5K-1 Problem 2. Write a function loss(x, q) to return Eita max(0, x¡ – x, + 1), where x is a 1darray of K floats, q is an integer with 0 < q < K – 1, and x; is the (j + 1)-th element of array x. Sample: if s = np.array( [5, 1, 3, 6]), then loss(s, 2) returns 7. (Not s[2]=3 .) 1 pass 3 def loss(x,q): 4 5 6 s = np.array([5, 1, 3, 6]) 7 loss(s, 2) 8.

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
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do NOT use any LOOPS! Do not use FOR, WHILE, ETC. Use Numpy.

**Problem 2**: Write a function `loss(x, q)` to return \(\sum_{{j=0, j \neq q}}^{{K-1}} \max(0, x_j - x_q + 1)\), where \(x\) is a 1-dimensional array of \(K\) floats, \(q\) is an integer with \(0 \leq q \leq K-1\), and \(x_j\) is the \((j + 1)\)-th element of array \(x\). 

**Sample**: If \(s = np.array([5, 1, 3, 6])\), then `loss(s, 2)` returns 7. (Note: \(s[2] = 3\).)

```python
1   pass
2   def loss(x, q):
3
4       s = np.array([5, 1, 3, 6])
5       loss(s, 2)
```

**Explanation**:

- The problem requires the implementation of a function `loss(x, q)` which computes a specific summation involving elements of the array \(x\), excluding the element at index \(q\).
- The summation involves calculating \(\max(0, x_j - x_q + 1)\) for each element \(x_j\) in the array except when \(j = q\).
- The example given sets \(x = [5, 1, 3, 6]\) and \(q = 2\) (which corresponds to the element 3 in array \(x\)). The calculation returns a result of 7.
Transcribed Image Text:**Problem 2**: Write a function `loss(x, q)` to return \(\sum_{{j=0, j \neq q}}^{{K-1}} \max(0, x_j - x_q + 1)\), where \(x\) is a 1-dimensional array of \(K\) floats, \(q\) is an integer with \(0 \leq q \leq K-1\), and \(x_j\) is the \((j + 1)\)-th element of array \(x\). **Sample**: If \(s = np.array([5, 1, 3, 6])\), then `loss(s, 2)` returns 7. (Note: \(s[2] = 3\).) ```python 1 pass 2 def loss(x, q): 3 4 s = np.array([5, 1, 3, 6]) 5 loss(s, 2) ``` **Explanation**: - The problem requires the implementation of a function `loss(x, q)` which computes a specific summation involving elements of the array \(x\), excluding the element at index \(q\). - The summation involves calculating \(\max(0, x_j - x_q + 1)\) for each element \(x_j\) in the array except when \(j = q\). - The example given sets \(x = [5, 1, 3, 6]\) and \(q = 2\) (which corresponds to the element 3 in array \(x\)). The calculation returns a result of 7.
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