def remove_baseline(df, method='ALS', segment=True, params=None):
wvls = np.array(df['wvl'].columns.values, dtype='float')
spectra = np.array(df['wvl'], dtype='float')
# set baseline removal object (br) to the specified method
if method == 'ALS':
br = ALS(**params)
elif method == 'Dietrich':
br = Dietrich(**params)
elif method == 'Polyfit':
br = PolyFit(**params)
elif method == 'AirPLS':
br = AirPLS(**params)
elif method == 'FABC':
br = FABC(**params)
elif method == 'KK':
br = KK(**params)
elif method == 'Median':
br = MedianFilter(**params)
elif method == 'Rubberband':
br = Rubberband(**params)
elif method == 'Wavelet a Trous + Spline':
br = wavelet_spline(**params)
elif method == 'Min + Interpolate':
br = minimum_interp(**params)
else:
print(f'{method} is not recognized!')
return 0
br.fit(wvls, spectra, segment=segment)
df_baseline = df.copy()
df_baseline['wvl'] = br.baseline
df['wvl'] = df['wvl'] - df_baseline['wvl']
return df, df_baseline
def run(self):
methodParameters = {
'num_iters_': self.n_iter_spin.value(),
'num_ranges_': self.numOfRangesSpinBox.value()
}
return methodParameters, self.getChangedValues(methodParameters,
Rubberband())
def remove_baseline(df, method='ALS', segment=True, params=None):
wvls = np.array(df['wvl'].columns.values, dtype='float')
spectra = np.array(df['wvl'], dtype='float')
# set baseline removal object (br) to the specified method
if method == 'ALS':
br = ALS()
elif method == 'Dietrich':
br = Dietrich()
elif method == 'Polyfit':
br = PolyFit()
elif method == 'AirPLS':
br = AirPLS()
elif method == 'FABC':
br = FABC()
elif method == 'KK':
br = KK()
elif method == 'Mario':
br = Mario()
elif method == 'Median':
br = MedianFilter()
elif method == 'Rubberband':
br = Rubberband()
elif method == 'Wavelet a Trous + Spline':
br = wavelet_spline()
elif method == 'Min + Interpolate':
br = minimum_interp()
else:
print(method + ' is not recognized!')
# if parameters are provided, use them to set the parameters of br
if params is not None:
for i in params.keys():
try:
setattr(br, i, params[i])
except:
print('Required keys are:')
print(br.__dict__.keys())
print('Exiting without removing baseline!')
return
br.fit(wvls, spectra, segment=segment)
df_baseline = df.copy()
df_baseline['wvl'] = br.baseline
df['wvl'] = df['wvl']-df_baseline['wvl']
return df, df_baseline
def connectWidgets(self):
br = Rubberband()
self.n_iter_spin.setValue(br.num_iters_)
self.numOfRangesSpinBox.setValue(br.num_ranges_)