def runFFT(images, apix=3.7, do_avg=True):
"""Run radially averaged FFT on an EMAN image.
Args:
images:
apix: angstroms per pixel
do_avg: compute average
Rets:
curve: radially-averaged FFT
sf_dx: corresponding x values.
"""
# This code by Steven Ludtke
nx = images[0]["nx"] + 2
ny = images[0]["ny"]
fftavg = EMData(nx, ny, 1)
fftavg.to_zero()
fftavg.set_complex(1)
for d in images:
d.process_inplace("mask.ringmean")
d.process_inplace("normalize")
df = d.do_fft()
df.mult(df.get_ysize())
fftavg.add_incoherent(df)
if do_avg:
fftavg.mult(1.0 / len(images))
curve = fftavg.calc_radial_dist(ny, 0, 0.5, 1)
sf_dx = 1.0 / (apix * 2.0 * ny)
return (curve, sf_dx)
def runFFT_err(images, apix=3.7, nresamples=1000, conf_int=95):
"""Run radially averaged FFT with bootstrapped error estimates.
Args:
images: images to operate on
apix: angstroms per pixel
nresmaples: number of bootstrap resamples
conf_int: confidence interval to calculate
Rets:
curve: average y-vals
conf_lo: low confidence bound
conf_hi: high confidence bound
sf_dx: x-vals
"""
bootidx = numpy.random.randint(len(images) - 1,
size=(nresamples, len(images)))
nx = images[0]["nx"]
ny = images[0]["ny"]
# compute FFT on everything
# for now also computing sample average
df = []
sampleavg = EMData(nx + 2, ny, 1)
sampleavg.to_zero()
sampleavg.set_complex(1)
for d in images:
d.process_inplace("mask.ringmean")
d.process_inplace("normalize")
curimg = d.do_fft()
curimg.mult(d.get_ysize())
sampleavg.add_incoherent(curimg)
df.append(curimg)
sampleavg.mult(1.0 / len(images))
# calculate average for each bootstrap resample
fftavg = EMData(nx + 2, ny, 1)
curve = []
for r in range(nresamples):
fftavg.to_zero()
fftavg.set_complex(1)
for idx in bootidx[r]:
fftavg.add_incoherent(df[idx])
fftavg.mult(1.0 / len(bootidx[r]))
curve.append(fftavg.calc_radial_dist(ny, 0, 0.5, 1))
cdata = numpy.vstack(curve)
xdata = numpy.array(range(cdata.shape[-1])) * 1.0 / (apix * 2.0 * ny)
return (sampleavg.calc_radial_dist(ny, 0, 0.5, 1),
numpy.percentile(cdata, 50 - conf_int/2, axis=0),
numpy.percentile(cdata, 50 + conf_int/2, axis=0),
xdata)
