# Plot of RMS/Mean from TProfile

I have some code which fills a nice TProfile graph, from which I can see the mean of all the entries in each bin as the bin content, with the RMS of those entries as the vertical error bar of that bin content. I would like to see a graph of the ratio RMS/mean for each bin, but searching on RootTalk yielded only partial answers.

In the end I tried two strategies but they seem to give different results. In one case, I did:

``` mean = h.ProjectionX() rms = h.ProjectionX('','C=E') rms.Divide(mean)```
where h is the original TProfile. This seems to work and gives a reasonable graph.

Separately, I did a more convoluted:

``````convert_type = numpy.double
rmsovermean = [h.GetBinError(i)/h.GetBinContent(i) for i in range(h.GetNbinsX())
if h.GetBinContent(i) !=0]
myX = [X[i] for i in range(h.GetNbinsX()) if h.GetBinContent(i) != 0]
rmsovermean = numpy.asarray(rmsovermean,dtype=numpy.double)
myX = numpy.asarray(myX,dtype=numpy.double)
gr_rmsovermean = ROOT.TGraph(len(rmsovermean),myX,rmsovermean)``````

where X is an array of the X coordinates used when filling the TProfile.

While the two give comparable results, they are not equal entry-by-entry. I know one of them is a TGraph and one is a TH1D, but there must be some other misunderstanding on my part between the two processes. Can someone perhaps explain the difference?

The TH1D is binned and hence does not retain the input data with full precision while the TGraph keeps/tracks the original input data … See the User’s Guide for more details.

Philippe.