def main(country):
cases, counties = select_country_specific_objects(country)
def funfig(obj, fig, axes):
kwargs = subplots[0].read_sliders(obj)
for subplot in subplots[1:]:
kwargs.update(subplot.read_sliders(obj))
if len(subplots) == 1:
axes = [axes]
else:
axes = np.reshape(axes, -1)
for (subplot, ax) in zip(subplots, axes):
subplot.plot(ax, cases, counties, **kwargs)
fig = PlotPyQt.Figure(
funfig,
nrows,
ncols,
figsize=(5 * ncols, 4.5 * nrows),
) #, tight=True, **kwargs)
for subplot in subplots:
subplot.add_sliders(fig, cases, counties)
fig.show()
def main(country):
from utils import select_country_specific_objects
cases, counties = select_country_specific_objects(country)
for data in ["infected","cured","deceased"]:
fig, axes = plt.subplots(1, 1, figsize=(6, 4.5))
plot(axes,
cases,
counties,
data,
# county="Suceava",
per_capita = True,
show_mean = True,
show_new = True,
show_countrylim="DE",
# title="",
)
fig.tight_layout()
break
plt.show()
plt.close()
def main(country):
from utils import select_country_specific_objects
cases, counties = select_country_specific_objects(country)
for data in ["infected","cured","deceased"]:
fig, axes = plt.subplots(1, 1, figsize=(6, 4.5))
for (ax, cmap, new_total) in zip([axes],["YlGnBu", "viridis"], ["New", "Total"]):
P = plot( ax,
cases,
counties,
new_total,
data,
prevdays=1,
per_capita = True,
cmap = cmap,
# title = "data",
# cbarlabel = "totalnew day popfactor",
)
fig.tight_layout()
plt.show()
plt.close()
exit()
def main(country):
cases, counties = select_country_specific_objects(country)
start = 13
folder0 = counties.country_code+"_fig/"
def folder1(task):
Q = task[0]["totalnew"] if "totalnew" in task[0].keys() else "both"
return folder0 + task[0]["data"] + "-" + Q
def prefix_(task):
Q = task[0]["totalnew"] if "totalnew" in task[0].keys() else "both"
return folder1(task) + "/" + task[0]["data"] + "-" + Q
def fname_(task,i):
return prefix_(task) + "_" + str(i+50).zfill(3)+".png"
tasks = [[{ "data": "infected", "totalnew": tn,
"per_capita": True, "prevdays": 14,
"window":5},
[10.5,5], # figsize
(121,plot_newtotal_vsTime,{"linewidth":4.5}),
(122,plot_map,{"cmap" : cmap,
"vminmax" : [0, vM],
"show_colorbar":True}),
] for (cmap,tn,vM) in []#("viridis","new",10),("cool","total",800)]
]+[
[ { "data": "infected",
"per_capita": True, "prevdays": 14,
"window":5},
[8.5,5.7], # figsize
(224,plot_map,{"cmap" : "plasma", "totalnew": "new",
"vminmax" : [0, 10],
"title" : "totalnew",
"cbarlabel": "",
}),
(211,plot_newtotal_vsTime,
{"linewidth":3.7,
"title": "Nr. data in county popfactor \n day"
}),
(223,plot_map,{"cmap" : "plasma", "totalnew": "total",
"vminmax" : [0, 800],
"cbarlabel": "",
"title" : "totalnew"}),
]]
if len(sys.argv) > 1:
try:
tasks = [tasks[i] for i in map(int, sys.argv[1: ]) if i in range(len(tasks))]
except:
pass
# in case sys.argv not provided or cannot be parsed to int
for task in filter(lambda t:len(t)>0,tasks):
prefix = prefix_(task)
common_params,figsize,*subplots = task
for i in cases.get_indices_all_days()[start:]:
fname = fname_(task,i)
print(i-start)
plt.figure(num=i,figsize=figsize)
for (ax,subplot,params) in subplots:
plt.subplot(ax)
subplot.plot(plt.gca(), cases, counties, day=cases.get_day(i),
**common_params, **params)
plt.tight_layout()
plt.savefig(fname, dpi=300, format="png")
plt.close()
for i in range(1,start_padding+1):
cmd = " ".join(["cp",fname_(task,start),fname_(task,start-i)])
os.system(cmd)
for i in range(1,end_padding+1):
cmd = " ".join(["cp", fname_(task, cases.get_dayindex()),
fname_(task, i + cases.get_dayindex())])
os.system(cmd)
cmd = f"ffmpeg -y -f image2 -r {framerate} -pattern_type glob -i '{prefix}_*.png' {folder1(task)}.mp4"
print(cmd)
os.system(cmd)
print()