analyze.py 文件源码

def plot_by_interval(data, zamg_dfs = None):
    p_vals = {}
    # sort by year
    for k in sorted(data):
        v = data[k]
        d_obj = datetime.datetime.strptime(k, key_pattern)

        series_key = datetime.datetime.strftime(d_obj, "%Y")
        #data_key = datetime.datetime.strftime(d_obj, "%m-%d")

        p_vals.setdefault(series_key, dict()).setdefault("x_vals", list()).append(d_obj)
        p_vals.setdefault(series_key, dict()).setdefault("y_vals", list()).append(v)

    plt.clf()

    fig, axis = plt.subplots(nrows=len(p_vals)*2, sharex=False, sharey=False)

    a_iter = iter(axis)

    for k in sorted(p_vals):
        v = p_vals[k]
        ax = next(a_iter)

        y_vals = v["y_vals"]
        x_vals = matplotlib.dates.date2num(v["x_vals"])
        ax.plot_date(x_vals, y_vals)
        # ax.plot(x_vals, y_vals)

        ax = next(a_iter)
        if zamg_dfs is not None and k in zamg_dfs:
            df = zamg_dfs[k]
            df['Wien Hohe Warte']['48,2486']['16,3564']['198.0']['Anhöhe']['Ebene']\
                ['Lufttemperatur']['Lufttemperatur um 14 MEZ (°C)'].plot(ax=ax)

    plt.show()