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Sgr A* VMT
2023-11-26 23:06:44 +08:00
parent 18a8397de5
commit ac40d56e10
1 changed files with 42 additions and 37 deletions
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79
arg_fit.py
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@@ -89,43 +89,48 @@ def data_process(path):
plt.plot(temp,line_fit(temp,linear_params[0],linear_params[1],linear_params[2]))
data0=line_fit(np.arange(5,80,0.01),linear_params[0],linear_params[1],linear_params[2])
return data0
plt.figure(figsize=(25, 15))
paths=['./data1','./data2','./data3','./data4']
datas=[]
num=241
threshold=int(input('threshold set(recommend start from 250):\n请输入阈值设置(默认推荐250):\n'))
try:
def main():
plt.figure(figsize=(25, 15))
paths=['./data1','./data2','./data3','./data4']
datas=[]
num=241
threshold=int(input('threshold set(recommend start from 250):\n请输入阈值设置(默认推荐250):\n'))
try:
for path in paths:
plt.subplot(num)
num+=1
datas.append(data_process(path))
except:
print("please make sure you have move the 4 data file to IDM folder\n请确认你有把4个文件拷到IDM文件夹内")
return
#反向求值
model=TempModel(1,-2.1429828e-05,-1.8980091e-10,3.6738370e-16,2943053.84,20.33)
p0=[-2.1429828e-05,-1.8980091e-10,3.6738370e-16]
params, params_covariance = curve_fit(fit,np.arange(5,80,0.01),np.hstack(datas),p0=p0,maxfev=1000000,ftol=1e-10,xtol=1e-10)
for path in paths:
plt.subplot(num)
num+=1
datas.append(data_process(path))
except:
print("please make sure you have move the 4 data file to IDM folder\n请确认你有把4个文件拷到IDM文件夹内")
#反向求值
model=TempModel(1,-2.1429828e-05,-1.8980091e-10,3.6738370e-16,2943053.84,20.33)
p0=[-2.1429828e-05,-1.8980091e-10,3.6738370e-16]
params, params_covariance = curve_fit(fit,np.arange(5,80,0.01),np.hstack(datas),p0=p0,maxfev=1000000,ftol=1e-10,xtol=1e-10)
for path in paths:
plt.subplot(num)
num+=1
data=[]
file_path = path # 替换为你的文件路径
with open(file_path, 'r') as file:
# 逐行读取文件内容
lines = file.readlines()
# 遍历每行内容
for line in lines:
data.append(line.split(','))
file.close()
full_data=pd.DataFrame(data[1:-1],columns=data[0])
temp=np.array(full_data['temp']).astype(np.float32)
freq=np.array(full_data['freq']).astype(np.float32)
freq=freq[::100]
temp=temp[::100]
result0=[]
for i in range(len(temp)):
result0.append(model.compensate(freq[i],temp[i],20.66))
plt.plot(temp[10:],result0[10:])
plt.savefig('fit.png')
print('fit result:')
print('tc_tcc:'+str(params[0])+'\ntc_tcfl:'+str(params[1])+'\ntc_tctl:'+str(params[2]))
data=[]
file_path = path # 替换为你的文件路径
with open(file_path, 'r') as file:
# 逐行读取文件内容
lines = file.readlines()
# 遍历每行内容
for line in lines:
data.append(line.split(','))
file.close()
full_data=pd.DataFrame(data[1:-1],columns=data[0])
temp=np.array(full_data['temp']).astype(np.float32)
freq=np.array(full_data['freq']).astype(np.float32)
freq=freq[::100]
temp=temp[::100]
result0=[]
for i in range(len(temp)):
result0.append(model.compensate(freq[i],temp[i],20.66))
plt.plot(temp[10:],result0[10:])
plt.savefig('fit.png')
print('fit result:')
print('tc_tcc:'+str(params[0])+'\ntc_tcfl:'+str(params[1])+'\ntc_tctl:'+str(params[2]))
if __name__== "__main__" :
main()