def obsolete_test_center_zoom_even(imsize,outsize,cx,cy,upsample_factor,doplot=False):
if imsize != outsize and np.abs(imsize-outsize)==1:
return "Yarrr, something's awry!"
pixspace = np.mean(np.diff(np.linspace(-5,5,imsize)))
image = gaussian(imsize)
image_shifted = gaussian(imsize,cx*pixspace,cy*pixspace)
zoom_pixspace = np.mean(np.diff(np.linspace(-5/float(upsample_factor),5/float(upsample_factor),imsize)))
image_shifted_zoomed = zoomed_gaussian(imsize,outsize,cx*zoom_pixspace, cy*zoom_pixspace,upsample_factor)
image_zoomed = zoomed_gaussian(imsize,outsize, 0, 0, upsample_factor)
#image_shifted_zoomed = zoomed_gaussian(outsize,pixspace/2,pixspace/2,upsample_factor)
middle = np.unravel_index(image.argmax(),image.shape)
ismax = np.unravel_index(image_shifted.argmax(),image.shape)
assert (ismax[0]-middle[0]) == cy
assert (ismax[1]-middle[1]) == cx
dmax = np.unravel_index(image_shifted_zoomed.argmax(),image.shape)
x,y,zoom = upsample.center_zoom_image(image_shifted, upsample_factor=upsample_factor, output_size=outsize, nthreads=4,
xshift=cx, yshift=cy, return_axes=True)
zmax = np.unravel_index(zoom.argmax(),zoom.shape)
#print 'image position of max:',dmax,' zoom position of max:',zmax
#print 'x,y max: ',x[zmax],y[zmax]
clf()
vshape = image.shape[0]*upsample_factor,image.shape[1]*upsample_factor
s1,s2 = outsize,outsize
roff = -int(np.round(float(vshape[0] - upsample_factor - s1)/2)) - (upsample_factor%2==0)
coff = -int(np.round(float(vshape[1] - upsample_factor - s2)/2)) - (upsample_factor%2==0)
if doplot:
if imsize * upsample_factor < 512:
fx,fy,fullzoom = upsample.center_zoom_image(image, xshift=cx, yshift=cy, upsample_factor=upsample_factor, nthreads=4, return_axes=True)
else:
fullzoom = None
if image.shape == zoom.shape:
plotthings(image,image_shifted,image_zoomed,zoom,cx,cy,upsample_factor,imsize,outsize,x,y,fullzoom=fullzoom)
else:
plotthings(image,image_shifted,image_zoomed[:image.shape[0],:image.shape[1]],zoom[:image.shape[0],:image.shape[1]], cx,cy,upsample_factor,imsize,outsize,x[:image.shape[0],:image.shape[1]],y[:image.shape[0],:image.shape[1]],fullzoom=fullzoom)
print " ".join(["%6.2f" % q for q in
(upsample_factor,imsize,outsize,cx,cy,x[zmax],y[zmax],zmax[1],zmax[0],dmax[1],dmax[0],x[zmax]-dmax[1],y[zmax]-dmax[0],
cx/float(upsample_factor),cy/float(upsample_factor),((zoom-image_zoomed)**2).sum(),
ismax[0]-middle[0],ismax[1]-middle[1])])
zmax = np.where(np.abs(zoom-zoom.max()) < 1e-8)
#assert np.round(np.mean(y[zmax])) == floor(image.shape[0]/2.+cy)
#assert np.round(np.mean(x[zmax])) == floor(image.shape[1]/2.+cx)
#assert (x[zmax]) == dmax[1]
#assert (y[zmax]) == dmax[0]
#if upsample_factor == 1 and image.shape==zoom.shape:
# assert dmax[0] == zmax[0]
# assert dmax[1] == zmax[1]
assert ((zoom-image_zoomed)**2).sum() < 0.001
def obsolete_test_center_zoom_even(imsize,outsize,cx,cy,upsample_factor,doplot=False):
if imsize != outsize and np.abs(imsize-outsize)==1:
return "Yarrr, something's awry!"
pixspace = np.mean(np.diff(np.linspace(-5,5,imsize)))
image = gaussian(imsize)
image_shifted = gaussian(imsize,cx*pixspace,cy*pixspace)
zoom_pixspace = np.mean(np.diff(np.linspace(-5/float(upsample_factor),5/float(upsample_factor),imsize)))
image_shifted_zoomed = zoomed_gaussian(imsize,outsize,cx*zoom_pixspace, cy*zoom_pixspace,upsample_factor)
image_zoomed = zoomed_gaussian(imsize,outsize, 0, 0, upsample_factor)
#image_shifted_zoomed = zoomed_gaussian(outsize,pixspace/2,pixspace/2,upsample_factor)
middle = np.unravel_index(image.argmax(),image.shape)
ismax = np.unravel_index(image_shifted.argmax(),image.shape)
assert (ismax[0]-middle[0]) == cy
assert (ismax[1]-middle[1]) == cx
dmax = np.unravel_index(image_shifted_zoomed.argmax(),image.shape)
x,y,zoom = upsample.center_zoom_image(image_shifted, upsample_factor=upsample_factor, output_size=outsize, nthreads=4,
xshift=cx, yshift=cy, return_axes=True)
zmax = np.unravel_index(zoom.argmax(),zoom.shape)
#print 'image position of max:',dmax,' zoom position of max:',zmax
#print 'x,y max: ',x[zmax],y[zmax]
clf()
vshape = image.shape[0]*upsample_factor,image.shape[1]*upsample_factor
s1,s2 = outsize,outsize
roff = -int(np.round(float(vshape[0] - upsample_factor - s1)/2)) - (upsample_factor%2==0)
coff = -int(np.round(float(vshape[1] - upsample_factor - s2)/2)) - (upsample_factor%2==0)
if doplot:
if imsize * upsample_factor < 512:
fx,fy,fullzoom = upsample.center_zoom_image(image, xshift=cx, yshift=cy, upsample_factor=upsample_factor, nthreads=4, return_axes=True)
else:
fullzoom = None
if image.shape == zoom.shape:
plotthings(image,image_shifted,image_zoomed,zoom,cx,cy,upsample_factor,imsize,outsize,x,y,fullzoom=fullzoom)
else:
plotthings(image,image_shifted,image_zoomed[:image.shape[0],:image.shape[1]],zoom[:image.shape[0],:image.shape[1]], cx,cy,upsample_factor,imsize,outsize,x[:image.shape[0],:image.shape[1]],y[:image.shape[0],:image.shape[1]],fullzoom=fullzoom)
print " ".join(["%6.2f" % q for q in
(upsample_factor,imsize,outsize,cx,cy,x[zmax],y[zmax],zmax[1],zmax[0],dmax[1],dmax[0],x[zmax]-dmax[1],y[zmax]-dmax[0],
cx/float(upsample_factor),cy/float(upsample_factor),((zoom-image_zoomed)**2).sum(),
ismax[0]-middle[0],ismax[1]-middle[1])])
zmax = np.where(np.abs(zoom-zoom.max()) < 1e-8)
#assert np.round(np.mean(y[zmax])) == floor(image.shape[0]/2.+cy)
#assert np.round(np.mean(x[zmax])) == floor(image.shape[1]/2.+cx)
#assert (x[zmax]) == dmax[1]
#assert (y[zmax]) == dmax[0]
#if upsample_factor == 1 and image.shape==zoom.shape:
# assert dmax[0] == zmax[0]
# assert dmax[1] == zmax[1]
assert ((zoom-image_zoomed)**2).sum() < 0.001
def obsolete_test_center_zoom_simple3(imsize,upsample_factor,doplot=False):
image = gaussian(imsize)
x,y,zoom = upsample.center_zoom_image(image,
upsample_factor=upsample_factor, output_size=image.shape,
nthreads=4, return_axes=True)
if imsize * upsample_factor < 512:
fx,fy,fullzoom = upsample.center_zoom_image(image,
upsample_factor=upsample_factor, nthreads=4, return_axes=True)
else:
fullzoom = None
if doplot:
plotthings(image,image,image,zoom,0,0,upsample_factor,imsize,imsize,x,y,fullzoom=fullzoom)
# in order for zooming to work, need to at least nyquist-sample peak
# (I think)
if imsize > 10:
assert ((image-zoom)**2).sum() < 0.001
def obsolete_test_center_zoom_simple3(imsize,upsample_factor,doplot=False):
image = gaussian(imsize)
x,y,zoom = upsample.center_zoom_image(image,
upsample_factor=upsample_factor, output_size=image.shape,
nthreads=4, return_axes=True)
if imsize * upsample_factor < 512:
fx,fy,fullzoom = upsample.center_zoom_image(image,
upsample_factor=upsample_factor, nthreads=4, return_axes=True)
else:
fullzoom = None
if doplot:
plotthings(image,image,image,zoom,0,0,upsample_factor,imsize,imsize,x,y,fullzoom=fullzoom)
# in order for zooming to work, need to at least nyquist-sample peak
# (I think)
if imsize > 10:
assert ((image-zoom)**2).sum() < 0.001
