diff --git a/README.md b/README.md index ab90e4d..42ffcda 100644 --- a/README.md +++ b/README.md @@ -62,9 +62,9 @@ where `c++ ROOT` isn't available. To set your backend, simply set the option `backend = 'uproot'` or `backend = 'ROOT'` when making your histograms (see the notebooks in `examples/` for more information. -**If no backend is declared, hepPlotter will first try to set the backend to c++ ROOT. +**If no backend is declared, hepPlotter will first try to set the backend to `c++ ROOT`. If that is unavailable, hepPlotter will try to use `uproot` as the backend.** -You can see the `backend` defined +You can see how the `backend` is defined [here](https://github.com/demarley/hepPlotter/blob/master/python/plotter.py#L136-L162). _If you are using raw data or binned data (stored in arrays), use the `uproot` backend._ @@ -74,9 +74,8 @@ _If you are using raw data or binned data (stored in arrays), use the `uproot` b ### Data/MC in 2 Dimensions Most commonly, data/mc plots are just for 1-dimensional distributions. -You can plot 2-dimensional data/mc plots, but this is not natively supported in hepPlotter. -Instead, as a user you can pass a 2-dimensional histogram (representing data/mc) -to hepPlotter to capture the ratio. +It is possible to plot 2-dimensional data/mc plots, but this is not natively supported in hepPlotter. +Instead, as a user you can pass a 2-dimensional histogram that represents the data/mc ratio to hepPlotter. Here is an example snippet of code: ``` @@ -99,7 +98,7 @@ hist.colorbar['title'] = "Data/MC" # text label for colorbar hist.initialize() # sets the parameters of the plot # Add data to the plot - just an example (not stored in example.root) -total_mc_hist = file.Get("totalMC2D") # access 2D MC data (may need to add multiple backgrounds together) +total_mc_hist = file.Get("totalMC2D") # access 2D MC data (may need to add multiple histograms) data_hist = file.Get("data2D") # access 2D data data_hist.Divide(total_mc_hist) # get the ratio hist.Add(datamc,name="datamc")