def pixel2scan(self, pt):
""" Convert pixels coordinates to scan coordinates (mV)
Arguments
---------
pt : array
points in pixel coordinates (x,y)
Returns
-------
ptx (array): point in scan coordinates (sweep, step)
"""
ptx = pgeometry.projectiveTransformation(self.Hi,
np.array(pt).astype(float))
extent, g0, g1, vstep, vsweep, arrayname = dataset2Dmetadata(
self.dataset, arrayname=self.arrayname, verbose=0)
nx = vsweep.size
ny = vstep.size
xx = extent
x = ptx
nn = pt.shape[1]
ptx = np.zeros((2, nn))
f = scipy.interpolate.interp1d([0, ny - 1], [xx[2], xx[3]],
assume_sorted=False,
fill_value='extrapolate')
ptx[1, :] = f(x[1, :]) # step
f = scipy.interpolate.interp1d([0, nx - 1], [xx[0], xx[1]],
assume_sorted=False,
fill_value='extrapolate')
ptx[0, :] = f(x[0, :]) # sweep
return ptx
def scan2pixel(self, pt):
""" Convert scan coordinates to pixel coordinates
Arguments
---------
pt : array
points in scan coordinates
Returns:
ptpixel (ndaray): points in pixel coordinates
"""
extent, g0, g1, vstep, vsweep, arrayname = dataset2Dmetadata(
self.dataset, arrayname=self.arrayname, verbose=0)
nx = vsweep.size
ny = vstep.size
xx = extent
x = pt
nn = pt.shape[1]
ptpixel = np.zeros((2, nn))
f = scipy.interpolate.interp1d([xx[2], xx[3]], [0, ny - 1],
assume_sorted=False)
ptpixel[1, :] = f(x[1, :])
f = scipy.interpolate.interp1d([xx[0], xx[1]], [0, nx - 1],
assume_sorted=False)
ptpixel[0, :] = f(x[0, :]) # sweep to pixel x
ptpixel = pgeometry.projectiveTransformation(
self.H,
np.array(ptpixel).astype(float))
return ptpixel
def transformGateScan(self, vals2D, nn=None):
""" Get a list of parameter names and [c1 c2 c3 c4] 'corner' values
to generate dictionary self.vals2D[name] = matrix of values.
Args:
vals2D (dict): keys are the gate names, values are matrices with the gate values.
nn : TODO.
Returns:
dict: tranformed gate values.
"""
vals2Dout = {}
zz = np.zeros(nn if nn is not None else (), dtype=float)
if isinstance(vals2D, dict):
xx = [vals2D.get(s, zz) for s in self.sourcenames]
xx = [x.flatten() for x in xx]
gate_values = np.vstack(xx).astype(float)
else:
xx = vals2D
gate_values = np.array(xx).astype(float)
gate_values_out = pgeometry.projectiveTransformation(
self.Vmatrix, gate_values)
for j, n in enumerate(self.targetnames):
vals2Dout[n] = gate_values_out[j].reshape(nn).astype(float)
return vals2Dout
def evaluateCross(param, im, verbose=0, fig=None, istep=1, istepmodel=1, linewidth=2,
usemask=False, use_abs=False, w=2.5):
""" Calculate cross matching score
Args:
param (array or list): used by createCross to create image template
im (numpy array):
Returns:
cost, patch, cdata, tuple
See also:
createCross
"""
samplesize = [int(im.shape[1] * istep / istepmodel), int(im.shape[0] * istep / istepmodel)]
param = np.array(param)
aa = param[3:]
H = evaluateCross.scaling0.copy()
H[0, 0] = istep / istepmodel
H[1, 1] = istep / istepmodel
dsize = (samplesize[0], samplesize[1])
patch = cv2.warpPerspective(im.astype(np.float32), H, dsize, None, (cv2.INTER_LINEAR), cv2.BORDER_CONSTANT, -1)
if verbose:
print('evaluateCross: patch shape %s' % (patch.shape,))
modelpatch, cdata = createCross(param, samplesize, centermodel=False, istep=istepmodel, verbose=verbose >= 2, w=w)
(cc, lp, hp, ip, op, _, _, _) = cdata
if use_abs:
dd = np.abs(patch) - modelpatch
else:
dd = patch - modelpatch
if usemask:
# near model mask
#mask = (modelpatch>1).astype(int)
# distance centre mask
imtmp = 10 + 0 * modelpatch.copy()
imtmp[int(imtmp.shape[1] / 2), int(imtmp.shape[0] / 2)] = 0
mask = scipy.ndimage.distance_transform_edt(imtmp)
mask = 1 - .75 * mask / mask.max()
dd = dd * mask
cost = np.linalg.norm(dd)
# area of intersection
rr = np.array([[0., im.shape[1]], [0, im.shape[0]]])
ppx = pgeometry.region2poly(np.array([[0, samplesize[0]], [0., samplesize[1]]]))
ppimage = pgeometry.region2poly(rr)
pppatch = pgeometry.projectiveTransformation(H, ppimage)
ppi = pgeometry.polyintersect(ppx.T, pppatch.T).T
A = pgeometry.polyarea(ppi.T)
A0 = pgeometry.polyarea(ppx.T)
# special rules
if np.abs(A / A0) < .85:
if verbose:
print(' add cost for A/A0: A %f A0 %f' % (A, A0))
cost += 4000
if aa[0] < 0 or aa[0] > np.pi / 2 - np.deg2rad(5):
cost += 10000
if aa[1] < np.pi or aa[1] > 3 * np.pi / 2:
if verbose:
print(' add cost for alpha')
cost += 10000
if aa[2] < np.pi or aa[2] > 3 * np.pi / 2:
if verbose:
print(' add cost for alpha')
cost += 10000
if aa[3] < 0 or aa[3] > np.pi / 2:
if verbose:
print(' add cost for alpha')
cost += 10000
if 1:
ccim = (np.array(im.shape) / 2 + .5) * istep
tmp = np.linalg.norm(ccim - param[0:2])
dcost = 2000 * pgeometry.logistic(tmp, np.mean(ccim), istep)
if verbose:
print(' add cost for image cc: %.1f' % dcost)
cost += dcost
if pgeometry.angleDiff(aa[0], aa[1]) < np.deg2rad(30):
if verbose:
print(' add cost for angle diff')
cost += 1000
if pgeometry.angleDiff(aa[2], aa[3]) < np.deg2rad(30):
if verbose:
print(' add cost for angle diff')
cost += 1000
if pgeometry.angleDiffOri(aa[0], aa[2]) > np.deg2rad(10):
cost += 10000
if pgeometry.angleDiffOri(aa[1], aa[3]) > np.deg2rad(10):
cost += 10000
if param[2] < 0:
if verbose:
print(' add cost for negative param')
cost += 10000
if np.abs(param[2]) > 7.:
if verbose:
print(' add cost large param[2]')
cost += 10000
if np.abs(param[2] - 10) > 8:
cost += 10000
if len(param) > 7:
if np.abs(pgeometry.angleDiff(param[7], np.pi / 4)) > np.deg2rad(30):
cost += 10000
if not fig is None:
_showIm(patch, fig=fig)
plt.title('Image patch: cost %.1f: istep %.2f' % (cost, istepmodel))
pgeometry.addfigurecopy(fig=fig)
plt.plot([float(lp[0]), float(hp[0])], [float(lp[1]), float(hp[1])], '.--m',
linewidth=linewidth, markersize=10, label='transition line')
plt.plot(cc[0], cc[1], '.m', markersize=12)
for ii in range(4):
if ii == 0:
lbl = 'electron line'
else:
lbl = None
plt.plot([op[ii, 0], ip[ii, 0]], [op[ii, 1], ip[ii, 1]], '.-',
linewidth=linewidth, color=[0, .7, 0], label=lbl)
pgeometry.plotLabels(np.array((op[ii, :] + ip[ii, :]) / 2).reshape((2, -1)), '%d' % ii)
if verbose >= 1:
_showIm(modelpatch, fig=fig + 1)
plt.title('Model patch: cost %.1f' % cost)
_showIm(np.abs(dd), fig=fig + 2)
plt.title('diff patch: cost %.1f' % cost)
plt.colorbar()
plt.show()
if verbose:
print('evaluateCross: cost %.4f' % cost)
#print('evaluateCross: param %s' % (str(param), ))
return cost, patch, cdata, (H, )
pass
