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snaphist - histogram of projected radii and radial velocities of a snapshot
snapscale in=in_file [parameter=value] ...
snaphist creates
a histogram of projected radii and radial velocities of the particles in
a snapshot. The histogram is weighted by the mass of the particles.
A number
of random angles can optionally be choosen for each point to be rotated
before it is projected. A random orientation is achieved by 2 rotations:
one in polar angle phi (0..2PI) followed by a random value of cos(theta)
where theta is 0..PI away from the Z axis. The histogram counts are then normalized
by nrand. This then means that the histograms are completely normalized,
it’s integral being the total mass.
A little on the background of this program:
(dumbell)
snaphist does not use yapp(3NEMO)
yet, it produces a table, meant
for mongo(1LOCAL)
or tabhist(1NEMO)
.
The following parameters
are recognized:
- in=in_file
- input file, in snapshot(5NEMO)
format. [Default:
none].
- rad=real-array
- boundaries of the projected radii which should be used
to construct the histogram. [0:2:0.05].
- vel=real-array
- boundaries of the radial
velocities which should be used to construct the histogram. [-2:2:0.1].
- nrand=int
- Number of random angles used for each point before it is projected. Only
positive values are used. [default: 0].
- seed=int
- A random seed for the random
number generator. A value of zero means time of day is taken as random seed.
[0].
- tab=r|v|s|rv
- Table needed of radii (r) or velocities (v). A scatter table
of velocity vs. radius can be obtained with s. If the option rv is taken,
and the number of bins in radius and velocity is the same, both radius
and velocity columns will be output. Radius in columns 1 and 2, velocity
in 3 and 4. [default: r].
snapprint(1NEMO)
, tabhist(1NEMO)
, tabplot(1NEMO)
When non-uniform bins are choosen, the centers of the bins appear in
the table, which is not exactly understandable for mongo.
Peter Teuben
~/src/pjt/nbody snaphist.c snaphist.1
19-jun-89 V1.0: created PJT
27-jul-89 V1.1: more efficient random angles PJT
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