CheML-gist

import pandas as pd
from rdkit.Chem import AllChem, DataStructs
from rdkit import Chem
from tensorflow import keras
from sklearn.model_selection import train_test_split
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.figure as figure
import time
import pubchempy as pcp

CheML-gist

              Value     95% CI
mu       532.500000   0.015259
sigma      1.420898   0.017044
A       1409.000000  19.921875
y0        -8.914062   7.589844
%gauss     1.000000   0.077148
R2         0.996224        NaN

CheML-gist

import numpy as np
import pandas as pd
from scipy.optimize import curve_fit
import matplotlib.pyplot as plt

#データ読み込み---------------------------------------------------------
sample_data = pd.read_csv('sample.csv', skiprows = 4, header = None)
x = sample_data.iloc[:, 0]
y = sample_data.iloc[:, 1]

CheML-gist

             Value     95% CI
mu      532.500000   0.015221
sigma     1.420898   0.016678
A      1409.000000  13.507812
y0       -8.914062   4.785156
FWHM      3.345671        NaN
R2        0.996224        NaN

CheML-gist

import numpy as np
import pandas as pd
from scipy.optimize import curve_fit
import matplotlib.pyplot as plt

#データ読み込み---------------------------------------------------------
sample_data = pd.read_csv('sample.csv', skiprows = 4, header = None)
x = sample_data.iloc[:, 0]
y = sample_data.iloc[:, 1]