转自Stackoverflow。备忘用。 Question I want to create a MATLAB-like cell array in Numpy. How can I accomplish this? Answer Matlab cell arrays are most similar to Pythonlists, since they can hold any object - butscipy.io.loadmatimports them as numpy object arrays - which is an array with...
axis1, axis2)Interchange two axes of an array.ndarray.TSame as self.transpose(), except that self is returned if self.ndim < 2.transpose(a[, axes])Permute the dimensions of an array.
搬运自:http://scipy.github.io/old wiki/pages/NumPy_for_Matlab_Users.html. 1、Introduction MATLAB和NumPy/SciPy有很多共同之处,但也有很多不同之处。创建NumPy和SciPy是为了用Python以最自然的
125, 216, 343, 512, 729])>>> a[2]8>>> a[2:5]array([ 8, 27, 64])>>> a[:6:2] = -1000 # equivalent to a[0:6:2] = -1000; from start to position 6, exclusive, set every 2nd element to -1000>>> aarray([-1000, 1, -1000, 27, -1000, 125, 216,...
If you are already familiar with MATLAB, you might find this tutorial useful to get started with Numpy. Arrays A numpy array is a grid of values, all of the same type, and is indexed by a tuple of nonnegative integers. The number of dimensions is the rank of the array; the shape ...
和MATLAB不同,*是元素逐个相乘,而不是矩阵乘法。在Numpy中使用dot来进行矩阵乘法: import numpy as np x = np.array([[1,2],[3,4]]) y = np.array([[5,6],[7,8]]) v = np.array([9,10]) w = np.array([11, 12]) # Inner product of vectors; both produce 219 print(v.dot(w))...
MATLAB文件 点之间的距离 Matplotlib 绘制图形 绘制多个图形 图像 Python Python是一种高级的,动态类型的多范型编程语言。很多时候,大家会说Python看起来简直和伪代码一样,这是因为你能够通过很少行数的代码表达出很有力的思想。举个例子,下面是用Python实现的经典的quicksort算法例子: def quicksort(arr): if len...
和MATLAB不同,*是元素逐个相乘,而不是矩阵乘法。在Numpy中使用dot来进行矩阵乘法: In [33] import numpy as np x = np.array([[1,2],[3,4]]) y = np.array([[5,6],[7,8]]) v = np.array([9,10]) w = np.array([11, 12]) # Inner product of vectors; both produce 219 print(v...
举个例子：import numpy as npa = np.array([[1,2], [3, 4], [5, 6]])bool_idx = (a > 2) # Find the elements of a that are bigger than 2; # this returns a numpy array of Booleans of the same # shape as a, where each slot of bool_idx tells # whether that ele...
bool_idx = (a > 2) # Find the elements of a that are bigger than 2; # this returns a numpy array of Booleans of the same # shape as a, where each slot of bool_idx tells # whether that element of a is > 2. print bool_idx # Prints "[[False False] ...