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convertor_xrdml.py
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convertor_xrdml.py
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import matplotlib_inline
import matplotlib.pyplot as plt
import numpy as np
import xrayutilities as xu
import glob
import os,re
# read files and sorted with time.
file_list = sorted(glob.glob("*.xrdml"),key=os.path.getmtime)
read_file = xu.io.XRDMLFile
"""Class method!"""
class make_read_list_class(object):
def __init__(self,file_list):
name = self.__dict__
for i in range(len(file_list)):
file = read_file(file_list[i])
name['data_' + str(i)] = file
All_data = make_read_list_class(file_list)
data_dict = All_data.__dict__
def find_times(data):
line_tmp = re.search(r'countTime with \D\d+',str(data_dict[data]))
times_tmp = re.findall(r'\d+',line_tmp[0])
num = int(times_tmp[0])
return num
class make_line_list_class(object):
def __init__(self,data_dict):
lines = self.__dict__
for d in data_dict:
line_name = f"line_{d}"
lines[line_name] = find_times(d)
num_dict = make_line_list_class(data_dict).__dict__
class make_count_dict():
def __init__(self,data_dict):
counts = self.__dict__
for d in data_dict:
count = data_dict[d].scan.ddict['counts']
if count.ndim > 1:
counts['count_' + str(d)] = np.sum(count,axis=0)/find_times(d)
else:
counts['count_' + str(d)] = count
count_averaged = make_count_dict(data_dict).__dict__
list_count = [value for value in count_averaged.values()]
all_count = np.concatenate(list_count)
class make_theta_dict():
def __init__(self,data_dict):
thetas = self.__dict__
for t in data_dict:
theta = data_dict[t].scan.ddict['2Theta']
if theta.ndim > 1:
thetas['2theta_' + str(t)] = theta[0]
else:
thetas['2theta_' + str(t)] = theta
theta_dict = make_theta_dict(data_dict).__dict__
list_theta = [value for value in theta_dict.values()]
all_theta = np.concatenate(list_theta)
plt.plot(all_theta,all_count)
plt.show()
final_data = np.array((all_theta,all_count))
np.savetxt("final_data.xy",final_data,delimiter=' ')