Vector Class

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Revision as of 16:40, 14 September 2017 by Admin (talk | contribs) (Vector Class Auto Create)
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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(Read Only):

Gets or sets the X component of the vector.

y(Read Only):

Gets or sets the Y component of the vector.

z(Read Only):

Gets or sets the Z component of the vector.

Methods

cross(vec):

: -> Vector

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)

angle(vec):

: -> float

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

l = v.angle(v2)

project(vec1, vec2):

:

Projects this vector onto the plan defined by vec1 and vec2. Both vec1 and vec2 must be normalized. The result will may not be normalized. vec1, vec2 - The vectors that specify the plane to project onto. Must be normalized.

v.project(v1, v2)

distance(vec):

: -> float

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

l = v.distance(v2)

lengthSquared():

: -> float

Returns the squared length of this vector.

l = v.lengthSquared()

copy():

: -> Vector

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

newV = v.copy()

normalize():

:

Makes the length of this vector 1.

m.normalize()

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):

:

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

v.reflect(v2)

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)

scale(x, y, z):

:

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)

length():

: -> float

Returns the length of this vector.

l = m.length()

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)

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