more finegrained grid in delay plots
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@@ -17,8 +17,7 @@ def plot(data, countries):
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40000, 42500, 45000, 47500,
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40000, 42500, 45000, 47500,
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50000, 52500, 55000, 57500,
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50000, 52500, 55000, 57500,
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60000, 62500, 65000, 67500,
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60000, 62500, 65000, 67500,
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70000, 72500, 75000, 77500,
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70000, 72500, 75000, 77500]+list(np.arange(80000,max(data["China"][3]),500))
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80000]
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time_china = data["China"][0]
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time_china = data["China"][0]
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case_date_china = np.array([time_china[np.argwhere(np.array(data["China"][3]) > cases)[0][0]] for cases in tcases])
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case_date_china = np.array([time_china[np.argwhere(np.array(data["China"][3]) > cases)[0][0]] for cases in tcases])
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@@ -28,7 +28,8 @@ def plot(data, countries):
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# plot delay
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# plot delay
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pp.clf()
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pp.clf()
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delay = {}
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delay = {}
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tcases = [50, 100, 500, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000] + list(np.arange(10000, np.max(data["United States"][3]), 2500))
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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))
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tcases.sort()
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time_us = data["United States"][0]
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time_us = data["United States"][0]
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try:
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try:
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