Store histograms in a large array depending on location in for loop

I'm trying to store histograms in an array full of nested arrays that are created in multiple for a loop.

The error that I am getting is that: 'TH1F' object has no attribute 'append'

Here's an example of how the code works (a simplified version):

hist = []
for c in range 2:  
  hist.append([])

  for e in range 4: 
    hist[c].append([])
    hist_m = ROOT.TH1F("some name","some name",0,0.0,50.0)
    hist[c][e].append(hist_m)

    for z in range 8:
      hist[c][e].append([])
      hist_m = ROOT.TH1F("some name","some name",0,0.0,50.0)
      hist[c][e][z].append(hist_m)  #crashes here

      for pT in range 32:
        hist[c][e][z].append([])
        hist_m = ROOT.TH1F("some name","some name",0,0.0,50.0)
        hist[c][e][z][pT].append(hist_m)

I'm trying to store all of these different histograms inside of this large array so that I can use them later in the code by simply using the index. But I am getting the error

'TH1F' object has no attribute 'append'

which I don't know how to fix. Any solutions?

The code crashes on this line:

hist[c][e][z].append( hist )

Thanks in advance!

Solution

Here, and in other places, you're overwriting your hist variable that otherwise points to the large "array" you're building:

hist = ROOT.TH1F("some name","some name",0,0.0,50.0)

Use a different name ...

EDIT: since you now changed the naming, consider that you first add a TH1F:

hist[c][e].append(hist_m)

and afterwards a fresh list:

hist[c][e].append([])

so now the first element of list hist[c][e] is a TH1F, the second is a new list. Ie., you have:

[[[<ROOT.TH1F object ("some name") at 0x556fd65038d0>, []]]]

and zero indexing (c == e == z == 0) selects that TH1F.

The data structure as you seem to envision (an indexing being both a histogram if no further indexing happens, but a list if it does), isn't going to work. (Granted, you can add a __getitem__ method to the TH1F class to return a list, but that'd be a rather odd thing to do.)

If you want to have a large, indexable, "array" of histograms, those histograms will all have to be on the final leaf nodes.