def main():
parser = ArgumentParser()
parser.add_argument('--group',
choices=['first', 'second', 'everything'],
default='everything')
parser.add_argument('--area')
parser.add_argument('-t', '--type', choices=['first', 'second'])
add_date_arg(parser,
help='first release to use',
default=earliest_vaccination)
add_date_arg(parser,
'--to-date',
default=find_latest('vaccination_cum_*')[1])
parser.add_argument('--duration', type=float, default=0.2)
parser.add_argument('--raise-errors', action='store_true')
args = parser.parse_args()
if args.type:
to_show = tuple_product_array(
[' '.join(w.capitalize() for w in args.area.split('-'))],
args.type.capitalize())
name = f'{args.area}_{args.type}'
else:
to_show = selection_mapping(args.from_date)[args.group]
name = args.group
dates = pd.date_range(args.from_date, args.to_date)
parallel_render(f'animated_vaccinations_{name}',
partial(render_plots, to_show, args.to_date),
dates,
duration=args.duration,
raise_errors=args.raise_errors)
def main():
parser = ArgumentParser()
parser.add_argument('left', type=series_from_string)
parser.add_argument('right', type=series_from_string)
parser.add_argument('--lf')
parser.add_argument('--rf')
parser.add_argument('--dpi', type=int, default=Map.dpi)
parser.add_argument('--width', type=int, default=15)
parser.add_argument('--height', type=int, default=2)
add_parallel_args(parser, default_output='none')
args = parser.parse_args()
df, data_date = summary_data(args.left + args.right)
earliest_date = data_start
latest_date = df.index.max().date()
to_date = parallel_to_date(args, latest_date)
dates = pd.date_range(args.from_date, to_date)
figsize = (args.width, args.height)
render = partial(render_dt, data_date, earliest_date, latest_date,
args.dpi, figsize, args.left, args.right, args.lf,
args.rf)
parallel_render(f'animated_summary_{args.width}_{args.height}', render,
dates, **parallel_params(args))
def main():
parser = ArgumentParser()
add_date_arg(parser, help='first release to use', default=earliest_testing)
add_parallel_args(parser,
default_duration=0.1,
default_output='gif',
from_date=False)
parser.add_argument('config', choices=BARS.keys())
add_date_arg(parser,
'--earliest',
help='min for x-axis',
default=second_wave)
parser.add_argument('--diff-log-scale', action='store_true')
parser.add_argument('--diff-no-lims', action='store_true')
parser.add_argument('--ylim', type=float)
parser.add_argument('--y-max-factor', type=float, default=1.02)
args = parser.parse_args()
config = Bars.get(args.config, earliest=args.earliest)
from_date = max(args.from_date, args.earliest)
dates = available_dates(config.metric,
config.data_file_stem,
earliest=from_date)
to_date = parallel_to_date(args, dates[0])
if to_date != dates[0]:
dates = [d for d in dates if d <= to_date]
latest_date = dates[0]
max_metric = config.data_for(latest_date)[0].sum(
axis=1).max() * args.y_max_factor
params = {}
if args.diff_no_lims:
params['diff_ylims'] = None
lines = config.lines_for(latest_date)
if lines:
params['line_ylim'] = max(l.data.max()
for l in lines) * args.y_max_factor
parallel_render(
f'animated_{args.config}',
partial(plot_bars,
config=config,
ylim=args.ylim or max_metric,
diff_log_scale=args.diff_log_scale,
show_title=True,
to_date=date.today(),
**params), dates,
**parallel_params(args, item_is_timestamp=False))
def main():
parser = ArgumentParser()
parser.add_argument('name')
parser.add_argument('text')
parser.add_argument('--fontsize', type=int, default=20)
parser.add_argument('--color', default='black')
add_parallel_args(parser, default_output='none')
args = parser.parse_args()
render = partial(render_text, args.text, args.fontsize, args.color)
to_date = parallel_to_date(args, date.today())
dates = pd.date_range(args.from_date, to_date)
params = parallel_params(args)
parallel_render(f'animated_text_{args.name}', render, dates, **params)
def main():
parser = ArgumentParser()
add_parallel_args(parser, default_output='gif', from_date='2020-03-15')
parser.add_argument('--data-date', default='*')
add_choices_arg(
parser, '--series', {
'cases': 'cases_demographics',
'deaths': 'deaths_demographics_for_comparison',
})
add_choices_arg(parser, '--type', {
'abs': False,
'pct': True,
})
args = parser.parse_args()
data_dates = set()
dates = None
maxes = {}
for s in args.series:
for t in args.type:
data, data_date, _ = data_for(args.data_date,
s,
earliest=args.from_date,
pct=t)
data_dates.add(data_date)
dates = data.index.values
maxes[s, t] = max(data.max())
if len(data_dates) != 1:
parser.error('--data-date, pick one: ' +
', '.join(str(d) for d in sorted(data_dates)))
name = 'animated_demographics'
parallel_render(
name,
partial(
plot_date,
series=args.series,
types=args.type,
maxes=maxes,
from_date=args.from_date,
data_date=args.data_date,
), dates, **parallel_params(args, dates))
def main():
parser = ArgumentParser()
add_parallel_args(parser,
default_duration=0.1,
default_output='gif',
from_date=False)
parser.add_argument('--max-cases', type=float, default=1_200_000)
parser.add_argument('--max-hospital', type=float, default=35_000)
args = parser.parse_args()
_, latest_date = load_data()
dates = pd.date_range('2021-02-19', latest_date)
parallel_render(
f'animated_prevalence',
partial(plot_prevalence,
max_cases=args.max_cases,
max_hospital=args.max_hospital,
latest=latest_date), dates, **parallel_params(args))
def main():
parser = ArgumentParser()
parser.add_argument('area_type', choices=MAPS.keys())
parser.add_argument('map')
parser.add_argument('--bare', action='store_true', help='just the map')
parser.add_argument('--no-legend', dest='legend', action='store_false', default=True)
parser.add_argument('--title', help='override title template')
parser.add_argument('--view', choices=views.keys())
parser.add_argument('--dpi', type=int)
parser.add_argument('--top', type=int, help='label the top n areas')
add_parallel_args(parser, default_duration='slowing')
args = parser.parse_args()
map = get_map(args.area_type, args.map)
view = args.view or map.default_view
views[view].check()
df, data_date = map.data
to_date = parallel_to_date(args, df.index.max().date(), map.default_exclude)
earliest_date = df.index.min().date()
dates = pd.date_range(args.from_date, to_date)
dpi = args.dpi or map.dpi
render = partial(
render_dt, data_date, earliest_date, args.area_type, args.map, view,
args.bare, args.legend, args.title, args.top, dpi
)
if args.raise_errors:
warnings.filterwarnings('error', category=UserWarning)
os.environ['PYTHONWARNINGS'] = 'error::UserWarning'
parallel_render(f'animated_map_{map.area_type}_{args.map}_{view}',
render, dates, **parallel_params(args, dates))