numpy中生成随机数的几种常用函数(小结)

array1 = np.random.random((3))
display(array1)
# -----------------------------------
array2 = np.random.random((3,4))
display(array2)
# -----------------------------------
array3 = np.random.rand(3)
display(array3)
# -----------------------------------
array4 = np.random.rand(2,3)
display(array4)

array9 = np.random.randint(low=1, high=10, size=6, dtype=np.int32)
display(array9)
# ---------------------------------------------------------
array10 = np.random.randint(low=1, high=10, size=(2,3), dtype=np.int64)
display(array10)
# ---------------------------------------------------------
array11 = np.random.randint(low=1, high=10, size=(2,3,4), dtype=np.int32)
display(array11)

array5 = np.random.randn(3)
display(array5)
# ---------------------------------------------
array6 = np.random.randn(2,3)
display(array6)
# ---------------------------------------------
array7 = np.random.normal(loc=2,scale=0.5,size=6)
display(array7)
# ---------------------------------------------
array8 = np.random.normal(loc=2,scale=0.5,size=6).reshape(2,3)
display(array8)

array11 = np.random.uniform(1,10,5)
display(array11)
# ---------------------------------
array12 = np.random.uniform(1,10,(2,3))
display(array12)

np.random.seed(3)
a = np.random.rand(3)
display(a)
np.random.seed(3)
b = np.random.rand(3)
display(b)
# --------------------------
np.random.seed()
a = np.random.rand(3)
display(a)
np.random.seed()
b = np.random.rand(3)
display(b)

c = np.arange(10)
display(c)
np.random.shuffle(c)
display(c)

d = np.random.choice([1,2,3,4], p=[0.1, 0.2, 0.3, 0.4])
display(d)

list1 = [0,0,0,0]
for i in range(100000):
  f = np.random.choice([1,2,3,4], p=[0.1, 0.2, 0.3, 0.4])
  list1[f-1] = list1[f-1] + 1
display(list1)

result_list = [value/sum(list1) for value in list1]
display(result_list)

list1 = [0,0]
for i in range(100000):
  f = np.random.choice([0,1], p=[0.5,0.5])
  list1[f] = list1[f] + 1
display(list1)

result_list = [value/sum(list1) for value in list1]
display(result_list)