rasmus/nafuma
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions

Clear up small bugs encountered during testing

Browse source
This commit is contained in:
rasmusvt 2022-06-16 17:55:42 +02:00
parent 303704c357
commit 0b89524ef1
1 changed files with 12 additions and 11 deletions
Download patch file Download diff file Expand all files Collapse all files

23
nafuma/xanes/calib.py
View file

@ -22,13 +22,13 @@ def find_element(data: dict) -> str:
'Ni': [8.0, 8.6] 'Ni': [8.0, 8.6]
} }
if element_energy_intervals['Mn'][0] < data['xanes_data']["ZapEnergy"][0] < element_energy_intervals['Mn'][1]: if (element_energy_intervals['Mn'][0] < data['xanes_data_original']["ZapEnergy"].iloc[0]) & (data['xanes_data_original']["ZapEnergy"].iloc[0] < element_energy_intervals['Mn'][1]):
edge = 'Mn' edge = 'Mn'
elif element_energy_intervals['Co'][0] < data['xanes_data']["ZapEnergy"][0] < element_energy_intervals['Fe'][1]: elif (element_energy_intervals['Fe'][0] < data['xanes_data_original']["ZapEnergy"].iloc[0]) & (data['xanes_data_original']["ZapEnergy"].iloc[0] < element_energy_intervals['Fe'][1]):
edge = 'Fe' edge = 'Fe'
elif element_energy_intervals['Co'][0] < data['xanes_data']["ZapEnergy"][0] < element_energy_intervals['Co'][1]: elif (element_energy_intervals['Co'][0] < data['xanes_data_original']["ZapEnergy"].iloc[0]) & (data['xanes_data_original']["ZapEnergy"].iloc[0] < element_energy_intervals['Co'][1]):
edge = 'Co' edge = 'Co'
elif element_energy_intervals['Ni'][0] < data['xanes_data']["ZapEnergy"][0] < element_energy_intervals['Ni'][1]: elif (element_energy_intervals['Ni'][0] < data['xanes_data_original']["ZapEnergy"].iloc[0]) & (data['xanes_data_original']["ZapEnergy"].iloc[0] < element_energy_intervals['Ni'][1]):
edge = 'Ni' edge = 'Ni'
@ -45,7 +45,7 @@ def pre_edge_fit(data: dict, options={}) -> pd.DataFrame:
default_options = { default_options = {
'edge_start': None, 'edge_start': None,
'log': False, 'log': False,
'logfile': f'{datetime.now().strftime("%Y-%m-%d-%H-%M-%S.log")}_pre_edge_fit.log', 'logfile': f'{datetime.now().strftime("%Y-%m-%d-%H-%M-%S")}_pre_edge_fit.log',
'save_plots': False, 'save_plots': False,
'save_folder': './' 'save_folder': './'
} }
@ -62,11 +62,12 @@ def pre_edge_fit(data: dict, options={}) -> pd.DataFrame:
if not options['edge_start']: if not options['edge_start']:
edge_starts = { edge_starts = {
'Mn': 6.42, 'Mn': 6.42,
'Fe': 7.11, 'Fe': 7.09,
'Co': 7.705, 'Co': 7.705,
'Ni': 8.3 'Ni': 8.3
} }
data['edge'] = find_element(data)
edge_start = edge_starts[data['edge']] edge_start = edge_starts[data['edge']]
# FIXME There should be an option to specify the interval in which to fit the background - now it is taking everything to the left of edge_start parameter, but if there are some artifacts in this area, it should be possible to # FIXME There should be an option to specify the interval in which to fit the background - now it is taking everything to the left of edge_start parameter, but if there are some artifacts in this area, it should be possible to
@ -79,7 +80,7 @@ def pre_edge_fit(data: dict, options={}) -> pd.DataFrame:
for i, filename in enumerate(data['path']): for i, filename in enumerate(data['path']):
if options['log']: if options['log']:
aux.write_log(message=f'Fitting background on {filename} ({i} / {len(data["path"])}', options=options) aux.write_log(message=f'Fitting background on {os.path.basename(filename)} ({i+1} / {len(data["path"])})', options=options)
#Fitting linear function to the background #Fitting linear function to the background
params = np.polyfit(pre_edge_data["ZapEnergy"],pre_edge_data[filename],1) params = np.polyfit(pre_edge_data["ZapEnergy"],pre_edge_data[filename],1)
@ -95,15 +96,15 @@ def pre_edge_fit(data: dict, options={}) -> pd.DataFrame:
if not os.path.isdir(options['save_folder']): if not os.path.isdir(options['save_folder']):
os.makedirs(options['save_folder']) os.makedirs(options['save_folder'])
dst = os.path.join(options['save_folder'], filename) + '_pre_edge_fit.png' dst = os.path.join(options['save_folder'], os.path.basename(filename)) + '_pre_edge_fit.png'
fig, (ax1, ax2) = plt.subplots(1,2,figsize=(10,5)) fig, (ax1, ax2) = plt.subplots(1,2,figsize=(10,5))
data['xanes_data'].plot(x='ZapEnergy', y=filename, color='black', ax=ax1) data['xanes_data_original'].plot(x='ZapEnergy', y=filename, color='black', ax=ax1)
pre_edge_fit_data.plot(x='ZapEnergy', y=filename, color='red', ax=ax1) pre_edge_fit_data.plot(x='ZapEnergy', y=filename, color='red', ax=ax1)
ax1.axvline(x = max(pre_edge_data['ZapEnergy']), ls='--') ax1.axvline(x = max(pre_edge_data['ZapEnergy']), ls='--')
ax1.set_title(f'{os.path.basename(filename)} - Full view', size=20) ax1.set_title(f'{os.path.basename(filename)} - Full view', size=20)
data['xanes_data'].plot(x='ZapEnergy', y=filename, color='black', ax=ax2) data['xanes_data_original'].plot(x='ZapEnergy', y=filename, color='black', ax=ax2)
pre_edge_fit_data.plot(x='ZapEnergy', y=filename, color='red', ax=ax2) pre_edge_fit_data.plot(x='ZapEnergy', y=filename, color='red', ax=ax2)
ax2.axvline(x = max(pre_edge_data['ZapEnergy']), ls='--') ax2.axvline(x = max(pre_edge_data['ZapEnergy']), ls='--')
ax2.set_xlim([min(pre_edge_data['ZapEnergy']), max(pre_edge_data['ZapEnergy'])]) ax2.set_xlim([min(pre_edge_data['ZapEnergy']), max(pre_edge_data['ZapEnergy'])])
@ -111,7 +112,7 @@ def pre_edge_fit(data: dict, options={}) -> pd.DataFrame:
ax2.set_title(f'{os.path.basename(filename)} - Fit region', size=20) ax2.set_title(f'{os.path.basename(filename)} - Fit region', size=20)
plt.savefig(dst) plt.savefig(dst, transparent=False)
plt.close() plt.close()