def get_data(self, file_name: str, file_path: str):
wl_list = [] # 波长 / um
n_list = [] # 折射率
k_list = [] # 消光系数
# 1 读入数据
lines = self.open_file(path=file_path)
for line_index in range(int(self.start_row) - 1, lines.__len__()):
data = lines[line_index].replace('\n', '').split(',')
wl_list.append(float(data[int(self.wl_start_rol) - 1]))
n_list.append(float(data[int(self.n_start_rol) - 1]))
k_list.append(float(data[int(self.k_start_rol) - 1]))
# 2 波长单位变换到um
from_unit = ScienceUnit.Length.um
to_unit = ScienceUnit.Length.um
if from_unit != to_unit:
# X轴的单位变换
for data in wl_list:
data = ScienceUnitConverter.convert(
from_unit_class=from_unit.__class__,
to_unit_class=to_unit.__class__,
from_unit=from_unit.value,
to_unit=to_unit.value,
value=data)
# 3 wl_bound单位变换,截取需要数据
wl_unit_symbol = str(self.wl_bound[0])
# 通过名称获取枚举的函数
wl_unit = ScienceUnit.get_from_symbol(ScienceUnit.Length,
wl_unit_symbol)
self.wl_lower_bound = ScienceUnitConverter.convert(
from_unit_class=wl_unit.__class__,
to_unit_class=to_unit.__class__,
from_unit=wl_unit.value,
to_unit=to_unit.value,
value=self.wl_bound[1])
self.wl_upper_bound = ScienceUnitConverter.convert(
from_unit_class=wl_unit.__class__,
to_unit_class=to_unit.__class__,
from_unit=wl_unit.value,
to_unit=to_unit.value,
value=self.wl_bound[2])
for index in range(wl_list.__len__()):
if wl_list[index] < self.wl_lower_bound <= wl_list[index + 1]:
self.lower_index = index + 1
elif wl_list[index] <= self.wl_upper_bound < wl_list[index + 1]:
self.upper_index = index + 1
else:
pass
print("Interception Index: ({},{})".format(self.lower_index,
self.upper_index))
self.bound_valid = True
if self.bound_valid:
return wl_list[self.lower_index:self.upper_index], n_list[
self.lower_index:self.
upper_index], k_list[self.lower_index:self.upper_index]
else:
return wl_list, n_list, k_list
def on_radioButton_ldc_dm_clicked(self):
if self.radioButton_ldc_dm.isChecked():
self.comboBox_ldc_units.addItems(['m', 'mm', 'um', 'nm', 'A'])
self.comboBox_ldc_units.setCurrentText('nm')
self.calculate_object = 'Dm'
self.unit = ScienceUnit.get_from_symbol('nm')
else:
print(
"UNKNOWN LognormalDistributionCalculatorDialog on_radioButton_ldc_dm_clicked"
)
def on_pushButton_ldc_calculate_clicked(self):
# TODO：sigma是对于随机变量Y的，需要转化成X的sigma再进行计算才行
self.miu = float(self.lineEdit_ldc_miu.text())
self.x_from = float(self.lineEdit_ldc_from.text())
self.x_to = float(self.lineEdit_ldc_to.text())
self.sigma = float(self.lineEdit_ldc_sigma.text())
self.unit = ScienceUnit.get_from_symbol(
str(self.comboBox_ldc_units.currentText()))
self.points = int(self.lineEdit_ldc_points.text())
self.x_list = np.linspace(self.x_from, self.x_to, self.points)
self.f_list = lognorm.pdf(self.x_list,
self.sigma,
loc=0,
scale=self.miu)
print("miu={},x_from={},x_to={},sigma={},unit={},x_list={},f_list={}.".
format(self.miu, self.x_from, self.x_to, self.sigma,
self.unit.get_symbol(), self.x_list, self.f_list))
def on_pushButton_mdc_conversion_clicked(self):
# 获取to_unit_dict目标单位
length_unit = ScienceUnit.get_from_symbol(
self.comboBox_mdc_length_CGS.currentText(
)) if self.is_si_to_cgs else ScienceUnit.get_from_symbol(
self.comboBox_mdc_length_SI.currentText())
volume_unit = ScienceUnit.get_from_symbol(
self.comboBox_mdc_volume_CGS.currentText(
)) if self.is_si_to_cgs else ScienceUnit.get_from_symbol(
self.comboBox_mdc_volume_SI.currentText())
h_unit = ScienceUnit.get_from_symbol(
self.comboBox_mdc_H_CGS.currentText(
)) if self.is_si_to_cgs else ScienceUnit.get_from_symbol(
self.comboBox_mdc_H_SI.currentText())
m_unit = ScienceUnit.get_from_symbol(
self.comboBox_mdc_M_CGS.currentText(
)) if self.is_si_to_cgs else ScienceUnit.get_from_symbol(
self.comboBox_mdc_M_SI.currentText())
bj_unit = ScienceUnit.get_from_symbol(
self.comboBox_mdc_BJ_CGS.currentText(
)) if self.is_si_to_cgs else ScienceUnit.get_from_symbol(
self.comboBox_mdc_BJ_SI.currentText())
miu_unit = ScienceUnit.get_from_symbol(
self.comboBox_mdc_miu_CGS.currentText(
)) if self.is_si_to_cgs else ScienceUnit.get_from_symbol(
self.comboBox_mdc_miu_SI.currentText())
to_unit_dict = {
'l': length_unit,
'w': length_unit,
't': length_unit,
'V': volume_unit,
'm': ScienceUnit.Mass.g.value, # 这里暂时没有开放给前端
'Ms_cal': m_unit,
'J_cal': ScienceUnit.Dimensionless.DN.value,
'Hm': h_unit,
'Hcb': h_unit,
'Hcj': h_unit,
'Ms': m_unit,
'Mm': m_unit,
'Mr': m_unit,
'Bs': bj_unit,
'Bm': bj_unit,
'Br': bj_unit,
'Js': bj_unit,
'Jm': bj_unit,
'Jr': bj_unit,
'Hk': h_unit,
'Q': ScienceUnit.Dimensionless.DN.value,
'Dm': length_unit,
'sigma': ScienceUnit.Dimensionless.DN.value,
'H_raw': h_unit,
'M_raw': m_unit,
'H': h_unit,
'M': m_unit,
'B': bj_unit,
'J': bj_unit,
'χ': ScienceUnit.Dimensionless.DN.value, # FIXME:这里可能会有问题
'μ': miu_unit,
'μr': ScienceUnit.Dimensionless.DN.value,
}
# 对loaded_data进行单位转换
self.converted_data = []
for science_data in self.loaded_data:
file_dic = science_data.get_file_dic()
file_name = science_data.get_file_name()
file_type = science_data.get_file_type()
data_dict = {}
for sheet_name, physical_quantity_list in science_data.get_data_dict(
).items():
converted_physical_quantity_list = []
for physical_quantity in physical_quantity_list:
converted_physical_quantity_list.append(
PhysicalQuantity(
name=physical_quantity.get_name(),
unit=to_unit_dict.get(
physical_quantity.get_name()),
data=science_unit_convert(
physical_quantity.get_data(),
physical_quantity.get_unit(),
to_unit_dict.get(
physical_quantity.get_name()))))
data_dict.update(
{sheet_name: converted_physical_quantity_list})
file_name = file_name + '-CGS' if self.is_si_to_cgs else file_name + '-IS'
self.converted_data.append(
ScienceData(file_dic=file_dic,
file_name=file_name,
file_type=file_type,
data_dict=data_dict))
print('on_pushButton_mdc_conversion_clicked: CONVERSION FINISHED.')
# 开始写入
for science_data in self.converted_data:
ScienceWriter.write_file(science_data)
print('on_pushButton_mdc_conversion_clicked: WRITE FINISHED.')
def read_file(file_dic: str, file_full_name_list: list) -> (list, bool):
is_si_to_cgs = False
science_data_list = []
for file_full_name in file_full_name_list:
if file_full_name.split('.').__len__() == 1:
print("Skip: No extension name.")
else:
file_name, file_extension_name = file_full_name.split('.')
science_file_type = ScienceFileType.get_by_extension_name(
file_extension_name)
print(file_name, science_file_type)
if science_file_type == ScienceFileType.TXT or science_file_type == ScienceFileType.CSV:
with open(file_dic + '/' + file_full_name, 'r') as file:
# 读取CSV和TXT文件,n个文件组合起来是1个ScienceData，不过因为n个文件也是可以拆分开的，所以这里不依照para和data等名称对其进行合并
table_head_list = []
table_body_list = []
if science_file_type == ScienceFileType.TXT:
txt_str = file.read()
rows = txt_str.split('\n')
for row_index in range(rows.__len__()):
row_data = rows[row_index].split('\t')
if row_index == 0:
table_head_list = row_data[:-1]
else:
table_body_list.append(row_data[:-1])
else:
csv_reader = csv.reader(file)
table_head_list = next(csv_reader)
for row in csv.reader(file):
table_body_list.append(row)
table_body_cols = list(zip(*table_body_list))
physical_quantity_list = []
for index in range(table_head_list.__len__()):
name, unit_str = table_head_list[index].replace(
')', '').split('(')
unit = ScienceUnit.get_from_symbol(unit_str)
physical_quantity_list.append(
PhysicalQuantity(name=name,
unit=unit,
data=list(
table_body_cols[index])))
science_data_list.append(
ScienceData(
file_dic=file_dic,
file_name=file_name,
file_type=science_file_type.value,
data_dict={file_name: physical_quantity_list}))
elif science_file_type == ScienceFileType.XLSX:
# 读取XLSX文件，1个文件就是1个ScienceData
workbook = load_workbook(file_dic + '/' + file_full_name)
sheet_name_list = workbook.get_sheet_names()
data_dict = {}
for sheet_name in sheet_name_list:
worksheet = workbook.get_sheet_by_name(sheet_name)
physical_quantity_list = []
for col in worksheet.iter_cols():
name, unit_str = col[0].value.replace(
')', '').split('(')
unit = ScienceUnit.get_from_symbol(unit_str)
data_list = []
for cell in col[1:]:
data_list.append(cell.value)
print(name, unit, data_list)
physical_quantity_list.append(
PhysicalQuantity(name=name,
unit=unit,
data=data_list))
data_dict.update({sheet_name: physical_quantity_list})
science_data_list.append(
ScienceData(file_dic=file_dic,
file_name=file_name,
file_type=science_file_type.value,
data_dict=data_dict))
else:
print('ScienceReader.read_file.ERROR UNKNOWN FILE TYPE.')
only_once_flag = True
for key, value in science_data_list[0].get_data_dict().items():
if only_once_flag:
is_si_to_cgs = value[0].get_unit() in SI_UNIT_LIST
only_once_flag = False
return science_data_list, is_si_to_cgs
def get_data(self, file_path_dict: dict):
wl_list_m, [n_list_m, k_list_m] = self.iterate_data(
file_path=file_path_dict.get('metal').get('nk'),
start_row=self.start_row_m,
x_start_col=self.wl_start_rol_m,
y_start_col_list=[self.n_start_rol_m, self.k_start_rol_m])
wl_list_epsilon_1_prime_m, [
e_list_epsilon_1_prime_m
] = self.iterate_data(
file_path=file_path_dict.get('metal').get('epsilon_1_prime'),
start_row=self.start_row_epsilon_1_prime_m,
x_start_col=self.wl_start_rol_epsilon_1_prime_m,
y_start_col_list=[self.e_start_rol_epsilon_1_prime_m])
wl_list_epsilon_2_prime_m, [
e_list_epsilon_2_prime_m
] = self.iterate_data(
file_path=file_path_dict.get('metal').get('epsilon_2_prime'),
start_row=self.start_row_epsilon_2_prime_m,
x_start_col=self.wl_start_rol_epsilon_2_prime_m,
y_start_col_list=[self.e_start_rol_epsilon_2_prime_m])
wl_list_d, [n_list_d, k_list_d] = self.iterate_data(
file_path=file_path_dict.get('dielectric').get('nk'),
start_row=self.start_row_d,
x_start_col=self.wl_start_rol_d,
y_start_col_list=[self.n_start_rol_d, self.k_start_rol_d])
wl_list, [theta_list] = self.iterate_data(
file_path=file_path_dict.get('theta_on_wl'),
start_row=self.start_row_theta_on_wl,
x_start_col=self.wl_start_rol,
y_start_col_list=[self.theta_start_rol])
# 2 波长的单位变换到um
wl_to_unit = ScienceUnit.Length.um
wl_from_unit_m = ScienceUnit.get_from_symbol(ScienceUnit.Length,
self.wl_unit_m)
wl_from_unit_epsilon_1_prime_m = ScienceUnit.get_from_symbol(
ScienceUnit.Length, self.wl_unit_epsilon_1_prime_m)
wl_from_unit_epsilon_2_prime_m = ScienceUnit.get_from_symbol(
ScienceUnit.Length, self.wl_unit_epsilon_2_prime_m)
wl_from_unit_d = ScienceUnit.get_from_symbol(ScienceUnit.Length,
self.wl_unit_d)
wl_from_unit_theta_on_wl = ScienceUnit.get_from_symbol(
ScienceUnit.Length, self.wl_unit_theta_on_wl)
if wl_from_unit_m != wl_to_unit:
for index in range(wl_list_m.__len__()):
wl_list_m[index] = ScienceUnitConverter.convert(
from_unit_class=wl_from_unit_m.__class__,
to_unit_class=wl_to_unit.__class__,
from_unit=wl_from_unit_m.value,
to_unit=wl_to_unit.value,
value=wl_list_m[index])
if wl_from_unit_epsilon_1_prime_m != wl_to_unit:
for index in range(wl_list_m.__len__()):
wl_list_epsilon_1_prime_m[index] = ScienceUnitConverter.convert(
from_unit_class=wl_from_unit_epsilon_1_prime_m.__class__,
to_unit_class=wl_to_unit.__class__,
from_unit=wl_from_unit_epsilon_1_prime_m.value,
to_unit=wl_to_unit.value,
value=wl_list_epsilon_1_prime_m[index])
if wl_from_unit_epsilon_2_prime_m != wl_to_unit:
for index in range(wl_list_m.__len__()):
wl_list_epsilon_2_prime_m[index] = ScienceUnitConverter.convert(
from_unit_class=wl_from_unit_epsilon_2_prime_m.__class__,
to_unit_class=wl_to_unit.__class__,
from_unit=wl_from_unit_epsilon_2_prime_m.value,
to_unit=wl_to_unit.value,
value=wl_list_epsilon_2_prime_m[index])
if wl_from_unit_d != wl_to_unit:
for index in range(wl_list_m.__len__()):
wl_list_d[index] = ScienceUnitConverter.convert(
from_unit_class=wl_from_unit_d.__class__,
to_unit_class=wl_to_unit.__class__,
from_unit=wl_from_unit_d.value,
to_unit=wl_to_unit.value,
value=wl_list_d[index])
if wl_from_unit_theta_on_wl != wl_to_unit:
for index in range(wl_list.__len__()):
wl_list[index] = ScienceUnitConverter.convert(
from_unit_class=wl_from_unit_theta_on_wl.__class__,
to_unit_class=wl_to_unit.__class__,
from_unit=wl_from_unit_theta_on_wl.value,
to_unit=wl_to_unit.value,
value=wl_list[index])
# 3 wl_bound单位变换,截取需要数据
wl_from_bound_unit = ScienceUnit.get_from_symbol(
ScienceUnit.Length, self.wl_bound_unit)
self.wl_lower_bound = ScienceUnitConverter.convert(
from_unit_class=wl_from_bound_unit.__class__,
to_unit_class=wl_to_unit.__class__,
from_unit=wl_from_bound_unit.value,
to_unit=wl_to_unit.value,
value=self.wl_lower_bound)
self.wl_upper_bound = ScienceUnitConverter.convert(
from_unit_class=wl_from_bound_unit.__class__,
to_unit_class=wl_to_unit.__class__,
from_unit=wl_from_bound_unit.value,
to_unit=wl_to_unit.value,
value=self.wl_upper_bound)
wl_lower_index, wl_upper_index = self.found_bound_index(
wl_list, self.wl_lower_bound, self.wl_upper_bound)
wl_lower_index_m, wl_upper_index_m = self.found_bound_index(
wl_list_m, self.wl_lower_bound, self.wl_upper_bound)
wl_lower_index_epsilon_1_prime_m, wl_upper_index_epsilon_1_prime_m = self.found_bound_index(
wl_list_epsilon_1_prime_m, self.wl_lower_bound,
self.wl_upper_bound)
wl_lower_index_epsilon_2_prime_m, wl_upper_index_epsilon_2_prime_m = self.found_bound_index(
wl_list_epsilon_2_prime_m, self.wl_lower_bound,
self.wl_upper_bound)
wl_lower_index_d, wl_upper_index_d = self.found_bound_index(
wl_list_d, self.wl_lower_bound, self.wl_upper_bound)
self.bound_valid = True
if self.bound_valid:
# 注意：list[a:b]是不包含b索引对应的内容的所以需要+1
return (wl_list_m[wl_lower_index_m:wl_upper_index_m+1], n_list_m[wl_lower_index_m:wl_upper_index_m+1], k_list_m[wl_lower_index_m:wl_upper_index_m+1]), \
(wl_list_epsilon_1_prime_m[wl_lower_index_epsilon_1_prime_m:wl_upper_index_epsilon_1_prime_m+1], e_list_epsilon_1_prime_m[wl_lower_index_epsilon_1_prime_m:wl_upper_index_epsilon_1_prime_m+1]), \
(wl_list_epsilon_2_prime_m[wl_lower_index_epsilon_2_prime_m:wl_upper_index_epsilon_2_prime_m+1], e_list_epsilon_2_prime_m[wl_lower_index_epsilon_2_prime_m:wl_upper_index_epsilon_2_prime_m+1]), \
(wl_list_d[wl_lower_index_d:wl_upper_index_d+1], n_list_d[wl_lower_index_d:wl_upper_index_d+1], k_list_d[wl_lower_index_d:wl_upper_index_d+1]), \
(wl_list[wl_lower_index:wl_upper_index+1], theta_list[wl_lower_index:wl_upper_index+1])
else:
return (wl_list_m, n_list_m, k_list_m), \
(wl_list_epsilon_1_prime_m, e_list_epsilon_1_prime_m), \
(wl_list_epsilon_2_prime_m, e_list_epsilon_2_prime_m), \
(wl_list_d, n_list_d, k_list_d), \
(wl_list, theta_list)
def get_data(self, file_name: str, file_path: str):
h_list = []
bg_m_list = []
m_list = []
bg_lines = self.open_file(path=self.bg_file_path)
lines = self.open_file(path=file_path)
length = self.size_dict[file_name][0] # 单位 mm
width = self.size_dict[file_name][1] # 单位 mm
thickness = self.size_dict[file_name][2] # 单位 nm #S070
volume = length * width * thickness * 1e-9 # 单位 cm^3
# 有的文件会出现有H没有对应M的情况
if self.H_start_row != self.M_start_row:
print("WARNING: self.H_start_row != self.M_start_row.")
for line_index in range(int(self.H_start_row) - 1, lines.__len__()):
# print(line_index, ":", lines[line_index])
try:
bg_data = bg_lines[line_index].replace('\n', '').replace(
'\t', ',').split(',')
data = lines[line_index].replace('\n',
'').replace('\t',
',').split(',')
h_list.append(float(data[int(self.H_start_col) - 1]))
bg_m_list.append(float(bg_data[int(self.M_start_col) - 1]))
m_list.append(float(data[int(self.M_start_col) - 1]))
except IndexError:
print(
"IndexError: list index out of range. It is normal for data from DENJIKEN."
)
break
# 去背底
if m_list.__len__() > bg_m_list.__len__():
bg_m_list = bg_m_list + (m_list.__len__() -
bg_m_list.__len__()) * [bg_m_list[-1]]
m_list = np.subtract(m_list, bg_m_list[:m_list.__len__()])
# Z轴校准(尽量让曲线是中心对称的)
m_list = np.subtract(m_list, np.average(m_list))
# 单位转换 [Oe,emu] 转 [A/m,A/m]
print(self.H_start_unit)
print(
ScienceUnit.get_from_description_with_symbol_bracket(
self.H_start_unit))
h_list = science_unit_convert(
from_list=h_list,
from_unit=ScienceUnit.Magnetization.Oe.value,
to_unit=ScienceUnit.Magnetization.A_m_1.value)
if self.M_start_unit == "*Magn.Moment(emu)":
m_list = np.divide(m_list, volume)
self.M_start_unit = "emu/cm^3"
m_list = science_unit_convert(
from_list=m_list,
from_unit=ScienceUnit.get_from_symbol(self.M_start_unit),
to_unit=ScienceUnit.Magnetization.A_m_1.value)
else:
m_list = science_unit_convert(
from_list=m_list,
from_unit=ScienceUnit.get_from_symbol(self.M_start_unit),
to_unit=ScienceUnit.Magnetization.A_m_1.value)
# 调整数据：1切割正向和负向回线2把负向回线逆时针旋转180度3每一项取平均值合并
# 1 切割
# 最高级别注意！！！ 这里需要进行2次切割：
# 1次是时间梯度也就是按照磁场增减方向
# 1次是磁场大小的正负切割，如果同时包含了正负的磁场那么在接近于0附近的时候ODEINT函数内部计算必定不收敛
# 这里定义一个有4个数组的元组，按照顺序分别代表 H下降，H正 H下降，H负 H上升，H负 H上升，H正
trend_break_index = 0
sign_break_index = []
for i in range(h_list.size):
# 这里后方需要进行两次判断的理由是因为实际的H控制有一定的误差，不是一直单调变化的
if (h_list[0] > h_list[1] and h_list[i] < h_list[i + 1]
and h_list[i + 1] < h_list[i + 2]
and h_list[i + 2] < h_list[i + 3]) or (
h_list[0] < h_list[1] and h_list[i] > h_list[i + 1]
and h_list[i + 1] > h_list[i + 2]
and h_list[i + 2] > h_list[i + 3]):
trend_break_index = i
break
# 注意！此处判断H方向翻转的条件：i+1为0 i和i+2符号相反 OR i+1不为0 i和i+1符号相反
for i in range(h_list.size):
if len(sign_break_index) == 2:
break
elif (h_list[i] * h_list[i + 2] < 0 and h_list[i + 1]
== 0) or (h_list[i + 1] * h_list[i + 2] < 0):
sign_break_index.append(i + 1)
h1_list = []
h2_list = []
h3_list = []
h4_list = []
m1_list = []
m2_list = []
m3_list = []
m4_list = []
if sign_break_index[0] < trend_break_index < sign_break_index[1]:
# 检查break index 的有效性
h1_list = h_list[1:sign_break_index[0]]
h2_list = h_list[sign_break_index[0] + 1:trend_break_index]
h3_list = h_list[trend_break_index + 1:sign_break_index[1]]
h4_list = h_list[sign_break_index[1] + 1:]
m1_list = m_list[1:sign_break_index[0]]
m2_list = m_list[sign_break_index[0] + 1:trend_break_index]
m3_list = m_list[trend_break_index + 1:sign_break_index[1]]
m4_list = m_list[sign_break_index[1] + 1:]
else:
print(
'BREAK INDEX 错误L:trend_break_index={0},sign_break_index_1={1},sign_break_index_2={2}'
.format(trend_break_index, sign_break_index[0],
sign_break_index[1]))
# 2 旋转
# 翻转第2和第4的横坐标，保证所有曲线的起点都是从m_max
# 注意：曲线是有方向的切忌翻转，翻转后第2支和第4支全部都不收敛
# h2_list = h2_list[::-1]
# h4_list = h4_list[::-1]
# m2_list = m2_list[::-1]
# m4_list = m4_list[::-1]
if np.mean(h1_list) > 0:
# 第1象限开始的曲线
self.begin_first_quadrant = True
h2_list = np.multiply(h2_list, -1)
h3_list = np.multiply(h3_list, -1)
m2_list = np.multiply(m2_list, -1)
m3_list = np.multiply(m3_list, -1)
else:
self.begin_first_quadrant = False
# 第3象限开始的曲线
h1_list = np.multiply(h1_list, -1)
h4_list = np.multiply(h4_list, -1)
m1_list = np.multiply(m1_list, -1)
m4_list = np.multiply(m4_list, -1)
# 3 拼装
m_0_list = np.array([m1_list[0], m2_list[0], m3_list[0], m4_list[0]])
break_index_list = np.array([
h1_list.size, h1_list.size + h2_list.size,
h1_list.size + h2_list.size + h3_list.size,
h1_list.size + h2_list.size + h3_list.size + h4_list.size
])
h_list = np.concatenate([h1_list, h2_list, h3_list, h4_list])
m_list = np.concatenate([m1_list, m2_list, m3_list, m4_list])
return h_list, m_list, m_0_list, break_index_list, length, width, thickness
def __init__(self, parent):
self.parent = parent
# 模型 1:Jiles-Atherton,模型 2:Brillouin,模型 3:Langevin,模型 4:Takacs
# 默认模型为3:Langevin
self.model = 3
# 饱和磁化强度(A/m)-LOG 10 kOe~795775A/m
self.ms_min = 100. # 0.00125664 kG
self.ms_max = 100000000. #
# 磁耦合系数(J/(Tm^3))
self.a_min = 1e3
self.a_max = 1e5
# 不可逆损耗系数(??)
self.k_min = 1e3
self.k_max = 1e5
# 磁畴耦合系数(??)
self.alfa_min = 0.0
self.alfa_max = 1.0
# 可逆磁化系数(1)
self.c_min = 0.0
self.c_max = 1.0
# 轨道量子数，是自然数(1)
self.j_min = 1.
self.j_max = 1.e5
# 颗粒尺寸分布的标准差(1)
self.sigma_min = 0.
self.sigma_max = 5.
# 轨道量子数的朗德因子(1)
self.g_j = sci_const.Lande_g_Factor(3 / 2, 3, 9 / 2) # Co2+ ion
# self.g_j = 1.60 # calculated
# self.g_j = 1.72 #observed
# 温度(K)
self.temp = 300.
# 初始化参数
self.ms = self.ms_max
self.a = self.a_max
self.k = self.k_max
self.alfa = self.alfa_min
self.c = self.c_min
self.j = self.j_min
self.sigma = self.sigma_min
# 录入文件相关系数和自定义UI组件
self.file_path = []
self.file_name = []
self.table_view_file_model = QtGui.QStandardItemModel()
self.resetTableViewHeaderItems(
tableviewmodel=self.table_view_file_model)
self.last_model_index = None
# 结果的自定义UI组件
self.list_view_results_model = QtGui.QStandardItemModel()
# 结果字典，键是文件名
self.result_dict = {}
# plot相关的弹窗的UI及其初始化,用tabUI预留出可能出现的多张图片
self.dialog_plot_M = QtWidgets.QDialog()
self.tab_plot_M = QtWidgets.QTabWidget(self.dialog_plot_M)
self.tab_plot_M.setGeometry(QtCore.QRect(10, 0, 1061, 678))
self.tab_plot_M_magnetization = QtWidgets.QWidget()
self.tab_plot_M.addTab(self.tab_plot_M_magnetization, "")
_translate = QtCore.QCoreApplication.translate
self.tab_plot_M.setTabText(
self.tab_plot_M.indexOf(self.tab_plot_M_magnetization),
_translate("MainWindow", "Magnetization Curves"))
self.layout_plot_M_magnetization = QtWidgets.QVBoxLayout()
self.fig_M_magnetization = plt.Figure()
self.canvas_M_magnetization = FigureCanvas(self.fig_M_magnetization)
self.magnetization_unit_list = ScienceUnit.get_unit_list_by_classification(
ScienceUnit.Magnetization)