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more finegrained grid in delay plots

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fordprefect
2020-03-30 12:55:46 +02:00
parent bf79f2f69f
commit 3f5fd93a75
2 changed files with 3 additions and 3 deletions
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3
delay_from_china.py
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@@ -17,8 +17,7 @@ def plot(data, countries):
40000, 42500, 45000, 47500,
50000, 52500, 55000, 57500,
60000, 62500, 65000, 67500,
70000, 72500, 75000, 77500,
80000]
70000, 72500, 75000, 77500]+list(np.arange(80000,max(data["China"][3]),500))
time_china = data["China"][0]
case_date_china = np.array([time_china[np.argwhere(np.array(data["China"][3]) > cases)[0][0]] for cases in tcases])

3
delay_from_usa.py
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@@ -28,7 +28,8 @@ def plot(data, countries):
# plot delay
pp.clf()
delay = {}
tcases = [50, 100, 500, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000] + list(np.arange(10000, np.max(data["United States"][3]), 2500))
tcases = [50, 100, 500, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 80500,81000,81500,82000,83000,835000,84000,84500] + list(np.arange(10000, np.max(data["United States"][3]), 2500))
tcases.sort()
time_us = data["United States"][0]
try: