3.1 使用random()函数生成数组 要生成多个随机数,我们可以给random()函数传递一个shape参数: importnumpyasnpfromnumpyimportrandom random_array=np.random.random((3,4))print("Random array for numpyarray.com:")print(random_array) Python Copy Output: 这将生成一个3×4的二维数组,其中每个元素都是0到1之...
array([1, 0, 0, 0, 1, 1, 0, 0, 1, 0]) >>> np.random.randint(1, size=10) array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0]) Generate a 2 x 4 array of ints between 0 and 4, inclusive: >>> np.random.randint(5, size=(2, 4)) array([[4, 0, 2, 1], [3, 2,...
3,2,2,0]])Generatea1x3arraywith3differentupperboundsnp.random.randint(1,[3,5,10])array([2,2,9])# randomGeneratea1by3arraywith3differentlowerboundsnp.random.randint([1,5,7],10)array([9,8,7])# randomGeneratea2by4arrayusingbroadcastingwithdtypeofuint8np.random.randint([1,3,5,7],[[...
均匀分布常用主要四个方法,表示[0, 1)之间均匀分布的rand和random,表示[low, high)之间的uniform,随机整数randint a、服从[0, 1)之间的均匀分布: numpy.random.rand(d0, d1, ..., dn) b、[0, 1)之间均匀抽样: numpy.random.random(size=None) 和rand函数功能一样,参数不同而已 c、在区间[low, high...
使用numpy.random:生成随机数组的函数。 复制 # Generate a random integer between0and9rand_int=np.random.randint(10)print(rand_int) 1. 2. 3. numpy.linspace:在指定范围内生成均匀间隔的数字。 复制 # Generate an arrayof5values from0to10(inclusive)arr=np.linspace(0,10,5)# Print the arrayprint...
# Generatea random integer between 0 and 9rand_int= np.random.randint(10) print(rand_int) numpy.linspace:在指定范围内生成均匀间隔的数字。 # Generate an array of 5 values from 0 to 10 (inclusive)arr= np.linspace(0,10,5)# Print the arrayprint(arr) ...
使用numpy.random:生成随机数组的函数。 # Generate a random integer between 0 and 9 rand_int = np.random.randint(10) print(rand_int) numpy.linspace:在指定范围内生成均匀间隔的数字。 # Generate an array of 5 values from 0 to 10 (inclusive) ...
python - How to get a random number between a float range? - Stack Overflow 假设我们要得到[4,7)内的随机浮点数矩阵 import numpy.random as npr rng=npr.default_rng() size=(3,4) C=rng.uniform(4,7,size) print(f"{C=}") 1.
_array)# generate 1D array of 5 random numbers between 0 and 1float_array = np.random.rand(5)print("\n1D Random Float Array:\n",float_array)# generate 2D array of shape (3, 4) with random integersresult = np.random.randint(0,10, (3,4))print("\n2D Random Integer Array:\n",...
Each sample is an int in the range `[0, N)`. """ return self.sample(n_samples) # 从概率分布`probs`中生成随机抽样整数,范围在[0, N)之间def sample(self, n_samples=1): """ Generate random draws from the `probs` distribution over integers in [0, N). Parameters --- n_samples:...