nCoV Predictor

Date:

1 Mar 2019

• code

import urllib.request, json
import matplotlib.pyplot as plt
import numpy as np
from scipy.optimize import curve_fit

url = 'https://view.inews.qq.com/g2/getOnsInfo?name=disease_h5'

with urllib.request.urlopen(url) as dataUrl:
    data = json.loads(dataUrl.read().decode())['data']
    data = json.loads(data)
    for key, value in data.items():
        print(key)

chinaDayList = data["chinaDayList"]
confirm = [i['confirm'] for i in chinaDayList]
date = [i['date'] for i in chinaDayList]

plt.plot(date,confirm,'.',label='original data')

def logistic(x, a, b, c):
    return a/(1+np.exp(-b*(x-c)))

xdata = np.array(range(len(confirm)))
popt, pcov = curve_fit(logistic, xdata, confirm)
xdata *=2
plt.plot(xdata, logistic(xdata, *popt), 'r-',
         label='fit: a=%5.3f, b=%5.3f, c=%5.3f' % tuple(popt))
plt.title('nCoV china total: logistic regression')
plt.legend()
plt.show()