[SciPy-user] object too deep??

Emanuele Zattin emanuelez@gmail....
Fri Jun 29 07:40:22 CDT 2007


I have this optimization problem:

this function returns the sum of some gaussians given their parameters
in arrays:

def gaussian(height, center_x, center_y, width):
    """Returns a gaussian function with the given parameters"""
    width = float(width)
    return lambda x,y:
sum(height*exp(-(((center_x-x)/width)**2+((center_y-y)/width)**2)/2))

this function tries to fit given a starting image:

def fitgaussian(data, obj_x, obj_y, obj_v):
    """Returns (height, x, y, width)
    the gaussian parameters of a 2D distribution found by a fit"""
    #params = moments(data)
    params = obj_v, obj_x-obj_x[0]+2, obj_y-obj_y[0]+2, ones(len(obj_x))
    errorfunction = lambda p: ravel(gaussian(*p)(*indices(data.shape)) - data)
    p, success = leastsq(errorfunction, params)
    return p

and i use them with:

# how many maxima here?
max_list = [i]
for j in range(len(obj_x)):
	if obj_x[j] >= x1 and obj_x[j] < x2 and obj_y[j] >= y1 and obj_y[j] <
y2 and j != i:
		max_list.append(j)
#for indices in max_list:
ml = array(max_list)
params = fitgaussian(neigh, obj_x[ml], obj_y[ml], obj_v[ml])
print len(max_list), params

but i get an error like:

In [9]: run cutoff
---------------------------------------------------------------------------
<type 'exceptions.ValueError'>            Traceback (most recent call last)

/home/emanuelez/Tesi/Code/cutoff.py in <module>()
    174 # FIND OBJECTS PROPERTIES
    175 # -----------------------
--> 176 get_objects_info(blurred, 2, obj_x, obj_y, obj_v)
    177
    178

/home/emanuelez/Tesi/Code/cutoff.py in get_objects_info(image, size,
obj_x, obj_y, obj_v)
    143                 #for indices in max_list:
    144                 ml = array(max_list)
--> 145                 params = fitgaussian(neigh, obj_x[ml],
obj_y[ml], obj_v[ml])
    146                 print len(max_list), params
    147

/home/emanuelez/Tesi/Code/cutoff.py in fitgaussian(data, obj_x, obj_y, obj_v)
    124     params = obj_v, obj_x-obj_x[0]+2, obj_y-obj_y[0]+2, ones(len(obj_x))
    125     errorfunction = lambda p:
ravel(gaussian(*p)(*indices(data.shape)) - data)
--> 126     p, success = leastsq(errorfunction, params)
    127     return p
    128

/usr/lib/python2.5/site-packages/scipy/optimize/minpack.py in
leastsq(func, x0, args, Dfun, full_output, col_deriv, ftol, xtol,
gtol, maxfev, epsfcn, factor, diag)
    264         if (maxfev == 0):
    265             maxfev = 200*(n+1)
--> 266         retval =
_minpack._lmdif(func,x0,args,full_output,ftol,xtol,gtol,maxfev,epsfcn,factor,diag)
    267     else:
    268         if col_deriv:

<type 'exceptions.ValueError'>: object too deep for desired array
WARNING: Failure executing file: <cutoff.py>


What does "object too deep for desired array" mean? I'm really puzzled
about this.

Thanks for any help or suggestion!

Emanuele


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