def generate_all_plots(withSyntheticData=True):
ts, bnn, ts_sorted, Bundeslaender_sorted, dates, datacolumns = dataMangling.dataMangled(
withSynthetic=withSyntheticData)
print()
print("Plotting takes a bit of time. Patience please. Thanks.")
done = dataPlotting.plot_all_Bundeslaender(ts,
bnn,
dates,
datacolumns,
ifPrint=False)
print("plot_all_Bundeslaender: %d items" % len(done))
listOfAGSs = ts["AGS"].tolist()
print("Plotting %d images, for each Kreis. Patience please: " %
len(listOfAGSs))
done = dataPlotting.plot_Kreise(ts,
bnn,
dates,
datacolumns,
listOfAGSs,
ifPrint=False)
print("plot_Kreise done: %d items" % len(done))
print()
return True
def generate_all_pages(withSyntheticData=True):
ts, bnn, ts_sorted, Bundeslaender_sorted, dates, datacolumns = dataMangling.dataMangled(
withSynthetic=withSyntheticData)
print()
distances = districtDistances.load_distances()
cmap = dataTable.colormap()
haupt = dataFiles.load_master_sheet_haupt(
timestamp="") # timestamp="" means newest
print()
Bundeslaender_filenames = dataPages.Bundeslaender_alle(
Bundeslaender_sorted,
ts,
ts_sorted,
datacolumns,
bnn,
distances,
cmap,
km=50,
haupt=haupt)
print(Bundeslaender_filenames)
fn = dataPages.Deutschland(Bundeslaender_sorted, datacolumns, cmap,
ts_sorted, bnn)
print("\n" + fn)
return True
def generate_hotspot_files():
ts, bnn, ts_sorted, Bundeslaender_sorted, dates, datacolumns = dataMangling.dataMangled(
ifPrint=False)
distances = districtDistances.load_distances()
print(
"50 km, relative threshold; or absolute threshold, and not already among relative threshold:"
)
for AGS in (5558, 16072, 9163, 16076, 9473, 9263, 9278, 8231, 4011, 5382,
9362, 9478, 5370, 3459, 9463, 9376, 9475, 5554, 8231, 4012,
3352, 16052, 9473, 7315, 3159, 9771, 5754, 3361, 15003, 5570,
3103, 6632, 3458, 3401, 5170, 5111, 5915, 5112, 9188, 9279,
7334, 9173, 5366, 5158, 7312, 11000, 5112, 3241, 9162, 5913,
4011, 5315, 6412, 9761, 5958, 16055, 1051, 5122, 3460, 8128,
7232, 5113, 2000, 5911, 8136, 5562):
neighbour_districts_table_page(AGS=AGS,
distances=distances,
km=50,
bnn=bnn)
print("\n100 km:")
for AGS in (5754, ):
neighbour_districts_table_page(AGS=AGS,
distances=distances,
km=100,
bnn=bnn)
print("\n150 km")
for AGS in ():
neighbour_districts_table_page(AGS=AGS,
distances=distances,
km=150,
bnn=bnn)
def loadAndShowSomeExtremeValues():
print("\n show some insights\n")
ts, bnn, ts_sorted, Bundeslaender_sorted, dates, datacolumns = dataMangling.dataMangled(
withSynthetic=True)
# print (ts_sorted.columns)
showSomeExtremeValues(ts_sorted, datacolumns)
showBundeslaenderRanked(Bundeslaender_sorted, datacolumns)
filenames.append(filename)
population += pop_BL
if ifPrint:
print(title, filename)
done.append((title, filename))
print("\nTotal population covered:", population)
if ifPrint:
print("%d filenames written: %s" % (len(filenames), filenames))
return done
if __name__ == '__main__':
# ts, bnn = dataFiles.data(withSynthetic=True)
# dates = dataMangling.dates_list(ts)
ts, bnn, ts_sorted, Bundeslaender_sorted, dates, datacolumns = dataMangling.dataMangled(
withSynthetic=True)
examples = True
if examples:
test_plot_Kreis(ts, bnn, dates, datacolumns)
test_plot_Bundesland(ts, bnn, dates, datacolumns)
test_plot_Bundesland(ts,
bnn,
dates,
datacolumns,
Bundesland="Deutschland")
longrunner = True
if longrunner:
plot_Kreise(ts, bnn, dates, datacolumns, ts["AGS"].tolist())
plot_all_Bundeslaender(ts, bnn, dates, datacolumns)
'green': ((0.0, 0.0, 1.0),
(0.5, 0.0, 0.0),
(1.0, 0.0, 0.0))}
cmap = mcolors.LinearSegmentedColormap('my_colormap', cdict, 100)
"""
# cmap = matplotlib.colors.LinearSegmentedColormap.from_list("", ["green","yellow","red"])
cmap = matplotlib.colors.LinearSegmentedColormap.from_list(
"", ["green", "yellow", "red"])
cmap.set_bad("white")
return cmap
if __name__ == '__main__':
ts, bnn, ts_sorted, Bundeslaender_sorted, dates, datacolumns = dataMangling.dataMangled(
)
AGS = 1001
AGS = 5370
print(ts_sorted["centerday"][AGS])
cmap = colormap()
print(toHTMLRow(ts_sorted, AGS, datacolumns, cmap, labels=["%s" % AGS]))
district_AGSs = [1001, 1002, 5370, 9377]
district_AGSs = ts_sorted.index.tolist()
distances = districtDistances.load_distances()
print(
Districts_to_HTML_table(ts_sorted,