# Vector Class

The vector class holds a single 3 component vector. A vector describes a direction in space, and it's important to use a vector or Position as appropriate for the data that is being calculated. When being multiplied by a Matrix, this class will implicitly have a 4th component (W component) of 0. A new vector can be created without any arguments, with 3 arguments for the x,y,z values, or with a single argument which is a variable that has 3 entries such as a list of length 3, or a position or vector. Examples of creating a vector:

```
v = tdu.Vector() # starts as (0, 0, 0)
v2 = tdu.Vector(0, 0, -1)
values = [0, 1, 0]
v3 = tdu.Vector(values)
```

## Members

`x`

→ `float`

:

Gets or sets the X component of the vector.

`y`

→ `float`

:

Gets or sets the Y component of the vector.

`z`

→ `float`

:

Gets or sets the Z component of the vector.

## Methods

`normalize()`

→ `None`

:

Makes the length of this vector 1.

m.normalize()

`angle(vec)`

→ `float`

:

Returns the angel (in degrees) between the current vector (vec1) and another vector (vec2).

l = v.angle(v2)

`lerp(vec, vec, t)`

→ `vec`

:

Returns vec1 * (1.0 - t) + vec2 * t, i.e., the linear interpolation of vec1 and vec2 using the floating-point value t. The value for t is not restricted to the range [0, 1]. The vec1 referes to the current vector.

l = v.lerp(v, v2, t)

`project(vec1, vec2)`

→ `None`

:

Projects this vector onto the plan defined by vec1 and vec2. Both vec1 and vec2 must be normalized. The result may not be normalized.

- vec1, vec2 - The vectors that specify the plane to project onto. Must be normalized.
v.project(v1, v2)

`lengthSquared()`

→ `float`

:

Returns the squared length of this vector.

l = v.lengthSquared()

`scale(x, y, z)`

→ `None`

:

Scales each component of the vector by the specified values.

- x, y, z - The values to scale each component of the vector by.
v.scale(1, 2, 1)

`lerp(vec, vec, t)`

→ `vec`

:

Returns vec1 * (1.0 - t) + vec2 * t, i.e., the linear interpolation of vec1 and vec2 using the floating-point value t. The value for t is not restricted to the range [0, 1]. The vec1 referes to the current vector.

l = v.lerp(v, v2, t)

`reflect(vec)`

→ `None`

:

Reflects the current vector (vec) according to another vector (vec2).

v.reflect(v2)

`cross(vec)`

→ `vec`

:

Returns the cross product of this vector and the passed vector. The operation is self cross vec.

- vec - The other vector to use to calculate the cross product.
c = v.cross(otherV)

`length()`

→ `float`

:

Returns the length of this vector.

l = m.length()

`dot(vec)`

→ `float`

:

Returns the dot product of this vector and the passed vector.

- vec - The other vector to use to calculate the dot product
d = v.dot(otherV)

`distance(vec)`

→ `float`

:

Returns the distance of the current vector (vec1) to another vector (vec2).

l = v.distance(v2)

`copy()`

→ `vec`

:

Returns a new vector that is a copy of the vector.

newV = v.copy()

### Special Functions

`tdu.Vector[i]`

→ `float`

:

Gets or sets the component of the vector specified by i, where i can be 0, 1, or 2.

y = v[1] v[1] = y * 2.0

```
tdu.Vector * float
float * tdu.Vector
```

→ `vec`

:

Scales the vector by the give float scalar and returns a new vector as the result.

v = v * 2.0 v = 2.0 * v

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