def plot_single_area_all_sources(area, sw, cap_limit=2.):
print('-' * 58)
print('-' * 20 + ' ' + area + ' ' + '-' * 20)
print('= Getting data...')
pu = plotter.PlotUtils(sw.png_dir_path, cap_limit=cap_limit)
output = StringIO()
header_set = False
for name, source in sw.sources:
print('= Gathering for:', name)
states, daily_cases_path = sw.get_daily_cases(source=source)
if states is None:
with open(daily_cases_path, 'r') as f:
contents = f.readlines()
for index, line in enumerate(contents):
contents[index] = line.replace(area, area + '_' + name)
if header_set:
contents = contents[1:]
output.writelines(contents)
header_set = True
output.seek(0)
states = pd.read_csv(output,
usecols=[0, 1, 2],
index_col=['state', 'date'],
parse_dates=['date'],
squeeze=True).sort_index()
pu.plot_all_states(states,
dump_file_name='all_sources_realtime_rt',
ncols=3)
print('-' * 26 + ' DONE ' + '-' * 26)
def plot_test_eu_incoherent_data():
sw_eu = sweeper.SweeperEU()
sw_eu.create_output_dirs()
pu = plotter.PlotUtils(sw_eu.png_dir_path)
pu.create_dump_dir()
states, daily_cases_path = sw_eu.get_daily_cases_cssegi()
state_name = 'France'
print(states[state_name].to_string())
window = 7
pu.debug = True
pu.plot_state_cases_per_day(states, state_name, window)
pu.plot_state_realtime_rt(states, state_name, window)
def plot_all_in_one(area, sw, start_date='2020-03-01', cap_limit=2.):
print('-' * 58)
print('-' * 20 + ' ' + area + ' ' + '-' * 20)
print('= Getting data...')
pu = plotter.PlotUtils(sw.png_dir_path,
start_date=start_date,
cap_limit=cap_limit)
states, daily_cases_path = sw.get_cases_by_county()
if states is None:
states = pd.read_csv(daily_cases_path,
usecols=[0, 1, 2],
index_col=['state', 'date'],
parse_dates=['date'],
squeeze=True).sort_index()
pu.plot_all_states(states)
print('-' * 26 + ' DONE ' + '-' * 26)
def plot_single_area(area, sw, source=None):
print('-' * 58)
print('-' * 20 + ' ' + area + ' ' + '-' * 20)
print('= Getting data...')
pu = plotter.PlotUtils(sw.png_dir_path)
states, daily_cases_path = sw.get_daily_cases(source=source)
if states is None:
states = pd.read_csv(daily_cases_path,
usecols=[0, 1, 2],
index_col=['state', 'date'],
parse_dates=['date'],
squeeze=True).sort_index()
state_name = area
window = 7
pu.plot_state_cases_per_day(states, state_name, window)
pu.plot_state_realtime_rt(states, state_name, window)
print('-' * 26 + ' DONE ' + '-' * 26)
def plot_test_ro_incoherent_data():
sw_ro = sweeper.SweeperRO()
sw_ro.create_output_dirs()
pu = plotter.PlotUtils(sw_ro.png_dir_path,
start_date='2020-04-01',
cap_limit=4.)
pu.create_dump_dir()
states, daily_cases_path = sw_ro.get_cases_by_county()
states = pd.read_csv(daily_cases_path,
usecols=[0, 1, 2],
index_col=['state', 'date'],
parse_dates=['date'],
squeeze=True).sort_index()
state_name = 'BR'
# state_name = 'IS'
print(states[state_name].to_string())
window = 7
pu.debug = True
pu.plot_state_cases_per_day(states, state_name, window)
pu.plot_state_realtime_rt(states, state_name, window)
#!/usr/bin/env python
import pandas as pd
import plotter
from matplotlib import pyplot as plt
pu = plotter.PlotUtils('')
fig, ax = plt.subplots(figsize=(600 / 72, 400 / 72))
url = 'https://raw.githubusercontent.com/nytimes/covid-19-data/master/us-states.csv'
states = pd.read_csv(url,
usecols=[0, 1, 3],
index_col=['state', 'date'],
parse_dates=['date'],
squeeze=True).sort_index()
state_name = 'New York'
cases = states.xs(state_name).rename(f"{state_name} cases")
original, smoothed = pu.prepare_cases(cases)
posteriors = pu.get_posteriors(smoothed)
hdis = pu.highest_density_interval(posteriors)
most_likely = posteriors.idxmax().rename('ML')
# Look into why you shift -1
result = pd.concat([most_likely, hdis], axis=1)
result.tail()