Top Related Projects
The fundamental package for scientific computing with Python.
A computer algebra system written in pure Python
SciPy library main repository
matplotlib: plotting with Python
Statsmodels: statistical modeling and econometrics in Python
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Quick Overview
Math as Code is a GitHub repository that provides a reference guide for mathematical symbols and their equivalent representations in code. It aims to bridge the gap between mathematical notation and programming languages, making it easier for developers to translate mathematical concepts into code.
Pros
- Helps developers understand and implement mathematical concepts in code
- Covers a wide range of mathematical symbols and their programming equivalents
- Provides examples in multiple programming languages
- Regularly updated and maintained by the community
Cons
- Not a comprehensive guide for all mathematical concepts
- May not cover all programming languages or frameworks
- Some explanations might be too brief for complex mathematical concepts
- Requires basic understanding of both mathematics and programming
Code Examples
This project is not a code library but rather a reference guide. Therefore, there are no specific code examples to provide. Instead, the repository offers explanations and comparisons between mathematical notation and code representations.
Getting Started
As this is a reference guide and not a code library, there are no specific getting started instructions. Users can simply visit the GitHub repository and browse the content to find the information they need. The guide is organized into sections based on different mathematical concepts, making it easy to navigate and find relevant information.
Competitor Comparisons
The fundamental package for scientific computing with Python.
Pros of numpy
- Comprehensive numerical computing library with extensive functionality
- Highly optimized for performance, utilizing C and Fortran implementations
- Widely used in scientific computing, data analysis, and machine learning
Cons of numpy
- Steeper learning curve due to its extensive API and functionality
- Larger codebase and installation size compared to lightweight alternatives
- May be overkill for simple mathematical operations or small projects
Code comparison
math-as-code:
# No direct code implementation, focuses on mathematical notation explanations
numpy:
import numpy as np
# Create an array and perform operations
arr = np.array([1, 2, 3, 4, 5])
result = np.sum(arr) + np.mean(arr)
Summary
math-as-code is a documentation-focused repository that explains mathematical concepts using code notation, while numpy is a full-fledged numerical computing library. math-as-code serves as an educational resource for understanding mathematical concepts in programming terms, whereas numpy provides practical tools for numerical computations and data manipulation in Python.
math-as-code is more suitable for learning and understanding mathematical concepts, while numpy is essential for implementing complex numerical operations and algorithms in real-world applications.
A computer algebra system written in pure Python
Pros of SymPy
- Comprehensive symbolic mathematics library with extensive functionality
- Active development and large community support
- Integrates well with other scientific Python libraries
Cons of SymPy
- Steeper learning curve for beginners
- Can be slower for complex computations compared to specialized tools
- Requires Python environment and dependencies
Code Comparison
math-as-code:
// Summation
sum = 0
for (let i = 1; i <= n; i++) {
sum += i
}
SymPy:
from sympy import symbols, summation
n = symbols('n')
sum = summation(n, (n, 1, n))
Summary
math-as-code is a GitHub repository that provides a reference for mathematical notation in code form, primarily using JavaScript. It's more of an educational resource than a functional library.
SymPy, on the other hand, is a full-fledged symbolic mathematics library for Python. It offers a wide range of mathematical operations and is actively maintained by a large community.
While math-as-code is excellent for learning how to translate mathematical concepts into code, SymPy provides practical tools for solving complex mathematical problems programmatically.
SciPy library main repository
Pros of scipy
- Comprehensive scientific computing library with a wide range of mathematical functions and algorithms
- Actively maintained with regular updates and a large community of contributors
- Extensive documentation and integration with other scientific Python libraries
Cons of scipy
- Steeper learning curve for beginners due to its extensive functionality
- Larger package size and potential performance overhead for simple mathematical operations
- Requires installation and management of dependencies
Code comparison
math-as-code:
// Summation
const sum = [1, 2, 3, 4].reduce((a, b) => a + b, 0);
scipy:
import numpy as np
# Summation
sum = np.sum([1, 2, 3, 4])
Summary
math-as-code is a GitHub repository that provides a reference for mathematical notation in code form, primarily focusing on JavaScript. It serves as an educational resource for developers to understand mathematical concepts in programming.
scipy is a robust scientific computing library for Python, offering a wide range of mathematical tools and algorithms. It's suitable for complex scientific computations and data analysis tasks.
While math-as-code is more of a learning resource, scipy is a practical tool for implementing advanced mathematical operations in Python projects. The choice between them depends on the specific needs of the project and the developer's familiarity with the respective languages and libraries.
matplotlib: plotting with Python
Pros of matplotlib
- Comprehensive plotting library with extensive functionality
- Well-established, mature project with large community support
- Integrates seamlessly with NumPy and other scientific Python libraries
Cons of matplotlib
- Steeper learning curve for beginners
- More complex setup and configuration for basic plots
- Larger codebase and dependencies
Code Comparison
matplotlib:
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(0, 2*np.pi, 100)
y = np.sin(x)
plt.plot(x, y)
plt.show()
math-as-code:
// No direct plotting functionality
// Focuses on mathematical concepts in code
const sin = Math.sin;
const x = 1;
const result = sin(x);
Summary
matplotlib is a powerful plotting library for Python, offering extensive visualization capabilities. It's ideal for complex data visualization tasks but may be overwhelming for simple plots. math-as-code, on the other hand, is a guide that explains mathematical concepts using code examples, primarily in JavaScript. It doesn't provide plotting functionality but serves as an educational resource for understanding mathematical operations in programming contexts.
Statsmodels: statistical modeling and econometrics in Python
Pros of statsmodels
- Comprehensive statistical library with a wide range of models and tools
- Actively maintained with regular updates and improvements
- Integrates well with other scientific Python libraries like NumPy and Pandas
Cons of statsmodels
- Steeper learning curve due to its extensive functionality
- Larger codebase and dependencies, which may impact performance
- More complex installation process compared to simpler libraries
Code Comparison
statsmodels:
import statsmodels.api as sm
X = sm.add_constant(X)
model = sm.OLS(y, X)
results = model.fit()
print(results.summary())
math-as-code:
function sum(numbers) {
return numbers.reduce((a, b) => a + b, 0);
}
Summary
statsmodels is a powerful statistical library for Python, offering a wide range of models and tools for data analysis. It's well-maintained and integrates seamlessly with other scientific Python libraries. However, it has a steeper learning curve and a more complex codebase compared to math-as-code.
math-as-code, on the other hand, is a simpler repository focused on explaining mathematical concepts through code examples. It's more accessible for beginners and provides a straightforward approach to understanding mathematical operations in programming.
The choice between the two depends on the specific needs of the project and the user's level of expertise in statistics and programming.
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Pros of pandas
- Comprehensive data manipulation library with extensive functionality
- Actively maintained with frequent updates and large community support
- Efficient handling of large datasets and integration with other scientific Python libraries
Cons of pandas
- Steeper learning curve due to its extensive API and features
- Higher memory usage, especially for large datasets
- More complex setup and dependencies compared to a simple reference guide
Code Comparison
math-as-code (JavaScript):
const sum = [1, 2, 3, 4].reduce((a, b) => a + b, 0);
pandas (Python):
import pandas as pd
df = pd.DataFrame([1, 2, 3, 4])
sum = df[0].sum()
Summary
math-as-code is a concise reference guide for mathematical notation in code, while pandas is a powerful data manipulation library. math-as-code offers simplicity and ease of understanding for mathematical concepts, whereas pandas provides robust tools for data analysis and manipulation. The choice between them depends on the specific needs of the project: mathematical reference or comprehensive data handling.
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math-as-code
This is a reference to ease developers into mathematical notation by showing comparisons with JavaScript code.
Motivation: Academic papers can be intimidating for self-taught game and graphics programmers. :)
This guide is not yet finished. If you see errors or want to contribute, please open a ticket or send a PR.
Note: For brevity, some code examples make use of npm packages. You can refer to their GitHub repos for implementation details.
foreword
Mathematical symbols can mean different things depending on the author, context and the field of study (linear algebra, set theory, etc). This guide may not cover all uses of a symbol. In some cases, real-world references (blog posts, publications, etc) will be cited to demonstrate how a symbol might appear in the wild.
For a more complete list, refer to Wikipedia - List of Mathematical Symbols.
For simplicity, many of the code examples here operate on floating point values and are not numerically robust. For more details on why this may be a problem, see Robust Arithmetic Notes by Mikola Lysenko.
contents
- variable name conventions
- equals
=
â
â
:=
- square root and complex numbers
â
i
- dot & cross
·
Ã
â
- sigma
Σ
- summation - capital Pi
Î
- products of sequences - pipes
||
- hat
â
- unit vector - "element of"
â
â
- common number sets
â
â¤
â
â
- function
Æ
- prime
â²
- floor & ceiling
â
â
- arrows
- logical negation
¬
~
!
- intervals
- more...
variable name conventions
There are a variety of naming conventions depending on the context and field of study, and they are not always consistent. However, in some of the literature you may find variable names to follow a pattern like so:
- s - italic lowercase letters for scalars (e.g. a number)
- x - bold lowercase letters for vectors (e.g. a 2D point)
- A - bold uppercase letters for matrices (e.g. a 3D transformation)
- θ - italic lowercase Greek letters for constants and special variables (e.g. polar angle θ, theta)
This will also be the format of this guide.
equals symbols
There are a number of symbols resembling the equals sign =
. Here are a few common examples:
=
is for equality (values are the same)â
is for inequality (value are not the same)â
is for approximately equal to (Ï â 3.14159
):=
is for definition (A is defined as B)
In JavaScript:
// equality
2 === 3
// inequality
2 !== 3
// approximately equal
almostEqual(Math.PI, 3.14159, 1e-5)
function almostEqual(a, b, epsilon) {
return Math.abs(a - b) <= epsilon
}
You might see the :=
, =:
and =
symbols being used for definition.1
For example, the following defines x to be another name for 2kj.
In JavaScript, we might use var
to define our variables and provide aliases:
var x = 2 * k * j
However, this is mutable, and only takes a snapshot of the values at that time. Some languages have pre-processor #define
statements, which are closer to a mathematical define.
A more accurate define in JavaScript (ES6) might look a bit like this:
const f = (k, j) => 2 * k * j
The following, on the other hand, represents equality:
The above equation might be interpreted in code as an assertion:
console.assert(x === (2 * k * j))
square root and complex numbers
A square root operation is of the form:
In programming we use a sqrt
function, like so:
var x = 9;
console.log(Math.sqrt(x));
//=> 3
Complex numbers are expressions of the form , where is the real part and is the imaginary part. The imaginary number is defined as:
.
In JavaScript, there is no built-in functionality for complex numbers, but there are some libraries that support complex number arithmetic. For example, using mathjs:
var math = require('mathjs')
var a = math.complex(3, -1)
//=> { re: 3, im: -1 }
var b = math.sqrt(-1)
//=> { re: 0, im: 1 }
console.log(math.multiply(a, b).toString())
//=> '1 + 3i'
The library also supports evaluating a string expression, so the above could be re-written as:
console.log(math.eval('(3 - i) * i').toString())
//=> '1 + 3i'
Other implementations:
dot & cross
The dot ·
and cross Ã
symbols have different uses depending on context.
They might seem obvious, but it's important to understand the subtle differences before we continue into other sections.
scalar multiplication
Both symbols can represent simple multiplication of scalars. The following are equivalent:
In programming languages we tend to use asterisk for multiplication:
var result = 5 * 4
Often, the multiplication sign is only used to avoid ambiguity (e.g. between two numbers). Here, we can omit it entirely:
If these variables represent scalars, the code would be:
var result = 3 * k * j
vector multiplication
To denote multiplication of one vector with a scalar, or element-wise multiplication of a vector with another vector, we typically do not use the dot ·
or cross Ã
symbols. These have different meanings in linear algebra, discussed shortly.
Let's take our earlier example but apply it to vectors. For element-wise vector multiplication, you might see an open dot â
to represent the Hadamard product.2
In other instances, the author might explicitly define a different notation, such as a circled dot â
or a filled circle â
.3
Here is how it would look in code, using arrays [x, y]
to represent the 2D vectors.
var s = 3
var k = [ 1, 2 ]
var j = [ 2, 3 ]
var tmp = multiply(k, j)
var result = multiplyScalar(tmp, s)
//=> [ 6, 18 ]
Our multiply
and multiplyScalar
functions look like this:
function multiply(a, b) {
return [ a[0] * b[0], a[1] * b[1] ]
}
function multiplyScalar(a, scalar) {
return [ a[0] * scalar, a[1] * scalar ]
}
Similarly, matrix multiplication typically does not use the dot ·
or cross symbol Ã
. Matrix multiplication will be covered in a later section.
dot product
The dot symbol ·
can be used to denote the dot product of two vectors. Sometimes this is called the scalar product since it evaluates to a scalar.
It is a very common feature of linear algebra, and with a 3D vector it might look like this:
var k = [ 0, 1, 0 ]
var j = [ 1, 0, 0 ]
var d = dot(k, j)
//=> 0
The result 0
tells us our vectors are perpendicular. Here is a dot
function for 3-component vectors:
function dot(a, b) {
return a[0] * b[0] + a[1] * b[1] + a[2] * b[2]
}
cross product
The cross symbol Ã
can be used to denote the cross product of two vectors.
In code, it would look like this:
var k = [ 0, 1, 0 ]
var j = [ 1, 0, 0 ]
var result = cross(k, j)
//=> [ 0, 0, -1 ]
Here, we get [ 0, 0, -1 ]
, which is perpendicular to both k and j.
Our cross
function:
function cross(a, b) {
var ax = a[0], ay = a[1], az = a[2],
bx = b[0], by = b[1], bz = b[2]
var rx = ay * bz - az * by
var ry = az * bx - ax * bz
var rz = ax * by - ay * bx
return [ rx, ry, rz ]
}
For other implementations of vector multiplication, cross product, and dot product:
sigma
The big Greek Σ
(Sigma) is for Summation. In other words: summing up some numbers.
Here, i=1
says to start at 1
and end at the number above the Sigma, 100
. These are the lower and upper bounds, respectively. The i to the right of the "E" tells us what we are summing. In code:
var sum = 0
for (var i = 1; i <= 100; i++) {
sum += i
}
The result of sum
is 5050
.
Tip: With whole numbers, this particular pattern can be optimized to the following:
var n = 100 // upper bound
var sum = (n * (n + 1)) / 2
Here is another example where the i, or the "what to sum," is different:
In code:
var sum = 0
for (var i = 1; i <= 100; i++) {
sum += (2 * i + 1)
}
The result of sum
is 10200
.
The notation can be nested, which is much like nesting a for
loop. You should evaluate the right-most sigma first, unless the author has enclosed them in parentheses to alter the order. However, in the following case, since we are dealing with finite sums, the order does not matter.
In code:
var sum = 0
for (var i = 1; i <= 2; i++) {
for (var j = 4; j <= 6; j++) {
sum += (3 * i * j)
}
}
Here, sum
will be 135
.
capital Pi
The capital Pi or "Big Pi" is very similar to Sigma, except we are using multiplication to find the product of a sequence of values.
Take the following:
In code, it might look like this:
var value = 1
for (var i = 1; i <= 6; i++) {
value *= i
}
Where value
will evaluate to 720
.
pipes
Pipe symbols, known as bars, can mean different things depending on the context. Below are three common uses: absolute value, Euclidean norm, and determinant.
These three features all describe the length of an object.
absolute value
For a number x, |x|
means the absolute value of x. In code:
var x = -5
var result = Math.abs(x)
// => 5
Euclidean norm
For a vector v, âvâ
is the Euclidean norm of v. It is also referred to as the "magnitude" or "length" of a vector.
Often this is represented by double-bars to avoid ambiguity with the absolute value notation, but sometimes you may see it with single bars:
Here is an example using an array [x, y, z]
to represent a 3D vector.
var v = [ 0, 4, -3 ]
length(v)
//=> 5
The length
function:
function length (vec) {
var x = vec[0]
var y = vec[1]
var z = vec[2]
return Math.sqrt(x * x + y * y + z * z)
}
Other implementations:
- magnitude - n-dimensional
- gl-vec2/length - 2D vector
- gl-vec3/length - 3D vector
determinant
For a matrix A, |A|
means the determinant of matrix A.
Here is an example computing the determinant of a 2x2 matrix, represented by a flat array in column-major format.
var determinant = require('gl-mat2/determinant')
var matrix = [ 1, 0, 0, 1 ]
var det = determinant(matrix)
//=> 1
Implementations:
- gl-mat4/determinant - also see gl-mat3 and gl-mat2
- ndarray-determinant
- glsl-determinant
- robust-determinant
- robust-determinant-2 and robust-determinant-3, specifically for 2x2 and 3x3 matrices, respectively
hat
In geometry, the "hat" symbol above a character is used to represent a unit vector. For example, here is the unit vector of a:
In Cartesian space, a unit vector is typically length 1. That means each part of the vector will be in the range of -1.0 to 1.0. Here we normalize a 3D vector into a unit vector:
var a = [ 0, 4, -3 ]
normalize(a)
//=> [ 0, 0.8, -0.6 ]
Here is the normalize
function, operating on 3D vectors:
function normalize(vec) {
var x = vec[0]
var y = vec[1]
var z = vec[2]
var squaredLength = x * x + y * y + z * z
if (squaredLength > 0) {
var length = Math.sqrt(squaredLength)
vec[0] = x / length
vec[1] = y / length
vec[2] = z / length
}
return vec
}
Other implementations:
- gl-vec3/normalize and gl-vec2/normalize
- vectors/normalize-nd (n-dimensional)
element
In set theory, the "element of" symbol â
and â
can be used to describe whether something is an element of a set. For example:
Here we have a set of numbers A { 3, 9, 14 }
and we are saying 3
is an "element of" that set.
A simple implementation in ES5 might look like this:
var A = [ 3, 9, 14 ]
A.indexOf(3) >= 0
//=> true
However, it would be more accurate to use a Set
which only holds unique values. This is a feature of ES6.
var A = new Set([ 3, 9, 14 ])
A.has(3)
//=> true
The backwards â
is the same, but the order changes:
You can also use the "not an element of" symbols â
and â
like so:
common number sets
You may see some some large Blackboard letters among equations. Often, these are used to describe sets.
For example, we might describe k to be an element of the set â
.
Listed below are a few common sets and their symbols.
â
real numbers
The large â
describes the set of real numbers. These include integers, as well as rational and irrational numbers.
JavaScript treats floats and integers as the same type, so the following would be a simple test of our k â â example:
function isReal (k) {
return typeof k === 'number' && isFinite(k);
}
Note: Real numbers are also finite, as in, not infinite.
â
rational numbers
Rational numbers are real numbers that can be expressed as a fraction, or ratio (like â
). Rational numbers cannot have zero as a denominator.
This also means that all integers are rational numbers, since the denominator can be expressed as 1.
An irrational number, on the other hand, is one that cannot be expressed as a ratio, like Ï (PI).
â¤
integers
An integer, i.e. a real number that has no fractional part. These can be positive or negative.
A simple test in JavaScript might look like this:
function isInteger (n) {
return typeof n === 'number' && n % 1 === 0
}
â
natural numbers
A natural number, a positive and non-negative integer. Depending on the context and field of study, the set may or may not include zero, so it could look like either of these:
{ 0, 1, 2, 3, ... }
{ 1, 2, 3, 4, ... }
The former is more common in computer science, for example:
function isNaturalNumber (n) {
return isInteger(n) && n >= 0
}
â
complex numbers
A complex number is a combination of a real and imaginary number, viewed as a co-ordinate in the 2D plane. For more info, see A Visual, Intuitive Guide to Imaginary Numbers.
function
Functions are fundamental features of mathematics, and the concept is fairly easy to translate into code.
A function relates an input to an output value. For example, the following is a function:
We can give this function a name. Commonly, we use Æ
to describe a function, but it could be named A(x)
or anything else.
In code, we might name it square
and write it like this:
function square (x) {
return Math.pow(x, 2)
}
Sometimes a function is not named, and instead the output is written.
In the above example, x is the input, the relationship is squaring, and y is the output.
Functions can also have multiple parameters, like in a programming language. These are known as arguments in mathematics, and the number of arguments a function takes is known as the arity of the function.
In code:
function length (x, y) {
return Math.sqrt(x * x + y * y)
}
piecewise function
Some functions will use different relationships depending on the input value, x.
The following function Æ chooses between two "sub functions" depending on the input value.
This is very similar to if
/ else
in code. The right-side conditions are often written as "for x < 0" or "if x = 0". If the condition is true, the function to the left is used.
In piecewise functions, "otherwise" and "elsewhere" are analogous to the else
statement in code.
function f (x) {
if (x >= 1) {
return (Math.pow(x, 2) - x) / x
} else {
return 0
}
}
common functions
There are some function names that are ubiquitous in mathematics. For a programmer, these might be analogous to functions "built-in" to the language (like parseInt
in JavaScript).
One such example is the sgn function. This is the signum or sign function. Let's use piecewise function notation to describe it:
In code, it might look like this:
function sgn (x) {
if (x < 0) return -1
if (x > 0) return 1
return 0
}
See signum for this function as a module.
Other examples of such functions: sin, cos, tan.
function notation
In some literature, functions may be defined with more explicit notation. For example, let's go back to the square
function we mentioned earlier:
It might also be written in the following form:
The arrow here with a tail typically means "maps to," as in x maps to x2.
Sometimes, when it isn't obvious, the notation will also describe the domain and codomain of the function. A more formal definition of Æ might be written as:
A function's domain and codomain is a bit like its input and output types, respectively. Here's another example, using our earlier sgn function, which outputs an integer:
The arrow here (without a tail) is used to map one set to another.
In JavaScript and other dynamically typed languages, you might use documentation and/or runtime checks to explain and validate a function's input/output. Example:
/**
* Squares a number.
* @param {Number} a real number
* @return {Number} a real number
*/
function square (a) {
if (typeof a !== 'number') {
throw new TypeError('expected a number')
}
return Math.pow(a, 2)
}
Some tools like flowtype attempt to bring static typing into JavaScript.
Other languages, like Java, allow for true method overloading based on the static types of a function's input/output. This is closer to mathematics: two functions are not the same if they use a different domain.
prime
The prime symbol (â²
) is often used in variable names to describe things which are similar, without giving it a different name altogether. It can describe the "next value" after some transformation.
For example, if we take a 2D point (x, y) and rotate it, you might name the result (xâ², yâ²). Or, the transpose of matrix M might be named Mâ².
In code, we typically just assign the variable a more descriptive name, like transformedPosition
.
For a mathematical function, the prime symbol often describes the derivative of that function. Derivatives will be explained in a future section. Let's take our earlier function:
Its derivative could be written with a prime â²
symbol:
In code:
function f (x) {
return Math.pow(x, 2)
}
function fPrime (x) {
return 2 * x
}
Multiple prime symbols can be used to describe the second derivative Æâ²â² and third derivative Æâ²â²â². After this, authors typically express higher orders with roman numerals ÆIV or superscript numbers Æ(n).
floor & ceiling
The special brackets âxâ
and âxâ
represent the floor and ceil functions, respectively.
In code:
Math.floor(x)
Math.ceil(x)
When the two symbols are mixed âxâ
, it typically represents a function that rounds to the nearest integer:
In code:
Math.round(x)
arrows
Arrows are often used in function notation. Here are a few other areas you might see them.
material implication
Arrows like â
and â
are sometimes used in logic for material implication. That is, if A is true, then B is also true.
Interpreting this as code might look like this:
if (A === true) {
console.assert(B === true)
}
The arrows can go in either direction â
â
, or both â
. When A â B and B â A, they are said to be equivalent:
equality
In math, the <
>
â¤
and â¥
are typically used in the same way we use them in code: less than, greater than, less than or equal to and greater than or equal to, respectively.
50 > 2 === true
2 < 10 === true
3 <= 4 === true
4 >= 4 === true
On rare occasions you might see a slash through these symbols, to describe not. As in, k is "not greater than" j.
The âª
and â«
are sometimes used to represent significant inequality. That is, k is an order of magnitude larger than j.
In mathematics, order of magnitude is rather specific; it is not just a "really big difference." A simple example of the above:
orderOfMagnitude(k) > orderOfMagnitude(j)
And below is our orderOfMagnitude
function, using Math.trunc (ES6).
function log10(n) {
// logarithm in base 10
return Math.log(n) / Math.LN10
}
function orderOfMagnitude (n) {
return Math.trunc(log10(n))
}
Note: This is not numerically robust.
See math-trunc for a ponyfill in ES5.
conjunction & disjunction
Another use of arrows in logic is conjunction â§
and disjunction â¨
. They are analogous to a programmer's AND
and OR
operators, respectively.
The following shows conjunction â§
, the logical AND
.
In JavaScript, we use &&
. Assuming k is a natural number, the logic implies that k is 3:
if (k > 2 && k < 4) {
console.assert(k === 3)
}
Since both sides are equivalent â
, it also implies the following:
if (k === 3) {
console.assert(k > 2 && k < 4)
}
The down arrow â¨
is logical disjunction, like the OR operator.
In code:
A || B
logical negation
Occasionally, the ¬
, ~
and !
symbols are used to represent logical NOT
. For example, ¬A is only true if A is false.
Here is a simple example using the not symbol:
An example of how we might interpret this in code:
if (x !== y) {
console.assert(!(x === y))
}
Note: The tilde ~
has many different meanings depending on context. For example, row equivalence (matrix theory) or same order of magnitude (discussed in equality).
intervals
Sometimes a function deals with real numbers restricted to some range of values, such a constraint can be represented using an interval
For example we can represent the numbers between zero and one including/not including zero and/or one as:
- Not including zero or one:
- Including zero or but not one:
- Not including zero but including one:
- Including zero and one:
For example we to indicate that a point x
is in the unit cube in 3D we say:
In code we can represent an interval using a two element 1d array:
var nextafter = require('nextafter')
var a = [nextafter(0, Infinity), nextafter(1, -Infinity)] // open interval
var b = [nextafter(0, Infinity), 1] // interval closed on the left
var c = [0, nextafter(1, -Infinity)] // interval closed on the right
var d = [0, 1] // closed interval
Intervals are used in conjunction with set operations:
- intersection e.g.
- union e.g.
- difference e.g. and
In code:
var Interval = require('interval-arithmetic')
var nextafter = require('nextafter')
var a = Interval(3, nextafter(5, -Infinity))
var b = Interval(4, 6)
Interval.intersection(a, b)
// {lo: 4, hi: 4.999999999999999}
Interval.union(a, b)
// {lo: 3, hi: 6}
Interval.difference(a, b)
// {lo: 3, hi: 3.9999999999999996}
Interval.difference(b, a)
// {lo: 5, hi: 6}
See:
more...
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Contributing
For details on how to contribute, see CONTRIBUTING.md.
License
MIT, see LICENSE.md for details.
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