定义cnmda函数 def ce(a,m,n): ''' 参数: a:是一个Numpy数组 m:是第m维数组的索引 n:第m维数组的前n个元素的索引 返回值: ret: 一个numpy数组 ''' ret = 0 # 请在此添加切片的代码,实现找出多维数组a中第m个数组的前n个元素 并赋值给ret
时间: 2024-02-15 11:03:51 浏览: 179
好的,可以按照如下代码来定义cnmda函数:
import numpy as np
def cnmda(a, m, n):
ret = a[m, :n]
return ret
这个函数接受三个参数:a表示一个Numpy数组,m表示第m维数组的索引,n表示第m维数组的前n个元素的索引。函数的功能是找出多维数组a中第m个数组的前n个元素,并将其赋值给ret变量。具体实现中,我们可以使用切片的方式来实现。a[m, :n]表示选取a中第m个数组的前n个元素,然后将其赋值给ret变量,最后将ret返回即可。
相关问题
#chapter 3.svm multi classification exercise """ reference: https://www.jianshu.com/p/ba59631855a3 https://www.jianshu.com/p/ce96f1a04b72 https://blog.csdn.net/Big_Pai/article/details/89482752 """ import numpy as np import matplotlib.pyplot as plt import svm_bi_classification as svm_bi import svm_multi_classification as svm_multi def load_data(filename): with open(filename) as f: data = [] f.readline() # 跳过第一行 for line in f: line = line.strip().split() x1_f = float(line[0]) x2_f = float(line[1]) t_f = int(line[2]) data.append([x1_f, x2_f, t_f]) ret_f = np.array(data) np.random.shuffle(ret_f) return ret_f,这段代码的含义是什么
这段代码的含义是定义了一个函数load_data,用于从文件中读取数据,并将其转换为Numpy数组格式。具体来说,该函数的输入参数为文件名filename,输出为Numpy数组ret_f。在函数内部,该函数首先打开指定文件,然后跳过文件的第一行(假设该文件的第一行为表头),接着逐行读取数据,并将其转换为浮点型(x1_f、x2_f)和整型(t_f),最后将转换后的数据存储到列表data中。最后,将列表data转换为Numpy数组格式,并随机打乱数据的顺序,将其作为函数的返回值。
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