We report on an adaptive binning approach designed for data visualization within scientific disciplines where counting statistics are expected to follow Poisson distributions. We envisage a wide range of applications stemming from astrophysics to the condensed matter sciences. Our main focus of interest concerns, however, neutron spectroscopy data from single-crystal samples where signals span a four-dimensional space defined by three spatial coordinates plus time. This makes widely used equal-width binning schemes inadequate since physically relevant information is often concentrated within rather small regions of such a space. Our aim is thus to generate optimally binned data sets from one-dimensional to three-dimensional volumes to provide the experimentalist with enhanced ability to carry out searches within a four-dimensional space. Several binning algorithms are then scrutinized against experimental as well as simulated data.

1.
I.
Bustinduy
,
F. J.
Bermejo
,
T. G.
Perring
, and
G.
Bordel
,
Nucl. Instrum. Methods Phys. Res. A
546
,
498
(
2005
).
2.
W. K.
Leow
and
R.
Li
,
Comput. Vis. Image Underst.
94
,
67
(
2004
).
3.
M. J.
Bayley
and
P.
Willett
,
J. Mol. Graphics Modell.
17
,
10
(
1999
).
4.
M.
Roederer
,
A.
Treister
,
W.
Moore
, and
L. A.
Herzenberg
,
Cytometry
45
,
37
(
2001
).
5.
M.
Roederer
,
W.
Moore
,
A.
Treister
,
R. R.
Hardy
, and
L. A.
Herzenberg
,
Cytometry
45
,
47
(
2001b
).
6.
M.
Roederer
and
R. R.
Hardy
,
Cytometry
45
,
56
(
2001
).
7.
P.
Rubin
 et al (
CLEO Collaboration
),
Phys. Rev. Lett.
93
,
111801
(
2004
).
8.
B.
Aubert
 et al,
Phys. Rev. D
72
,
052008
(
2005
).
9.
J. S.
Sanders
and
A. C.
Fabian
,
Mon. Not. R. Astron. Soc.
325
,
178
(
2001
).
10.
M.
Cappellari
and
Y.
Copin
,
Mon. Not. R. Astron. Soc.
342
,
345
(
2003
).
11.
S.
Diehl
and
T. S.
Statler
,
Mon. Not. R. Astron. Soc.
368
,
497
(
2006
).
12.
H.
Samet
,
ACM Comput. Surv.
16
,
187
(
1984
).
13.
Q.
Du
,
M.
Faber
, and
M.
Gunzburger
,
SIAM Rev.
41
,
637
(
1999
).
14.
S.
Valette
and
J. M.
Chassery
,
Comput. Graph. Forum
23
,
381
(
2004
).
15.
S.
Hiller
,
H.
Hellwig
, and
O.
Deussen
,
Comput. Graph. Forum
22
,
515
(
2003
).
16.
C. G.
Wager
,
B. A.
Coull
, and
N.
Lange
,
J. R. Stat. Soc. Ser. B (Stat. Methodol.)
66
,
429
(
2004
).
17.
J.
Cortes
,
S.
Martinez
,
T.
Karatas
, and
F.
Bullo
,
IEEE Trans. Rob. Autom.
20
,
243
(
2004
).
18.
Q.
Du
and
M.
Gunzburger
,
Appl. Math. Comput.
133
,
591
(
2002
).
19.
Q.
Du
and
D.
Wang
,
Int. J. Numer. Methods Eng.
56
,
1355
(
2003
).
20.
A. B.
Mendes
and
I. H.
Themido
,
Int. Trans. Oper. Res.
11
,
1
(
2004
).
21.
S. P.
Lloyd
,
IEEE Trans. Inf. Theory
28
,
129
(
1982
).
22.
A.
Gersho
,
IEEE Trans. Inf. Theory
25
,
373
(
1979
).
23.
Y.
Linde
,
A.
Buzo
, and
R. M.
Gray
,
IEEE Trans. Commun.
28
,
84
(
1980
).
24.
B.
Lake
,
D. A.
Tennant
,
C. D.
Frost
, and
S. D.
Nagler
,
Nat. Mater.
4
,
329
(
2005
).
25.
T.
Huberman
,
R.
Coldea
, and
R. A.
Cowley
,
Phys. Rev. B
72
,
014413
(
2005
).
26.
T. G.
Perring
, ISIS Experimental Report,
2001
(unpublished).
27.
C. R.
Johnson
,
IEEE Comput. Graphics Appl.
24
,
13
(
2004
).
28.
C. R.
Johnson
and
A. R.
Sanderson
,
IEEE Comput. Graphics Appl.
23
,
6
(
2003
).
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