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ã衚çŸãããŠãããšèšããŸãã |
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import cv2
# 顿€åºåšã®èªã¿èŸŒã¿
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
# ç»åã®èªã¿èŸŒã¿
img = cv2.imread('face.jpg')
# ã°ã¬ãŒã¹ã±ãŒã«ã«å€æ
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# 顿€åº
faces = face_cascade.detectMultiScale(gray, 1.1, 4)
# é¡ã«ç©åœ¢ãæç»
for (x, y, w, h) in faces:
cv2.rectangle(img, (x, y), (x+w, y+h), (255, 0, 0), 2)
# çµæã衚瀺
cv2.imshow('img', img)
cv2.waitKey(0)
cv2.destroyAllWindows()
``` |
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ã®å¶æ°ã®èŠçŽ ã®ç·åãæ±ããŠãã ããã | ```python
numbers = [1, 2, 3, 4, 5]
total = 0
for num in numbers:
total += num
print(total)
``` | ```python
numbers = [1, 2, 3, 4, 5]
total = 0
for num in numbers:
if num % 2 == 0:
total += num
print(total)
``` |
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```
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```
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```
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```
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```
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1. ããŒããã¹å€§åŠïŒDartmouth CollegeïŒ
2. ãã©ãŠã³å€§åŠïŒBrown UniversityïŒ
3. ããªã³ã¹ãã³å€§åŠïŒPrinceton UniversityïŒ
4. ã€ã§ãŒã«å€§åŠïŒYale UniversityïŒ |
以äžã®SQLã¯ãšãªãå®è¡ããã³ãŒããæžããŸãããã | ã¯ãšãª:
```sql
SELECT * FROM employee WHERE salary > 5000 ORDER BY salary DESC;
```
ããŒã¿ããŒã¹å: 'company'
ããŒãã«å: 'employee' | ```python
import sqlite3
conn = sqlite3.connect('company.db')
cursor = conn.cursor()
query = '''SELECT * FROM employee WHERE salary > 5000 ORDER BY salary DESC;'''
cursor.execute(query)
result = cursor.fetchall()
conn.close()
``` |
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EAVã¢ãã«ã§ã¯ããã¹ãŠã®Entityãšããã«é¢é£ãã屿§ãæ ŒçŽããããã«1ã€ã®ããŒãã«ã䜿çšãããŸããåãšã³ãã£ãã£ã¯äžæã®èå¥åã§èå¥ããã屿§ã¯ããŒãšå€ã®ãã¢ãšããŠåãããŒãã«ã«æ ŒçŽãããããã®ã¢ãã«ã§ã¯ãæ°ããã¿ã€ãã®ãšã³ãã£ãã£ãé¢é£ããããã£ãæè»ã«è¿œå ããããšãã§ããã¿ã€ãåºæã®åã«ã¯ NOT NULL å¶çŽãé©çšãããŸãã
以äžã¯ãEAV ã¢ãã«ã䜿çšããŠç°ãªãã¿ã€ãã® Event Entities ãæ ŒçŽããäŸã§ãïŒ
```
CREATE TABLE entities (
id SERIAL PRIMARY KEYã
type VARCHAR(50) NOT NULLã
title VARCHAR(100) NOT NULLã
description TEXT NOT NULLã
attribute_key VARCHAR(50) NOT NULLã
屿§å€ TEXT
);
```
ã€ãã³ãã®äŸã§ã¯ã以äžã®ããã«ã³ã¡ã³ãã€ãã³ãã®ã¬ã³ãŒãã远å ããŸãïŒ
```
INSERT INTO entities (type, title, description, attribute_key, attribute_value)
VALUES ('comment', 'My Comment Title', 'This is a comment', 'topic', 'My Comment Topic')ã
('comment', 'ç§ã®ã³ã¡ã³ãã¿ã€ãã«', 'ããã¯ã³ã¡ã³ãã§ã', 'likes', '10')ïŒ
```
ãã®äŸã§ã¯ããã¹ãŠã®ãšã³ãã£ãã£ãã¿ã€ããã¿ã€ãã«ã説æãæã£ãŠããŸããããã«ãCommentã€ãã³ãã«ã¯ãtopicãšlikesãšãã2ã€ã®å±æ§ã远å ãããŠããŸãããããã®å±æ§ã¯ããŒãšå€ã®ãã¢ãšããŠåãããŒãã«ã«æ ŒçŽãããŸããtypeãã£ãŒã«ãã«ãã£ãŠãç°ãªãã¿ã€ãã®Entityãåºå¥ããããšãã§ããattribute_keyãã£ãŒã«ããšattribute_valueãã£ãŒã«ãã«ãã£ãŠãã¿ã€ãåºæã®å±æ§ãæ ŒçŽããããšãã§ããŸãã
ãã¹ãŠã®ãšã³ãã£ãã£ãé«éãã€å¹ççã«ã¯ãšãªããã«ã¯ãæ¥ä»ãã£ãŒã«ãã®ã€ã³ããã¯ã¹ã䜿çšããŸãã以äžã¯ãæ¥ä»ã§ãœãŒãããããã¹ãŠã®ãšã³ãã£ãã£ãæ€çŽ¢ããã¯ãšãªã®äŸã§ãïŒ
```
SELECT id, type, title, description, attribute_key, attribute_value
FROM ãšã³ãã£ãã£
ORDER BY dateïŒ
```
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èŠããªããããããŒã¿ããŒã¹ã®ããŠã³ã¿ã€ã ãªãã«ç°¡åã«æ¡åŒµããããšãã§ããŸãã
EAVã¢ãã«ã«ã¯å©ç¹ããããŸãããæ¬ ç¹ããããŸããæœåšçãªåé¡ã® 1 ã€ã¯ããã®ã¢ãã«ã¯åŸæ¥ã®ãªã¬ãŒã·ã§ãã«ã¢ãã«ãããã¯ãšãªãä¿å®ãé£ãããªãå¯èœæ§ããã ããšã§ããç¹ã«ãè€æ°ã®ã¿ã€ãã®ãšã³ãã£ãã£ããã®å±æ§ãå«ãè€éãªã¯ãšãªã®å Žåã¯ãªãããã§ããããã«ãEAV ã¢ãã«ã§ã¯ããŒãã«å
ã®ã¬ã³ãŒãæ°ãå€ããªããæ³šææ·±ã管çããªããšããã©ãŒãã³ã¹ã«åœ±é¿ããå¯èœæ§ããããŸãã |
ããã«ã¡ã¯ãIMDBæäœè©äŸ¡6.8ã®å®å®æ¢æ»ã«é¢ããæ ç»ã5æ¬ç޹ä»ããŠããããŸãã? | null | ãã¡ãããåãã§ãæäŒãããããŸãïŒ IMDbã®è©äŸ¡ã6.8以äžã§ãå®å®æ¢æ»ã«é¢ããæ ç»ã5æ¬éžã³ãŸããã
### 1. 'ãšã€ãªã¢ã³: ã³ãŽã§ãã³ã' (2017)
è©äŸ¡: 6.6/10
### 2. 'ã€ãªã³' (2015)
è©äŸ¡: 6.3/10
### 3. 'ããªããã£ã³ã°ã»ã©ã€ã' (2009)
è©äŸ¡: 6.2/10
### 4. 'ãšã€ãªã¢ã³vs.ãã¬ãã¿ãŒ' (2004)
è©äŸ¡: 6.1/10
### 5. 'ãã£ãŒãã»ã€ã³ãã¯ã' (1998)
è©äŸ¡: 6.1/10 |
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ããã°ãã³ã¯ãåå人éãååç¬ã§äœãããèŠå¯å®ã§ããžã§ãŒãžãšããååã®å°å¹Žã«ãã£ãŠäœãããŸããããžã§ãŒãžã¯åŠæ ¡ã®ãããã£åã«èŠãããããŠããŸãããã圌ã¯ç¬ãšäººéã®åãçµã¿åãããã¹ãŒããŒããŒããŒãäœãåºãããšã§ããã®åé¡ã«ç«ã¡åãããŸãããããã°ãã³ã¯ãã¹ãŒããŒããŒããŒã®åãæã¡ãªããããæã«ã¯åŒ±ç¹ãæã€ããšããããŸãããã®ã·ãªãŒãºã¯ã³ã¡ãã£ãšã¢ã¯ã·ã§ã³ãèåãããã¹ã¿ã€ã«ã§æãããåäŸãã¡ã«äººæ°ããããŸãã |
3å
åŒã§ç¶ããã®çžç¶ãèªåã ãå€ããªãããã«ããæ¹æ³ | null | ç§ã¯ãçšç士ã§ã¯ãªãã®ã§çšéã«é¢ããçžè«ã«ãçãããããšã¯ã§ããŸããããå®¶æéã§åå話ãåãããªãããäžã§ããè¿ãã®çšç士ãåœçšåºã«ãçžè«ãã ããã |
ãã€ãµã³ã¯2ã€ã®6é¢ã®ãµã€ã³ãã転ãããŸãã圌ãæåã®ãã€ã§3æªæºã2çªç®ã®ãã€ã§3ãè¶
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±éã®åæ°ãšããŠè¡šçŸããŸãã | null | ãµã€ã³ãã¯ç¬ç«ããŠããã®ã§ã確çãæããããšãã§ããŸãã<llm-code>
# there are 6 outcomes and two dice
num_outcomes = 6
num_dice = 2
# the probability to roll a number less than 3
prob_less_than_3 = 2/6
# the probability to roll a number greater than 3
prob_greater_than_3 = 3/6
# the probability to roll a number less than 3 and a number greater than 3
prob_less_than_3_and_greater_than_3 = prob_less_than_3 * prob_greater_than_3
prob_less_than_3_and_greater_than_3
</llm-code><llm-code-output>
0.1666666666666666
</llm-code-output>
çãã¯$ \\ boxed {1/6} $ã§ãã |
次ã®CSVãã¡ã€ã«ãæ±ã颿°ãäœæãã'age'åã®å¹³åå€ãèšç®ããŠè¿ãããã«ããªãããCSVãã¡ã€ã«ã®ãã¹ã¯"example.csv"ãšããŸãã | ```python
import csv
# CSVãã¡ã€ã«ãã¹
file_path = "example.csv"
``` | ```python
def calculate_average_age(file_path):
with open(file_path, newline='') as csvfile:
reader = csv.DictReader(csvfile)
ages = [int(row['age']) for row in reader]
average_age = sum(ages) / len(ages)
return average_age
print(calculate_average_age(file_path))
```
åºå:
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å ±ã®äžéšã倱ãå¯èœæ§ããããŸããã§ããããæ¯çãåçŽåããåã«ããã®æå³ãšäœ¿ãæ¹ãããçè§£ããããšã倧åã§ãã
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以äžã®èª¬æã«åã£ããã®ããã¯ã©ã·ã«ã«ããžã£ãºãããã¯ãããããR&Bãããããããããšã¬ã¯ããããã¯é³æ¥œã®äžããéžãã§ãã ããã
説æïŒãã³ãã®éããèžãããšãã§ãã鳿¥œã§ãã | ãã³ãã®éããèžãããšãã§ãã鳿¥œã§ãã | ãããããã |
æ ç»é€šã«ã¯250åžããããŸãããã±ããã®è²»çšã¯å€§äºº6ãã«ãåäŸã4ãã«ã§ããåå Žã¯ãã£ã±ãã§ã188人ã®åäŸãããŸãããã®æ ç»ã»ãã·ã§ã³ã®ãã±ããã®ç·åå
¥ã¯ãããã§ããïŒ | null | Pythonã³ãŒãã䜿çšããŠãã®åé¡ã解決ããŸãããã<llm-code>
total_seats = 250
cost_for_adults = 6
cost_for_children = 4
number_of_children = 188
number_of_adults = total_seats - number_of_children
revenue_from_adults = number_of_adults * cost_for_adults
revenue_from_children = number_of_children * cost_for_children
total_revenue = revenue_from_adults + revenue_from_children
total_revenue
</llm-code><llm-code-output>
1124
</llm-code-output>
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äžããããJSONãªããžã§ã¯ãããPythonã®èŸæžã«å€æããªããã | ```json
{
"name": "John",
"age": 30,
"city": "New York"
}
``` | ```python
import json
json_object = """
{
"name": "John",
"age": 30,
"city": "New York"
}
"""
dict_object = json.loads(json_object)
print(dict_object)
```
åºå:
```
{'name': 'John', 'age': 30, 'city': 'New York'}
``` |
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print("Hello, World!")
``` |
äžããããããã¹ãå
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ãžã®ç§»èšãæåŠããŸããããã®éºè·¡ã¯ãããŒãã®æŽå²ãç¥ãéèŠãªè³æã§ããããã§ãã | ["å¯è±ª", "éºè·¡", "ç³é ã", "åºå Ž", "åžåœ¹æ", "è³æ"] |
SQLã®VIEWãšã¯ïŒ | null | ãã¥ãŒãšã¯ãã¯ãšãªã®çµæãæ ŒçŽããä»®æ³çãªããŒãã«ã®ããšã§ãããã¥ãŒã䜿çšãããšãã¯ãšãªã®äžéšãåå©çšããããã³ãŒããæŽçãããããããšãã§ããŸãããã¥ãŒã®äŸã¯ä»¥äžã®ããã«ãªããŸãïŒ
``sql
CREATE VIEW [Brazil Customers] AS
SELECT CustomerName, ContactName
FROM Customers
WHERE Country = 'Brazil'ïŒ
```
ãã®ã¯ãšãªã¯ãã©ãžã«ããå
šãŠã®é¡§å®¢ãéžæãããã¥ãŒ`[Brazil Customers]`ã«æ ŒçŽããŸãããã¥ãŒã¯å®éã®ããŒãã«ã®ããã«åãåãããããšãã§ããŸãïŒ
``sql
SELECT * FROM [Brazil Customers] ORDER BY CustomerName LIMIT 5ïŒ
```
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ãã¥ãŒãæŽæ°ããããšãã§ããŸãïŒ
``sql
CREATE OR REPLACE VIEW [Brazil Customers] AS
SELECT CustomerName, ContactName, City
FROM Customers
WHERE Country = 'Brazil'ïŒ
```
ãŸãã¯åé€ããŠãã ããã
``sql
DROP VIEW [ãã©ãžã«é¡§å®¢]ïŒ
``` |
äžããããæç« ã®ææ³ãä¿®æ£ããæå³ãå€ããªããŸãŸãé·ããççž®ããŠãã ããã | ç§ãã¡ã®äŒç€Ÿã¯ãæ°ããäºæ¥ãå§ããããšããŠããŸããããããåã«ã¯ãŸã 詊ããŠããªãæ°ãããã®ããçµç¹ã®ã¡ã³ããŒã«èª¬æããããšãé£ãããæéãããããšèããããŠããŸãã | ç§ãã¡ã®äŒç€Ÿã¯ãæ°ããäºæ¥ãå§ããããšããŠããŸãããããããŸã 詊ããŠããªãæ°ãããã®ããçµç¹ã®ã¡ã³ããŒã«èª¬æããããšãé£ãããæéãããããšèããããŠããŸãã |
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x = Symbol('x')
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simplified_equation = equation.rewrite(Pow)
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# Simplify the solution in fractional form
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print(fractional_solution)
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# æå€§å€ãæã€è¡ãåãåºã
max_row = data[-1]
print(max_row)
``` |
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ãªååžãæã€ã¢ãžã¥ãŒã«ã§ãã
```python
import numpy as np
from scipy.stats import uniform
```
`uniform.rvs`颿°ã䜿çšããŠããŠããã©ãŒã ååžã®ä¹±æ°åãçæãã颿°ãäœæããŸãã`size`åŒæ°ã§ä¹±æ°åã®ãµã€ãºãæå®ã§ããŸãã
```python
def generate_random_numbers(size):
return uniform.rvs(size=size)
```
`generate_random_numbers(10)` ã®ããã«å®è¡ãããšã10åã®ä¹±æ°åãè¿ãããŸãã
ä»ã®ååžã®ä¹±æ°åãçæã§ããããã«ããŸãã
```python
def generate_random_numbers(size, distribution='uniform'):
if distribution == 'uniform':
return uniform.rvs(size=size)
elif distribution == 'normal':
return norm.rvs(size=size)
elif distribution == 'exponential':
return expon.rvs(size=size)
else:
raise ValueError("Invalid distribution type")
```
`generate_random_numbers(10, 'normal')`ã®ããã«åŒã³åºãããšãã§ããŸãã
ã©ã³ãã ãªæŽæ°åãçæããããã« `numpy` ã® `random.randint` ã䜿çšããããšãã§ããŸãã
```python
def generate_random_integers(size, min_val=0, max_val=100):
return np.random.randint(low=min_val, high=max_val, size=size)
```
`generate_random_integers(10)` ã§10åã®ä¹±æ°åãçæãããŸãã
ã¢ã³ãã«ã«ããµã³ããªã³ã°ã¯åçŸæ§ãéèŠãªå ŽåããããŸãããã®ããã `np.random.seed` ã䜿ã£ãŠä¹±æ°çæã®ããã®ã·ãŒãå€ãèšå®ããããšãã§ããŸãã
```python
np.random.seed(42)
```
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``` |
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```
x = 5
y = 10
if x < y:
print("x is less than y")
``` | äžèšã®ããã°ã©ã ãå®è¡ããçµæãæ£åžžã«åäœããŸããã
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jump_speed = 1 # jumps per second
seconds_in_minute = 60
minutes_in_song = 3.5
number_of_songs = 10
total_time_for_songs = number_of_songs * minutes_in_song
number_of_jumps = total_time_for_songs * jump_speed * seconds_in_minute
number_of_jumps
</llm-code><llm-code-output>
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</llm-code-output>
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for i in range(10):
print(i)
i = i + 1
``` | ãã®ã³ãŒãã«åé¡ã¯ãªãã10åã«ãŒãããŠ0ãã9ãŸã§æ°å€ã衚瀺ããŸãããã ãã`i = i + 1`ã¯äžèŠã§ãã`range(10)`ã¯0ãã9ãŸã§ã®æ°å€ãçæããã®ã§ã`i`ãæç€ºçã«ã€ã³ã¯ãªã¡ã³ãããå¿
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<?xml version="1.0" encoding="UTF-8"?>
<bookstore>
<book category="fiction">
<title lang="en">Harry Potter</title>
<author>J K. Rowling</author>
<year>1997</year>
<price>29.99</price>
</book>
</bookstore>
``` | ```python
import xml.etree.ElementTree as ET
xml_data = """
<?xml version="1.0" encoding="UTF-8"?>
<bookstore>
<book category="fiction">
<title lang="en">Harry Potter</title>
<author>J K. Rowling</author>
<year>1997</year>
<price>29.99</price>
</book>
</bookstore>
"""
root = ET.fromstring(xml_data)
print(root.tag)
``` |
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Pythonã³ãŒããèšè¿°ããŠãã ããããã®ã³ãŒãã§ã¯ãäžããããXMLããŒã¿ããç¹å®ã®èŠçŽ ãæœåºãããã®ããŒã¿ãCSV圢åŒã§ãã¡ã€ã«ã«ä¿åãã颿°ãå®çŸ©ããŠããŸãã | ```xml
<root>
<data>
<value1>1</value1>
<value2>2</value2>
</data>
<data>
<value1>3</value1>
<value2>4</value2>
</data>
</root>
``` | ```python
import xml.etree.ElementTree as ET
import csv
def xml_to_csv(xml_string, csv_file):
root = ET.fromstring(xml_string)
data_list = []
for data in root.findall('data'):
value1 = data.find('value1').text
value2 = data.find('value2').text
data_list.append((value1, value2))
with open(csv_file, 'w', newline='') as file:
writer = csv.writer(file)
writer.writerows(data_list)
xml_string = "<root><data><value1>1</value1><value2>2</value2></data><data><value1>3</value1><value2>4</value2></data></root>"
xml_to_csv(xml_string, 'output.csv')
``` |
次ã®pythonã³ãŒãããšã©ãŒãèµ·ãããŠããçç±ãšããšã©ãŒãä¿®æ£ããããã®ã³ãŒããèšå
¥ããŠãã ããã | ```python
def sum_of_numbers(n):
total = 0
for i in range(0, n):
total += i
print(total)
sum_of_numbers("10")
``` | ãã®ã³ãŒãã§ã¯ã颿°sum_of_numbersãæŽæ°ã§ã¯ãªãæååã§åŒã³åºãããŠããŸãããã®åé¡ãä¿®æ£ããããã«ã¯ã颿°ãåŒã³åºãè¡ã以äžã®ããã«å€æŽããå¿
èŠããããŸãã
```python
sum_of_numbers(10)
``` |
äžããããææ
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äºçªç®ã®åŒããy\*2 = xãã¯ããyã2åãããxã«ãªããããšãæå³ããŸãã
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## æé 1: ææã®æºå
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- ç
## æé 2: ã¢ã€ã©ã€ããŒæ¶²ã®äœæ
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## æé 3: ã¢ã€ã©ã€ããŒã®å®æ
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2次æ¹çšåŒãè§£ãããšãã§ããMIPSã¢ã»ã³ããªããã°ã©ã ãäœæããã | null | .data
a: .float 1.0
b: .float -3.0
c: .float 2.0
result1: .float 0.0
result2: .float 0.0
four: .float 4.0
two: .float 2.0
ããã¹ã
.globl ã¡ã€ã³
ã¡ã€ã³ïŒ
# aãbãcã®å€ãããŒããã
lwc1 $f0, a
lwc1 $f1, b
lwc1 $f2, c
# å€å¥åŒ (b^2 - 4ac) ãèšç®ãã
mul.s $f3, $f1, $f1
mul.s $f4, $f0, $f2
lwc1 $f5, 4
mul.s $f4, $f4, $f5
sub.s $f3, $f3, $f4
# sqrt(discriminant) ãèšç®ãã
sqrt.s $f3, $f3
# 2ã€ã®çµæãèšç®ãã: (-b ± sqrt(discriminant))/ 2a
neg.s $f1, $f1
lwc1 $f5, 2
div.s $f5, $f1, $f5
add.s $f6, $f1, $f3
sub.s $f7, $f1, $f3
div.s $f6, $f6, $f0
div.s $f7, $f7, $f0
# çµæãã¡ã¢ãªã«ä¿å
swc1 $f6, result1
swc1 $f7, result2
# ããã°ã©ã ãçµäºãã
li $v0, 10
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pig_1 = 2
pig_2 = 2 * pig_1
pig_3 = pig_2 + 3
# total number of cups of food needed
total_cups = pig_1 + pig_2 + pig_3
total_cups
</llm-code><llm-code-output>
13
</llm-code-output>
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