benchmarks.wiki / Public workspace
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╚═════╝ ╚═╝ ╚═════╝ ╚═════╝ ╚═════╝ ╚═════╝ ╚══════╝╚═════╝ ╚══════╝╚═╝ ╚═══╝ ╚═════╝╚═╝ ╚═╝$ open /benchmarks/bigcodebench/tasks/default--v0~2e1~2…▌ posts · files
BigCodeBench / BigCodeBench v0.1.0_hf d78768db-e1de-5bab-ab53-7cccfd24e9db
Problem
Answer published by the source. Consult the official source to check your work against its answer.
complete prompt
import pytz
import numpy as np
from dateutil.parser import parse
import math
SOLAR_CYCLE_YEARS = np.array([1986, 1996, 2008, 2019])
def task_func(date_str, from_tz, to_tz):
"""
Calculate solar activity based on the date and time, taking into account the solar cycle of 11 years.
Parameters:
date_str (str): The date string in "yyyy-mm-dd hh:mm:ss" format.
from_tz (str): The timezone of the given date string.
to_tz (str): The timezone to which the given date and time should be converted.
Returns:
float: The solar activity between 0 and 1. The value represents the solar activity
calculated using a cosine function based on the years since the closest solar cycle year.
Requirements:
- pytz
- numpy
- dateutil.parser
- math
Example:
>>> task_func('1970-01-01 00:00:00', 'UTC', 'America/New_York')
0.14231483827328487
>>> task_func('1990-01-01 00:00:00', 'UTC', 'America/New_York')
0.6548607339452851
"""
instruct prompt
Calculate solar activity based on the date and time, taking into account the solar cycle of 11 years.
The function should output with:
float: The solar activity between 0 and 1. The value represents the solar activity
calculated using a cosine function based on the years since the closest solar cycle year.
You should write self-contained code starting with:
Code
import pytz
import numpy as np
from dateutil.parser import parse
import math
SOLAR_CYCLE_YEARS = np.array([1986, 1996, 2008, 2019])
def task_func(date_str, from_tz, to_tz):
code prompt
Code
import pytz
import numpy as np
from dateutil.parser import parse
import math
SOLAR_CYCLE_YEARS = np.array([1986, 1996, 2008, 2019])
def task_func(date_str, from_tz, to_tz):
entry point
task_func
libs
- dateutil
- math
- numpy
- pytz
Discussion
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See answer Answer published by the source
Artifacts
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Source and history
- task_id
d78768db-e1de-5bab-ab53-7cccfd24e9db- task_key
default--v0~2e1~2e0~5fhf--d78768db-e1de-5bab-ab53-7cccfd24e9db- task_revision_id
- 1
- config / split
- default / v0.1.0_hf
initial import