def PlotMoments(self):
data = self.canvas.img.get_array()
pm = self.procMoment
# data=ndi.median_filter(data, 3)
try:
data.ravel()[pm.mskIdx] = 0
except AttributeError as e:
print(e)
try:
data = data[pm.roi]
except AttributeError as e:
print(e)
# data=np.log(data+1)
# data[100:110,500:510]=1000 #y,x
# data[650:850,700:850]=0 #y,x
# pm.Process(np.log(data+1))
pm.Process(data)
xbar, ybar, cov = pm.GetIntertialAxis()
m = pm.resArr
m00 = m[0]
m01 = m[1]
m10 = m[2]
m11 = m[3]
m02 = m[4]
m20 = m[5]
xm = m10 / m00
ym = m01 / m00
u11 = (m11 - xm * m01) / m00
# u11[u11<0.]=0. #processing rounding error
u20 = (m20 - xm * m10) / m00
u02 = (m02 - ym * m01) / m00
a = (u20 + u02) / 2
b = np.sqrt(4 * u11**2 + (u20 - u02)**2) / 2
l0 = a + b
l1 = a - b
ang = 0.5 * np.arctan2(
2 * u11,
(u20 - u02)) / (2 * np.pi) * 360.0 # orientation value 0..1
exc = np.sqrt(
1 - l1 / l0
) # eccentricity :circle=0: http://en.wikipedia.org/wiki/Eccentricity_%28mathematics%29
print("xb:%g yb:%g cov:%g %g %g %g ang:%g exc:%g" %
((xm, ym) + tuple(cov.ravel()) + (ang, exc)))
# fig, ax = plt.subplots()
# ax.imshow(data,vmax=100,interpolation='nearest')
# plt.show()
ax = self.canvas.img.get_axes()
try:
for o in self.goMoment:
o.remove()
except AttributeError:
pass
self.goMoment = ProcMoment.PlotMoments(ax, xbar, ybar, cov)
ax.axis("image")
def OnShowMoments(self, event):
if event.IsChecked():
dlg = wx.FileDialog(
self,
"Choose valid mask file (e.g. pilatus_valid_mask.mat)",
os.getcwd(),
"",
"MATLAB files (*.mat)|*.mat|all (*.*)|*.*",
wx.FD_OPEN | wx.FD_CHANGE_DIR,
)
if dlg.ShowModal() == wx.ID_OK:
fnMatMsk = dlg.GetPath()
print("OnOpen", fnMatMsk)
dlg.Destroy()
if not fnMatMsk:
return
# fnMatMsk='/scratch/detectorData/cSAXS_2013_10_e14608_georgiadis_3D_for_Marianne/analysis/data/pilatus_valid_mask.mat'
self.procMoment = pm = ProcMoment()
pm.SetMskMat(fnMatMsk, False)
# roi=[603, 826, 200, 200]
# pm.roi=(slice(roi[1],roi[1]+roi[3]),slice(roi[0],roi[0]+roi[2]))
# pm.shape=(roi[3],roi[2])
# pm.SetProcess('python')
# pm.SetProcess('pyFast')
pm.SetProcess("c")
self.PlotMoments()
# self.canvas.img.draw()
data = self.canvas.img.get_array()
self.canvas.img.set_array(data)
fig, ax = plt.subplots(2)
v = data.sum(axis=0)
x = np.arange(v.size)
x0 = x.sum()
m0 = v.sum()
m1 = (v * x).sum()
m2 = (v * x * x).sum()
ax[0].plot(v)
m = m1 / m0
s = np.sqrt((m2 - (m1**2 / m0)) / m0)
xx = 1 / (s * np.sqrt(2 * np.pi)) * np.exp(-0.5 * ((x - m) / s)**2)
ax[0].set_title("%g | %g | %g | %g | %g" % (m0, m1, m2, m, s))
ax[0].hold(True)
ax[0].plot(xx * m0)
v = data.sum(axis=1)
ax[1].plot(v)
plt.show()
# print pm.resArr[0:3],pm.resArr[1]/pm.resArr[0],pm.resArr[2]/pm.resArr[0]
else:
for o in self.goMoment:
o.remove()
del self.goMoment
del self.procMoment
self.canvas.draw()