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fixing various typos in pynest docs #816

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merged 3 commits into from Sep 5, 2017
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fixing various typos in pynest docs #816

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7b05e21
fixing various typos in pynest docs
jessica-mitchell Aug 26, 2017
e5f94fa
fix formatting for ipython syntax
jessica-mitchell Sep 5, 2017
13c8702
fixing whitespace and IPython
jessica-mitchell Sep 5, 2017
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8 changes: 4 additions & 4 deletions extras/userdoc/md/documentation/part-1-neurons-and-simple-neural-networks.md
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Expand Up @@ -71,11 +71,11 @@ for.

dir(nest)

One such command is `nest.Models()`, which will return a list of all the
One such command is `nest.Models?`, which will return a list of all the
available models you can use. If you want to obtain more information about a
particular command, you may use Python’s standard help system.
particular command, you may use iPython’s standard help system.

nest.Models?
nest.Models?

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Thanks for changing.
Unfortunately there are still two little problems:

  • the i in iPython needs to be upper-case
  • there's a trailing whitespace in line 78, which needs to go away.

Sorry for being so niggling about this!

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No problem, thanks for your help

This will return the help text (docstring) explaining the use of this particular
function. There is a help system within NEST as well. You can open the help
Expand Down Expand Up @@ -377,7 +377,7 @@ current, and add a second neuron.
nest.SetStatus(neuron1, {"I_e": 376.0})
neuron2 = nest.Create("iaf_psc_alpha")
multimeter = nest.Create("multimeter")
nest.SetStatus(multimeter, {"withtime":True, "record_from":["V_m"]}
nest.SetStatus(multimeter, {"withtime":True, "record_from":["V_m"]})

We now connect `neuron1` to `neuron2`, and record the membrane potential from
`neuron2` so we can observe the postsynaptic potentials caused by the spikes of
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4 changes: 2 additions & 2 deletions extras/userdoc/md/documentation/part-2-populations-of-neurons.md
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Expand Up @@ -112,15 +112,15 @@ each of them, which is more efficient, and thus to be preferred. One way to do
it is to give a list of dictionaries which is the same length as the number of
nodes to be parameterised, for example using a list comprehension:

dVms = [{"V_m": Vrest+(Vth-Vrest)\*numpy.random.rand()} for x in epop1]
dVms = [{"V_m": Vrest+(Vth-Vrest)*numpy.random.rand()} for x in epop1]
nest.SetStatus(epop1, dVms)

If we only need to randomise one parameter then there is a more concise way by
passing in the name of the parameter and a list of its desired values. Once
again, the list must be the same size as the number of nodes to be
parameterised:

Vms = Vrest+(Vth-Vrest)\*numpy.random.rand(len(epop1))
Vms = Vrest+(Vth-Vrest)*numpy.random.rand(len(epop1))
nest.SetStatus(epop1, "V_m", Vms)

Note that we are being rather lax with random numbers here. Really we have to
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2 changes: 1 addition & 1 deletion extras/userdoc/md/documentation/part-3-connecting-networks-with-synapses.md
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Expand Up @@ -25,7 +25,7 @@ subdirectory: `pynest/examples/`.
## Parameterising synapse models

NEST provides a variety of different synapse models. You can see the available
models by using the command `Models(synapses)`, which picks only the synapse
models by using the command `nest.Models(mtype='synapses')`, which picks only the synapse
models out of the list of all available models.

Synapse models can be parameterised analogously to neuron models. You can
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