PyMISP/examples/situational-awareness/README.md

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## Explanation
* treemap.py is a script that will generate an interactive svg (attribute\_treemap.svg) containing a treepmap representing the distribution of attributes in a sample (data) fetched from the instance using "last" or "searchall" examples.
* It will also generate a html document with a table (attribute\_table.html) containing count for each type of attribute.
* test\_attribute\_treemap.html is a quick page made to visualize both treemap and table at the same time.
* tags\_count.py is a script that count the number of occurences of every tags in a fetched sample of Events in a given period of time.
* tag\_search.py is a script that count the number of occurences of a given tag in a fetched sample of Events in a given period of time.
* Events will be fetched from _days_ days ago to today.
* _begindate_ is the beginning of the studied period. If it is later than today, an error will be raised.
* _enddate_ is the end of the studied period. If it is earlier than _begindate_, an error will be raised.
* tag\_search.py allows research for multiple tags is possible by separating each tag by the | symbol.
* Partial research is also possible with tag\_search.py. For instance, search for "ransom" will also return tags containin "ransomware".
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* tags\_to\_graphs.py is a script that will generate several plots to visualise tags distribution.
* The studied _period_ can be either the 7, 28 or 360 last days
* _accuracy_ allows to get smallers splits of data instead of the default values
* _order_ define the accuracy of the curve fitting. Default value is 3
* It will generate two plots comparing all the tags:
* tags_repartition_plot that present the raw data
* tags_repartition_trend_plot that present the general evolution for each tag
* Then each taxonomies will be represented in three plots:
* Raw datas: in plot folder, named with the name of the corresponding taxonomy
* Trend: in plot folder, named _taxonomy_\_trend. general evolution of the data (linear fitting, curve fitting at order 1)
* Curve fitting: in plotlib folder, name as the taxonomy it presents.
:warning: These scripts are not time optimised
## Requierements
* [Pygal](https://github.com/Kozea/pygal/)
* [Matplotlib](https://github.com/matplotlib/matplotlib)