-
```
It is possible to build a spatially structured randomisation, where labels
are assigned randomly to groups based on spatial location such that there
is greater structure in the randomly generated …
-
```
A useful randomisation, which is essentially a cross-validation approach, is to
randomly delete some subset of labels from the cloned basedata, and then assess
how stable the analysis results ar…
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One potentially useful addition to the structured randomisations is to use the abundance based species richness estimators (Chao1, ACE) implemented in #420 to define the target richness scores.
Thi…
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Profiling indicates some of the bottlenecks are where a global precalc needs to be recalculated for each iteration of a randomisation. One example is the tree with equal length branches.
It shou…
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```
It would be useful to be able to take a tree generated separately from the
basedata and attach it as a cluster or similar output.
This would enable users to run analyses outside of Biodiverse …
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From Ann Wheeler:
> This all needs to be scriptable so if one has 100 - 200 images Fiji can munch through them and generate an results file exportable to Excel with:
>
> Columns corresponding to:
> …
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I'm getting low performance on non-replicated datasets...
What are recommendations for optimizing xor and ec goal data for high throughput?
I'm trying raid instead of jbod on chunkservers, but it see…
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We will be relying on the `allocated_on` date to calculate the Follow Up windows, so we need to ensure this data is accurate. However, all data entered from prior to the system going live in mid-Jan 2…
-
```
Currently the code works like this: transactions are received, their Merkle
branches are verified. They are sent to listeners and if the listeners find
them relevant, they are considered true po…
-
```
Currently the code works like this: transactions are received, their Merkle
branches are verified. They are sent to listeners and if the listeners find
them relevant, they are considered true po…