difference

What is the difference between bottom-up and top-down?

由 送分小仙女□ 提交于 2019-11-26 02:15:40
问题 The bottom-up approach (to dynamic programming) consists in first looking at the \"smaller\" subproblems, and then solve the larger subproblems using the solution to the smaller problems. The top-down consists in solving the problem in a \"natural manner\" and check if you have calculated the solution to the subproblem before. I\'m a little confused. What is the difference between these two? 回答1: rev4: A very eloquent comment by user Sammaron has noted that, perhaps, this answer previously

What's the difference between ViewData and ViewBag?

由 核能气质少年 提交于 2019-11-26 01:06:29
问题 I saw the ViewBag in MVC 3. How\'s that different than ViewData in MVC 2? 回答1: It uses the C# 4.0 dynamic feature. It achieves the same goal as viewdata and should be avoided in favor of using strongly typed view models (the same way as viewdata should be avoided). So basically it replaces magic strings : ViewData["Foo"] with magic properties : ViewBag.Foo for which you have no compile time safety. I continue to blame Microsoft for ever introducing this concept in MVC. The name of the

What's the difference between ViewData and ViewBag?

由 独自空忆成欢 提交于 2019-11-26 00:24:28
I saw the ViewBag in MVC 3. How's that different than ViewData in MVC 2? Darin Dimitrov It uses the C# 4.0 dynamic feature. It achieves the same goal as viewdata and should be avoided in favor of using strongly typed view models (the same way as viewdata should be avoided). So basically it replaces magic strings : ViewData["Foo"] with magic properties : ViewBag.Foo for which you have no compile time safety. I continue to blame Microsoft for ever introducing this concept in MVC. The name of the properties are case sensitive. Internally ViewBag properties are stored as name/value pairs in the

Java 8: Calculate difference between two LocalDateTime

由 你。 提交于 2019-11-26 00:21:05
问题 I am trying to calculate the difference between two LocalDateTime . The output needs to be of the format y years m months d days h hours m minutes s seconds . Here is what I have written: import java.time.Duration; import java.time.Instant; import java.time.LocalDateTime; import java.time.Period; import java.time.ZoneId; public class Main { static final int MINUTES_PER_HOUR = 60; static final int SECONDS_PER_MINUTE = 60; static final int SECONDS_PER_HOUR = SECONDS_PER_MINUTE * MINUTES_PER

Differences between Oracle JDK and OpenJDK

由 匆匆过客 提交于 2019-11-25 23:35:42
问题 NOTE: This question is from 2014. As of Java 11 OpenJDK and Oracle JDK are converging. Are there any crucial differences between Oracle and OpenJDK? For example, are the garbage collection and other JVM parameters the same? Does GC work differently between the two? 回答1: Both OpenJDK and Oracle JDK are created and maintained currently by Oracle only. OpenJDK and Oracle JDK are implementations of the same Java specification passed the TCK (Java Technology Certification Kit). Most of the vendors

Get the time difference between two datetimes

由 余生颓废 提交于 2019-11-25 23:11:09
问题 I know I can do anything and some more envolving Dates with momentjs. But embarrassingly, I\'m having a hard time trying to do something that seems simple: geting the difference between 2 times. Example: var now = \"04/09/2013 15:00:00\"; var then = \"04/09/2013 14:20:30\"; //expected result: \"00:39:30\" what I tried: var now = moment(\"04/09/2013 15:00:00\"); var then = moment(\"04/09/2013 14:20:30\"); console.log(moment(moment.duration(now.diff(then))).format(\"hh:mm:ss\")) //outputs 10:39

What is the difference between size and count in pandas?

由 半世苍凉 提交于 2019-11-25 23:08:39
问题 That is the difference between groupby(\"x\").count and groupby(\"x\").size in pandas ? Does size just exclude nil ? 回答1: size includes NaN values, count does not: In [46]: df = pd.DataFrame({'a':[0,0,1,2,2,2], 'b':[1,2,3,4,np.NaN,4], 'c':np.random.randn(6)}) df Out[46]: a b c 0 0 1 1.067627 1 0 2 0.554691 2 1 3 0.458084 3 2 4 0.426635 4 2 NaN -2.238091 5 2 4 1.256943 In [48]: print(df.groupby(['a'])['b'].count()) print(df.groupby(['a'])['b'].size()) a 0 2 1 1 2 2 Name: b, dtype: int64 a 0 2
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