def LoadShowImage(self):
QtGui.QApplication.setOverrideCursor(QCursor(Qt.WaitCursor))
#initialization
self.data_struct = data_struct.h5()
self.stk_sam = data_stack.data(self.data_struct)
self.stk_bkg = data_stack.data(self.data_struct)
self.anlz_sam = analyze.analyze(self.stk_sam)
self.anlz_bkg = analyze.analyze(self.stk_bkg)
self.common = common()
#load sample and background
if self.ui.samTxrm.isChecked() == True:
#self.new_stack_refresh()
self.stk_sam.new_data()
#self.stk.data_struct.delete_data()
self.anlz_sam.delete_data()
self.stk_sam.read_txrm(self.sam_filepath)
if self.ui.samXrm.isChecked() == True:
self.stk_sam.new_data()
self.anlz_sam.delete_data()
#self.sam_filelist = os.path.basename(str(self.sam_filepaths))
self.stk_sam.read_xrm_list(self.sam_filepaths)
if self.ui.bkgTxrm.isChecked() == True:
self.stk_bkg.new_data()
self.anlz_bkg.delete_data()
self.stk_bkg.read_txrm(self.bkg_filepath)
if self.ui.bkgXrm.isChecked() == True:
self.stk_bkg.new_data()
self.anlz_bkg.delete_data()
#self.bkg_filelist = os.path.basename(str(self.bkg_filepaths))
self.stk_bkg.read_xrm_list(self.bkg_filepaths)
self.common.stack_loaded == 1
#update image information
self.iev = int(self.stk_sam.n_ev)
x = self.stk_sam.n_cols
y = self.stk_sam.n_rows
z = self.iev
print(z)
self.ix = int(x / 2)
self.iy = int(y / 2)
#calculate scaleimg
sam_image_stack = self.stk_sam.absdata.copy()
bkg_image_stack = self.stk_bkg.absdata.copy()
self.scale_image_stack = np.true_divide(sam_image_stack,
bkg_image_stack)
#refresh_widgets
#show image
self.ShowImage()
QtGui.QApplication.restoreOverrideCursor()
def LoadShowImage(self):
QtGui.QApplication.setOverrideCursor(QCursor(Qt.WaitCursor))
#initialization
self.data_struct = data_struct.h5()
self.stk_sam = data_stack.data(self.data_struct)
self.stk_bkg = data_stack.data(self.data_struct)
self.anlz_sam = analyze.analyze(self.stk_sam)
self.anlz_bkg = analyze.analyze(self.stk_bkg)
self.common = common()
#load sample and background
if self.ui.samTxrm.isChecked() == True:
#self.new_stack_refresh()
self.stk_sam.new_data()
#self.stk.data_struct.delete_data()
self.anlz_sam.delete_data()
self.stk_sam.read_txrm(self.sam_filepath)
if self.ui.samXrm.isChecked() == True:
self.stk_sam.new_data()
self.anlz_sam.delete_data()
#self.sam_filelist = os.path.basename(str(self.sam_filepaths))
self.stk_sam.read_xrm_list(self.sam_filepaths)
if self.ui.bkgTxrm.isChecked() == True:
self.stk_bkg.new_data()
self.anlz_bkg.delete_data()
self.stk_bkg.read_txrm(self.bkg_filepath)
if self.ui.bkgXrm.isChecked() == True:
self.stk_bkg.new_data()
self.anlz_bkg.delete_data()
#self.bkg_filelist = os.path.basename(str(self.bkg_filepaths))
self.stk_bkg.read_xrm_list(self.bkg_filepaths)
self.common.stack_loaded == 1
#update image information
self.iev = int(self.stk_sam.n_ev)
x=self.stk_sam.n_cols
y=self.stk_sam.n_rows
z=self.iev
print(z)
self.ix = int(x/2)
self.iy = int(y/2)
#calculate scaleimg
sam_image_stack = self.stk_sam.absdata.copy()
bkg_image_stack = self.stk_bkg.absdata.copy()
self.scale_image_stack = np.true_divide(sam_image_stack,bkg_image_stack)
#refresh_widgets
#show image
self.ShowImage()
QtGui.QApplication.restoreOverrideCursor()
def LoadShowImage(self):
self.ui.status_bkgnorm.setText('status: running')
QtGui.QApplication.setOverrideCursor(QCursor(Qt.WaitCursor))
#initialization
self.data_struct = data_struct.h5()
self.stk_sam = data_stack.data(self.data_struct)
self.stk_bkg = data_stack.data(self.data_struct)
self.anlz_sam = analyze.analyze(self.stk_sam)
self.anlz_bkg = analyze.analyze(self.stk_bkg)
self.common = common()
#load sample and background
if self.ui.samTxrm.isChecked() == True:
#self.new_stack_refresh()
self.stk_sam.new_data()
#self.stk.data_struct.delete_data()
self.anlz_sam.delete_data()
self.stk_sam.read_txrm(self.sam_filepath, self.data_struct)
if self.ui.samXrm.isChecked() == True:
self.stk_sam.new_data()
self.anlz_sam.delete_data()
#self.sam_filelist = os.path.basename(str(self.sam_filepaths))
self.stk_sam.read_xrm_list(self.sam_filepaths)
if self.ui.bkgTxrm.isChecked() == True:
self.stk_bkg.new_data()
self.anlz_bkg.delete_data()
self.stk_bkg.read_txrm(self.bkg_filepath, self.data_struct)
if self.ui.bkgXrm.isChecked() == True:
self.stk_bkg.new_data()
self.anlz_bkg.delete_data()
#self.bkg_filelist = os.path.basename(str(self.bkg_filepaths))
self.stk_bkg.read_xrm_list(self.bkg_filepaths)
self.common.stack_loaded == 1
#update image information
self.iev = int(self.stk_sam.n_ev)
self.currentSliderStep = self.iev - 1
self.ev = self.data_struct.exchange.energy
#calculate scaleimg
sam_image_stack = self.stk_sam.absdata.copy()
bkg_image_stack = self.stk_bkg.absdata.copy()
self.scale_image_stack = np.true_divide(sam_image_stack,bkg_image_stack)
#show image
self.ShowImage(self.currentSliderStep,self.scale_min,self.scale_max,self.rawImagePosX,self.rawImagePosY,self.bin,self.edgeJump)
QtGui.QApplication.restoreOverrideCursor()
#refresh_widgets
self.ui.slider_img_maxscale.setEnabled(True)
self.ui.slider_img_minscale.setEnabled(True)
self.ui.slider_img.setEnabled(True)
self.ui.current_img.setEnabled(True)
self.ui.current_img.setText(str(self.iev))
self.ui.slider_img.setMinimum(1)
self.ui.slider_img.setMaximum(self.iev)
self.ui.total_img.setText(str(self.iev))
self.ui.status_bkgnorm.setText('status: complete')
self.ui.text_minscale.setText("Min 0 %")
self.ui.text_maxscale.setText("Max 100 %")
self.ui.select_point.setEnabled(True)
self.ui.update_spectrum.setEnabled(True)
self.ui.x_cord.setEnabled(True)
self.ui.y_cord.setEnabled(True)
self.ui.edit_edge_jump.setEnabled(True)
self.ui.pre_start.setMinimum(1)
self.ui.pre_start.setMaximum(self.iev)
self.ui.pre_end.setMinimum(1)
self.ui.pre_end.setMaximum(self.iev)
self.ui.post_start.setMinimum(1)
self.ui.post_start.setMaximum(self.iev)
self.ui.post_end.setMinimum(1)
self.ui.post_end.setMaximum(self.iev)
self.ui.edge_start.setMinimum(1)
self.ui.edge_start.setMaximum(self.iev)
self.ui.edge_end.setMinimum(1)
self.ui.edge_end.setMaximum(self.iev)
self.ui.text_pre_start.setText('PreEstart')
self.ui.text_pre_end.setText('PreEend')
self.ui.text_post_start.setText('PostEstart')
self.ui.text_post_end.setText('PostEend')
self.ui.text_edge_start.setText('EdgeStart')
self.ui.text_edge_end.setText('EdgeEnd')
def batch_mode():
verbose = 1
settingsfile = 'Mantis_batch_settings.txt'
version = '2.0.5'
wdir = ''
outdir = 'MantisResults'
filename = ''
save_hdf5 = 0
align_stack = 0
i0_file = ''
i0_histogram = 0
run_pca = 0
n_spca = 4
run_ca = 0
nclusters = 5
ca_thickness = 0
run_sa = 0
sa_spectra = []
sa_use_clspectra = 0
run_keyengs = 0
kengs_thresh = 0.10
save_png = 1
save_pdf = 0
save_svg = 0
try:
f = open(settingsfile, 'rt')
for line in f:
if ':' in line :
slist = line.split(':')
tag = slist[0]
value = ':'.join(slist[1:])
if tag == 'VERSION': version = float(value)
elif tag == 'WORK_DIR' : wdir = value.strip()
elif tag == 'OUTPUT_DIR_NAME' : outdir = value.strip()
elif tag == 'FILENAME' : filename = value.strip()
elif tag == 'ALIGN_STACK' : align_stack = value.strip()
elif tag == 'I0_FILE' : i0_file = value.strip()
elif tag == 'I0_HISTOGRAM' : i0_histogram = int(value)
elif tag == 'SAVE_HDF5' : save_hdf5 = int(value)
elif tag == 'RUN_PCA' : run_pca = int(value)
elif tag == 'N_SPCA' : n_spca = int(value)
elif tag == 'RUN_CLUSTER_ANALYSIS' : run_ca = int(value)
elif tag == 'N_CLUSTERS' : nclusters = int(value)
elif tag == 'THICKNESS_CORRECTION' : ca_thickness = int(value)
elif tag == 'RUN_SPECTRAL_ANALYSIS' : run_sa = int(value)
elif tag == 'SA_SPECTRUM' :
spname = value.strip()
if len(spname) > 0 :
sa_spectra.append(spname)
elif tag == 'SA_USE_CA_SPECTRA' : sa_use_clspectra = int(value)
elif tag == 'RUN_KEY_ENGS' : run_keyengs = int(value)
elif tag == 'KE_THRESHOLD' : kengs_thresh = float(value)
elif tag == 'SAVE_PNG' : save_png = int(value)
elif tag == 'SAVE_PDF' : save_pdf = int(value)
elif tag == 'SAVE_SVG' : save_svg = int(value)
f.close()
except:
print 'Error: Could not read in Mantis_batch_settings.txt.'
return
wdir = os.path.normpath(wdir)
if verbose:
print 'Version: ', version
print 'Working directory: ', wdir
if not os.path.exists(wdir):
print 'Error - Directory ', wdir, ' does not exist. Please specify working directory.'
return
outdir = os.path.join(wdir, outdir)
if not os.path.exists(outdir):
os.makedirs(outdir)
if not os.path.exists(outdir):
print 'Error: Did not find and could not create a new output directory.'
return
if save_png == 1:
print "Save .png images"
if save_pdf == 1:
print "Save .pdf images"
datastruct = data_struct.h5()
stk = data_stack.data(datastruct)
anlz = analyze.analyze(stk)
print 'Reading file:', filename
basename, extension = os.path.splitext(filename)
filepath = os.path.join(wdir, filename)
try:
if extension == '.hdf5':
stk.read_h5(filepath)
if extension == '.hdr':
stk.read_sdf(filepath)
if extension == '.stk':
stk.read_stk(filepath)
if extension == '.txrm':
stk.read_txrm(filepath)
if extension == '.xrm':
stk.read_xrm(filepath)
if extension == '.tif':
stk.read_tiff(filepath)
except:
print "Error: Could not load stack."
return
if align_stack:
print 'Aligning the stack'
xshifts = np.zeros((stk.n_ev))
yshifts = np.zeros((stk.n_ev))
referenceimage = stk.absdata[:,:,0].copy()
for i in range(stk.n_ev):
img2 = stk.absdata[:,:,i]
if i==0:
xshift, yshift, ccorr = stk.register_images(referenceimage, img2,
have_ref_img_fft = False)
else:
xshift, yshift, ccorr = stk.register_images(referenceimage, img2,
have_ref_img_fft = True)
# #Limit the shifts to MAXSHIFT chosen by the user
# if (self.maxshift > 0):
# if (abs(xshift) > self.maxshift):
# xshift = npy.sign(xshift)*self.maxshift
# if (abs(yshift) > self.maxshift):
# yshift = npy.sign(yshift)*self.maxshift
xshifts[i] = xshift
yshifts[i] = yshift
#Apply shifts
for i in range(stk.n_ev):
img = stk.absdata[:,:,i]
if (abs(xshifts[i])>0.02) or (abs(yshifts[i])>0.02):
shifted_img = stk.apply_image_registration(img, xshifts[i], yshifts[i])
stk.absdata[:,:,i] = shifted_img
if datastruct.spectromicroscopy.normalization.white_spectrum is not None:
print "I0 loaded"
else:
print "Loading I0"
if i0_histogram == 1:
print 'Getting I0 from the histogram'
stk.calc_histogram()
averagefluxmax = np.max(stk.histogram)
histmin = 0.98*averagefluxmax
histmax = averagefluxmax
stk.i0_from_histogram(histmin, histmax)
elif len(i0_file) > 0:
print 'Reading I0 from file:', i0_file
i0basename, i0extension = os.path.splitext(i0_file)
i0filepath = os.path.join(wdir, i0_file)
stk.read_stk_i0(i0filepath, i0extension)
else:
print "Please either set I0_HISTOGRAM to 1 to calculate I0 or specify I0 file."
return
if datastruct.spectromicroscopy.normalization.white_spectrum is None:
print 'Error: I0 not loaded'
return
if save_hdf5 == 1:
fnameh5 = os.path.join(wdir,basename+'_MantisBatch.hdf5')
stk.write_h5(fnameh5, data_struct)
print 'Saving data to HDF5 file:', fnameh5
pca_calculated = 0
if run_pca == 1:
print "Running PCA Analysis"
anlz.calculate_pca()
print "Chosen number of significant components:", n_spca
print "Suggested number of significant components:", anlz.numsigpca
pca_calculated = 1
anlz.numsigpca = n_spca
save_pca(outdir, filename, stk, anlz, save_png, save_pdf, save_svg)
ca_calculated = 0
if run_ca == 1:
if pca_calculated == 0:
anlz.calculate_pca()
print "Running Cluster Analysis"
print "Number of clusters", nclusters
if ca_thickness == 1:
print "Thickness correction enabled"
nclusters = anlz.calculate_clusters(nclusters, ca_thickness)
ca_calculated = 1
save_ca(outdir, filename, stk, anlz, save_png, save_pdf, save_svg)
if run_sa == 1:
print "Running Spectral Analysis"
if len(sa_spectra) > 0:
print "Loading spectra:", sa_spectra
for i in range(len(sa_spectra)):
sppath = os.path.join(wdir, sa_spectra[i])
anlz.read_target_spectrum(filename=sppath)
if sa_use_clspectra == 1:
if ca_calculated == 1:
print "Loading cluster spectra"
anlz.add_cluster_target_spectra()
else:
print "Please set RUN_CLUSTER_ANALYSIS to 1 to calculate cluster spectra."
if anlz.n_target_spectra > 1:
save_spa(outdir, filename, stk, anlz, save_png, save_pdf, save_svg)
if run_keyengs == 1:
if pca_calculated == 0:
anlz.calculate_pca()
print "Finding key energies"
print "Threshold for finding key energies:", kengs_thresh
key_engs= anlz.calc_key_engs(kengs_thresh)
save_keyeng(key_engs, outdir, filename, stk, anlz, save_png, save_pdf, save_svg)
if (save_hdf5 == 1) and (pca_calculated == 1) :
fnameh5 = os.path.join(wdir,basename+'_MantisBatch.hdf5')
stk.write_results_h5(fnameh5, data_struct, anlz)
print "Finished doing Mantis analysis"
return
def ExportAthena(self):
self.scale_image_stack = None
self.log_image_stack = None
self.raw_bulk = None
self.norm_image_stack = None
self.norm_bulk = None
QtGui.QApplication.setOverrideCursor(QCursor(Qt.WaitCursor))
#initialization
self.data_struct = data_struct.h5()
self.stk_sam = data_stack.data(self.data_struct)
self.stk_bkg = data_stack.data(self.data_struct)
self.anlz_sam = analyze.analyze(self.stk_sam)
self.anlz_bkg = analyze.analyze(self.stk_bkg)
#load sample and background
if self.ui.samTxrm.isChecked() == True:
#self.new_stack_refresh()
self.stk_sam.new_data()
#self.stk.data_struct.delete_data()
self.anlz_sam.delete_data()
self.stk_sam.read_txrm(self.sam_filepath, self.data_struct)
if self.ui.samXrm.isChecked() == True:
self.stk_sam.new_data()
self.anlz_sam.delete_data()
#self.sam_filelist = os.path.basename(str(self.sam_filepaths))
self.stk_sam.read_xrm_list(self.sam_filepaths)
if self.ui.bkgTxrm.isChecked() == True:
self.stk_bkg.new_data()
self.anlz_bkg.delete_data()
self.stk_bkg.read_txrm(self.bkg_filepath, self.data_struct)
if self.ui.bkgXrm.isChecked() == True:
self.stk_bkg.new_data()
self.anlz_bkg.delete_data()
#self.bkg_filelist = os.path.basename(str(self.bkg_filepaths))
self.stk_bkg.read_xrm_list(self.bkg_filepaths)
#update image information
self.iev = int(self.stk_sam.n_ev)
self.ev = self.data_struct.exchange.energy
self.sam_image_stack = self.stk_sam.absdata.copy()
self.bkg_image_stack = self.stk_bkg.absdata.copy()
self.stk_sam = None
self.stk_bkg = None
self.anlz_sam = None
self.anlz_bkg = None
X = self.rawImagePosX
Y = self.rawImagePosY
self.r_data = np.zeros(self.iev, dtype=np.int)
if self.bin > 1 :
sam_data = np.array(self.sam_image_stack[(X-self.bin/2):(X+self.bin/2+1),(Y-self.bin/2):(Y+self.bin/2+1),0:self.iev])
bkg_data = np.array(self.bkg_image_stack[(X-self.bin/2):(X+self.bin/2+1),(Y-self.bin/2):(Y+self.bin/2+1),0:self.iev])
self.sam_image_stack = None
self.bkg_image_stack = None
self.sam_data = np.mean(np.mean(sam_data, axis=0), axis=0)
self.bkg_data = np.mean(np.mean(bkg_data, axis=0), axis=0)
else:
self.sam_data = np.array(self.sam_image_stack[X,Y,0:self.iev])
self.bkg_data = np.array(self.bkg_image_stack[X,Y,0:self.iev])
self.sam_image_stack = None
self.bkg_image_stack = None
wildcard = "TXT (*.txt)"
filepath = QtGui.QFileDialog.getSaveFileName(self, 'Save Spectrum to Athena', '', wildcard)
f = open(filepath,'w')
f.write(' Energy: I0 It Ir\n')
for i in range(self.iev):
f.write("%14.5f%14.4f%14.4f%14.4f\n"%(self.ev[i],self.bkg_data[i],self.sam_data[i],self.r_data[i]))
f.close()
QtGui.QApplication.restoreOverrideCursor()