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modec_xml_read.py
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# -*- coding: utf-8 -*-
"""
Created on Sun Feb 18 18:55:56 2018
@author: xsp
"""
import xml.etree.ElementTree as ET
import numpy as np
import matplotlib.pyplot as plt
import re
class modec_xml_opfile:
# 初始化类
def __init__(self, filename):
# 文件名信息存储
self.xml_opfile = filename
# 各物理量单位字符串
self.time_unit = ''
self.power_unit = ''
self.flux_unit = ''
self.dens_unit = ''
self.activity_unit = ''
self.ampc_unit = ''
self.wmpc_unit = ''
self.toxi_unit = ''
self.absrate_unit = ''
self.prodrate_unit = ''
# 各物理量ndarray
self.time_array = np.array([])
self.power_array = np.array([])
self.flux_array = np.array([])
self.kinf_array = np.array([])
# 中子消失率和中子产生率的存储数组
self.nucl_absrate_array = np.array([])
self.nucl_prodrate_array = np.array([])
# 放射性活度存储数组
self.nucl_activity_array = np.array([])
self.nucl_activity_loop_array = np.array([])
self.nucl_activity_stockage_array = np.array([])
# AMPC存储数组
self.nucl_ampc_array = np.array([])
self.nucl_ampc_loop_array = np.array([])
self.nucl_ampc_stockage_array = np.array([])
# 核素物质的量存储数组
self.nucl_concentration_array = np.array([])
self.nucl_concentration_loop_array = np.array([])
self.nucl_concentration_stockage_array = np.array([])
# 核素衰变热存储数组
self.nucl_decayheat_array = np.array([])
self.nucl_decayheat_loop_array = np.array([])
self.nucl_decayheat_stockage_array = np.array([])
# 核素放射性毒性存储数组
self.nucl_toxi_array = np.array([])
self.nucl_toxi_loop_array = np.array([])
self.nucl_toxi_stockage_array = np.array([])
# WMPC存储数组
self.nucl_wmpc_array = np.array([])
self.nucl_wmpc_loop_array = np.array([])
self.nucl_wmpc_stockage_array = np.array([])
# 核素名称，ID，原子序数以及相对原子质量
self.nucl_name_array = np.array([])
self.nucl_zai_array = np.array([],dtype=int)
self.nucl_z_array = np.array([],dtype=int)
self.nucl_a_array = np.array([])
# 解析XML文件
self.parse_modec_xml_opfile()
def parse_modec_xml_opfile(self):
tree = ET.parse(self.xml_opfile)
root = tree.getroot()
for child in root:
if child.tag == 'Time':
self.time_unit = child.attrib["unit"]
self.time_array = np.fromstring(child.text,sep=' ')
if child.tag == 'Power':
self.power_unit = child.attrib["unit"]
self.power_array = np.fromstring(child.text,sep=' ')
if child.tag == 'Flux':
self.flux_unit = child.attrib["unit"]
self.flux_array = np.fromstring(child.text,sep=' ')
if child.tag == 'K-infinite':
self.kinf_array = np.fromstring(child.text,sep=' ')
if child.tag == 'Nuclides':
zone_attrib = child.attrib["zone"]
if zone_attrib == "core":
for childchild in child:
if childchild.tag == 'Concentration':
self.dens_unit = childchild.attrib["unit"]
# 核素浓度array
flag = 1
for childchildchild in childchild:
self.nucl_zai_array = np.append(self.nucl_zai_array,int(childchildchild.attrib["zai"]))
self.nucl_name_array = np.append(self.nucl_name_array,childchildchild.attrib["name"])
if flag == 1:
self.nucl_concentration_array = np.append(self.nucl_concentration_array,np.fromstring(childchildchild.text,sep=' '))
else:
self.nucl_concentration_array = np.vstack((self.nucl_concentration_array,np.fromstring(childchildchild.text,sep=' ')))
flag += 1
if childchild.tag == 'RadioActivity':
self.activity_unit = childchild.attrib["unit"]
# 放射性活度array
flag = 1
for childchildchild in childchild:
if flag == 1:
self.nucl_activity_array = np.append(self.nucl_activity_array,np.fromstring(childchildchild.text,sep=' '))
else:
self.nucl_activity_array = np.vstack((self.nucl_activity_array,np.fromstring(childchildchild.text,sep=' ')))
flag += 1
if childchild.tag == 'DecayHeat':
self.decayheat_unit = childchild.attrib["unit"]
# 衰变热
flag = 1
for childchildchild in childchild:
if flag == 1:
self.nucl_decayheat_array = np.append(self.nucl_decayheat_array,np.fromstring(childchildchild.text,sep=' '))
else:
self.nucl_decayheat_array = np.vstack((self.nucl_decayheat_array,np.fromstring(childchildchild.text,sep=' ')))
flag += 1
if childchild.tag == 'AMPC':
self.ampc_unit = childchild.attrib["unit"]
# AMPC
flag = 1
for childchildchild in childchild:
if flag == 1:
self.nucl_ampc_array = np.append(self.nucl_ampc_array,np.fromstring(childchildchild.text,sep=' '))
else:
self.nucl_ampc_array = np.vstack((self.nucl_ampc_array,np.fromstring(childchildchild.text,sep=' ')))
flag += 1
if childchild.tag == 'WMPC':
self.wmpc_unit = childchild.attrib["unit"]
# WMPC
flag = 1
for childchildchild in childchild:
if flag == 1:
self.nucl_wmpc_array = np.append(self.nucl_wmpc_array,np.fromstring(childchildchild.text,sep=' '))
else:
self.nucl_wmpc_array = np.vstack((self.nucl_wmpc_array,np.fromstring(childchildchild.text,sep=' ')))
flag += 1
if childchild.tag == 'RadioToxicity':
self.toxi_unit = childchild.attrib["unit"]
# 毒性
flag = 1
for childchildchild in childchild:
if flag == 1:
self.nucl_toxi_array = np.append(self.nucl_toxi_array,np.fromstring(childchildchild.text,sep=' '))
else:
self.nucl_toxi_array = np.vstack((self.nucl_toxi_array,np.fromstring(childchildchild.text,sep=' ')))
flag += 1
if childchild.tag == 'NeuProdRate':
self.prodrate_unit = childchild.attrib["unit"]
# 中子产生率
flag = 1
for childchildchild in childchild:
if flag == 1:
self.nucl_prodrate_array = np.append(self.nucl_prodrate_array,np.fromstring(childchildchild.text,sep=' '))
else:
self.nucl_prodrate_array = np.vstack((self.nucl_prodrate_array,np.fromstring(childchildchild.text,sep=' ')))
flag += 1
if childchild.tag == 'NeuAbsRate':
self.absrate_unit = childchild.attrib["unit"]
# 中子吸收率
flag = 1
for childchildchild in childchild:
if flag == 1:
self.nucl_absrate_array = np.append(self.nucl_absrate_array,np.fromstring(childchildchild.text,sep=' '))
else:
self.nucl_absrate_array = np.vstack((self.nucl_absrate_array,np.fromstring(childchildchild.text,sep=' ')))
flag += 1
if zone_attrib == "stockage":
for childchild in child:
if childchild.tag == 'Concentration':
flag = 1
for childchildchild in childchild:
if flag == 1:
self.nucl_concentration_stockage_array = np.append(self.nucl_concentration_stockage_array,np.fromstring(childchildchild.text,sep=' '))
else:
self.nucl_concentration_stockage_array = np.vstack((self.nucl_concentration_stockage_array,np.fromstring(childchildchild.text,sep=' ')))
flag += 1
if childchild.tag == 'RadioActivity':
# 放射性活度array
flag = 1
for childchildchild in childchild:
if flag == 1:
self.nucl_activity_stockage_array = np.append(self.nucl_activity_stockage_array,np.fromstring(childchildchild.text,sep=' '))
else:
self.nucl_activity_stockage_array = np.vstack((self.nucl_activity_stockage_array,np.fromstring(childchildchild.text,sep=' ')))
flag += 1
if childchild.tag == 'DecayHeat':
# 衰变热
flag = 1
for childchildchild in childchild:
if flag == 1:
self.nucl_decayheat_stockage_array = np.append(self.nucl_decayheat_stockage_array,np.fromstring(childchildchild.text,sep=' '))
else:
self.nucl_decayheat_stockage_array = np.vstack((self.nucl_decayheat_stockage_array,np.fromstring(childchildchild.text,sep=' ')))
flag += 1
if childchild.tag == 'AMPC':
# AMPC
flag = 1
for childchildchild in childchild:
if flag == 1:
self.nucl_ampc_stockage_array = np.append(self.nucl_ampc_stockage_array,np.fromstring(childchildchild.text,sep=' '))
else:
self.nucl_ampc_stockage_array = np.vstack((self.nucl_ampc_stockage_array,np.fromstring(childchildchild.text,sep=' ')))
flag += 1
if childchild.tag == 'WMPC':
# WMPC
flag = 1
for childchildchild in childchild:
if flag == 1:
self.nucl_wmpc_stockage_array = np.append(self.nucl_wmpc_stockage_array,np.fromstring(childchildchild.text,sep=' '))
else:
self.nucl_wmpc_stockage_array = np.vstack((self.nucl_wmpc_stockage_array,np.fromstring(childchildchild.text,sep=' ')))
flag += 1
if childchild.tag == 'RadioToxicity':
# 毒性
flag = 1
for childchildchild in childchild:
if flag == 1:
self.nucl_toxi_stockage_array = np.append(self.nucl_toxi_stockage_array,np.fromstring(childchildchild.text,sep=' '))
else:
self.nucl_toxi_stockage_array = np.vstack((self.nucl_toxi_stockage_array,np.fromstring(childchildchild.text,sep=' ')))
flag += 1
if zone_attrib == "loop":
for childchild in child:
if childchild.tag == 'Concentration':
flag = 1
for childchildchild in childchild:
if flag == 1:
self.nucl_concentration_loop_array = np.append(self.nucl_concentration_loop_array,np.fromstring(childchildchild.text,sep=' '))
else:
self.nucl_concentration_loop_array = np.vstack((self.nucl_concentration_loop_array,np.fromstring(childchildchild.text,sep=' ')))
flag += 1
if childchild.tag == 'RadioActivity':
# 放射性活度array
flag = 1
for childchildchild in childchild:
if flag == 1:
self.nucl_activity_loop_array = np.append(self.nucl_activity_loop_array,np.fromstring(childchildchild.text,sep=' '))
else:
self.nucl_activity_loop_array = np.vstack((self.nucl_activity_loop_array,np.fromstring(childchildchild.text,sep=' ')))
flag += 1
if childchild.tag == 'DecayHeat':
# 衰变热
flag = 1
for childchildchild in childchild:
if flag == 1:
self.nucl_decayheat_loop_array = np.append(self.nucl_decayheat_loop_array,np.fromstring(childchildchild.text,sep=' '))
else:
self.nucl_decayheat_loop_array = np.vstack((self.nucl_decayheat_loop_array,np.fromstring(childchildchild.text,sep=' ')))
flag += 1
if childchild.tag == 'AMPC':
# AMPC
flag = 1
for childchildchild in childchild:
if flag == 1:
self.nucl_ampc_loop_array = np.append(self.nucl_ampc_loop_array,np.fromstring(childchildchild.text,sep=' '))
else:
self.nucl_ampc_loop_array = np.vstack((self.nucl_ampc_loop_array,np.fromstring(childchildchild.text,sep=' ')))
flag += 1
if childchild.tag == 'WMPC':
# WMPC
flag = 1
for childchildchild in childchild:
if flag == 1:
self.nucl_wmpc_loop_array = np.append(self.nucl_wmpc_loop_array,np.fromstring(childchildchild.text,sep=' '))
else:
self.nucl_wmpc_loop_array = np.vstack((self.nucl_wmpc_loop_array,np.fromstring(childchildchild.text,sep=' ')))
flag += 1
if childchild.tag == 'RadioToxicity':
# 毒性
flag = 1
for childchildchild in childchild:
if flag == 1:
self.nucl_toxi_loop_array = np.append(self.nucl_toxi_loop_array,np.fromstring(childchildchild.text,sep=' '))
else:
self.nucl_toxi_loop_array = np.vstack((self.nucl_toxi_loop_array,np.fromstring(childchildchild.text,sep=' ')))
flag += 1
self.nucl_z_array = np.int_(self.nucl_zai_array / 10000)
self.nucl_a_array =np.float_(np.int_(self.nucl_zai_array / 10) - self.nucl_z_array * 1000)
def plt_time_evolution(self, nucl_name = [], **kwargs):
# key = y_axis, x_axis
# value = 'linear', 'log'
# key = format
# value = 'sep' 'comb'
# plt_array = []
if 'object' in kwargs:
value = kwargs['object']
if value == 'concentration':
plt_array = self.nucl_concentration_array
elif value == 'activity':
plt_array = self.nucl_activity_array
elif value == 'decayheat':
plt_array = self.nucl_decayheat_array
elif value == 'toxicity':
plt_array = self.nucl_toxi_array
else:
raise Exception('Unknown \'object\' value')
else:
plt_array = self.nucl_concentration_array
if 'format' in kwargs:
value = kwargs['format']
if value == 'sep':
for nucl in nucl_name:
if not any(char.isdigit() for char in nucl):
elem = [i for i, item in enumerate(self.nucl_name_array) if nucl == re.match(r'[a-zA-Z]+', item)[0]]
elem_concentration_array = np.full_like(plt_array[0], 0.0)
for elem_ in elem:
elem_concentration_array += plt_array[elem_]
plt.plot(self.time_array/3600./24.,elem_concentration_array,'o-')
plt.text(self.time_array.max() / 3600. /24. ,
elem_concentration_array.max() * .8 + elem_concentration_array.min() * .2, nucl)
else:
index = np.where(self.nucl_name_array == nucl)
plt.plot(self.time_array / 3600. / 24., plt_array[index[0][0]],'o-')
plt.text(self.time_array.max() / 3600. / 24. * 0.8,
plt_array[index[0][0]].max() * .8 +
plt_array[index[0][0]].min() * .2
, nucl)
if 'x_axis' in kwargs:
plt.xscale(kwargs['x_axis'])
if 'y_axis' in kwargs:
plt.yscale(kwargs['y_axis'])
plt.ylabel(kwargs['object'])
plt.xlabel("time(days)")
plt.grid(True)
# plt.show()
plt.savefig(nucl)
plt.close()
elif value == 'comb':
com_nucl = np.full_like(plt_array[0], 0.0)
for nucl in nucl_name:
if not any(char.isdigit() for char in nucl):
elem = [i for i, item in enumerate(self.nucl_name_array) if nucl == re.match(r'[a-zA-Z]+', item)[0]]
for elem_ in elem:
com_nucl += plt_array[elem_]
else :
index = np.where(self.nucl_name_array == nucl)
com_nucl += plt_array[index[0][0]]
plt.plot(self.time_array / 3600. / 24., com_nucl, 'o-')
plt.text(self.time_array.max() / 3600. / 24. * 0.8,
com_nucl.max() * .8 + com_nucl.min() * .2
, nucl)
if 'x_axis' in kwargs:
plt.xscale(kwargs['x_axis'])
if 'y_axis' in kwargs:
plt.yscale(kwargs['y_axis'])
plt.ylabel(kwargs['object'])
plt.xlabel("time(days)")
plt.grid(True)
# plt.show()
if 'savefig' in kwargs:
plt.savefig(kwargs['savefig'])
else:
plt.savefig('0')
# plt.close()
else:
plt.figure()
for nucl in nucl_name:
if not any(char.isdigit() for char in nucl):
elem = [i for i, item in enumerate(self.nucl_name_array) if nucl == re.match(r'[a-zA-Z]+', item)[0]]
elem_concentration_array = np.full_like(plt_array[0], 0.0)
for elem_ in elem:
elem_concentration_array += plt_array[elem_]
plt.plot(self.time_array/3600./24.,elem_concentration_array,'o-')
plt.text(self.time_array.max() / 3600. /24. ,
elem_concentration_array.max() * .8 + elem_concentration_array.min() * .2, nucl)
else :
index = np.where(self.nucl_name_array==nucl)
plt.plot(self.time_array/3600/24,plt_array[index[0][0]],'o-')
plt.text(self.time_array.max()/3600/24*0.8,
plt_array[index[0][0]].max()*.8 +
plt_array[index[0][0]].min()*.2, nucl)
# ,bbox=dict(facecolor='red', alpha=0.5))
# plt.annotate(nucl,
# xy = (self.time_array.max()/3600/24*0.8,
# self.nucl_concentration_array[index[0][0]].max()*.8 +
# self.nucl_concentration_array[index[0][0]].min()*.2),
# xytext = (self.time_array.max()/3600/24*0.8,
# self.nucl_concentration_array[index[0][0]].max()*.8 +
# self.nucl_concentration_array[index[0][0]].min()*.2))
if 'x_axis' in kwargs:
plt.xscale(kwargs['x_axis'])
if 'y_axis' in kwargs:
plt.yscale(kwargs['y_axis'])
plt.ylabel(kwargs['object'])
plt.xlabel("time(days)")
plt.grid(True)
if 'savefig' in kwargs:
plt.savefig(kwargs['savefig'])
else:
plt.savefig('0')
# plt.show()
def output_time_evolution(self, nucl_name = [], **kwargs):
# key = y_axis, x_axis
# value = 'linear', 'log'
# key = format
# value = 'sep' 'comb'
# plt_array = []
if 'object' in kwargs:
value_o = kwargs['object']
if value_o == 'concentration':
nucl_array = self.nucl_concentration_array
nucl_str = self.dens_unit
elif value_o == 'activity':
nucl_array = self.nucl_activity_array
unit_str = self.activity_unit
elif value_o == 'decayheat':
nucl_array = self.nucl_decayheat_array
unit_str = self.decayheat_unit
elif value_o == 'toxicity':
nucl_array = self.nucl_toxi_array
unit_str = self.toxi_unit
else:
raise Exception('Unknown \'object\' value')
else:
value_o = 'concentration'
nucl_array = self.nucl_concentration_array
nucl_str = self.dens_unit
time_ = self.time_array/3600./24./365.25
for nucl in nucl_name:
# 文件名
if nucl == "Total":
# 文件名
out_file = open('Total_' + value_o + "_evolution.dat",'w')
# 文件头
out_file.write("========> {object_} evolution of total nuclides ({unit_}) <========\n\n".
format(object_ = value_o, unit_ = unit_str))
# 输出结果
out_file.write("{Time:<15s}".format(Time= 'Time(years)'))
elem_concentration_array = np.full_like(nucl_array[0], 0.0)
for i in range(nucl_array.shape[0]):
elem_concentration_array += nucl_array[i]
out_file.write("{nuclide_name:<16s}".format(nuclide_name = nucl))
out_file.write('\n')
for i in range(time_.size):
out_file.write("{:<15E}".format(time_[i]))
out_file.write("{:<16.9E}".format(elem_concentration_array[i]))
out_file.write('\n')
out_file.close()
else:
out_file = open(nucl + '_' + value_o + "_evolution.dat",'w')
# 文件头
out_file.write("========> {object_} evolution of {nucl_}({unit_}) <========\n\n".
format(object_ = value_o, nucl_ = nucl, unit_ = unit_str))
# 输出结果
out_file.write("{Time:<15s}".format(Time= 'Time(years)'))
if not any(char.isdigit() for char in nucl):
elem = [i for i, item in enumerate(self.nucl_name_array) if nucl == re.match(r'[a-zA-Z]+', item)[0]]
elem_concentration_array = np.full_like(nucl_array[0], 0.0)
for elem_ in elem:
out_file.write("{nuclide_name:<16s}".format(nuclide_name = self.nucl_name_array[elem_]))
elem_concentration_array += nucl_array[elem_]
out_file.write("{nuclide_name:<16s}".format(nuclide_name="Total"))
out_file.write('\n')
for i in range(time_.size):
out_file.write("{:<15E}".format(time_[i]))
for elem_ in elem:
out_file.write("{:<16.9E}".format(nucl_array[elem_][i]))
out_file.write("{:<16.9E}".format(elem_concentration_array[i]))
out_file.write('\n')
else:
index = np.where(self.nucl_name_array == nucl)
out_file.write("{nuclide_name:<16s}".format(nuclide_name = self.nucl_name_array[index[0][0]]))
out_file.write('\n')
for i in range(time_.size):
out_file.write("{:<15E}".format(time_[i]))
out_file.write("{:<16.9E}".format(self.nucl_name_array[index[0][0]][i]))
out_file.write('\n')
out_file.close()