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apdavison

Ticket Summary Component Milestone Type Created
Description
#64 Check that behaviour of `neuron` and `nest2` modules is independent of the number of processors unspecified Release 0.5.0 task 04/03/08
#100 Test for IF_cond exp and alpha do not work on NEST2 all Release 0.4.2 defect 06/21/08

Problem is linked to the delay of the synapses. It seems that using a 0.01 timestep instead of a 0.1 one triggers a problem. Need to check

#26 Add `Population` method for easily specifying neuron location in space common Release 0.5.0 enhancement 05/16/07

Currently, the positions of neurons in space can only be specified by iterating over the whole population in Python, and using the setPosition() method of the ID class.

We should add a new method or methods to the Population class that allows the positions to be specified from a numpy array or using some algorithm, e.g., 'random positioning within a cylindrical volume', 'hexagonal close packed with separation x', etc.

Might be worth looking at neuroConstruct to see how Padraig Gleeson does it.

#37 Allow changing of individual connection parameters in low-level API common Release 0.5.0 enhancement 01/08/08

see r141. The nest2 module has a Connection class, which we could implement for the other modules as well.

#102 SubPopulation should be extracted from a Population object all Release 0.5.0 enhancement 06/21/08

It could be useful to be able to extract Population objects from a Population, meaning to have SubPopulations?. I don't really know what will be the simplest and nicest way to do that, but that's just a proposal.

#113 Add `Projection.record_weights()` or something similar all Release 0.6.0 enhancement 08/27/08
#8 Create a NEURON equivalent of Eilif's adapting I&F model in NEST hoc Release 0.5.0 task 04/24/07

The adapting I&F neuron should be a standard model. This exists in NEST, and I think it exists in PCSIM, so a NEURON version is needed.

#18 Test multicompartmental models with `neuron` module unspecified Release 0.5.0 task 04/24/07

As a test of the adequacy of the connection/projection API, a test model that contains multi-compartmental neurons and multiple synaptic locations within the cells. An olfactory bulb model would be a particularly challenging example, as the bulb has both axo-dendritic and dendro-dendritic synapses

#91 cellparams in create() and Population() common Release 0.5.0 defect 05/05/08

The cellparams-(dictionary)-arguments passed to create() and Population.init() have different names (param_dict & cellparams, respectively). Since the same dict is passed, they should be called the same...

#118 `FixedNumberPre/PostConnector(n, allow_self_connections=False)` do not guarantee to create `n` connections all Release 0.5.0 defect 10/03/08

As these are currently implemented, if the pre- and post-synaptic populations are the same and we do not allow a neuron to connect to itself, we first pick n sources/targets and then remove any that have pre neuron==post neuron. This means that sometimes there are n-1 connections.

It would be better to first remove the no-connections-allowed neuron from the list before picking the n values.

#35 Access to neuron variables via properties of the ID class common Release 0.5.0 enhancement 11/14/07

Cell parameters can be accessed using the ID class, e.g. cell1.tau_m. It might also be nice to access variables, such as the membrane potential, as cell1.v, etc.

#38 Standard way to specify a time varying current injection common Release 0.5.0 enhancement 01/08/08

It would be nice to be able to inject a time varying current into any standard cell in a simulator-independent way. This could be done in two ways:

(1) Create a new standard cell, CurrentSource, and extend connect(), Projection to allow non-synaptic connections

(2) Create an Electrode class, then either

(a) allow the i_offset parameter of each standard cell to be an Electrode object rather than a float.

(b) create an inject() function in the low-level API and/or an inject() method for the ID object.

I don't much like (1), since it does not fit with the general principle of spike-based communication, although if we allow gap-junction connections in future, it would fit better.

Concerning (2), if we add RC-circuit properties to the Electrode class, it could also be used to extend record_v().

(2b) would probably be simpler to implement than (2a)

#55 Add `describe()` method to `Population`, `Projection` and other PyNN classes common Release 0.5.0 enhancement 03/22/08

The describe() method would return a human-readable description of the object, summarizing type, label, component members, parameter values (including range, mean, etc if these are heterogeneous).

The idea behind this is to make it easier to spot bugs in your (and PyNN's) code, to spot obvious differences between what you think you've built and what has actually been built.

The syntax I have in mind is something along the lines of:

describe(self, template=default_template, renderer=default_renderer)

where renderer should be an object with a render(data, template) method. [describe() calls render() with the provided template and a data dict, and returns the string returned by render()].

This will give the flexibility to easily tune the output (level of verbosity, format (plain text, HTML, XML, JSON)) without having to modify the describe() method itself.

#65 Add a `get_simulator()` function common Release 0.5.0 enhancement 04/09/08

Currently, I tend to do: 

  import sys
  simulator = sys.argv[1]
  exec("import pyNN.%s as sim" % simulator)

to let the simulator be specified on the command line.

To reduce this to a single statement, and add error checking, it would be useful to encapsulate it in a function in common, and use optparse from the standard library to handle passing additional arguments and options.

#92 IF_cond_exp and IF_cond_alpha not implemented in nest1 nest Release 0.4.2 enhancement 05/12/08

they exist but are not implemented in nest1 (or generate an error for IF_cond_exp).

to reproduce:

In [1]: import pyNN.nest1 as sim

In [2]: sim.setup()

(snip)

In [5]: sim.create(sim.IF_cond_alpha)

NotImplementedError? Traceback (most recent call last)

/home/perrinet/NeuroTools/examples/single_neuron/<ipython console> in <module>()

/home/perrinet/python/site-packages/pyNN/nest1/init.py in create(cellclass, param_dict, n)

178 assert n > 0, 'n must be a positive integer' 179 if isinstance(cellclass, type):

--> 180 celltype = cellclass(param_dict)

181 cell_gids = pynest.create(celltype.nest_name, n) 182 cell_gids = [ID(pynest.getGID(gid)) for gid in cell_gids]

/home/perrinet/python/site-packages/pyNN/common.py in init(self, *args, **kwargs)

583 584 def init(self, *args, **kwargs):

--> 585 raise NotImplementedError?("The %s model is not available for this simulator." % self.class.name)

586 587 # ==============================================================================

NotImplementedError?: The IF_cond_alpha model is not available for this simulator.

In [6]: sim.create(sim.IF_cond_exp)

SLIError Traceback (most recent call last)

/home/perrinet/NeuroTools/examples/single_neuron/<ipython console> in <module>()

/home/perrinet/python/site-packages/pyNN/nest1/init.py in create(cellclass, param_dict, n)

179 if isinstance(cellclass, type): 180 celltype = cellclass(param_dict)

--> 181 cell_gids = pynest.create(celltype.nest_name, n)

182 cell_gids = [ID(pynest.getGID(gid)) for gid in cell_gids] 183 pynest.setDict(cell_gids, celltype.parameters)

/usr/local/lib/python2.5/site-packages/pynest/hl_api.py in create(objstr, count)

97 98 for n in range(count):

---> 99 sr(objstr+' Create')

100 cobj+=[spp()] 101 return cobj

/usr/local/lib/python2.5/site-packages/pynest/hl_api.py in catching_sr(cmd)

55 errorname = spp() 56 commandname = spp()

---> 57 raise SLIError, 'PyNEST SLI error in sr(): '+errorname+' in '+commandname

58 59 # set the deault sr function to the one that catches errors

SLIError: PyNEST SLI error in sr(): UndefinedName? in iaf_cond_exp

In [7]:

#114 `dummy` or `test` module to check argument types, etc in code before starting a time-consuming run all Release 0.5.0 enhancement 09/09/08

Sometimes code that follows a long, tedious build or run has incorrect argument types, etc It would be nice to be able to catch these bugs before running the script on the real simulator

My suggested way to do this would be to run with import pyNN.dummy

#1 Combine print() and print_v() into a single write() that takes what-to-print as an argument unspecified Release 0.5.0 task 04/24/07

Some simulators allow writing variables other than spike times and membrane potential to file. To support these, we should have a single function and a single Population method for writing variables to file.

Also, python tends to use write(), rather than print(), for this kind of thing.

This should be done in a separate branch until we've made a release with the current API.

#42 Refactoring of connection book-keeping in `nest2` nest2 Release 0.5.0 task 02/19/08

A general refactoring of connection book-keeping in nest2 is needed. We are storing too much information in the Projection class that is also stored within NEST. It might be slightly slower to have to look it up when needed, but there should be a large decrease in memory required.

Currently, we store 1D arrays _sources, _targets, and _targetPorts, so 3xNxM values, assuming all-to-all connectivity between a Population of size N and one of size M. If we assume that cell ids in a Population are consecutive (this is the case, but should be more strictly checked), then it is not necessary to store anything except the first id in a Population - we simply filter the connection dicts returned by nest.GetConnections() and keep only the connections that have target ids within the post-synaptic population. This might be complicated somewhat when running a distributed simulation.

Need to create some performance benchmarks to check that the performance hit of the lookups is not too great.

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