Joel Lawhead wrote:
So each time I add data to metakit I want to:
1. Throw out duplicates (done)
2. Get the latest timestamp (done)
3. Remove targets and their trails 30+ seconds older than the latest timestamp. (not sure)
You can get this almost for free by ordering the column on epoch. Epoch will have to come first in the table definition.
orderedTable = table.ordered(1)
Then, add the data to the table. Now you can get the appropriate epochs by
lasttime = orderedTable[-1].epoch
# use locate to find the index of lasttime - 30, this is done using binary search
trailsMinus30index, count = orderedTable.locate(epoch=lasttime-30)
# now that we have the index, extract all epochs > trailsMinus30index
trailsMinus30 = orderedTable[trailsMinus30index:]
This is fairly easy :)
4. Group the targets by id (no problem)
5. Access each target id by group and sort it by head (the latest point) and trail (all the other track points). (not sure)
Any metakit view can be sorted, even the subview created by a groupby column. I've make a little test script for you to play with. The following uses in memory storages and is a great way to play with metakit data in the interpreter.
import metakit, random
st = metakit.storage()
vw = st.getas("test[epoch:I,id:I,date,latitude,longitude]")
vw = vw.ordered(1)for i in range(100): r = int(100*random.random()) id = int(4*random.random()) vw.append((r,id))
# extract the last epoch - 30 index, count = vw.locate(epoch=vw[-1].epoch-30) trails = vw[index:] # group by ids trails = trails.groupby(trails.id, "data")
# sort the data for each id by epoch metakit.dump(trails[0].data.sort(vw.epoch))
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