我用Python和Java编写了一个程序来搜索等式的最小整数解：
a ^ 5 + b ^ 5 + c ^ 5 + d ^ 5 = e ^ 5（预期输出为133 ^ 5 + 110 ^ 5 + 84 ^ 5 + 27 ^ 5 = 144 ^ 5）
直接计算功率和根（＆＃34;直接计算＆＃34;方法）或计算并存储在数组中（＆＃34;功率查找＆＃34;方法）。查看第五个权力，如n5 = fifth_power [n]。使用数组＆＃39; fifth_power`中的二进制搜索计算第五个幂根。
如果重要的话，我在NetBeans上运行它。需要：
Drupal\Core\Database\ConnectionNotDefinedException: The specified database connection is not defined: default in [error]
/Users/myusername/.kalabox/apps/canchascrd8/code/core/lib/Drupal/Core/Database/Database.php:361
Stack trace:
#0 /Users/myusername/.kalabox/apps/canchascrd8/code/core/lib/Drupal/Core/Database/Database.php(166):
Drupal\Core\Database\Database::openConnection('default', 'default')
#1 [internal function]: Drupal\Core\Database\Database::getConnection('default')
#2 /Users/myusername/.kalabox/apps/canchascrd8/code/core/lib/Drupal/Component/DependencyInjection/Container.php(254): call_user_func_array(Array,
Array)
#3 /Users/myusername/.kalabox/apps/canchascrd8/code/core/lib/Drupal/Component/DependencyInjection/Container.php(177):
Drupal\Component\DependencyInjection\Container->createService(Array, 'database')
#4 /Users/myusername/.kalabox/apps/canchascrd8/code/core/lib/Drupal/Component/DependencyInjection/Container.php(494):
Drupal\Component\DependencyInjection\Container->get('database', 1)
#5 /Users/myusername/.kalabox/apps/canchascrd8/code/core/lib/Drupal/Component/DependencyInjection/Container.php(236):
Drupal\Component\DependencyInjection\Container->resolveServicesAndParameters(Array)
#6 /Users/myusername/.kalabox/apps/canchascrd8/code/core/lib/Drupal/Component/DependencyInjection/Container.php(177):
Drupal\Component\DependencyInjection\Container->createService(Array, 'cache.backend.d...')
#7 /Users/myusername/.kalabox/apps/canchascrd8/code/core/lib/Drupal/Core/Cache/ChainedFastBackendFactory.php(85):
Drupal\Component\DependencyInjection\Container->get('cache.backend.d...')
#8 /Users/myusername/.kalabox/apps/canchascrd8/code/core/lib/Drupal/Core/Cache/CacheFactory.php(79):
Drupal\Core\Cache\ChainedFastBackendFactory->get('bootstrap')
#9 [internal function]: Drupal\Core\Cache\CacheFactory->get('bootstrap')
#10 /Users/myusername/.kalabox/apps/canchascrd8/code/core/lib/Drupal/Component/DependencyInjection/Container.php(254): call_user_func_array(Array,
Array)
#11 /Users/myusername/.kalabox/apps/canchascrd8/code/core/lib/Drupal/Component/DependencyInjection/Container.php(177):
Drupal\Component\DependencyInjection\Container->createService(Array, 'cache.bootstrap')
#12 /Users/myusername/.kalabox/apps/canchascrd8/code/core/lib/Drupal/Component/DependencyInjection/Container.php(494):
Drupal\Component\DependencyInjection\Container->get('cache.bootstrap', 1)
#13 /Users/myusername/.kalabox/apps/canchascrd8/code/core/lib/Drupal/Component/DependencyInjection/Container.php(236):
Drupal\Component\DependencyInjection\Container->resolveServicesAndParameters(Array)
#14 /Users/myusername/.kalabox/apps/canchascrd8/code/core/lib/Drupal/Component/DependencyInjection/Container.php(177):
Drupal\Component\DependencyInjection\Container->createService(Array, 'module_handler')
#15 /Users/myusername/.kalabox/apps/canchascrd8/code/core/lib/Drupal/Core/DrupalKernel.php(520):
Drupal\Component\DependencyInjection\Container->get('module_handler')
#16 /Users/myusername/.kalabox/apps/canchascrd8/code/core/lib/Drupal/Core/DrupalKernel.php(678):
Drupal\Core\DrupalKernel->preHandle(Object(Symfony\Component\HttpFoundation\Request))
#17 /usr/local/Cellar/drush/8.1.3/libexec/lib/Drush/Boot/DrupalBoot8.php(150):
Drupal\Core\DrupalKernel->prepareLegacyRequest(Object(Symfony\Component\HttpFoundation\Request))
#18 /usr/local/Cellar/drush/8.1.3/libexec/includes/bootstrap.inc(354): Drush\Boot\DrupalBoot8->bootstrap_drupal_full()
#19 /usr/local/Cellar/drush/8.1.3/libexec/commands/user/user.drush.inc(389): drush_bootstrap(5)
#20 /usr/local/Cellar/drush/8.1.3/libexec/includes/command.inc(373): drush_user_login()
#21 /usr/local/Cellar/drush/8.1.3/libexec/includes/command.inc(224): _drush_invoke_hooks(Array, Array)
#22 /usr/local/Cellar/drush/8.1.3/libexec/includes/command.inc(192): drush_command()
#23 /usr/local/Cellar/drush/8.1.3/libexec/lib/Drush/Boot/BaseBoot.php(67): drush_dispatch(Array)
#24 /usr/local/Cellar/drush/8.1.3/libexec/includes/preflight.inc(66): Drush\Boot\BaseBoot->bootstrap_and_dispatch()
#25 /usr/local/Cellar/drush/8.1.3/libexec/drush.php(12): drush_main()
有没有办法提升Python性能？我不是在寻找更好的数学（某种筛分）。我正在寻找更好的实现＆＃34;对于a，b，c，d的每个组合计算它们的一些功率，检查总和是否是完美的功率。如果是 - 打印结果＆＃34;。
预计Python运行速度比Java慢20倍吗？
Python 3.5
30. s (Python, direct)
20. s (Python, lookup)
5.6 s (Java, direct)
0.8 s (Java, lookup)
Java 8：
from array import *
import math
import time
#PYTHON, BRUTEFORCE : ~30 s
millis1 = int(round(time.time() * 1000))
keep_searching = True
a=1
result=""
while(keep_searching):
a+=1
for b in range(1,a+1):
for c in range(1,b+1):
for d in range(1,c+1):
sum=math.pow(a,5)+math.pow(b,5)+math.pow(c,5)+math.pow(d,5)
root = math.pow(sum,0.2)
e = round(root)
e5 = math.pow(e,5)
if(e5==sum):
result="{}^5 + {}^5 + {}^5 + {}^5 = {}^5".format(int(a),int(b), int(c),int(d), int(e))
keep_searching = False
millis2 = int(round(time.time() * 1000))
print(result)
print("Found solution in {} ms".format(millis2-millis1))
#PYTHON, PRECOMPUTE POWERS: ~20 s
millis3 = int(round(time.time() * 1000))
#fifth_power #175 is enough
size=176
fifth_power = [None] * size
for i in range(size):
fifth_power[i]=long(math.pow(i,5))
millis4 = int(round(time.time() * 1000))
#returns value if it is a perfect power (32 returns 2)
#returns -1 if between perfect powers, -2 if greater than max value in array, -3 if smaller than min value in array
def check_perfect_power(number, min, max, fifth_power):
current=int((min+max)/2)
while(max>=min):
if(number==fifth_power[current]):
return current
elif(number>fifth_power[current]):
min=current+1
current=int((max+min)/2)
else:
max=current-1
current=int((max+min)/2)
if(min>=len(fifth_power)):
return -2
if(max<0):
return -3
return -1
keep_searching = True
a=0
result=""
while(keep_searching):
a+=1
for b in range(1,a+1):
for c in range(1,b+1):
for d in range(1,c+1):
mymax=min(int(a*1.32)+1, size-1)
e=check_perfect_power(fifth_power[a]+fifth_power[b]+fifth_power[c]+fifth_power[d], a, mymax, fifth_power)
if(e>0):
result="{}^5 + {}^5 + {}^5 + {}^5 = {}^5".format(int(a),int(b), int(c),int(d), int(e))
keep_searching = False
millis5 = int(round(time.time() * 1000))
print(result)
print("Populated in {} ms, find solution in {} ms".format(millis4-millis3,millis5-millis4))
答案 0 :(得分：1)
from array import *
import time
import numpy as np
#PYTHON, BRUTEFORCE : ~30 s
millis1 = int(round(time.time() * 1000))
keep_searching = True
a = 1
result = ""
while(keep_searching):
a += 1
a_pow = a ** 5
for b in xrange(1, a+1):
b_pow = b ** 5
for c in xrange(1, b+1):
c_pow = c ** 5
for d in xrange(1, c+1):
d_pow = d ** 5
sum_pow = a_pow + b_pow + c_pow + d_pow
root = sum_pow ** 0.2
e = round(root)
e5 = e ** 5
if(e5 == sum_pow):
result="{}^5 + {}^5 + {}^5 + {}^5 = {}^5".format(a, b, c, d, e)
keep_searching = False
millis2 = int(round(time.time() * 1000))
print(result)
print("Found solution in {} ms".format(millis2-millis1))
Python 2.7，包含一些代码优化
133 ^ 5 + 110 ^ 5 + 84 ^ 5 + 27 ^ 5 = 144.0 ^ 5 在8333 ms找到解决方案
从CPU到CPU可能有点不同。
答案 1 :(得分：1)
如何改进java代码？
int size = 200;
long[] pow5 = new long[size];
for (int i = 1; i < size; ++i)
{
long sqr = i * i;
pow5[i] = sqr * sqr * i;
}
for (int a = 1; a < size; ++a)
{
for (int b = 1; b <= a; ++b)
{
for (int c = 1; c <= b; ++c)
{
int e = a + 1;
for (int d = 1; d <= c; ++d)
{
long sum = pow5[a] + pow5[b] + pow5[c] + pow5[d];
while(pow5[e] < sum){ e++; }
if (pow5[e] == sum)
{
System.out.println(a + "^5 + " + b + "^5 + " + c + "^5 + " + d + "^5 = " + e + "^5");
return;
}
}
}
}
}