dev. of 7 runs, 100 loops each)12.2ms+_143μs per loop (mean+_ std. dev. of 7 runs, 100 loops each) Common Data Structures Lists 普通操作 切片 Tuples Dictionary Loops Numpy Array Operations Slicing Broadcasting Efficient Numpy Code __EOF__ 本文作者: hzyuan 本文链接: https://www...
newshape : int or tuple of ints The new shape should be compatible with the original shape. If an integer, then the result will be a 1-D array of that length. One shape dimension can be -1. In this case, the value is inferred from the length of the array and remaining dimensions...
j]`>>>a[tuple(s)]array([[2,5],[7,11]])另
https://stackoverflow.com/questions/28491230/indexing-a-numpy-array-with-a-list-of-tuples X[tuple(zip(*idx1))] X[idx2[:,0], idx2[:,1]]
b = np.array([[1, 2], [2, 3], [4, 5]]) a = np.ones_like(b) print(a) # [[1 1] # [1 1] # [1 1]] empty矩阵 Return a new array of given shape and type, without initializing entries. import numpy as np a = np.empty([2, 2]) ...
array([[0,1,2],[3,4,5]])>>>np.ones_like(x)array([[1,1,1],[1,1,1]]) 1. 2. 3. 4. 5. 6. 7. 8. zeros(shape[, dtype, order]) #根据给定的shape,和dtype生成一个由0填充的数组 例: >>>np.zeros(5)array([0.,0.,0.,0.,0.]) ...
#array([3, 6, 9]) #数组中的每个元素进行对应的四则运算。 b = a + 10 b #array([11, 12, 13]) a+b #array([12, 14, 16]) #数组的四则运算则是对应位置的元素进行四则运算 a = np.arange(10).reshape((2, 5)) a #array([[0, 1, 2, 3, 4], ...
shape : (N,) tuple of ints dtype:传递给function的参数(下标)的数据类型,默认为float。 代码语言:javascript 复制 >>>deffunc(i):returni%4+1>>>np.fromfunction(func,(10,))#下标从0到9array([1.,2.,3.,4.,1.,2.,3.,4.,1.,2.])>>>np.fromfunction(lambda i,j:i+j,(3,3),dtype=...
>>> x = np.array([2,3,1,0]) >>> x = np.array([2, 3, 1, 0]) >>> x = np.array([[1,2.0],[0,0],(1+1j,3.)]) # note mix of tuple and lists,and types >>> x = np.array([[ 1.+0.j, 2.+0.j], [ 0.+0.j, 0.+0.j], [ 1.+1.j, 3.+0.j]]) ...
· resize(): 也是改变array的形态。不同的是,resize是直接修改这个对象的,而reshape则会生成一个新的对象 flatten操作只是针对规则shape的ndarray,如果是不规则的列表可以使用自定义的flatten函数 flatten = lambda x: [y for l in x for y in flatten(l)] if type(x) in [tuple, list, np.ndarray] els...