import os
import pandas as pd
import numpy as np
import sys
import seaborn as sns
import matplotlib.pyplot as plt
sys.path.append('../')
from load_paths import load_box_paths
datapath, projectpath, wdir, exe_dir, git_dir = load_box_paths()
from processing_helpers import *
"""
df = pd.read_csv(os.path.join(datapath, 'covid_IDPH', 'Corona virus reports', 'il_cdc_thru_0811.csv'),low_memory=False)
print(df)
"""
"""Read in only relevant columns """
column_list = [
'icu_length', 'hosp_length', 'age_group', 'res_county', 'res_state',
'hosp_yn', 'icu_yn', 'death_yn'
]
df = pd.read_csv(os.path.join(datapath, 'covid_IDPH', 'Corona virus reports',
'il_cdc_thru_0811.csv'),
usecols=column_list)
print(df)
"""Remove Missings and Unknowns """
df = df.dropna(subset=["hosp_length"])
df = df.dropna(subset=["age_group"])
df = df.dropna(subset=["death_yn"])
df = df[df['age_group'] != 'Unknown']
df = df[df['icu_yn'] != 'Unknown']
logging.basicConfig(level="DEBUG")
logging.getLogger("matplotlib").setLevel(
"INFO") # Matplotlib has noisy debugs
args = parse_args()
emodl_template = args.emodl_template
model = args.model
scenario = args.scenario
if args.running_location is None:
if os.name == "posix":
args.running_location = "NUCLUSTER"
else:
args.running_location = "Local"
_, _, wdir, exe_dir, git_dir = load_box_paths(
Location=args.running_location)
Location = os.getenv("LOCATION") or args.running_location
if not Location:
raise ValueError("Please provide a running location via environment "
"variable or CLI parameter.")
# Only needed on non-Windows, non-Quest platforms
docker_image = os.getenv("DOCKER_IMAGE")
emodl_dir = os.path.join(git_dir, 'emodl')
cfg_dir = os.path.join(git_dir, 'cfg')
yaml_dir = os.path.join(git_dir, 'experiment_configs')
log.debug(f"Running in Location = {Location}")
if sys.platform not in ['win32', 'cygwin']:
log.debug(f"Running in a non-Windows environment; "
region_label=region_label,
first_day=first_day,
last_day=last_day,
plot_path=plot_path)
if __name__ == '__main__':
args = parse_args()
stem = args.stem
Location = args.Location
first_plot_day = pd.Timestamp('2020-02-13')
last_plot_day = pd.Timestamp.today() + pd.Timedelta(15, 'days')
datapath, projectpath, wdir, exe_dir, git_dir = load_box_paths(
Location=Location)
exp_names = [
x for x in os.listdir(os.path.join(wdir, 'simulation_output'))
if stem in x
]
for exp_name in exp_names:
sim_output_path = os.path.join(wdir, 'simulation_output', exp_name)
plot_path = os.path.join(sim_output_path, '_plots')
"""Get group names"""
grp_list, grp_suffix, grp_numbers = get_group_names(
exp_path=sim_output_path)
for grp_nr in grp_numbers:
print("Start processing region " + str(grp_nr))
compare_ems(exp_name,
ems_nr=int(grp_nr),
import shutil
import stat
import sys
import numpy as np
import pandas as pd
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import seaborn as sns
mpl.rcParams['pdf.fonttype'] = 42
from processing_helpers import CI_50, CI_25, CI_75, CI_2pt5, CI_97pt5
from load_paths import load_box_paths
datapath, projectpath, WDIR, EXE_DIR, GIT_DIR = load_box_paths()
log = logging.getLogger(__name__)
def DateToTimestep(date, startdate):
datediff = date - startdate
timestep = datediff.days
return timestep
def TimestepToDate(timesteps, startdate):
dates = startdate + pd.Timedelta(timesteps, 'days')
return dates
