def main(self, img, roi):
"""Create dialog and image inside it"""
self.img = img
self.roi = roi
transimg1, odimg1 = imageprocess.calc_absimage(np.dstack(
[img[:, :, 1], img[:, :, 5], img[:, :, 3]]),
norm_edge=True)
transimg2, odimg2 = imageprocess.calc_absimage(np.dstack(
[img[:, :, 2], img[:, :, 6], img[:, :, 4]]),
norm_edge=True)
odimg1 = imageprocess.normalize_edgestrip(odimg1)
odimg2 = imageprocess.normalize_edgestrip(odimg2)
balance = odimg1[roi].mean() / odimg2[roi].mean()
self.ax1.imshow(transimg1, vmin=0, vmax=1.35, cmap=mpl.cm.gray)
self.ax2.imshow(transimg2, vmin=0, vmax=1.35, cmap=mpl.cm.gray)
self.balance_label.setText('The balance is %s' % balance)
def main(self, img, roi):
"""Create dialog and image inside it"""
self.img = img
self.roi = roi
transimg1, odimg1 = imageprocess.calc_absimage(np.dstack([img[:, :, 1],
img[:, :, 5],
img[:, :, 3]]),
norm_edge=True)
transimg2, odimg2 = imageprocess.calc_absimage(np.dstack([img[:, :, 2],
img[:, :, 6],
img[:, :, 4]]),
norm_edge=True)
odimg1 = imageprocess.normalize_edgestrip(odimg1)
odimg2 = imageprocess.normalize_edgestrip(odimg2)
balance = odimg1[roi].mean() / odimg2[roi].mean()
self.ax1.imshow(transimg1, vmin=0, vmax=1.35, cmap=mpl.cm.gray)
self.ax2.imshow(transimg2, vmin=0, vmax=1.35, cmap=mpl.cm.gray)
self.balance_label.setText('The balance is %s'%balance)
def main(self, img, roi):
"""Create dialog and image inside it"""
self.img = img
self.roi = roi
pwa = img[:,:,0]
pwoa = img[:,:,1]
df = img[:,:,2]
pwa=pwa[roi]
pwoa=pwoa[roi]
df=df[roi]
transimg1, odimg1 = imageprocess.calc_absimage(img,norm_edge=True)
##transimg, odimg, com, n0, a, bprime = norm_and_guess(img)
##rad_coord, rad_profile = radial_interpolate(odimg, com, 0.3)
##self.ax.plot(rad_coord, rad_profile)
##self.ax.set_xlabel(r'pix')
##self.ax.set_ylabel(r'OD')
pixcal = 10e-6 # 10um / pix
# normalized the image
transimg, odimg, com, n0, q, bprime = norm_and_guess(transimg1)
# choose starting values for fit
x, y, width_x, width_y = fitfuncs2D.gaussian_moments_2D(odimg)
guess = np.zeros(10.)
guess[0:4] = [com[0], com[1], width_x, width_y]
guess[4] = n0
guess[5:] = [q, 0., 0., 0., 0.]
# do the fit, and find temperature and number of atoms
ans = fitfuncs2D.fit2dfuncraw(fitfuncs2D.idealfermi_2D_angled, pwa, pwoa, df, guess, tol=1e-10)
ToverTF, N = fitfuncs2D.ideal_fermi_numbers_2D_angled(ans, pixcal)
#print ans
#print 'T/TF = ', ToverTF[0]
#print 'N = %1.2f million'%(N * 1e-6)
self.ax.text(0.1, 0.8, str(ans))
self.ax.text(0.1, 0.4, 'T/TF = %1.3f'%(ToverTF[0]))
self.ax.text(0.1, 0.2, 'N = %1.2f million'%(N * 1e-6))
## show the fit residuals
residuals = fitfuncs2D.residuals_2D(odimg, ans, func=fitfuncs2D.idealfermi_2D_angled, smooth=4, showfig=False)
self.ax1.imshow(residuals, vmin=0, vmax=.1, cmap=mpl.cm.gray)
self.ax2.imshow(odimg, vmin=0, vmax=1.35, cmap=mpl.cm.gray)
def create_window(self, img, roi, name):
"""A misnomer, but this is what the function Odysseus calls.
**Inputs**
* img: 2d-array, containing the image data
* roi: tuple of slices, contains two slice objects, one for each
image axis. The tuple can be used as a 2D slice object.
* name: string, the name of the plugin
"""
rawframes = imageio.import_rawframes(self.imgpath)
transimg, odimg = imageprocess.calc_absimage(rawframes)
# set the ROI
transimg = transimg[roi]
texreport.generate_report(rawframes, transimg, self.imgpath, showpdf=False)
# no window, so return None
return None
def show_rawframes(rawdata, figname=None, showfig=False):
"""Plots the transmission image together with the 3 raw images
**Inputs**
* rawdata: 3D array, containing pwa, pwoa, df. Last dimension is frame
index
* figname: str, if not None the figure is saved with this filename
* showfig: bool, if True pop up a figure with pylab.show()
**Outputs**
* fig: matplotlib figure instance
"""
transimg, odimg = calc_absimage(rawdata)
aspect = transimg.shape[0]/float(transimg.shape[1])
fig = pylab.figure(figsize=(8, 8*aspect))
ax1 = fig.add_subplot(221)
ax2 = fig.add_subplot(222)
ax3 = fig.add_subplot(223)
ax4 = fig.add_subplot(224)
ax1.imshow(transimg, cmap=pylab.cm.gray, vmin=0, vmax=1.35)
ax2.imshow(rawdata[:, :, 0], cmap=pylab.cm.gray)
ax3.imshow(rawdata[:, :, 1], cmap=pylab.cm.gray)
ax4.imshow(rawdata[:, :, 2], cmap=pylab.cm.gray)
for ax in [ax1, ax2, ax3, ax4]:
ax.set_xticks([])
ax.set_yticks([])
_save_or_show(figname=figname, showfig=showfig)
return fig
def show_rawframes(rawdata, figname=None, showfig=False):
"""Plots the transmission image together with the 3 raw images
**Inputs**
* rawdata: 3D array, containing pwa, pwoa, df. Last dimension is frame
index
* figname: str, if not None the figure is saved with this filename
* showfig: bool, if True pop up a figure with pylab.show()
**Outputs**
* fig: matplotlib figure instance
"""
transimg, odimg = calc_absimage(rawdata)
aspect = transimg.shape[0] / float(transimg.shape[1])
fig = pylab.figure(figsize=(8, 8 * aspect))
ax1 = fig.add_subplot(221)
ax2 = fig.add_subplot(222)
ax3 = fig.add_subplot(223)
ax4 = fig.add_subplot(224)
ax1.imshow(transimg, cmap=pylab.cm.gray, vmin=0, vmax=1.35)
ax2.imshow(rawdata[:, :, 0], cmap=pylab.cm.gray)
ax3.imshow(rawdata[:, :, 1], cmap=pylab.cm.gray)
ax4.imshow(rawdata[:, :, 2], cmap=pylab.cm.gray)
for ax in [ax1, ax2, ax3, ax4]:
ax.set_xticks([])
ax.set_yticks([])
_save_or_show(figname=figname, showfig=showfig)
return fig
def create_window(self, img, roi, name):
"""A misnomer, but this is what the function Odysseus calls.
**Inputs**
* img: 2d-array, containing the image data
* roi: tuple of slices, contains two slice objects, one for each
image axis. The tuple can be used as a 2D slice object.
* name: string, the name of the plugin
"""
rawframes = imageio.import_rawframes(self.imgpath)
transimg, odimg = imageprocess.calc_absimage(rawframes)
# set the ROI
transimg = transimg[roi]
texreport.generate_report(rawframes,
transimg,
self.imgpath,
showpdf=False)
# no window, so return None
return None
