c4d.utils.noise.C4DNoise¶

class c4d.utils.noise.C4DNoise¶: An important technique for generating procedural textures is the use of fractal noise.

See also

Noise Types.

Overview¶

`static C4DNoise.CreateMenuContainer`	Creates a menu container with the different noise options available:
`static C4DNoise.HasOctaves`	Checks if a certain noise type supports the octaves parameter.
`static C4DNoise.HasCycles`	Checks if a certain noise type supports the cycles parameter.
`static C4DNoise.HasAbsolute`	Checks if a certain noise type supports the absolute parameter.
`static C4DNoise.EvaluateSampleOffset`	Evaluates the sample offset.

C4DNoise.__init__

type seed: int

`C4DNoise.InitFbm`	Initializes fractal brownian motion.
`C4DNoise.Noise`	Samples a 2D or 3D noise.
`C4DNoise.SNoise`	Generate a periodic signed noise value.
`C4DNoise.Turbulence`	Generate a turbulence value, this is a sum of multiple noises with different frequency.
`C4DNoise.Fbm`	Generate a periodic Fractional Brownian Motion value.
`C4DNoise.RidgedMultifractal`	Generate a periodic fractal function used for such things as landscapes or mountain ranges.

Members¶

static C4DNoise.CreateMenuContainer(bIncludeNone=False)¶

Creates a menu container with the different noise options available:

import c4d

bc = c4d.utils.noise.C4DNoise.CreateMenuContainer(False)
for index, name in bc:
    print index, name

Parameters: bIncludeNone (bool) – Include the none option.
Return type: c4d.BaseContainer
Returns: Generated noise menu.

static C4DNoise.HasOctaves(t)¶

Checks if a certain noise type supports the octaves parameter.

Parameters: t (int) – Noise type.
Return type: bool
Returns: True if octaves is supported, otherwise False.

static C4DNoise.HasCycles(t)¶

Checks if a certain noise type supports the cycles parameter.

Parameters: t (int) – Noise type.
Return type: bool
Returns: True if cycles is supported, otherwise False.

static C4DNoise.HasAbsolute(t)¶

Checks if a certain noise type supports the absolute parameter.

Parameters: t (int) – Noise type.
Return type: bool
Returns: True if absolute is supported, otherwise False.

static C4DNoise.EvaluateSampleOffset(type, rOctaves, rDelta)¶

Evaluates the sample offset.

Parameters

type (int) – Noise type.
rOctaves (float) – Number of octaves.
rDelta (float) – Delta.

Return type

float

Returns

The sample offset.

C4DNoise.__init__(self, seed=665)¶

Parameters: seed (int) – Noise seed.

C4DNoise.InitFbm(self, lMaxOctaves, rLacunarity, h)¶

Initializes fractal brownian motion.

Parameters

lMaxOctaves (int) – The maximum octave.
rLacunarity (float) – This parameter controls the scale of each successive fractal overlay.
h (float) – H-Parameter

Return type

bool

Returns

Initializes fractal brownian motion

C4DNoise.Noise(self, t, two_d, p, time=0.0, octaves=4.0, absolute=False, sampleRad=0.25, detailAtt=0.25, t_repeat=0)¶

Samples a 2D or 3D noise.

Parameters

t (int) –
The noise Type: Noise Types

Note

Please use InitFbm() before you use one of the following noise types: NOISE_ZADA, NOISE_DISPL_VORONOI, NOISE_OBER, NOISE_FBM, NOISE_BUYA.
two_d (bool) – True for 2D Sampling, False for 3D Sampling
p (c4d.Vector) – Noise coordinate.
time (float) – Time.
octaves (float) – Octaves, if supported. See HasOctaves()
absolute (bool) – Absolute value, if supported. See HasAbsolute()
sampleRad (float) – Sample radius.
detailAtt (float) – Detail attenuation.
t_repeat (int) – Must be 2^x - 1, where x = [1..10], i.e. one of 1, 3, 7, 15, 31, 63, 127, 255, 511, and 1023. A noise repeats itself in time every 1024 units. Using a smaller repeat the noise will repeat at an earlier time.

Return type

float

Returns

Noise sample.

C4DNoise.SNoise(self, p, lRepeat, t=0.0)¶

Generate a periodic signed noise value.

Parameters

p (c4d.Vector) – Noise coordinate.
lRepeat (int) – Must be 2^x - 1, where x = [1..10], i.e. one of 1, 3, 7, 15, 31, 63, 127, 255, 511, and 1023. A noise repeats itself in time every 1024 units. Using a smaller lRepeat the noise will repeat at an earlier time.
t (float) – The time.

Return type

float

Returns

Signed noise value, this is between -1.0 and 1.0.

C4DNoise.Turbulence(self, p, rOctaves, bAsolute, lRepeat, t=0.0)¶

Generate a turbulence value, this is a sum of multiple noises with different frequency.

Parameters

p (c4d.Vector) – Turbulence coordinate
rOctaves (float) – The number of octaves.
bAbsolute (bool) – True for absolute values.
lRepeat (int) – Must be 2^x - 1, where x = [1..10], i.e. one of 1, 3, 7, 15, 31, 63, 127, 255, 511, and 1023. A noise repeats itself in time every 1024 units. Using a smaller lRepeat the noise will repeat at an earlier time.
t (float) – The time.

Return type

float

Returns

Noise sample.

C4DNoise.Fbm(self, p, rOctaves, lRepeat, t=0.0)¶

Generate a periodic Fractional Brownian Motion value.

Note

Needs the call InitFbm() before.

Warning

The rOctaves value must not exceed the value passed to InitFbm() but can be lower.

Parameters

p (c4d.Vector) – The evaluation point.
rOctaves (float) – The octaves
lRepeat (int) – Must be 2^x - 1, where x = [1..10], i.e. one of 1, 3, 7, 15, 31, 63, 127, 255, 511, and 1023. A noise repeats itself in time every 1024 units. Using a smaller repeat the noise will repeat at an earlier time.
t (float) – The time

Return type

float

Returns

The fbm value.

C4DNoise.RidgedMultifractal(self, p, rOctaves, rOffset, rGain, lRepeat, t=0)¶

Generate a periodic fractal function used for such things as landscapes or mountain ranges.

Note

Needs the call InitFbm() before.

Warning

The rOctaves value must not exceed the value passed to InitFbm() but can be lower.

Parameters

p (c4d.Vector) – The evaluation point.
rOctaves (float) – The octave.
rOffset (float) – The zero offset, this controls the multifractality.
rGain (float) – The amplification of the fractal value.
lRepeat (float) – Must be 2^x - 1, where x = [1..10], i.e. one of 1, 3, 7, 15, 31, 63, 127, 255, 511, and 1023. A noise repeats itself in time every 1024 units. Using a smaller lrepeat the noise will repeat at an earlier time.
t (float) – The time.

Return type

float

Returns

The fractal value.