;pro plot_adc_lin, ps = ps
;restore, 'LOG10-09-09B.sav'
; loads date, and data


; Data is [17, Nsamples] long. data[0, *] is the ADC input, while
; data[1:16, *] are the readouts.

input = reform(data[0, *])

;print, max(input)
;print, min(input)
;print, max(input) - min(input)
;print, (max(input) - min(input)) / 64.

for n = 2, 16 do input = [input, reform(data[0, *])]

; transpose the data to make it line up with the index
readout = transpose(data[1:16, *])


; Now screen out everything above 4094, since that's basically
; high rail

goodOnes = where(readout le 4094 and readout gt 0)
input = input[goodOnes]
readout = readout[goodOnes]

; Downward slope
slopeStart = ( min(readout) - max(readout) ) / ( max(input) - min(input) )

; Now infer back to zero to figure out the intercept:
interceptStart = max(readout) - slopeStart * min(input)

start = [slopeStart, interceptStart]

result = MPFITFUN('MYLIN', input, readout, $
	fltarr(n_elements(readout)) + 1., start, yfit = yfit, bestnorm = best, dof = dof, /quiet)

residuals = yfit - readout

inBin = histogram(input, reverse_indices = inds)


nbins = n_elements(inBin)
vals = fltarr(nbins)
index= vals
dev = vals
for i = 0, nbins - 1 do begin
   if inBin[i] eq 0 then continue
   thisInd = inds[inds[i]:inds[i+1]-1]
   vals[i] = average(residuals[thisInd])
   dev[i] = stddev(residuals[thisind])   
   index[i] = input[inds[inds[i]]]
endfor

step = nbins / 64.

;print, nbins

!p.multi = [0, 1, 1]
xrange = [0, max(index) - min(input)]
yrange = [-10, 10]
;plot, (input - min(input)) / step, residuals, psym = 3, $
;	/xst, /yst, xrange = xrange, yrange = yrange,$
;	ytit="Residuals",xtit="ADC steps / 64",tit="ADC linearity
;	test", charsize=1.5
plot, (index - min(input)), vals, psym = 3, $
      /xst, /yst, xrange = xrange, yrange = yrange, $
      ytit = "Output ADC Residuals from Linear", xtit ="Input ADC Setting", tit = "ADC Linearity Test", charsize = 1.5

;oplot, (index - min(input)) / step, vals/inBin, color = 5

;oplot, (index - min(input)) / step, smooth(vals / inBin, step, /Nan, /edge_truncate),$
;	psym=0, col=250
;plot, (index - min(input)) / step, smooth(vals / inBin, step, /Nan, /edge_truncate),$
;      xrange = xrange, yrange = yrange / 2.5, psym =4 , /xst,/yst, $
;      xtit="ADC step / 64", charsize=1.5

!p.multi = 0

end