RCP: 0.7.5, AHC, the number of clusters tool bar spinner should adjust its maximum value according to the columns/rows current computing mode

The number of clusters tool bar spinner should adjust its maximum value according to the columns/rows current computing mode. At this moment, there’s an R eval error, if the clusters number is higher than the number of entries.
The TBX AHC class should also implements some tests about this.

(from redmine: issue id 836, created on 2014/05/28 by Sebastien Jacquot)

assigned to @project_3134_bot_c287846fb4704c83fd27510cd997e5a9

added type::feature ui + 1 deleted label

changed milestone to %TXM 0.8.1

The verification tests have been implemented in the UI.
The maximum number of clusters has been fixed as this : rows count - 1 and columns count –1, according to the computing mode (rows or columns) for CA and Lexical Table because FatoMineR can’t compute a AHC where the cluster numbers is equals to the number of rows/cols. Is it normal ?

Other tasks to do:

- add a test, when the CAH command will be available from the Partition nodes, to check if the parts number is greater than 3 (a CAH need at least 4 parts ? Actually I think FactoMine R can compute 3 parts AHC dendrogram but can not generate the clusters, need to recheck this point) DONE

- FactoMineR seems to manage a maximum of 16 clusters when plotting with plot.HCPC(), it may be a FactoMineR bug linked to the plotting of inertia barplot
We can see when computing a AHC on rows that the barplot never exceeds 16 bars and trying to plot more than 16 clusters results in an error in R source code. After some tests plot.HCPC() with argument tree.barplot=FALSE can exceed 16 clusters. A solution may be to plot the inertia barplot in another SWT component with plot.HCPC (res.hcpc, choice = "bar"), as for the CA singular values.
The results generated by HCPC() and used in AHC can contain more clusters than 16 but FactoMineR doesn’t seems to manage to draw them with plot.HCPC(). At this moment, I fixed the max clusters to 16 in the UI tool bar. We may investigate this and also limit the maximum clusters to 16 in the AHC preference page, if it’s confirmed. NOTE: We could generate charts with more clusters directly form the HCPC() result by using the JFC charts engine since it doesn’t use plot.HCPC(). In this case we need to find a way to define the max clusters count outside the AHC class, maybe at the charts engine levels, e.g. ChartsEngine.getMaxAvailableClusters(AHC ahc) which could return 16 for the R implementation and the real maximum for the JFC implementation

• define if implement these verifications at AHC TBX level, before/during step computing, is useful

(from redmine: written on 2014/06/04 by Sebastien Jacquot)

New issue for other points: #2740

(from redmine: written on 2020/01/23 by Sebastien Jacquot)

closed

assigned to @sjacquot and unassigned @project_3134_bot_c287846fb4704c83fd27510cd997e5a9

added charts tool::ahc labels

changed title from RCP: 0.7.5, CAH, the number of clusters tool bar spinner should adjust its maximum value according to the columns/rows current computing mode to RCP: 0.7.5, AHC, the number of clusters tool bar spinner should adjust its maximum value according to the columns/rows current computing mode

changed the description