Numpy

青旅半醒 2023-07-04 04:54 10阅读 0赞

[1.基本教程 ][1._]

[2.numpy中的mean()函数--求平均值][2.numpy_mean_--]

[3.【Python】均值np.mean()，方差np.var()，标准差np.std()][3._Python_np.mean_np.var_np.std]

[4.【Python】numpy 中的 copy 问题详解][4._Python_numpy _ copy]

> **5.对numpy数组加常数的理解**
> 
>     import numpy as np
>     
>     data = np.array([1,2,3])
>     print(data+1)
> 
> 输出
> 
> \[2 3 4\]

> **6.np.exp(B) : 求e的幂次方、np.sqrt(B):求B的开方**
> 
>     import numpy as np
>     B = np.arange(3)
>     print (B)
>     print (np.exp(B))    # 打印e的幂次方，e是一个常数为2.71828
>     print (np.sqrt(B))  # 打印B里每个元素的开方
>     print(B**2)         # 对B求平方
> 
>

[7.Python fminunc 的替代方法][7.Python fminunc]

[8.np.where(y==1) 返回y=1的下标][8.np.where_y_1_ _y_1]

[9.matplotlib.pyplot.axis()与matplotlib.pyplot.axes()结构及用法][9.matplotlib.pyplot.axis_matplotlib.pyplot.axes]

> 设置定义域和值域

[10.Python-Numpy函数：np.round(),np.around(),np.floor(),np.ceil()][10.Python-Numpy_np.round_np.around_np.floor_np.ceil]

> 一np.round()函数的作用：对给定的数组进行四舍五入，可以指定精度，同np.around()

[11.plt.contour等高线绘制][11.plt.contour]

[12.numpy.random.randint用法][12.numpy.random.randint]

[12.numpy.random.uniform介绍][12.numpy.random.uniform]

> 返回ndarray，从取值空间随机取样

[1._]: https://www.runoob.com/numpy/numpy-tutorial.html
[2.numpy_mean_--]: https://blog.csdn.net/lilong117194/article/details/78397329
[3._Python_np.mean_np.var_np.std]: https://blog.csdn.net/Vici__/article/details/100126558
[4._Python_numpy _ copy]: https://blog.csdn.net/u010099080/article/details/59111207
[7.Python fminunc]: https://blog.csdn.net/csdn_inside/article/details/81558079
[8.np.where_y_1_ _y_1]: https://blog.csdn.net/qq_37354021/article/details/102907159
[9.matplotlib.pyplot.axis_matplotlib.pyplot.axes]: https://blog.csdn.net/The_Time_Runner/article/details/89888206
[10.Python-Numpy_np.round_np.around_np.floor_np.ceil]: https://blog.csdn.net/qq_41121879/article/details/103001925
[11.plt.contour]: https://blog.csdn.net/qq_42505705/article/details/88771942
[12.numpy.random.randint]: https://blog.csdn.net/u011851421/article/details/83544853
[12.numpy.random.uniform]: https://blog.csdn.net/u013920434/article/details/52507173