Adding sketch for normalization and flattening

This commit is contained in:
halvorhv 2022-06-15 16:00:47 +02:00
parent 7676bd06af
commit 7485adef07

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@ -356,4 +356,30 @@ def finding_e0(path, options={}):
print("Edge shift estimated by the double differential zero-point is "+str(round(edge_shift_doublediff,5)))
if options['print'] == True:
ax4.axvline(x=edge_shift_doublediff,color="green")
return df_smooth, filenames, edge_shift_diff
def normalization(data,options={}):
required_options = ['print']
default_options = {
'print': False,
}
options = aux.update_options(options=options, required_options=required_options, default_options=default_options)
#Finding the normalization constant µ_0(E_0), by subtracting the value of the pre-edge-line from the value of the post-edge line at e0
normalization_constant=post_edge_fit_function(e0) - pre_edge_fit_function(e0)
#subtracting background (as in pre_edge_subtraction)
#dividing the background-subtracted data with the normalization constant
def flattening(data,options={}):
#only picking out zapenergy-values higher than edge position (edge pos and below remains untouched)
df_e0_and_above=df.loc[df['ZapEnergy'] > edge_shift_diff]
flattened_data = post_edge_fit_function(df_e0_and_above['ZapEnergy']) - pre_edge_fit_function(df_e0_and_above['ZapEnergy'])
#make a new dataframe with flattened values