def read_and_convert(filename,
start_wav=None,
stop_wav=None,
data_type="absorbance",
sample_info=None):
if sample_info is None:
sample_info = ir_map.sample_info()
omnic_object = OmnicMap.OmnicMap(filename)
wavenumbers = None
if wavenumbers is None:
n_wav = omnic_object.data.shape[2]
if (start_wav is None) or (stop_wav is None):
if omnic_object.info['OmnicInfo'] is not None:
start_wav = omnic_object.info['OmnicInfo']['First X value']
stop_wav = omnic_object.info['OmnicInfo']['Last X value']
n_wav = omnic_object.info['OmnicInfo']['Number of points']
else:
raise ValueError(
'There is an issue with the Ominc file or its parser. Make sure that the meta info from the header is present and parsed correctly.'
)
wavenumbers = np.linspace(start_wav, stop_wav, n_wav)
image_grid_param = omnic_object.info['OmnicInfo'][
'Mapping stage parameters']
image_mask = np.ones(omnic_object.data.shape[0:2]) > 0.5
# build the basis object
this_ir_map = ir_map.ir_map(wavenumbers=wavenumbers,
sample_info=sample_info,
data_type=data_type)
this_ir_map.add_image_cube(omnic_object.data, image_mask, image_grid_param)
return this_ir_map
def save(self, sample_id='simulated_dataset'):
"""Save the simulated dataset as an hdf5 file.
Arguments:
----------
sample_id : A string that identifies the sample, spaces will be substituted for underscores.
"""
si = sample_info(
sample_id=sample_id,
sample_meta_data=
f"This dataset has {self.NbaseSpectra} components and map size is {self.Ny} * {self.Nx}"
)
si.show()
self.spectra_map_gen() # generate simulated dataset
y, x = np.where(self.mask)
self.xy = np.c_[x, y]
ir_data = ir_map(self.wavenumber, si, with_factorization=True)
ir_data.add_data(spectrum=self.data, xy=self.xy)
ir_data.to_image_cube()
ir_data.add_factorization(component=self.spectraMat,
component_coef=self.densityVecsCondense,
prefix='MCR')
ir_data.write_as_hdf5(f'{sample_id}.h5')
def read_npy(filename, wavenumbers=None, data_type="absorbance", sample_info=None):
if sample_info is None:
sample_info = ir_map.sample_info()
data = np.load(filename)
if wavenumbers is None:
wavenumbers = np.arange(data.shape[2])
image_grid_param = [0, 0, 1, 1]
image_mask = np.ones(data.shape[0:2]) > 0.5
this_ir_map = ir_map.ir_map(wavenumbers=wavenumbers,
sample_info=sample_info,
data_type=data_type)
this_ir_map.add_image_cube(data, image_mask, image_grid_param)
return this_ir_map
def read_npz(filename, data_type="absorbance", sample_info=None):
if sample_info is None:
sample_info = ir_map.sample_info()
npzFile = np.load(filename)
for k in npzFile.files:
if 'energy' in k:
wavenumbers = npzFile[k]
else:
data = npzFile[k]
image_grid_param = [0, 0, 1, 1]
image_mask = np.ones(data.shape[0:2]) > 0.5
this_ir_map = ir_map.ir_map(wavenumbers=wavenumbers,
sample_info=sample_info,
data_type=data_type)
this_ir_map.add_image_cube(data, image_mask, image_grid_param)
return this_ir_map
def openBtnClicked(self):
# open omnic map file
if self.fileFormat == 'map':
self.filePath, self.fileName, canceled = uiGetFile(
'Open map file', self.path, "Omnic Map Files (*.map)")
elif self.fileFormat == 'npy':
self.filePath, self.fileName, canceled = uiGetFile(
'Open npy file', self.path, "Numpy array Files (*.npy)")
if canceled:
self.infoBox.setText('Open file canceled.')
return
# set sample_id
if self.sampleName.text() == 'None':
sample_info = ir_map.sample_info(sample_id=self.fileName[:-4])
else:
sample_info = ir_map.sample_info(sample_id=self.sampleName.text())
#try to open omnic map file
try:
if self.fileFormat == 'map':
self.irMap = read_and_convert(self.filePath + self.fileName,
sample_info=sample_info)
elif self.fileFormat == 'npy':
self.irMap = read_npy(self.filePath + self.fileName,
sample_info=sample_info)
except Exception as error:
self.infoBox.setText(error.args[0] +
f'\nFailed to open file: {self.fileName}.')
else:
if self.fileFormat == 'map':
# check whether to perform T->A conversion
spec0 = self.irMap.imageCube[0, 0, :]
maxSpecY = np.max(spec0)
if (not self.T2AConvert.isChecked()) and (maxSpecY >=
self.minYLimit):
userMsg = YesNoDialog(
f'max(Y) of the first spectrum is greater than {self.minYLimit}, \
while the "Auto T->A" box is not checked. \nPlease make sure data format is in absorbance.\
\nDo you want to perform "Auto T->A" conversion?')
userChoice = userMsg.choice()
if userChoice == QMessageBox.Yes:
self.T2AConvert.setChecked(True)
self.irMap.imageCube = -np.log10(self.irMap.imageCube /
100 + self.epsilon)
self.irMap.data = -np.log10(self.irMap.data / 100 +
self.epsilon)
self.infoBox.setText(
f'User chooses to perform T->A conversion in {self.fileName}.'
)
else:
self.infoBox.setText(
f'User chooses not to perform T->A conversion in {self.fileName}.'
)
elif maxSpecY >= self.minYLimit:
self.irMap.imageCube = -np.log10(self.irMap.imageCube /
100 + self.epsilon)
self.irMap.data = -np.log10(self.irMap.data / 100 +
self.epsilon)
self.infoBox.setText(
f'T->A conversion is performed in {self.fileName}.')
else:
self.infoBox.setText(
f"{self.fileName}'s datatype is absorbance. \nT->A conversion is not performed."
)
self.dataCube = np.moveaxis(np.flipud(self.irMap.imageCube), -1, 0)
# set up required data/properties in self.imageview
row, col = self.irMap.imageCube.shape[
0], self.irMap.imageCube.shape[1]
wavenumbers = self.irMap.wavenumbers
rc2ind = {tuple(x[1:]): x[0] for x in self.irMap.ind_rc_map}
self.updateImage(row, col, wavenumbers, rc2ind, self.dataCube)
# set up required data/properties in self.spectra
self.spectra.wavenumbers = self.imageview.wavenumbers
self.spectra.rc2ind = self.imageview.rc2ind
self.spectra._data = self.irMap.data
def run(self):
n_files = len(self.filePaths)
for i, filePath in enumerate(self.filePaths):
folderPath = os.path.dirname(filePath) + '/'
fileName = os.path.basename(filePath)
# set sample_id
if self.sampleName == 'None':
sample_info = ir_map.sample_info(sample_id=fileName[:-4])
else:
sample_info = ir_map.sample_info(sample_id=self.sampleName)
# try open omnic map and show image
try:
irMap = read_and_convert(filePath, sample_info=sample_info)
except Exception as error:
self.sigText.emit(error.args[0] +
f'\nFailed to open file: {fileName}.')
MsgBox(error.args[0] + f'\nFailed to open file: {fileName}.')
break
else:
# check whether to perform T->A conversion
spec0 = irMap.imageCube[0, 0, :]
maxSpecY = np.max(spec0)
if (not self.T2AConvertStatus) and (maxSpecY >=
self.minYLimit):
userMsg = YesNoDialog(
f'max(Y) of the first spectrum is greater than {self.minYLimit}, \
while the "Auto T->A" box is not checked. \nPlease make sure data format is in absorbance.\
\nDo you want to perform "Auto T->A" conversion?')
# get user choice
userMsg.addButton(QMessageBox.YesToAll)
userChoice = userMsg.choice()
if userChoice == QMessageBox.YesToAll: # set 'auto T->A' on
self.sigT2A.emit(True)
if (userChoice
== QMessageBox.YesToAll) or (userChoice
== QMessageBox.Yes):
irMap.imageCube = -np.log10(irMap.imageCube / 100 +
self.epsilon)
irMap.data = -np.log10(irMap.data / 100 + self.epsilon)
self.sigText.emit(
f'User chooses to perform T->A conversion in {fileName}.'
)
else:
self.sigText.emit(
f'User chooses not to perform T->A conversion in {fileName}.'
)
elif maxSpecY >= self.minYLimit:
irMap.imageCube = -np.log10(irMap.imageCube / 100 +
self.epsilon)
irMap.data = -np.log10(irMap.data / 100 + self.epsilon)
self.sigText.emit(
f'T->A conversion is performed in {fileName}.')
else:
self.sigText.emit(
f"{fileName}'s datatype is absorbance. \nT->A conversion is not performed."
)
dataCube = np.moveaxis(np.flipud(irMap.imageCube), -1, 0)
# set up required data/properties in self.imageview and show image
row, col = irMap.imageCube.shape[0], irMap.imageCube.shape[1]
wavenumbers = irMap.wavenumbers
rc2ind = {tuple(x[1:]): x[0] for x in irMap.ind_rc_map}
self.sigImage.emit((row, col, wavenumbers, rc2ind, dataCube))
# save hdf5
h5Name = fileName[:-4] + '.h5'
try:
irMap.write_as_hdf5(folderPath + h5Name)
self.sigText.emit(
f'#{i + 1} out of {n_files} maps HDF5-conversion complete! \
\nHDF5 File Location: {folderPath + h5Name}')
except Exception as error:
MsgBox(error.args[0], 'error')
break
# QTimer.singleShot(0, lambda: self.infoBox.setText(f'Start processing #{i + 1} out of {n_files} files.'))
# MsgBox('All file conversion complete!')
self.quit()
def batchBtnClicked(self):
folderPath, canceled = uiGetDir('Select a folder', self.path)
if canceled:
self.infoBox.setText('Open folder canceled.')
return
filePaths = glob(folderPath + '*.map')
# if no map file was found
if not filePaths:
MsgBox('No .map file was found.\nPlease select another folder')
self.infoBox.setText(
'No .map file was found in the selected folder.')
return
#try to use thread
# mapConverter = BatchMapConverter(self.T2AConvert.isChecked(), self.sampleName.text(),\
# self.epsilon, self.minYLimit, filePaths)
# mapConverter.sigText.connect(lambda x:self.infoBox.setText(x))
# mapConverter.sigImage.connect(lambda x:self.updateImage(*x))
# mapConverter.sigT2A.connect(lambda x:self.T2AConvert.setChecked(x))
# mapConverter.start()
# ToDo : change this Long loop to thread
n_files = len(filePaths)
for i, filePath in enumerate(filePaths):
fileName = os.path.basename(filePath)
# set sample_id
if self.sampleName.text() == 'None':
sample_info = ir_map.sample_info(sample_id=fileName[:-4])
else:
sample_info = ir_map.sample_info(
sample_id=self.sampleName.text())
# try open omnic map and show image
try:
irMap = read_and_convert(filePath, sample_info=sample_info)
except Exception as error:
self.infoBox.setText(error.args[0] +
f'\nFailed to open file: {fileName}.')
MsgBox(error.args[0] + f'\nFailed to open file: {fileName}.')
break
else:
# check whether to perform T->A conversion
spec0 = irMap.imageCube[0, 0, :]
maxSpecY = np.max(spec0)
if (not self.T2AConvert.isChecked()) and (maxSpecY >=
self.minYLimit):
userMsg = YesNoDialog(
f'max(Y) of the first spectrum is greater than {self.minYLimit}, \
while the "Auto T->A" box is not checked. \nPlease make sure data format is in absorbance.\
\nDo you want to perform "Auto T->A" conversion?')
# get user choice
userMsg.addButton(QMessageBox.YesToAll)
userChoice = userMsg.choice()
if userChoice == QMessageBox.YesToAll: # set 'auto T->A' on
self.T2AConvert.setChecked(True)
if (userChoice
== QMessageBox.YesToAll) or (userChoice
== QMessageBox.Yes):
irMap.imageCube = -np.log10(irMap.imageCube / 100 +
self.epsilon)
irMap.data = -np.log10(irMap.data / 100 + self.epsilon)
self.infoBox.setText(
f'User chooses to perform T->A conversion in {fileName}.'
)
else:
self.infoBox.setText(
f'User chooses not to perform T->A conversion in {fileName}.'
)
elif maxSpecY >= self.minYLimit:
irMap.imageCube = -np.log10(irMap.imageCube / 100 +
self.epsilon)
irMap.data = -np.log10(irMap.data / 100 + self.epsilon)
self.infoBox.setText(
f'T->A conversion is performed in {fileName}.')
else:
self.infoBox.setText(
f"{fileName}'s datatype is absorbance. \nT->A conversion is not performed."
)
dataCube = np.moveaxis(np.flipud(irMap.imageCube), -1, 0)
# set up required data/properties in self.imageview and show image
row, col = irMap.imageCube.shape[0], irMap.imageCube.shape[1]
wavenumbers = irMap.wavenumbers
rc2ind = {tuple(x[1:]): x[0] for x in irMap.ind_rc_map}
self.updateImage(row, col, wavenumbers, rc2ind, dataCube)
# save hdf5
h5Name = fileName[:-4] + '.h5'
try:
irMap.write_as_hdf5(folderPath + h5Name)
self.infoBox.setText(
f'#{i+1} out of {n_files} maps HDF5-conversion complete! \
\nHDF5 File Location: {folderPath + h5Name}')
except Exception as error:
MsgBox(error.args[0], 'error')
break
QApplication.processEvents()
MsgBox('All file conversion complete!')
)
wavenumbers = np.linspace(start_wav, stop_wav, n_wav)
image_grid_param = omnic_object.info['OmnicInfo'][
'Mapping stage parameters']
image_mask = np.ones(omnic_object.data.shape[0:2]) > 0.5
# build the basis object
this_ir_map = ir_map.ir_map(wavenumbers=wavenumbers,
sample_info=sample_info,
data_type=data_type)
this_ir_map.add_image_cube(omnic_object.data, image_mask, image_grid_param)
return this_ir_map
if __name__ == "__main__":
map_name = '190519_N2_L2w1_mp2' + '.map'
file_name = '../../ir_data/' + map_name
sample_id = file_name
sample_id = sample_id.replace("../", "")
sample_id = sample_id.replace(".map", "")
sample_id = sample_id.replace("/", "_")
sample_id = sample_id.replace(" ", "_")
print(sample_id)
sample_info = ir_map.sample_info(sample_id=sample_id,
sample_meta_data='Hello World')
data = read_and_convert(file_name, sample_info=sample_info)
data.write_as_hdf5('../../ir_data/' + map_name + '.h5')
