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fix requirements

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This commit is contained in:
Sgr A* VMT
2023-11-26 03:35:02 +08:00
parent 9344e72f89
commit 0cd08b09ef
2 changed files with 16 additions and 14 deletions
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21
arg_fit.py
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@@ -2,6 +2,7 @@
from scipy.optimize import curve_fit from scipy.optimize import curve_fit
import numpy as np import numpy as np
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
import pandas as pd
import warnings import warnings
warnings.filterwarnings("ignore") warnings.filterwarnings("ignore")
class TempModel: class TempModel:
@@ -49,7 +50,6 @@ def area_find(temp,freq):
i=j=100 i=j=100
i_flag=True i_flag=True
j_flag=True j_flag=True
threshold=250
for c in range(100): for c in range(100):
if(i_flag): if(i_flag):
i=i+100 i=i+100
@@ -79,8 +79,9 @@ def data_process(path):
for line in lines: for line in lines:
data.append(line.split(',')) data.append(line.split(','))
file.close() file.close()
temp=np.array(data[1:-1],dtype=float)[:,5] full_data=pd.DataFrame(data[1:-1],columns=data[0])
freq=np.array(data[1:-1],dtype=float)[:,3] temp=np.array(full_data['temp']).astype(np.float32)
freq=np.array(full_data['freq']).astype(np.float32)
freq=freq[::100] freq=freq[::100]
temp=temp[::100] temp=temp[::100]
plt.plot(temp[10:],freq[10:]) plt.plot(temp[10:],freq[10:])
@@ -92,17 +93,16 @@ plt.figure(figsize=(25, 15))
paths=['./data1','./data2','./data3','./data4'] paths=['./data1','./data2','./data3','./data4']
datas=[] datas=[]
num=241 num=241
try: threshold=int(input('threshold set(recommend start from 250):\n'))
for path in paths: for path in paths:
plt.subplot(num) plt.subplot(num)
num+=1 num+=1
datas.append(data_process(path)) datas.append(data_process(path))
except:
print("check if the data is prepared!")
#反向求值 #反向求值
model=TempModel(1,-2.1429828e-05,-1.8980091e-10,3.6738370e-16,2943053.84,20.33) 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] 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=1000,ftol=1e-10,xtol=1e-10) 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: for path in paths:
plt.subplot(num) plt.subplot(num)
num+=1 num+=1
@@ -115,8 +115,9 @@ for path in paths:
for line in lines: for line in lines:
data.append(line.split(',')) data.append(line.split(','))
file.close() file.close()
temp=np.array(data[1:-1],dtype=float)[:,5] full_data=pd.DataFrame(data[1:-1],columns=data[0])
freq=np.array(data[1:-1],dtype=float)[:,3] temp=np.array(full_data['temp']).astype(np.float32)
freq=np.array(full_data['freq']).astype(np.float32)
freq=freq[::100] freq=freq[::100]
temp=temp[::100] temp=temp[::100]
result0=[] result0=[]

1
requirements.txt
View File

@@ -2,3 +2,4 @@
numpy>=1.16.6 numpy>=1.16.6
scipy>=1.10.0 scipy>=1.10.0
matplotlib>=3.7.0 matplotlib>=3.7.0
pandas>=1.4.2