I mainly used jetheme to build my genealogical tree, which is a merge between information I wrote in structured yaml files, gedcom files coming from family members and information retrieved by program on genealogical sites (16 pieces of my genealogical tree merged with the information I typed).
Then I implemented chi square tests on Gauquelin data from cura.free.fr. I wrote the whole chain : define a group, pre-compute all useful informations (astrological and numerological data of the persons of the group), compute expected and observed repartitions, display repartitions, compute chi square and p-values. I observed planetary effects everywhere ! Meaningless because expected repartitions were not correctly implemented : I started to implement Gauquelin 1957 book for astronomical corrections using what Ertel calls method n°4 (Gauquelin's standard method) in the book "The tenacious mars effect" (Ertel / Irving, 1996), p SE - 39. Then realized that I would need supplementary information to compute demographical deviations. I decided to generate expected repartitions using shuffling (called methods 5 and 6 by Ertel), and didn't do it because time was missing.
I then realized that the first thing to do is to gather data and started an other program, Gauquelin5.
Jetheme is installed on my machine, I use it occasionaly to work on my genealogical tree ; I haven't worked on it since 2017, but I'll be back on this software.
I have not published jetheme code because it's really at a draft stage.
Main flaws of the program :
The storage. I'm stuck with graph databases because there is no standard like SQL for relational databases. SPARQL from W3C, Cypher from neo4j, Cayley from Google... the Gremlins API ? I didn't know which solution to adopt. Then I used a relational database (postgresql) to simulate a graph database structure, using YAGO model
(s, p, o, t, l, x)- subject predicate object time location context. I found that really great : I have only one type of table to store all type of data : person, parent-child relation, person-group relation etc. Great because I can add new types of things in the storage without changing the structure of the database. The inconvenient is that I must implement myself the navigation through the graph. Current implementation works, using cache and pre-computations for complex queries, but it's not designed to scale to large datasets, and my purpose is not to implement graph dtabase on top of postgresql !
- The database structure is too complex : each user of the application has one postgresql cluster, to guarantee a separation of data and secure the privacy. Convenient because a user have at his/her disposal several databases, each composed by several schemas. But too heavy to manage.
- The program can import gedcom files and yaml files written in a syntax called jth1. But exporting a tree managed by jetheme to a standard format (gedcom) has not been coded. This is a major inconvenient because it makes users prisonner from jetheme.
List of domiciles
Genealogical tree with sun position in sign (not Grothendieck)
Ancestors, radial view (not Grothendieck)
Atrology group - Sun in signs
A1, Sun in sign, round view
A1, Mars in Gauquelin sectors, flat view
A1, numerology on birth date, round view
LearnSome notions used by jetheme are made browsable.