test_and_case_data.py

   1 #!/usr/bin/env python
   2 # coding: utf-8
   3 # %%
   4 import itertools
   5 import collections
   6 import json
   7 import pandas as pd
   8 import numpy as np
   9 from scipy.stats import gmean
  10 import datetime
  11 import os
  12 import sqlalchemy
  13
  14 import matplotlib as mpl
  15 import matplotlib.pyplot as plt
  16 import matplotlib.animation as ani
  17 plt.ioff()
  18
  19
  20 # %%
  21 chart_start_date = '2020-09-15'
  22
  23
  24 # %%
  25 connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid'
  26
  27
  28 # %%
  29 engine = sqlalchemy.create_engine(connection_string)
  30
  31 # %%
  32 query_string = '''select uk_data.date,
  33     uk_data.new_cases, uk_data_7.new_cases as new_cases_7,
  34     uk_data.new_tests, uk_data_7.new_tests as new_tests_7,
  35     uk_data.new_pcr_tests, uk_data_7.new_pcr_tests as new_pcr_7,
  36     uk_data.new_pillar_1_2_tests as new_pillar_12, uk_data_7.new_pillar_1_2_tests as new_pillar_12_7,
  37      uk_data.new_cases::float / uk_data.new_tests as fraction_positive,
  38         uk_data_7.new_cases / uk_data_7.new_tests as fraction_positive_7
  39     from uk_data left outer join uk_data_7 using (date)
  40     order by uk_data.date'''
  41 tests_data = pd.read_sql_query(query_string, engine,
  42     index_col='date',
  43     parse_dates = ['date'])
  44
  45 # %%
  46 pri_y_max = int((tests_data.dropna().loc[chart_start_date: , 'new_tests_7'].max() * 1.1) / 100 ) * 100
  47 ax = tests_data.dropna().loc[chart_start_date: , 'new_tests_7'].plot(figsize=(10, 8),
  48                                                                style=['k-'],
  49                                                                legend=False,
  50                                                                ylim=(0, pri_y_max))
  51 ax.set_title('Tests done and new cases (7 day moving average)')
  52 ax.legend(['Tests, 7 day moving average'], loc='lower left')
  53 ax.set_ylabel('Tests')
  54 sec_y_max = int((tests_data.dropna().loc[chart_start_date:, 'new_cases_7'].max() * 1.1) / 100) * 100
  55 ax = tests_data.dropna().loc[chart_start_date:, 'new_cases_7'].plot(ax=ax, secondary_y=True, style='r--')
  56 ax.set_ylim((0, sec_y_max))
  57 ax.legend(['Cases (7 day moving average)'], loc='lower right')
  58 ax.set_ylabel('New cases')
  59 plt.savefig('tests_and_cases.png')
  60
  61
  62 # %%
  63 ax = (tests_data.loc[chart_start_date: , ['fraction_positive', 'fraction_positive_7']] * 100).plot(figsize=(10, 8),
  64                                                                                                   style=['b:', 'k-'], legend=False)
  65 ax.set_title('Fraction of tests with positive results')
  66 ax.legend(['Fraction positive (%)', 'Fraction positive (%), 7 day moving average'], loc='upper left')
  67 ax.set_ylabel('Fraction positive')
  68 cases_axis_max = (1.0 * tests_data.loc[chart_start_date:].new_cases_7.max()
  69                   * tests_data.loc[chart_start_date:].fraction_positive.max()
  70                   / tests_data.loc[chart_start_date:].fraction_positive_7.max()
  71                   )
  72
  73 ax2 = ax.twinx()
  74 ax2 = tests_data.loc[chart_start_date:, 'new_cases_7'].plot(ax=ax2, secondary_y=True, style='r--')
  75 ax2.set_ylim(-1000, cases_axis_max)
  76 ax2.legend(['Cases (7 day moving average)'], loc='center left')
  77 ax2.set_ylabel('New cases')
  78 plt.savefig('fraction_positive_tests.png')
  79
  80
  81 # %%
  82 ax = tests_data.dropna().loc[chart_start_date:].plot(x='fraction_positive_7', y='new_tests_7',
  83                                                   figsize=(8, 8),
  84                                                   legend=None)
  85 ax.set_xlabel("Fraction of tests that are positive")
  86 ax.set_ylabel("Number of tests")
  87 for d in tests_data.dropna().loc[chart_start_date::15].index:
  88     ax.plot(tests_data.loc[d, 'fraction_positive_7'], tests_data.loc[d, 'new_tests_7'], 'o',
  89                         markersize=8)#, markerfacecolor=marker_col, markeredgecolor=marker_col)
  90     ax.text(tests_data.loc[d, 'fraction_positive_7'] + 0.0002, tests_data.loc[d, 'new_tests_7'],
  91             s = d.strftime("%d %B %Y"))
  92 plt.savefig('fraction_positive_tests_vs_tests.png')
  93
  94
  95 # %%
  96 fig = plt.figure(figsize=(8, 8))
  97 plt.ylabel('Number of tests')
  98 plt.xlabel('Fraction of tests that are positive')
  99 all_data = tests_data.dropna().loc[chart_start_date:]
 100
 101
 102 minx = all_data.fraction_positive_7.min() * 0.9
 103 maxx = all_data.fraction_positive_7.max() * 1.1
 104 miny = all_data.new_tests_7.min() * 0.9
 105 maxy = all_data.new_tests_7.max() * 1.1
 106
 107 plt.xlim(minx, maxx)
 108 plt.ylim(miny, maxy)
 109 # plt.legend(None)
 110
 111 def build_state_frame(i):
 112     this_data = all_data[:i]
 113     plt.clf()
 114     plt.ylabel('Number of tests')
 115     plt.xlabel('Fraction of tests that are positive')
 116     plt.xlim(minx, maxx)
 117     plt.ylim(miny, maxy)
 118     p = plt.plot(this_data.fraction_positive_7, this_data.new_tests_7)
 119     p[0].set_color('r')
 120     for d in this_data[::15].index:
 121         plt.plot(this_data.loc[d, 'fraction_positive_7'],
 122                 this_data.loc[d, 'new_tests_7'], 'o',
 123                 markersize=8, markerfacecolor='r', markeredgecolor='r')
 124         plt.text(this_data.loc[d, 'fraction_positive_7'] + 0.0002,
 125                 this_data.loc[d, 'new_tests_7'],
 126             s = d.strftime("%d %B %Y"))
 127
 128 animator = ani.FuncAnimation(fig, build_state_frame,
 129                              frames=all_data.shape[0]+1,
 130                              interval=100,
 131                              repeat_delay=200,
 132                              repeat=True)
 133 animator.save('tests_vs_fraction_positive.mp4')
 134 # plt.show()
 135
 136
 137 # %%
 138 os.system('rm tests_vs_fraction_positive_animation.png')
 139 os.system('ffmpeg -i tests_vs_fraction_positive.mp4 -plays 0 -final_delay 1 -f apng tests_vs_fraction_positive_animation.png')
 140
 141
 142 # %%
 143
 144
 145
 146