In[1]:importnumpyasnp In[2]:np.random.seed(0)In[3]:defcompute_rec(values):...:output=np.empty(len(values))...:foriinrange(len(values)):...:output[i]=1.0/values[i]...:returnoutput...:In[4]:values=np.random.randint(1,10,size=5)In[5]:compute_rec(values)Out[5]:array([...
3. 算术操作函数 3.1 numpy.add()和 numpy.subtract()执行逐元素的加法和减法操作。 3.2 numpy.multiply()和 numpy.divide()分别执行逐元素的乘法和除法操作。 4. 统计计算函数 4.1 numpy.mean()和 numpy.median()分别计算数组元素的平均值和中位数。 4.2 numpy...
In [64]: arr Out[64]: array([[-2.0016, -0.3718], [ 1.669 , -0.4386]]) In [65]: np.tile(arr, (2, 1)) Out[65]: array([[-2.0016, -0.3718], [ 1.669 , -0.4386], [-2.0016, -0.3718], [ 1.669 , -0.4386]]) In [66]: np.tile(arr, (3, 2)) Out[66]: array([[-2.0...
(提示: array[::2]) 代码语言:javascript 代码运行次数:0 运行 AI代码解释 Z = np.zeros((8,8),dtype=int) Z[1::2,::2] = 1 Z[::2,1::2] = 1 print(Z) 20. 考虑一个 (6,7,8) 形状的数组,其第100个元素的索引(x,y,z)是什么? (提示: np.unravel_index) 代码语言:javascript 代码...
In the first example, all of the elements have been multiplied by 10. In the second, the corresponding values(相应值) in each "cell" in the array have been added to each oher. In this chapter and throughout the book, I use the standard NumPy convention of always using "import numpy ...
创建一个元素未被初始化(uninitialized “garbage” values)的数组。语法:numpy.empty(shape, dtype=float, order='C')shape,数组形状,int or tuple of intdtype,数据类型,默认为numpy.float64.order,数组填充顺序,行优先(C)或者列优先(F),默认为 C In [10]: np.empty(5) Out[10]: array([8.20939596e-...
plt.title("Image plot of $\sqrt{x^2+y^2}$ for a grid of values") plt.show() 将条件逻辑表述为数组运算 importnumpy as np#numpy.where函数是 x if condition else y的矢量化版本。fromnumpy.matlibimportrandn xarr= np.array([1.1,1.2,1.3,1.4,1.5]) ...
Z = np.ones((5,5))Z = np.pad(Z, pad_width=1, mode='constant', constant_values=0)print(Z) 1. 17.以下表达式的结果是什么?(★☆☆) 0 * np.nannp.nan == np.nannp.inf > np.nannp.nan - np.nannp.nan in set([np.nan])0.3 == 3 * 0.1print(0 * np.nan)print(np.nan =...
importnumpyasnp# Create an ndarray of integers in the range# 0 up to (but not including) 1,000,000array=np.arange(1e6)# Convert it to a listlist_array=array.tolist() Let’s compare how long it takes to multiply all the values in the array by five, using the IPythontimeitmagic fu...
Array1: [ 0 10 20 40 60 80] Array2: [10, 30, 40, 50, 70]Unique sorted array of values that are in either of the two input arrays: [ 0 10 20 30 40 50 60 70 80]Click me to see the sample solution23. Test All Elements are True...