Covid_19_DINN/plot_datasets.py

import numpy as np
import pandas as pd
from src.plotter import Plotter

DS_DIR = './datasets/'
SRC_DIR = './results/'
SIM_DIR = './visualizations/'

STATE_LOOKUP = {'Schleswig_Holstein' : 'Schleswig-Holstein',
                'Hamburg' : 'Hamburg', 
                'Niedersachsen' : 'Niedersachsen', 
                'Bremen' : 'Bremen',
                'Nordrhein_Westfalen' : 'North Rhine-Westphalia',
                'Hessen' : 'Hessen',
                'Rheinland_Pfalz' : 'Rhineland-Palatinate',
                'Baden_Wuerttemberg' : 'Baden-Württemberg',
                'Bayern' : 'Bavaria',
                'Saarland' : 'Saarland',
                'Berlin' : 'Berlin',
                'Brandenburg' : 'Brandenburg',
                'Mecklenburg_Vorpommern' : 'Mecklenburg-Western Pomerania',
                'Sachsen' : 'Saxony',
                'Sachsen_Anhalt' : 'Saxony-Anhalt',
                'Thueringen' : 'Thuringia'}

plotter = Plotter()

data = []
in_text_data = [np.genfromtxt(DS_DIR + f'SIR_data.csv', delimiter=',')[1:], 1]
for state in STATE_LOOKUP.keys():
    # print(f"plot {state}")
    state_data_5 = np.genfromtxt(DS_DIR + f'I_RKI_{state}_1_5.csv', delimiter=',')[1]
    state_data_14 = np.genfromtxt(DS_DIR + f'I_RKI_{state}_1_14.csv', delimiter=',')[1]
    sir_data = np.genfromtxt(DS_DIR + f'SIR_RKI_{state}_1_14.csv', delimiter=',')[1:]
    data.append(sir_data)
    t = np.arange(0, 1200, 1)

    if state in ["Schleswig_Holstein", "Berlin", "Thueringen"]:
        in_text_data.append(sir_data)

    plotter.plot(t, 
                 [state_data_14, state_data_5], 
                 [r'$\alpha=\frac{1}{14}$', r'$\alpha=\frac{1}{5}$'],
                 f'{state}_datasets',
                 f'{STATE_LOOKUP[state]}',
                 (12,6),
                 xlabel='time / days',
                 ylabel='amount of people')
    
do_log=False
plotter.cluster_plot(t,
                     data[:6],
                     [r'$S$', r'$I$', r'$R$'],
                     (2, 3),
                     (6,6),
                     "state_sir_cluster_1",
                     list(STATE_LOOKUP.values())[:6],
                     xlabel='time / days',
                     ylabel='amount of people',
                     y_log_scale=do_log,
                     add_y_space=0.05,
                     number_of_legend_columns=3,
                     same_axes=False,
                     ylim=(0, 1.85e7))
plotter.cluster_plot(t,
                     data[7:],
                     [r'$S$', r'$I$', r'$R$'],
                     (3, 3),
                     (6,6),
                     "state_sir_cluster_2",
                     list(STATE_LOOKUP.values())[7:],
                     xlabel='time / days',
                     ylabel='amount of people',
                     y_log_scale=do_log,
                     add_y_space=0.03,
                     number_of_legend_columns=3,
                     same_axes=False,
                     ylim=(0, 1.85e7))

germany_data = np.genfromtxt(DS_DIR + f'SIR_RKI_Germany_1_14.csv', delimiter=',')[1:]
in_text_data[1] = germany_data

plotter.plot(t,
             germany_data,
             [r'$S$', r'$I$', r'$R$'],
             'germany_single_sir',
             'Germany',
             (6,6),
             plot_legend=False,
             xlabel='time / days',
             ylabel='amount of people',)

plotter.cluster_plot(t, 
                     in_text_data,
                     [r'$S$', r'$I$', r'$R$'],
                     (2, 3),
                     (6, 6),
                     "in_text_SIR",
                     ["synthetic SIR data", "Germany", 'Schleswig Holstein', 'Berlin', 'Thuringia'],
                     xlabel='time / days',
                     ylabel='amount of people',
                     legend_loc=(0.51, 0.8),
                     add_y_space=0,
                     same_axes=False,
                     free_axis=(0, 1),
                     plot_all_labels=False)