from datetime import datetime
from utils import read_batch_run, read_case_data, read_run, infection_rate
from plot import comparison_plots
#%%
sns.set_style("whitegrid")
sns.set_context("paper")
sns.set_palette("deep")
dateFormater = ConciseDateFormatter(AutoDateLocator())
#%%
rki, hospital = read_case_data("berlin-cases.csv", "berlin-hospital.csv")
#%%
def infections(f):
ev = pd.read_csv(f, sep="\t")
no_inf = set(ev.infected).difference(set(ev.infector))
res = np.sort(
np.concatenate(
(ev['infector'].value_counts().array, np.zeros(len(no_inf)))))
return pd.DataFrame(res)
"""
#%%
sns.set_style("whitegrid")
sns.set_context("paper")
sns.set_palette("deep")
dateFormater = ConciseDateFormatter(AutoDateLocator())
palette = sns.color_palette()
#%%
rki, meldedatum, hospital = read_case_data("berlin-cases.csv",
"berlin-cases-meldedatum.csv",
"berlin-hospital.csv")
#%%
import zipfile
z = zipfile.ZipFile(
"../../../../../public-svn/matsim/scenarios/countries/de/episim/battery/2021-02-09/paperAggr/summaries/79.zip"
)
with z.open("79.outdoorFraction.tsv") as f:
df = pd.read_csv(f,
delimiter="\t",
index_col=0,
parse_dates=[1],