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Fixing functions

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This commit is contained in:
halvorhv 2022-04-08 13:28:47 +02:00
parent baa253ab3e
commit 7962b3fc5c
1 changed files with 3 additions and 17 deletions
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18
beamtime/xanes/calib.py
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@ -126,18 +126,7 @@ def post_edge_normalization(path, options={}):
if edge == 'Ni': if edge == 'Ni':
edge_stop = 8.361 edge_stop = 8.361
#============================================================= df_end= df_bkgd_sub.loc[df_bkgd_sub["ZapEnergy"] > edge_stop] # new dataframe only containing the post edge, where a regression line will be calculated in the for-loop below
#absolute_difference_function = lambda list_value : abs(list_value - edge_stop)
#edge_stop_value = min(df_bkgd_sub["ZapEnergy"], key=absolute_difference_function)
#end_index=df_bkgd_sub[df_bkgd_sub["ZapEnergy"]==edge_stop_value].index.values[0]
#Defining x-range for linear fit
#df_fix=df_bkgd_sub
#df_fix.dropna(inplace=True)
#df_end=df_fix[end_index:] #The region of interest for the post edge
#Fitting linear function to the pre-edge using the background corrected intensities to make the post edge fit
#===============================================================
df_end= df_bkgd_sub.loc[df_bkgd_sub["ZapEnergy"] > edge_stop] # new dataframe only containing the post edge -> to be fitted
df_end.dropna(inplace=True) #Removing all indexes without any value, as some of the data sets misses the few last data points and fucks up the fit df_end.dropna(inplace=True) #Removing all indexes without any value, as some of the data sets misses the few last data points and fucks up the fit
df_postedge = pd.DataFrame(df_bkgd_sub["ZapEnergy"]) #making a new dataframe df_postedge = pd.DataFrame(df_bkgd_sub["ZapEnergy"]) #making a new dataframe
@ -149,17 +138,14 @@ def post_edge_normalization(path, options={}):
function_post_list.append(function_post) function_post_list.append(function_post)
df_postedge.insert(1,files,y_post) #adding a new column with the y-values of the fitted post edge df_postedge.insert(1,files,y_post) #adding a new column with the y-values of the fitted post edge
#print(filenames[0])
#print(df_postedge)
#Plotting the background subtracted signal with the post-edge regression line and the start point for the linear regression line #Plotting the background subtracted signal with the post-edge regression line and the start point for the linear regression line
if options['print'] == True: if options['print'] == True:
ax = df_bkgd_sub.plot(x = "ZapEnergy",y=filenames) #defining x and y ax = df_bkgd_sub.plot(x = "ZapEnergy",y=filenames) #defining x and y
plt.axvline(x = min(df_end["ZapEnergy"])) plt.axvline(x = min(df_end["ZapEnergy"]))
fig = plt.figure(figsize=(15,15)) fig = plt.figure(figsize=(15,15))
df_postedge.plot(x="ZapEnergy", y=filenames,color="Green",ax=ax, legend=False) df_postedge.plot(x="ZapEnergy", y=filenames,color="Green",ax=ax, legend=False)
#print(function_post_list)
#print(function_post)
ax = df_bkgd_sub.plot(x = "ZapEnergy",y=filenames, legend=False) #defining x and y ax = df_bkgd_sub.plot(x = "ZapEnergy",y=filenames, legend=False) #defining x and y
df_postedge.plot(x="ZapEnergy", y=filenames,color="Green",ax=ax, legend=False) df_postedge.plot(x="ZapEnergy", y=filenames,color="Green",ax=ax, legend=False)
plt.axvline(x = min(df_end["ZapEnergy"])) plt.axvline(x = min(df_end["ZapEnergy"]))
return df_bkgd_sub, df_postedge