如何得到高斯拟合直方图？

Question

我有一个表格的pandas.DataFrame

index     ABC       

1         -40       
2         -30       
3         -30       
4         -20       
5         -20       
6         -10       
7         -10       
8         -10      
9          0      
10         0       
11         0       
12         0       
13         10       
14         10       
15         10      
16         10      
17         20     
18         20      
19         20       
20         30       
21         40    

我想做ABC的数据分析。

'ABC'.

• Gaussian

1. 绘制了一幅直方图，将histogram.
2. Measure的全宽度拟合为半高宽。我想按上述顺序进行。我该怎么办？

Answer 1

试试这个：

1.绘制直方图

_, bins, _ = plt.hist(data, 20, density=1, alpha=0.5)

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2.高斯拟合

_, bins, _ = plt.hist(data, 20, density=1, alpha=0.5)
mu, sigma = scipy.stats.norm.fit(data)
best_fit_line = scipy.stats.norm.pdf(bins, mu, sigma)
plt.plot(bins, best_fit_line)

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3.半妇女问题

x = data.index.values
y = np.array(data['ABC'])

def lin_interp(x, y, i, half):
    return x[i] + (x[i+1] - x[i]) * ((half - y[i]) / (y[i+1] - y[i]))

def half_max_x(x, y):
    half = max(y)/2.0
    signs = np.sign(np.add(y, -half))
    zero_crossings = (signs[0:-2] != signs[1:-1])
    zero_crossings_i = np.where(zero_crossings)[0]
    return [lin_interp(x, y, zero_crossings_i[0], half),
            lin_interp(x, y, zero_crossings_i[1], half)]
hmx = half_max_x(x,y)
fwhm = hmx[1] - hmx[0]