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from Packages import *
class DxReader:
'''This module is designed to help retrieve spectral data as well as metadata of smaples from jcamp file'''
def __init__(self, path):
self.__path = path.replace('\\','/')
self.__dxfile = jc.jcamp_readfile(self.__path)
# Access samples data
self.__nb = self.__dxfile['blocks'] # Get the total number of blocks = The total number of scanned samples
self.__list_of_blocks = self.__dxfile['children'] # Store all blocks within a a list
self.__wl = self.__list_of_blocks[0]["x"] # Wavelengths/frequencies/range
# Start retreiving the data
specs = np.zeros((self.__nb, len(self.__list_of_blocks[0]["y"])), dtype=float) # preallocate a np matrix for sotoring spectra
self.idx = np.arange(self.__nb) # This list is designed to store samples name
self.__met = {}
for i in range(self.__nb): # Loop over the blocks
specs[i] = self.__list_of_blocks[i]['y']
block_met = { 'name':self.__list_of_blocks[i]['title'],
'origin':self.__list_of_blocks[i]['origin'],
'date':self.__list_of_blocks[i]['date'],
'time':self.__list_of_blocks[i]['time'],
'spectrometer/data system':self.__list_of_blocks[i]['spectrometer/data system'],
'instrumental parameters':self.__list_of_blocks[i]['instrumental parameters'],
'xunits':self.__list_of_blocks[i]['xunits'],
'yunits':self.__list_of_blocks[i]['yunits'],
'xfactor':self.__list_of_blocks[i]['xfactor'],
'yfactor':self.__list_of_blocks[i]['yfactor'],
'firstx':self.__list_of_blocks[i]['firstx'],
'lastx':self.__list_of_blocks[i]['lastx'],
'firsty':self.__list_of_blocks[i]['firsty'],
'miny': self.__list_of_blocks[i]['miny'],
'maxy': self.__list_of_blocks[i]['maxy'],
'npoints':self.__list_of_blocks[i]['npoints'],
'concentrations':self.__list_of_blocks[i]['concentrations'],
'deltax':self.__list_of_blocks[i]['deltax'],
}
self.__met[f'{i}'] = block_met
self.metadata_ = pd.DataFrame(self.__met).T
self.spectra = pd.DataFrame(np.fliplr(specs), columns= self.__wl[::-1]) # Storing spectra in a pd.dataframe
#### Concentrarions
self.pattern = r"\(([^,]+),(\d+(\.\d+)?),([^)]+)"
aa = self.__list_of_blocks[0]['concentrations']
a = '\n'.join(line for line in aa.split('\n') if "NCU" not in line and "<<undef>>" not in line)
n_elements = a.count('(')
## Get the name of analyzed chamical elements
elements_name = []
for match in re.findall(self.pattern, a):
elements_name.append(match[0])
## Retrieve concentrationds
df = self.metadata_['concentrations']
cc = {}
for i in range(self.metadata_.shape[0]):
cc[df.index[i]] = self.conc(df[str(i)])
### dataframe conntaining chemical data
self.chem_data = pd.DataFrame(cc, index=elements_name).T
### Method for retrieving the concentration of a single sample
def conc(self,sample):
prep = '\n'.join(line for line in sample.split('\n') if "NCU" not in line and "<<undef>>" not in line)
c = []
for match in re.findall(self.pattern, prep):
c.append(match[1])
concentration = np.array(c)
return concentration
@property
def specs_df_(self):
return self.spectra
@property
def md_df_(self):
return self.metadata_
@property
def chem_data_(self):
return self.chem_data