| 1 | TODO (Synapses) |
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| 2 | --------------- |
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| 3 | * faster S.w[:,i] (more generally, when 1 argument is :) |
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| 4 | in general, faster synapse_indexes() |
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| 5 | * Synapses with same underlying data (synaptic variables) as another Synapses object (for delayed STDP) |
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| 6 | |
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| 7 | * S[P,Q]='...' : with subgroups, shift the values of i,j |
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| 8 | * S[:,:]='i<j' : int |
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| 9 | * S[:,:]=array or sequence (boolean or int) |
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| 10 | |
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| 11 | * Update: Have namespaces partially built at run time (call state_(var)), |
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| 12 | or better, extract synaptic events from the synaptic state matrix; |
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| 13 | same stuff for postsynaptic variables |
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| 14 | * Synapses.compress(): have the Network object call it for all objects that have it? |
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| 15 | * accelerate Synapses.generate_code() (.any()) |
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| 16 | * compress: perhaps replace dynamic arrays by arrays |
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| 17 | * SynapticVariable: should be usable as a numpy array |
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| 18 | * deal with suffixes (v_post, v_pre) |
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| 19 | * Synapses.generate_code: check if postsynaptic variables are modified |
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| 20 | * More careful namespace creation in Synapses.update()(see reset/threshold) |
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| 21 | * SpikeQueue callback (to Synapses): this way the clock is only for state updates |
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| 22 | * Bound checks in setitem/getitem |
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| 23 | * Factor things in code generation |
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| 24 | * Faster queue: C version of propagate or insert? |
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| 25 | * Faster Synapses.update() |
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| 26 | * State updates |
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| 27 | * Replace spike queue data with a dynamic array object? |
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| 28 | * Replace NeuronGroup.__init__ with own stuff |
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| 29 | * include static variables in pre/post code |
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| 30 | * have a list of variable names |
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| 31 | * S.connect_random: fixed number of presynaptic neurons |
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| 32 | * S.connect_one_to_one (or 'i==j') |
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| 33 | * StateMonitor (already works with synapse indexes): |
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| 34 | what is needed is handling more general indexes in SynapticVariable |
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| 35 | (e.g. lists of tuples) |
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| 36 | * Code generation |
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| 37 | * Gap junctions |
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