len(y)),numpy.repeat(y,len(x))])array([[1,4],[2,4],[3,4],[1,5],[2,5],[3,5]])[[x0,y0]forx0inxfory0iny]# 查找元素np.where(condition,[x,y])#[x,y]为可选项,满足条件返回x,不满足条件返回y>>>np.where(a<4,a,-1)# -1 is broadcastarray([[0,1...
numpy.hsplit(ary, indices_or_sections) Split an array into multiple sub-arrays horizontally (column-wise). 数组平铺 numpy.tile(A, reps) Construct an array by repeating A the number of times given by reps. 将原矩阵横向、纵向地复制 numpy.repeat(a, repeats, axis=None) Repeat elements of an...
array, asarray, arange, eye, identity, full, full_like, zeros, zeros_like, ones, ones_like, empty, empty_like, linspace, numpy.random.RandomState.rand, numpy.random.RandomState.randn, fromfunction, fromfile numpy.array()# 将输入数据(列表、元祖、数组或其他系列类型) 转换为ndarray; numpy推断d...
# [array([[11, 12, 13, 14]]), array([[16, 17, 18, 19], # [21, 22, 23, 24]]), array([], shape=(0, 4), dtype=int32)] y = np.split(x, [1, 3], axis=1) print(y) # [array([[11], # [16], # [21]]), array([[12, 13], # [17, 18], # [22, 23]]...
numpy.repeat(a, repeats, axis=None) Parameters: Return value: repeated_array [ndarray]: Output array that has the same shape as a, except along the specified axis. Example: Repeating a scalar using numpy.repeat() >>> import numpy as np ...
numpy包含两种基本的数据类型:数组(array)和矩阵(matrix)。无论是数组,还是矩阵,都由同种元素组成。 下面是测试程序: # coding:utf-8 import numpy as np # print(dir(np)) M = 3 #---Matrix--- A = np.matrix(np.random.rand(M,M)) # 随机数矩阵 print('原矩阵:'...
numpy数组基本操作,包括copy, shape, 转换(类型转换), type, 重塑等等。这些操作应该都可以使用numpy.fun(array)或者array.fun()来调用。 Basic operations copyto(dst, src[, casting, where])Copies values from one array to another, broadcasting as necessary. ...
ptp([axis, out]) :返回指定轴方向的最大值减去最小值. put(indices, values[, mode]) :用给定的value替换矩阵本身给定索引(indices)位置的值 ravel([order]) :返回一个数组,该数组是一维数组或平数组 repeat(repeats[, axis]) :重复矩阵中的元素,可以沿指定轴方向重复矩阵元素,repeats为重复次数 ...
#Create array from image data M = np.array(img) #Display array from image data display(Image.fromarray(M)) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 1、缩小图像 def reduce_image_size_by_n(image, n): # Get the height and width of the image ...
| a.compress(condition, axis=None, out=None) | | Return selected slices of this array along given axis. | | Refer to `numpy.compress` for full documentation. | | See Also | --- | numpy.compress : equivalent function | | conj(...) | a.conj() | | Complex-conjugate all elements....