Two state markov model¶
In [39]:
import random as random
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
sns.set()
%matplotlib inline
In [40]:
random.choice(["O","c"])
Out[40]:
'O'
In [41]:
allstate=[]
for i in range(10000):
allstate.append(random.choice(["O","C"]))
#print(s)
In [42]:
len(allstate)
Out[42]:
10000
In [43]:
allstate.count("O")
Out[43]:
5136
In [44]:
allstate.count("C")
Out[44]:
4864
In [45]:
np.random.choice(["O","c"],p=[0.9,0.1])
Out[45]:
'O'
In [46]:
allstate=[]
for i in range(10000):
allstate.append(np.random.choice(["O","C"],p=[0.9,0.1]))
In [47]:
len(allstate)
Out[47]:
10000
In [48]:
allstate.count("C")
Out[48]:
1007
In [49]:
allstate.count("O")
Out[49]:
8993
In [50]:
allstate=[]
for i in range(100):
allstate.append(np.random.choice([10,0],p=[0.5,0.5]))
In [51]:
plt.figure(figsize=[14,4])
X = []
Y = []
for x,y in enumerate(allstate):
plt.scatter(x,y)
X.append(x)
Y.append(y)
plt.plot(X,Y,'-')
plt.show()
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