bin value are not unique

[shawnhsueh]

I found that in line 544-548 of pymbar/fes.py you wrote

                # how do we label the bins? if N-dimensional:
                # bins[0] + bins[1]*bin_length[1]**1 + bins[2]*bin_length[2]**2
                sample_label[n] = int(
                    np.sum([bin_n[n][d] * bin_length[d] ** d for d in range(dims)])
                )

However, this setting can not give unique bin values. For example, given bin_length=[100,2], bins=(30,1) and bins=(32,0) would have the same bin value of 32 (i.e. 30*100**0+1*2**1=32*100**0+0*2**1=32).

Non-unique bin values would cause under-counting of histogram_data["bin_order"] in line 566-576 of pymbar/fes.py

        if b == 0:
            bin_order = {}
            i = 0
            for bv in bin_label.values():
                if bv not in bin_order:
                    bin_order[bv] = i
                    i += 1
            histogram_data["bin_order"] = bin_order
            histogram_data["bin_label"] = bin_label
        else:
            bin_order = self.histogram_data["bin_order"]

I would suggest to correct line 546-548 of pymbar/fes.py to be

                sample_label[n] = int(
                    np.sum([bin_n[n][d] * np.sum(bin_length[:d+1]) ** d for d in range(dims)])
                )

[mikemhenry]

@shawnhsueh would you be willing to make this change and submit a PR?

Thanks!

[mikemhenry]

We can then discuss the proposed change there. Normally it is good to talk about the plan for the change before writing the code, but this seems like a small enough fix to jump straight to a PR (pull request).

[shawnhsueh]

OK. I've created a pull request #478.