I am learning Java, and am confuse on when to choose double or float for my real numbers or int. It feels like, it doesn’t matter because from my limited experience (with Java) both of them deliver the same results, but I don’t want to go further down the learning curve with Java and have a bad habit of using either messing up my code, and not having a clue as to why. So, when should you use float and double?
New to programming and curious: what's the main difference between float and double? When should I use one over the other?
Thanks! 🙏😊
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I would assume that since floats require less memory it would be the better choice. My java teacher always says use a double though.
Dealing with any type of floating point numbers is a science as they are not exact. Essentially it boils down to doubles being accurate to a greater number of decimal places and if you are using a JVM memory is not likely to be a problem.
If you are doing finance type tasks there are specific classes that should be used - the same as if the data is to be stored in a database - which will guarantee accuracy of your decimal places (up to a specified point)
Memory is cheap. Imprecision is usually less so.
Let this be a lesson to you: Just because a metric exists doesn't mean that you should try to minimize it.
Hello, I'm currently making a small matrix library in java, specifically for use with neural networks. So far I've done nearly all the functions and I used floats.
My question is if it would be better to use floats or doubles for this task, neural networks need precise values but are also very resource heavy.
Floats, doubles or write everything twice for overloading. Any ideas?
EDIT: Thanks for the answers, i finished version 1.0 today. If anyone wants to check it out feel free, just go here, hopefully it works well.
I would use doubles, then benchmark with practical data and see if the performance is acceptable. If not, try it with floats.
Besides the increased precision of doubles, more recent aspects of the JDK (like streams) (okay, maybe just streams) tend to focus on doubles, ints, and longs and generally ignore the other primitive types.
What do you mean by write everything twice? A constructor/method with a parameter of type double can accept a float.
From my textbook:
When you write a floating-point literal in your program code, Java assumes it to be of the double data type. A double value is not compatible with a float variable because a double can be much larger or smaller than the allowable range for a float. As a result, code such as the following will cause an error:
Example 1:
float number; number = 23.5; //Error!
You can force a double to be treated as a float, by suffixing it with the letter F or f. The preceding code can be rewritten in the following manner to prevent an error:
Example 2:
float number; number = 23.5F; //This will work. ===================================================
I can't figure out why example 1 produces an error. Why is 23.5 considered a double? I thought it was a float.
AFAIK, float numbers are precise up to 7 decimal digits of accuracy. 23.5 only has 1 decimal digit. What am I not understanding? I thought by typing 'float number;' you are declaring the number variable to be a float. Why would you need the extra step of adding an F?
Thanks
The Wikipedia page on it is a good place to start.
To sum up:
floatis represented in 32 bits, with 1 sign bit, 8 bits of exponent, and 23 bits of the significand (or what follows from a scientific-notation number: 2.33728*1012; 33728 is the significand).doubleis represented in 64 bits, with 1 sign bit, 11 bits of exponent, and 52 bits of significand.
By default, Java uses double to represent its floating-point numerals (so a literal 3.14 is typed double). It's also the data type that will give you a much larger number range, so I would strongly encourage its use over float.
There may be certain libraries that actually force your usage of float, but in general - unless you can guarantee that your result will be small enough to fit in float's prescribed range, then it's best to opt with double.
If you require accuracy - for instance, you can't have a decimal value that is inaccurate (like 1/10 + 2/10), or you're doing anything with currency (for example, representing $10.33 in the system), then use a BigDecimal, which can support an arbitrary amount of precision and handle situations like that elegantly.
A float gives you approx. 6-7 decimal digits precision while a double gives you approx. 15-16. Also the range of numbers is larger for double.
A double needs 8 bytes of storage space while a float needs just 4 bytes.
Why would someone even use an int or a float?
I ask this because while int does use less data, you risk overflows and also in general a double is more accurate. How significant is the amount of data saved actually that one would choose that over a double?
How significant is the amount of data saved actually that one would choose that over a double?
While i think that one of the most important points for using an int is really that it is an integer, i.e. pure with no decimals (as others have pointed out), i also wanted to address this question.
A double is twice as big as an int or float. This will not be an issue in a small program you write for a class and it won't even be an issue in many industry-level applications, but there are certainly times where doubling the amount of data that you have to transmit for no gain whatsoever (if you don't happen to need the added precision of a double) can have a huge impact. At work we often deal with the transmission of tens or hundreds of gigabytes of data. Of course, this number wouldn't be exactly twice as large if we used doubles instead of wherever possible, but it would certainly grow a substantial amount, which would certainly influence transmission times noticeably.
It is certainly fine to generally worry more about things like code readability than performance or space requirements, but there are applications where you do need to worry about size. And i don't think getting into the habit of using double "just because" is a good thing.
Most of what is said is only half correct. Remember that int/float and other primitive are represented using x amount of bits. In the days that java started off with embedded systems with limited memory thus you had to constraint how much memory your program could use to do operations and how much memory it needed to use overall. This is where good use of primitive types comes in.
Not really. If you’ve got millions of them and don’t need the precision the space saving helps.
It’s a bit like saying byte is outdated because longs exist (and there are people saying this on the internet...)
The precision of float is low enough that when using it then displaying the numeric results to the user, the user would have good reasons to be confused as the results would seem visibly incorrect. Doubles don't really have this problem, they're not exact but their precision is enough to satisfy normal users. That's why floats seem like an outdated idea.
However, if you don't display the numeric results to the user, then float's precision is likely to be good enough. Think image manipulation or rendering. Double precision is usually useless here, lost in the display capacities of our devices. And floats take half the memory and less time to compute. They're a better choice in such situations.
LibGDX is a framework mostly used for game development.
In game development you usually have to do a whole lot of number crunching in real-time and any performance you can get matters. That's why game developers usually use float whenever float precision is good enough.
The size of the FPU registers in the CPU is not the only thing you need to consider in this case. In fact most of the heavy number crunching in game development is done by the GPU, and GPUs are usually optimized for floats, not doubles.
And then there is also:
- memory bus bandwidth (how fast you can shovel data between RAM, CPU and GPU)
- CPU cache (which makes the previous less necessary)
- RAM
- VRAM
which are all precious resources of which you get twice as much when you use 32bit float instead of 64bit double.
Floats use half as much memory as doubles.
They may have less precision than doubles, but many applications don't require precision. They have a larger range than any similarly-sized fixed point format. Therefore, they fill a niche that needs wide ranges of numbers but does not need high precision, and where memory usage is important. I've used them for large neural network systems in the past, for example.
Moving outside of Java, they're also widely used in 3D graphics, because many GPUs use them as their primary format - outside of very expensive NVIDIA Tesla / AMD FirePro devices, double-precision floating point is very slow on GPUs.
TL;DR in Java a "double" is a 64-bit float and a "float" is a 32-bit float; in Python a "float" is a 64-bit float (and thus equivalent to a Java double). There doesn't appear to be a natively implemented 32-bit float in Python (I know numpy/pandas has one, but I'm talking about straight vanilla Python with no imports).
In many programming languages, a double variable type is a higher precision float and unless there was a performance reason, you'd just use double (vs. a float). I'm almost certain early in my programming "career", I banged my head against the wall because of precision issues while using floats thus I avoided floats like the plague.
In other languages, you need to type a variable while declaring it.
Java: int age=30
Python: age=30
As Python doesn't have (or require?) typing a variable before declaring it, I never really thought about what the exact data type was when I divided stuff in Python, but on my current project, I've gotten in the habit of hinting at variable type for function/method arguments.
def do_something(age: int, name: str):
I could not find a double data type in Python and after a bunch of research it turns out that the float I've been avoiding using in Python is exactly a double in Java (in terms of precision) with just a different name.
Hopefully this info is helpful for others coming to Python with previous programming experience.
P.S. this is a whole other rabbit hole, but I'd be curious as to the original thought process behind Python not having both a 32-bit float (float) and 64-bit float (double). My gut tells me that Python was just designed to be "easier" to learn and thus they wanted to reduce the number of basic variable types.
Newbie game dev here and I was looking around at some tutorials and noticed that most of them use floats for decimal values instead of doubles. From what I know, doubles have more precision that floats, so why don't they just all use doubles instead of floats?
I'm an absoulte beginner in C and I dont understand the difference. Float is for decimal numbers, but double is for decimal numbers too? I've already googled it, but I still dont understand. English isnt my first language so please could someone give me a simple explanation? Thanks! :)
Since your question is mostly about performance, this article presents you with some specific calculations (keep in mind though that this article is specific to neural networks, and your calculations may be completely different to what they're doing in the article): http://web.archive.org/web/20150310213841/http://www.heatonresearch.com/content/choosing-between-java%E2%80%99s-float-and-double
Some of the relevant material from the link is reproduced here:
Both double and float can support relatively large numbers. The upper and lower range are really not a consideration for neural networks. Float can handle numbers between 1.40129846432481707e-45 to 3.40282346638528860e+38...Basically, float can handle about 7 decimal places. A double can handle about 16 decimal places.
Matrix multiplication is one of the most common mathematical operations for neural network programming. By no means is it the only operation, but it will provide a good benchmark. The following program will be used to benchmark a double.
Skipping all the code, the table on the website shows that for a 100x100 matrix multiplication, they have a gain in performance of around 10% if they use doubles. For a 500x100 matrix multiplication, the performance loss because of using doubles is around 7%. And for a 1000x1000 matrix multiplication, that loss is around 17%.
For the small 100x100 matrix switching to float may actually decrease performance. As the size of the matrix increases, the percent gain increases. With a very large matrix the performance gain increases to 17%. 17% is worth considering.
Normally, I would use a double, because float doesn't have sufficient accuracy for many numerical use cases, and the performance difference is small enough not to matter.
As always, performance is implementation dependent so you will need to benchmark on your particular case in order to determine if it "matters" or not.
In general I have found:
- The performance difference for individual operations is pretty small, especially on 64-bit machines. Both a
floatand alongwill fit in a 64-bit machine word. Often there is zero difference. floats have a slight advantage in that they consume less memory, and this can help with reducing CPU cache pressure. I've found floats to be 30-50% faster when doing simple operations over large arrays.