for sharing (instead of having analysis_v4_p3.2_final.py you just have analysis.py). Other researchers can replicate exactly what you did. This will save you time, if someone emails you for example. 
 
+* Need to sync files across your various lab computers/clusters and laptop you use at home and don't want to use Dropbox? Use [rsync](https://www.digitalocean.com/community/tutorials/how-to-use-rsync-to-sync-local-and-remote-directories-on-a-vps) instead. 
+```bash
+rsync -zavr -e ssh --delete --include '*/' --include='*include_these_files.[ext]' --exclude='*' [local_dir] [remote_server]:[remote_dir]
+```
 * You or your lab may be most familiar with Matlab. It is worth considering a switch to [Python](https://www.python.org/). Python offers simpler syntax, enables system wide interfacing, is open source, free and for these reasons is being used by more and more scientists. Replication is far easier with Python than Matlab. 
 
 * Thomas Wiecki provides a [great introduction](http://nbviewer.jupyter.org/format/slides/github/twiecki/pydata_ninja/blob/master/PyData%20Ninja.ipynb#/) to becoming a python data ninja.
 
 * [Anaconda](https://www.continuum.io/downloads) provides a scientific distribution of python that enables high performance computing and analysis. 
 
-* Become a pro at [bash shortcuts](https://ss64.com/bash/syntax-keyboard.html) - it will seriously save you a lot of time. 
+* Become a pro at [bash shortcuts](https://ss64.com/bash/syntax-keyboard.html)- it will seriously save you a lot of time. 
 
 * Simulate data and make sure that your analysis works the way you think that it is working.