I have to admit I find this all sort of disappointing.

First, the  PFBL12C is a really poor way to represent EXAFS data.  It uses
a hard-to-parse and hard-to-interpret format and has many unlabeled
columns.  It appears to include this really odd notion that recording
"angle" is somehow better than recording energy, and saves a
ridiculuously over-sampled spectrum that needs smoothing because of the
high noise per recorded point.   It is, in short, a really poor way to
represent EXAFS data.  We've seen it for many years, we've written papers
and published supported code for better representations of EXAFS data.
 Still, we get questions about using data recorded in such files.  Data
files this complex need a way to convert them into something useful.

Second, the limitations you are seeing are due to using the outdated,
no-longer-supported (for several years now actually) Ifeffit library.
These data can be read and processed without problem with Larch, the
replacement for Ifeffit.

Stop using Ifeffit.  Use Larch instead.  Really.

An example script to use larch for your `fail.dat` file is listed below.
It is somewhat complicated because the raw data file is such a poor
representation of EXAFS data.

--Matt

##### larch script to read, smooth and process data in the horrible PFBL12C
format
# read raw data, extract angle, i0, sum of fluorescence
datafile = 'fail.dat'
rawdat = read_ascii(datafile)

def degrees2eV(angle, dspace=1.63747):
    from scipy.constants import hbar, c, e
    hbarc = 1.e10*hbar*c/e
    return (pi*hbarc/dspace) / sin(angle*pi/180.0)
#enddef

rawdat.angle  = rawdat.data[0, :]  # angle in degrees.  yikes!
rawdat.energy = degrees2eV(rawdat.angle)
rawdat.i0     = rawdat.data[42, :]
rawdat.fluor  = rawdat.data[3:42, :].sum(axis=0)

# smooth data with Savitzky-Golay (data is ~evenly sampled in angle)
smoothed       = group(energy=rawdat.energy)
smoothed.i0    = savitzky_golay(rawdat.i0,    5, 1)
smoothed.fluor = savitzky_golay(rawdat.fluor, 5, 1)

newplot(smoothed.energy, rawdat.fluor, win=3)
plot(smoothed.energy, smoothed.fluor, zorder=50, linewidth=4, win=3)

### create "normal" XAFS energies, finely spaced over edge,
### but spaced evenly in k for the EXAFS

e0    = 8980.0  # nominal Cu K edge
emin  = smoothed.energy.min()
emax  = smoothed.energy.max() - 5.0
epre1 = e0 - 20.0
epre2 = e0 + 20.0
kmin  = etok(20.0)
kmax  = etok(emax-e0)

def make_range(start, stop, step):
    npts = max(2, 1 + int(0.1 + abs(stop-start)/abs(step)))
    return linspace(start, stop, npts)
#enddef

en_new = concatenate((make_range(emin, epre1, 5),
                      make_range(epre1+0.5, epre2-0.5, 0.5),
                      e0 + ktoe(make_range(kmin, kmax, 0.05))))

# now interpolate smoothed data onto this energy grid
dat       = group(energy=en_new, filename=datafile)
dat.i0    = interp(smoothed.energy, smoothed.i0,    dat.energy)
dat.fluor = interp(smoothed.energy, smoothed.fluor, dat.energy)
dat.mu    = dat.fluor / dat.i0

# run autobk
autobk(dat, rbkg=0.8, kweight=1)

# plot data
plot_mu(dat, show_norm=True)
plot_chik(dat, kweight=1, win=2)

###################################################
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