From cef047beb77e8298499167e1a901113202a039cc Mon Sep 17 00:00:00 2001
From: fordprefect <fordprefect@dukun.de>
Date: Sat, 21 Mar 2020 21:02:06 +0100
Subject: [PATCH] delay from china in days

---
 delay_from_china.py | 71 +++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 71 insertions(+)
 create mode 100644 delay_from_china.py

diff --git a/delay_from_china.py b/delay_from_china.py
new file mode 100644
index 0000000..970a416
--- /dev/null
+++ b/delay_from_china.py
@@ -0,0 +1,71 @@
+"""
+Plot delay of countries
+"""
+import matplotlib.pyplot as pp
+import numpy as np
+name="delay"
+
+def plot(data, countries):
+    for loc in data:
+        if loc not in countries:
+            continue
+        time, new_cases, new_deaths, total_cases, total_deaths = data[loc]
+        
+        pp.figure(name)
+        day_of_above_hundred_cases = np.argwhere(np.array(total_cases) > 100)[0][0]
+        
+        new_time_axis = np.arange(len(time)) - day_of_above_hundred_cases
+        pp.plot(new_time_axis, np.array(total_cases), label=f"{loc} - {day_of_above_hundred_cases}", marker=".")
+
+    pp.yscale("log")
+    pp.xticks(rotation=45)
+    pp.legend(frameon=False)
+    pp.tight_layout()
+
+    pp.savefig(name+".png")
+
+    # plot delay
+    pp.clf()
+    delay = {}
+    tcases = [50, 100, 500, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000, 12500, 15000, 17500,
+            20000, 22500, 25000, 27500,
+            30000, 32500, 35000, 37500,
+            40000, 42500, 45000, 47500,
+            50000, 52500, 55000, 57500,
+            60000, 62500, 65000, 67500,
+            70000, 72500, 75000, 77500,
+            80000]
+
+    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])
+    total_cases_china = data["China"][3]
+    for loc in data:
+        if loc not in countries:
+            continue
+        if loc in ["China", "World"]:
+            continue
+        this_delay = []
+        for i, cases in enumerate(tcases):
+            try:
+                case_date = data[loc][0][np.argwhere(np.array(data[loc][3]) > cases)[0][0]]
+            except:
+                this_delay.append(np.nan)
+                continue
+            #case_date = np.array([time_china[np.argwhere(np.array(data[loc][3]) > cases)[0][0]] for cases in tcases])
+        
+            this_delay.append((case_date_china[i] - case_date).days)
+
+        delay[loc] = this_delay
+
+    sort = np.argsort(delay)
+    
+    for loc in delay:
+        pp.plot(tcases, delay[loc], label=loc, marker=".")
+    #pp.plot(np.arange(len(delay)), np.array(delay)[sort] - np.min(delay), marker="o", linestyle="")
+    #pp.xticks(ticks=np.arange(len(delay)), labels=np.array(d_loc)[sort])
+    pp.xticks(rotation=45)
+    pp.legend(frameon=False)
+    pp.xlabel("total cases")
+    pp.ylabel("delay to china [days]")
+    pp.tight_layout()
+    pp.savefig(name+"num.png")