Hello All,

I'm genuinely perplexed about what factors should go into choosing an appropriate d_star_sq to calculate bin_centers() in cctbx.miller.binner. This decision may be a nuance because it doesn't seem change the output significantly (except for low resolution bins). But if it doesn't matter significantly, then why have the parameter in the first place?

James


py> binner = miller.setup_binner(n_bins=10)
py> binner.show_summary()
unused:         - 81.7405 [   0/0   ]
bin  1: 81.7405 -  6.1396 [2341/2341]
bin  2:  6.1396 -  4.8734 [2213/2213]
bin  3:  4.8734 -  4.2574 [2185/2185]
bin  4:  4.2574 -  3.8681 [2168/2168]
bin  5:  3.8681 -  3.5909 [2177/2177]
bin  6:  3.5909 -  3.3792 [2156/2156]
bin  7:  3.3792 -  3.2099 [2137/2137]
bin  8:  3.2099 -  3.0702 [2144/2144]
bin  9:  3.0702 -  2.9520 [2133/2133]
bin 10:  2.9520 -  2.8501 [2135/2135]
unused:  2.8501 -         [   0/0   ]
py> centers = binner.bin_centers(1)
py> list(1 / centers)
[11.421375552155686,
 5.4336997182888345,
 4.544594791289144,
 4.053431451445772,
 3.7243527058119903,
 3.481806175995981,
 3.292371389128289,
 3.138504394416836,
 3.0099330507138475,
 2.9001646196929975]
py> centers = binner.bin_centers(4)
py> list(1 / centers**(1 / 4))
[7.301226942489155,
 5.330776416864701,
 4.514065417212759,
 4.039592121777967,
 3.716672320747147,
 3.4770032890247498,
 3.28912114749567,
 3.13617782414047,
 3.0081962210988116,
 2.8988250671976883]