Currently if you specify an odour subset that includes a duplicate odour (e.g. the blank) it errors out suggesting you might like to subset by channel numbers. But there is a special case when CO2 is being delivered and the same channel number is associated with another odour. For this case it is better just to subset by odour name, but remove any duplicate waves for odours that we have requested.

If the same numbered channel is used with two different labels in an ODD config, merge.spiketimes will try to merge all data from that numbered channel but then confuses the channel labels.

1. warn/error when there are duplicated channel numbers
2. use number+label to uniquely identify channels.

Note that 2. could break some cells somewhere unless we only use label when number alone is insufficient to identify. We might recognise this e.g. by checking that every row of data has the same number of stimulations.

i.e. they should not be counted for the purpose of N in the calculation of S

> as.repeatedTrain(Spikes2[[200]],xlim-c(0,3000))
$OilBl
Error in plot.window(...) : need finite 'xlim' values
In addition: Warning messages:
1: In FUN(X[[4L]], ...) : no non-missing arguments to max; returning -Inf
2: In FUN(X[[4L]], ...) : no non-missing arguments to max; returning -Inf
3: In FUN(X[[4L]], ...) : no non-missing arguments to max; returning -Inf
4: In FUN(X[[4L]], ...) : no non-missing arguments to max; returning -Inf

Fundamentally, this may involve some changes to the STAR package to incorporate a notion of the time window over which spikes were mesasured (even if there were no spikes).

Unfortunately the start of the pulse is only recorded in the pxp file that determines the TTL pulse.

@sfrechter came across this recently for e.g. file 4 of this cell /Volumes/JData5/JPeople/Shahar/Data/151231/nm20151231c0 when he was trying out odour shuffling.

The docs for divide say the following:

FIXME Teach this to cope with repeat blocks with different odours in different order

This will make it easier to attach other information such as the analogue voltage traces later on. The place to do this is in CollectSpikesFromSweeps but we will need to make sure that this propagates through e.g. merge and divide.spiketimes.

The main motivation for this is to deal with Shahar's data collection with shuffled odour presentations. At the moment this works for spikes (see #13) but not for the average voltage traces which are therefore averages of the wrong sweeps. Previously we have been using Igor to generate those average waves. Now we will need to do it in R.

This will be essential to prepare for an eventual CRAN release.

This one is easy in principle (with some change of interface).

scale:
  function(x, center, scale)
scale.ts:
  function(waves, yrange)

to match OdourResponseFromSpikes rather than a PlotFrequency arg

Hi @jefferis,

Would you please provide the manual to run gphys?

Thank you.

... because sometimes we want to plot a spike response without subtracting a baseline count

(see also #3)
This one is not so obvious to me:

split:
  function(x, f, drop, ...)
split.spiketimes:
  function(st, blocksize)

maybe I need to change the function name

was not treating values <=1 as fractions

• and then the ability to rbind the response vectors (perhaps as multi time series?)