BIN_INDEX_WT

BIN_INDEX_WT (INDEX, WT, INDMAX)  Returns data sorted into bins along an X axis

Examples: This function is called by the script frequency_histogram2.jnl

Here is an annotated example similar to frequency_histogram2.jnl

yes? ! Define some data to use - we need a 1-D list in X

yes? LET myvar = { 9.04, 8.67, 8.96, 9.29, 9.18, 9.42,\
...? 9.43, 9.33, 9.19, 9.22, 9.12, 9.36, 9.22, 9.04, 8.92, 9.00, 8.59,\
...? 8.31, 8.69, 8.20, 8.86, 7.98, 7.80, 8.29, 7.94, 8.05, 7.85, 7.55,\
...? 7.56, 6.82, 7.04, 6.66, 6.56, 7.36, 6.52}

yes? ! Get the data range and define some bins.

yes? stat/brief myvar
 
 Total # of data points: 35 (35*1*1*1*1*1)
 # flagged as bad  data: 0
 Minimum value: 6.52
 Maximum value: 9.43
 Mean    value: 8.372 (unweighted average)

yes? LET vmin = 6.5
yes? LET vmax = 10
yes? LET vdelta = 0.5

yes? ! Compute number of bins
yes? LET vn = INT((vmax-vmin)/vdelta + 0.5) + 1

yes? ! Sort the data 
yes? LET sort_var = SAMPLEI(myvar, SORTI(myvar))

yes? ! Define a weight function for each data point, here all 1.
yes? ! The weights need to be sorted identically to the data so 
yes? ! weights stay with the right data values.

yes? LET wt_index = 1+0*myvar
yes? LET sort_wt = SAMPLEI(wt_index, SORTI(myvar))

yes? ! Vindex is the bin number corresponding to the data value

yes? LET vindex = INT((sort_var-vmin)/vdelta + 0.5) + 1
yes? list sort_var, vindex
             X: 0.5 to 35.5
 Column  1: SORT_VAR is SAMPLEI(MYVAR, SORTI(MYVAR))
 Column  2: VINDEX is INT((SORT_VAR-VMIN)/VDELTA + 0.5) + 1
         SORT_VAR  VINDEX
1    /  1:   6.520  1.000
2    /  2:   6.560  1.000
3    /  3:   6.660  1.000
4    /  4:   6.820  2.000
5    /  5:   7.040  2.000
6    /  6:   7.360  3.000
7    /  7:   7.550  3.000
8    /  8:   7.560  3.000
9    /  9:   7.800  4.000
10   / 10:   7.850  4.000
11   / 11:   7.940  4.000
12   / 12:   7.980  4.000
13   / 13:   8.050  4.000
14   / 14:   8.200  4.000
15   / 15:   8.290  5.000
16   / 16:   8.310  5.000
17   / 17:   8.590  5.000
18   / 18:   8.670  5.000
19   / 19:   8.690  5.000
20   / 20:   8.860  6.000
21   / 21:   8.920  6.000
22   / 22:   8.960  6.000
23   / 23:   9.000  6.000
24   / 24:   9.040  6.000
25   / 25:   9.040  6.000
26   / 26:   9.120  6.000
27   / 27:   9.180  6.000
28   / 28:   9.190  6.000
29   / 29:   9.220  6.000
30   / 30:   9.220  6.000
31   / 31:   9.290  7.000
32   / 32:   9.330  7.000
33   / 33:   9.360  7.000
34   / 34:   9.420  7.000
35   / 35:   9.430  7.000

yes? ! BIN_INDEX_WT counts the number of items in each bin

yes? LET fh_fbins = BIN_INDEX_WT(vindex, sort_wt, vn)
yes? list fh_fbins
             VARIABLE : BIN_INDEX_WT(VINDEX, SORT_WT, VN)
             SUBSET   : 9 points (X)
 1   / 1:   3.00
 2   / 2:   2.00
 3   / 3:   3.00
 4   / 4:   6.00
 5   / 5:   5.00
 6   / 6:  11.00
 7   / 7:   5.00
 8   / 8:   0.00
 9   / 9:   0.00

 
yes? ! Now make a plot, using one of the bar_chart scripts
yes? ! Define an independent axis for the bin plot

yes? DEFINE AXIS/Y=`vmin`:`vmax`:`vdelta` yax
 !-> DEFINE AXIS/Y=6.5:10:0.5 yax

yes? ! Define the count variable to send to bar_chart2 
yes? ! (see yes? go/help bar_chart2.jnl)

yes? LET fh_wc = RESHAPE(fh_fbins, y[gy=yax])
yes? LET wt_count = MISSING(fh_wc, 0.)

yes? GO bar_chart2 PLOT/LINE/COLOR=blue wt_count y

yes? ! or a filled chart
yes? ! (see yes? go/help bar_chart3.jnl)

yes? GO bar_chart3 POLY/LINE/NOLABEL/FILL wt_count wt_count

NOTE:  Defining the bins as above puts the center of the bins at the points vmin, vmin+vdelta, vmin+2*vdelta, ...  The commands could be instead defined to make, for instance, bins from 6.0:6.5, then 6.5:7.0, then 7.0:7.5, etc.