def makestate(im, pos, rad, slab=None, mem_level='hi'):
"""
Workhorse for creating & optimizing states with an initial centroid
guess.
This is an example function that works for a particular microscope. For
your own microscope, you'll need to change particulars such as the psf
type and the orders of the background and illumination.
Parameters
----------
im : :class:`~peri.util.RawImage`
A RawImage of the data.
pos : [N,3] element numpy.ndarray.
The initial guess for the N particle positions.
rad : N element numpy.ndarray.
The initial guess for the N particle radii.
slab : :class:`peri.comp.objs.Slab` or None, optional
If not None, a slab corresponding to that in the image. Default
is None.
mem_level : {'lo', 'med-lo', 'med', 'med-hi', 'hi'}, optional
A valid memory level for the state to control the memory overhead
at the expense of accuracy. Default is `'hi'`
Returns
-------
:class:`~peri.states.ImageState`
An ImageState with a linked z-scale, a ConfocalImageModel, and
all the necessary components with orders at which are useful for
my particular test case.
"""
if slab is not None:
o = comp.ComponentCollection(
[
objs.PlatonicSpheresCollection(pos, rad, zscale=zscale),
slab
],
category='obj'
)
else:
o = objs.PlatonicSpheresCollection(pos, rad, zscale=zscale)
p = exactpsf.FixedSSChebLinePSF()
npts, iorder = _calc_ilm_order(im.get_image().shape)
i = ilms.BarnesStreakLegPoly2P1D(npts=npts, zorder=iorder)
b = ilms.LegendrePoly2P1D(order=(9 ,3, 5), category='bkg')
c = comp.GlobalScalar('offset', 0.0)
s = states.ImageState(im, [o, i, b, c, p])
runner.link_zscale(s)
if mem_level != 'hi':
s.set_mem_level(mem_level)
opt.do_levmarq(s, ['ilm-scale'], max_iter=1, run_length=6, max_mem=1e4)
return s
# particle_positions
n=100
# random_particles = np.c_[np.random.random(n), np.random.random(n),np.zeros(n)]*200.0
tile = util.Tile(200)
small_im = util.RawImage(imFile, tile=tile)
zpixel=1
xpixel=1
zscale=zpixel/xpixel
particle_radii = 8.0
particles = objs.PlatonicSpheresCollection(particle_positions, particle_radii, zscale=zscale)
objects = comp.comp.ComponentCollection([particles], category='obj')
background = comp.ilms.LegendrePoly2P1D(order=(4,2,2), category='bkg')
illumination = comp.ilms.BarnesStreakLegPoly2P1D(npts=(4, 2, 2))
offset = comp.GlobalScalar(name='offset', value=0.)
point_spread_function = comp.exactpsf.ChebyshevLineScanConfocalPSF(pxsize=xpixel)
model = models.ConfocalDyedParticlesModel()
st = states.ImageState(small_im, [objects, illumination, background, point_spread_function], mdl=model)
st.update('zscale', zscale)
savefile = "/Volumes/PhD/expDesign/test/"+datetime.now().strftime("%Y%m%d-%H%M%S") + "_unoptimized"
runner.link_zscale(st)
runner.optimize_from_initial(st)
savefile = "/Volumes/PhD/expDesign/test/"+datetime.now().strftime("%Y%m%d-%H%M%S") + "_inital_optimized"
states.save(st,savefile)
# new_st = runner.get_particles_featuring(8)