Changes for page BluePyOpt

Last modified by abonard on 2025/04/10 15:12

From version 1.1
edited by adavison
on 2023/02/27 16:46
Change comment: There is no comment for this version
To version 7.1
edited by abonard
on 2025/04/10 15:03
Change comment: There is no comment for this version

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1 -XWiki.adavison
1 +XWiki.abonard
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1 -Available tutorials:
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3 -* [[Creating a simple cell optimisation>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/simplecell/simplecell.ipynb||rel=" noopener noreferrer" target="_blank"]] (beginner)
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3 +* ((( ==== **[[Beginner >>||anchor = "HBeginner-1"]]** ==== )))
4 +
5 +* ((( ==== **[[Intermediate >>||anchor = "HIntermediate-1"]]** ==== )))
6 +
7 +=== **Beginner** ===
8 +
9 +=== [[Creating a simple cell optimisation>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/simplecell/simplecell.ipynb||rel=" noopener noreferrer" target="_blank"]] ===
10 +
11 +**Level**: beginner(%%) **Type**: interactive tutorial
12 +
13 +This notebook will explain how to set up an optimisation of simple single compartmental cell with two free parameters that need to be optimised. As this optimisation is for example purpose only, no real experimental data is used in this notebook.
14 +=== [[Optimisation using the CMA evolutionary strategy>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/cma_strategy/cma.ipynb||rel=" noopener noreferrer" target="_blank"]] ===
15 +
16 +**Level**: beginner(%%) **Type**: interactive tutorial
17 +
18 +This notebook will explain how to optimise a model using the covariance matrix adaptation (CMA) optimisation strategy. BluePyOpt includes two flavors of CMA: a single objective one and a hybrid single/multi objective one.
19 +=== [[Optimising synaptic parameters>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/expsyn/ExpSyn.ipynb||rel=" noopener noreferrer" target="_blank"]] ===
20 +
21 +**Level**: beginner(%%) **Type**: interactive tutorial
22 +
23 +This notebook shows how the parameters of a NEURON point process (in this case a synapse), can be optimised using BluePyOpt.
24 +=== **Intermediate** ===
25 +
26 +=== [[Creating an optimisation with meta parameters>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/metaparameters/metaparameters.ipynb||rel=" noopener noreferrer" target="_blank"]] ===
27 +
28 +**Level**: intermediate(%%) **Type**: interactive tutorial
29 +
30 +This notebook will explain how to set up an optimisation that uses metaparameters (parameters that control other parameters)
31 +=== [[Setup of a cell model with multi electrode simulation for local field potential recording>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/l5pc_lfpy/L5PC_LFPy.ipynb||rel=" noopener noreferrer" target="_blank"]] ===
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33 +**Level**: intermediate(%%) **Type**: interactive tutorial
34 +
35 +This notebook will demonstrate how to instantiate a cell model and evaluator that include local field potential (LFP) computation and its recording using a simulated multi electrode array (MEA).
36 +