55. What is the equivalent of enumerate for numpy arrays? (★★☆)

 arr = np.arange(9).reshape(3,3)

 for index, value in np.ndenumerate(arr):

     print(index, value)

 for index in np.ndindex(arr.shape):

     print(index, arr[index])

运行结果：

(0, 0) 0
(0, 1) 1
(0, 2) 2
(1, 0) 3
(1, 1) 4
(1, 2) 5
(2, 0) 6
(2, 1) 7
(2, 2) 8
(0, 0) 0
(0, 1) 1
(0, 2) 2
(1, 0) 3
(1, 1) 4
(1, 2) 5
(2, 0) 6
(2, 1) 7
(2, 2) 8

56. Generate a generic 2D Gaussian-like array (★★☆)

 x,y = np.meshgrid(np.linspace(-1,1,10),np.linspace(-1,1,10))

 d = np.sqrt(x*x+y*y)

 sigma,mu = 1.0,0.0

 g = np.exp(-(d-mu)**2/(2.0*sigma**2))

 print(g)

运行结果：（太长）略

57. How to randomly place p elements in a 2D array? (★★☆)

 arr = np.zeros((10,10))

 np.put(arr,np.random.choice(range(10*10),3,replace=False),25)

 print(arr)

运行结果：

[[ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
[ 0. 0. 0. 0. 0. 0. 25. 0. 0. 0.]
[ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
[ 0. 25. 0. 0. 0. 0. 0. 0. 0. 0.]
[ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
[ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
[ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
[ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
[ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
[ 0. 25. 0. 0. 0. 0. 0. 0. 0. 0.]]

58. Subtract the mean of each row of a matrix (★★☆)

 arr = np.random.randint(1,5,(5,5))

 arr2 = arr - arr.mean(axis=1,keepdims=True)

 print(arr)

 print(arr2)

运行结果：

[[3 1 4 2 2]
[1 1 1 4 4]
[1 3 2 4 2]
[4 4 1 4 3]
[3 1 3 2 1]]
[[ 0.6 -1.4 1.6 -0.4 -0.4]
[-1.2 -1.2 -1.2 1.8 1.8]
[-1.4 0.6 -0.4 1.6 -0.4]
[ 0.8 0.8 -2.2 0.8 -0.2]
[ 1. -1. 1. 0. -1. ]]

59. How to sort an array by the nth column? (★★☆)

 arr = np.random.randint(1,10,(3,3))

 print(arr)

 arr = arr[arr[:,0].argsort()]

 print(arr)

运行结果：

[[3 6 4]
[8 6 1]
[9 1 9]]
[[3 6 4]
[8 6 1]
[9 1 9]]

60. How to tell if a given 2D array has null columns? (★★☆)

 arr = np.random.randint(0,6,(3,3))

 print(arr)

 print((~arr.any(axis=1)).any())

运行结果：

[[5 4 1]
[2 4 0]
[2 4 3]]
False

61. Find the nearest value from a given value in an array (★★☆)

 arr = np.random.uniform(0,1,10)

 print(arr)

 x= 0.5

 print(arr.flat[np.abs(arr - x).argmin()])

运行结果：

[0.90305224 0.48639632 0.27508478 0.54555147 0.71661301 0.21709767
0.03780985 0.90465381 0.22589984 0.42418026]
0.4863963171374911

62. Considering two arrays with shape (1,3) and (3,1), how to compute their sum using an iterator? (★★☆)

 arr1 = np.arange(3).reshape(3,1)

 arr2 = np.arange(3).reshape(1,3)

 it = np.nditer([arr1,arr2,None])

 for x,y,z in it:

     z[...] = x + y

 print(it.operands[2])

运行结果：

[[0 1 2]
[1 2 3]
[2 3 4]]

63. Create an array class that has a name attribute (★★☆)

 class NamedArray(np.ndarray):

     def __new__(cls, array, name="no name"):

         obj = np.asarray(array).view(cls)

         obj.name = name

         return obj

     def __array_finalize__(self,obj):

         if obj is None:

             return

         self.info = getattr(obj,'name','no name')

 arr = NamedArray(np.arange(10),"range_10")

 print(arr.name)

运行结果：range_10

64. Consider a given vector, how to add 1 to each element indexed by a second vector (be careful with repeated indices)? (★★★)

 arr1 = np.ones(10)

 arr2 = np.random.randint(1,10,20)

 np.add.at(arr1,arr2,1)

 print(arr2)

 print(arr1)

运行结果：

[5 8 2 2 5 4 4 4 7 1 3 8 5 4 9 3 7 3 1 3]
[1. 3. 3. 5. 5. 4. 1. 3. 3. 2.]

65. How to accumulate elements of a vector (X) to an array (F) based on an index list (I)? (★★★)

 arr1 = np.ones(10)

 arr2 = np.random.randint(1,10,10)

 print(arr2)

 print(np.bincount(arr2,arr1))

运行结果：

[7 4 4 2 6 9 3 1 1 7]
[0. 2. 1. 1. 2. 0. 1. 2. 0. 1.]