Here are some examples of using tgridmap
:
stilts tgridmap in=ravedr4.fits coords=HRV nbins=20
ravedr4.fits
.
The output is a table with columns
HRV
, giving the central value of each bin, and
COUNT
, giving the number of input rows with HRV
values in that bin;
additional columns HRV_lo
and HRV_hi
give the
lower and upper bounds of the bin.
The bin size is determined from the actual range of the HRV values
in the input table, combined with the requested bin count of 20;
however, the bin size will be chosen as some round number,
so the bin count (number of rows in the output table)
may not be exactly as requested.
stilts tgridmap in=ravedr4.fits coords=HRV binsizes=100 bounds=-450:450 sparse=false
sparse=false
parameter means that rows will be output
for all 9 bins, even if some of them are empty.
Note supplying bin geometry in this way allows control of bin boundaries;
in this case HRV=0 is in the middle of a bin not at a bin boundary.
This will also be faster, since no initial scan to determine
actual data ranges has to be performed.
stilts tgridmap in=edr3-local.fits icmd='addcol nobs astrometric_n_good_obs_al' icmd='addcol g_abs phot_g_mean_mag+5*log10(parallax*0.01)' coords='bp_rp g_abs' binsizes='0.125 0.5' bounds='-1:6 -5:20' cols='1;count;NUM nobs;sum;SUM_NOBS nobs;mean;MEAN_NOBS' out=grid-stats.vot sparse=false
bp_rp
and g_abs
coordinate values
for each grid point,
as well as columns NUM containing source density,
and columns SUM_NOBS and MEAN_NOBS containing respectively
the sum and mean of the nobs
column in each grid cell.
Since sparse=false
the number and arrangement
of output rows is determined by the binsizes and bounds (57*51 rows)
independent of the input data, and could be compared
with similar runs on different input tables.
The icmd=addcol...
parameters prepare values for accumulation
ahead of the actual gridding step for convenience though this isn't
essential, the relevant expressions could be used directly in the
coords
and cols
parameters if preferred.