nCoV Predictor
=============================================================

:Date: 1 Mar 2019

- code

.. code-block:: python
    
    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()