On Wed, Aug 15, 2012 at 12:33 PM, Adam Dershowitz
<adershow...@exponent.com>wrote:
> I am trying to find all cases where a value transitions above a
> threshold. So, my code first does a getwherelist to find values that are
> above the threshold, then it uses that list to find immediately prior
> values that are below. The code is working, but the second part, searching
> through just a smaller subset is much slower (First search is on the order
> of 1 second, while the second is a minute).
> Is there any way to get this second part of the search in-kernal? Or any
> more general way to do a search for values above a threshold, where the
> prior value is below?
> Essentially, what I am looking for is a way to speed up that second search
> for "all rows in a prior defined list, where a condition is applied to the
> table"
>
> My table is just seconds and values, in chronological order.
>
> Here is the code that I am using now:
>
> h5data = tb.openFile("AllData.h5","r")
> table1 = h5data.root.table1
>
> #Find all values above threshold:
> thelist= table1.getWhereList("""Value > 150""")
>
> #From the above list find all values where the immediately prior value
> is below:
> transition=[]
> for i in thelist:
> if (table1[i-1]['Value'] < 150) and (i != 0) :
> transition.append(i)
>
Hey Adam,
Sorry for taking a while to respond. Assuming you don't mind one of these
being <= or >=, you don't really need the second loop with a little index
arithmetic:
import numpy as np
inds = np.array(thelist)
dinds = inds[1:] - inds[:-1]
transition = dinds[(1 < dinds)]
This should get you an array of all of the transition indices since
wherever the difference in indices is greater than 1 the Value must have
dropped below the threshold and then returned back up.
Be Well
Anthony
>
> Thanks,
>
>
>
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