make all plotting modules future proof by accepting kwargs

all_countries.py

@@ -20,7 +20,7 @@ corr = {"Chile": 10000,
         "Turkey": 100000,
 }
 
-def plot(data, countries, pop):
+def plot(data, countries, pop, **kwargs):
     figsize = (10,5)
 
     for loc in data:

basics.py

@@ -4,7 +4,7 @@ Plot total cases of countries over time on log scale
 import matplotlib.pyplot as pp
 import numpy as np
 
-def plot(data, countries, pop):
+def plot(data, countries, pop, **kwargs):
     figsize = (10,5)
     tcp, tc = pp.subplots(figsize=figsize)  # total cases
     tdp, td = pp.subplots(figsize=figsize)  # total deaths

death_per_case.py

@@ -5,7 +5,7 @@ import matplotlib.pyplot as pp
 import numpy as np
 name="death_per_case"
 
-def plot(data, countries, pop):
+def plot(data, countries, pop, **kwargs):
     figsize = (10,5)
     for loc in data:
         if loc not in countries:

delay_from_china.py

@@ -5,7 +5,7 @@ import matplotlib.pyplot as pp
 import numpy as np
 name="delay"
 
-def plot(data, countries, pop):
+def plot(data, countries, pop, **kwargs):
     figsize = (10,5)
 
     # plot delay

delay_from_usa.py

@@ -5,7 +5,7 @@ import matplotlib.pyplot as pp
 import numpy as np
 name="delay"
 
-def plot(data, countries, pop):
+def plot(data, countries, pop, **kwargs):
     figsize = (10,5)
     for loc in data:
         if loc not in countries:

doubling_time.py

@@ -8,7 +8,7 @@ name="doubling_time"
 def moving_average(x, w):
     return np.convolve(x, np.ones(w), 'valid') / w
 
-def plot(data, countries, pop):
+def plot(data, countries, pop, **kwargs):
     figsize = (10,5)
     for loc in data:
         if loc not in countries:

normalized_to_first_death.py

@@ -5,7 +5,7 @@ import matplotlib.pyplot as pp
 import numpy as np
 name="normalized_to_first_death"
 
-def plot(data, countries, pop):
+def plot(data, countries, pop, **kwargs):
     figsize = (10,5)
     for loc in data:
         if loc not in countries:

normalized_to_ten_cases.py

@@ -5,7 +5,7 @@ import matplotlib.pyplot as pp
 import numpy as np
 name="normalized_to_100_cases"
 
-def plot(data, countries, pop):
+def plot(data, countries, pop, **kwargs):
     figsize = (10,5)
     for loc in data:
         if loc not in countries:

percent_increase.py

@@ -8,7 +8,7 @@ name="percent_increase"
 def moving_average(x, w):
     return np.convolve(x, np.ones(w), 'valid') / w
 
-def plot(data, countries, pop):
+def plot(data, countries, pop, **kwargs):
     figsize = (10,5)
     for loc in data:
         if loc not in countries: