DataPipeline/Processing.py
def baselinecorrection(self, x, y, segmentsize=0.3):
        """Detect and remove baseline by dividing list into segments and
           then interpolating the result over all x values"""        
        seg = int(len(x) * segmentsize)
        bx=[];by=[]
        for i in range(0,len(x),seg):
            m = np.min(y[i:i+seg])
            bx.append(i)
            by.append(m)
        by = np.interp(x, bx, by)
        y=y-by
        return x, y
Detect and remove baseline by dividing list into segments and
           then interpolating the result over all x values
Detect and remove baseline by dividing list into segments and
then interpolating the result over all x values
Detect and remove baseline by dividing list into segments and then interpolating the result over all x values
def baselinecorrection(self, x, y, segmentsize=0.3):
        seg = int(len(x) * segmentsize)
        bx=[];by=[]
        for i in range(0,len(x),seg):
            m = np.min(y[i:i+seg])
            bx.append(i)
            by.append(m)
        by = np.interp(x, bx, by)
        y=y-by
        return x, y
def baselinecorrection ( self , x , y , segmentsize = 0.3 ) : seg = int ( len ( x ) * segmentsize ) bx = [ ] ; by = [ ] for i in range ( 0 , len ( x ) , seg ) : m = np . min ( y [ i : i + seg ] ) bx . append ( i ) by . append ( m ) by = np . interp ( x , bx , by ) y = y - by return x , y
Detect and remove baseline by dividing list into segments and
then interpolating the result over all x values
Detect and remove baseline by dividing list into segments and then interpolating the result over all x values
"""Detect and remove baseline by dividing list into segments and
           then interpolating the result over all x values"""
self
x
y
segmentsize