Comments (1)
mstimberg
commented on May 17, 2024
Even though we are now using numpy's random number generator both in Python and in C++, it's not trivial to get the same random numbers in both cases. Setting the seed is not quite enough if you have more than one random variable: At every timestep, Python will consume the first N numbers for xi_1 and another N numbers for xi_2. C++ on the other hand, will consume the first for xi_1, the second for xi_2, the third for xi_1, etc. A way to make it work would be to have two randn functions, one for each variable -- but that would make things complicated, again...
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Related Issues (20)
- Incompatible with numpy version >= 1.20 due to deprecated aliases HOT 5
- SpatialNeuron (spatialstateupdate) fails with numpy without scipy HOT 7
- Improve parser for model descriptions HOT 1
- Improve the MarkDown exporter
- Use randomised timesteps to avoid artificial synchronisation
- Improve Pyodide support
- [Question] Regarding the spatial neuron equation HOT 2
- GSL incompatibility with latest Cython beta
- Problem with storing Neurongroups in dictionaries HOT 1
- the Izhikevich_2007 example neuron model bug HOT 4
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- Random number generation on C++ standalone is slow HOT 3
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