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fixed_point.md

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 # Fixed Point
 
-Fixed point arithmetic is a simple and often [good enough](good_enough.md) representation of [fractional](rational_number.md) (non-integer) numbers, as opposed to [floating point](float.md) which we consider a bad, [bloated](bloat.md) alternative (in most cases). Probably in 99% cases when you think you need floating point, fixed point is actually what you need.
+Fixed point arithmetic is a simple and often [good enough](good_enough.md) method of computer representation of [fractional](rational_number.md) numbers (i.e. numbers with higher precision than [integers](integer.md), e.g. 4.03), as opposed to [floating point](float.md) which is a more complicated way of doing this which in most cases we consider a worse, [bloated](bloat.md) alternative. Probably in 99% cases when you think you need floating point, fixed point will do just fine.
 
 Fixed point has at least these advantages over floating point:
 
 - **It doesn't require a special hardware coprocessor** for efficient execution and so doesn't introduce a [dependency](dependency.md). Programs using floating point will run extremely slowly on systems without float hardware support as they have to emulate the complex hardware in software, while fixed point will run just as fast as integer arithmetic. For this reason fixed point is very often used in [embedded](embedded.md) computers.
 - It is **easier to understand and better predictable**, less tricky, [KISS](kiss.md), [suckless](sukless.md). (Float's IEEE 754 standard is 58 pages long, the paper *What Every Computer Scientist Should Know About Floating-Point Arithmetic* has 48 pages.)
 - Is easier to implement and so **supported in many more systems**. Any language or format supporting integers also supports fixed point.
-- Isn't ugly and doesn't waste values (positive and negative zero, denormalized numbers, ...).
+- Isn't ugly and **doesn't waste values** (unlike IEEE 754 with positive and negative zero, denormalized numbers, many [NaNs](nan.md) etc.).
 
 ## How It Works
 
-Fixed point uses a fixed (hence the name) number of digits (bits in binary) for the integer part and the rest for the fractional part (whereas floating point's fractional part varies in size). I.e. we split the binary representation of the number into two parts (integer and fractional) by IMAGINING a radix point at some place in the binary representation. That's basically it.
+Fixed point uses a fixed (hence the name) number of digits (bits in binary) for the integer part and the rest for the fractional part (whereas floating point's fractional part varies in size). I.e. we split the binary representation of the number into two parts (integer and fractional) by IMAGINING a radix point at some place in the binary representation. That's basically it. Fixed point therefore spaces numbers [uniformly](uniformity.md), as opposed to floating point whose spacing of numbers is non-uniform. 
 
 So, **we can just use an integer data type as a fixed point data type**, there is no need for libraries or special hardware support. We can also perform operations such as addition the same way as with integers. For example if we have a binary integer number represented as `00001001`, 9 in decimal, we may say we'll be considering a radix point after let's say the sixth place, i.e. we get `000010.01` which we interpret as 2.25 (2^2 + 2^(-2)). The binary value we store in a variable is the same (as the radix point is only imagined), we only INTERPRET it differently.