BPython:
-- epydoc Documentation for eeshlo's Noise module + small typo fix in Noise.c -- BPY_end_python closes .blend file opened by Library module when script doesn't do it by itself.
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source/blender/python/api2_2x/doc/Noise.py
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source/blender/python/api2_2x/doc/Noise.py
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# Blender.Noise submodule
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"""
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The Blender.Noise submodule.
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Noise and Turbulence
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====================
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This module can be used to generate noise of various types. This can be used
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for terrain generation, to create textures, make animations more 'animated',
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object deformation, etc. As an example, this code segment when scriptlinked
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to a framechanged event, will make the camera sway randomly about, by changing
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parameters this can look like anything from an earthquake to a very nervous or
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maybe even drunk cameraman... (the camera needs an ipo with at least one Loc &
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Rot key for this to work!):
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Example::
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from Blender import Get, Scene, Noise
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####################################################
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# This controls jitter speed
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sl = 0.025
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# This controls the amount of position jitter
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sp = 0.1
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# This controls the amount of rotation jitter
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sr = 0.25
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####################################################
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time = Get('curtime')
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ob = Scene.GetCurrent().getCurrentCamera()
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ps = (sl*time, sl*time, sl*time)
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# To add jitter only when the camera moves, use this next line instead
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#ps = (sl*ob.LocX, sl*ob.LocY, sl*ob.LocZ)
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rv = Noise.vTurbulence(ps, 3, 0, Noise.NoiseTypes.NEWPERLIN)
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ob.dloc = (sp*rv[0], sp*rv[1], sp*rv[2])
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ob.drot = (sr*rv[0], sr*rv[1], sr*rv[2])
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@type NoiseTypes: readonly dictionary
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@var NoiseTypes: The available noise types.
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- BLENDER
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- STDPERLIN
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- NEWPERLIN
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- VORONOI_F1
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- VORONOI_F2
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- VORONOI_F3
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- VORONOI_F4
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- VORONOI_F2F1
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- VORONOI_CRACKLE
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- CELLNOISE
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@type DistanceMetrics: readonly dictionary
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@var DistanceMetrics: The available distance metrics values for Voronoi.
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- DISTANCE
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- DISTANCE_SQUARED
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- MANHATTAN
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- CHEBYCHEV
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- MINKOVSKY_HALF
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- MINKOVSKY_FOUR
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- MINKOVISKY
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"""
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NoiseTypes = {'BLENDER':0, 'STDPERLIN':1}
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DistanceMetrics = {'DISTANCE':0}
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def random ():
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"""
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Returns a random floating point number."
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@rtype: float
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@return: a random number in [0, 1).
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"""
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def randuvec ():
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"""
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Returns a random unit vector.
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@rtype: 3-float list
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@return: a list of three floats.
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"""
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def setRandomSeed (seed):
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"""
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Initializes the random number generator.
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@type seed: int
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@param seed: the seed for the random number generator. If seed = 0, the
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current time will be used as seed, instead.
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"""
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def noise (xyz, type = NoiseTypes['STDPERLIN']):
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"""
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Returns general noise of the optional specified type.
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@type xyz: tuple of 3 floats
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@param xyz: (x,y,z) float values.
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@type type: int
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@param type: the type of noise to return. See L{NoiseTypes}.
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@rtype: float
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@return: the generated noise value.
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"""
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def vNoise (xyz, type = NoiseTypes['STDPERLIN']):
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"""
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Returns noise vector of the optional specified type.
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@type xyz: tuple of 3 floats
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@param xyz: (x,y,z) float values.
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@type type: int
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@param type: the type of noise to return. See L{NoiseTypes}.
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@rtype: 3-float list
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@return: the generated noise vector.
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"""
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def turbulence (xyz, octaves, hard, basis = NoiseTypes['STDPERLIN'],
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ampscale = 0.5, freqscale = 2.0):
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"""
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Returns general turbulence value using the optional specified noise 'basis'
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function.
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@type xyz: 3-float tuple
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@param xyz: (x,y,z) float values.
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@type octaves: int
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@param octaves: number of noise values added.
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@type hard: bool
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@param hard: noise hardness: 0 - soft noise; 1 - hard noise. (Returned value
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is always positive.)
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@type basis: int
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@param basis: type of noise used for turbulence, see L{NoiseTypes}.
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@type ampscale: float
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@param ampscale: amplitude scale value of the noise frequencies added.
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@type freqscale: float
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@param freqscale: frequency scale factor.
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@rtype: float
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@return: the generated turbulence value.
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"""
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def vTurbulence (xyz, octaves, hard, basis = NoiseTypes['STDPERLIN'],
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ampscale = 0.5, freqscale = 2.0):
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"""
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Returns general turbulence vector using the optional specified noise basis
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function.
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@type xyz: 3-float tuple
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@param xyz: (x,y,z) float values.
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@type octaves: int
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@param octaves: number of noise values added.
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@type hard: bool
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@param hard: noise hardness: 0 - soft noise; 1 - hard noise. (Returned
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vector is always positive.)
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@type basis: int
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@param basis: type of noise used for turbulence, see L{NoiseTypes}.
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@type ampscale: float
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@param ampscale: amplitude scale value of the noise frequencies added.
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@type freqscale: float
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@param freqscale: frequency scale factor.
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@rtype: 3-float list
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@return: the generated turbulence vector.
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"""
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def fBm (xyz, H, lacunarity, octaves, basis = NoiseTypes['STDPERLIN']):
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"""
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Returns Fractal Brownian Motion noise value (fBm).
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@type xyz: 3-float tuple
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@param xyz: (x,y,z) float values.
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@type H: float
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@param H: the fractal increment parameter.
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@type lacunarity: float
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@param lacunarity: the gap between successive frequencies.
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@type octaves: float
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@param octaves: the number of frequencies in the fBm.
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@type basis: int
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@param basis: type of noise used for the turbulence, see L{NoiseTypes}.
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@rtype: float
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@return: the generated noise value.
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"""
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def multiFractal (xyz, H, lacunarity, octaves, basis = NoiseTypes['STDPERLIN']):
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"""
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Returns Multifractal noise value.
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@type xyz: 3-float tuple
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@param xyz: (x,y,z) float values.
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@type H: float
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@param H: the highest fractal dimension.
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@type lacunarity: float
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@param lacunarity: the gap between successive frequencies.
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@type octaves: float
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@param octaves: the number of frequencies in the fBm.
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@type basis: int
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@param basis: type of noise used for the turbulence, see L{NoiseTypes}.
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@rtype: float
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@return: the generated noise value.
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"""
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def vlNoise (xyz, distortion, type1 = NoiseTypes['STDPERLIN'],
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type2 = NoiseTypes['STDPERLIN']):
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"""
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Returns Variable Lacunarity Noise value, a distorted variety of noise.
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@type xyz: 3-float tuple
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@param xyz: (x,y,z) float values.
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@type distortion: float
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@param distortion: the amount of distortion.
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@type type1: int
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@type type2: int
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@param type1: sets the noise type to distort.
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@param type2: sets the noise type used for the distortion.
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@rtype: float
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@return: the generated noise value.
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"""
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def heteroTerrain (xyz, H, lacunarity, octaves, offset,
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basis = NoiseTypes['STDPERLIN']):
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"""
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Returns Heterogeneous Terrain value.
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@type xyz: 3-float tuple
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@param xyz: (x,y,z) float values.
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@type H: float
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@param H: fractal dimension of the roughest areas.
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@type lacunarity: float
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@param lacunarity: gap between successive frequencies.
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@type octaves: float
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@param octaves: number of frequencies in the fBm.
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@type offset: float
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@param offset: it raises the terrain from 'sea level'.
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@type basis: int
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@param basis: noise basis determines the type of noise used for the
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turbulence, see L{NoiseTypes}.
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@rtype: float
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@return: the generated value.
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"""
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def hybridMFractal (xyz, H, lacunarity, octaves, offset, gain,
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basis = NoiseTypes['STDPERLIN']):
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"""
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Returns Hybrid Multifractal value.
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@type xyz: 3-float tuple
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@param xyz: (x,y,z) float values.
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@type H: float
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@param H: fractal dimension of the roughest areas.
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@type lacunarity: float
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@param lacunarity: gap between successive frequencies.
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@type octaves: float
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@param octaves: number of frequencies in the fBm.
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@type offset: float
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@param offset: it raises the terrain from 'sea level'.
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@type gain: float
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@param gain: scale factor.
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@type basis: int
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@param basis: noise basis determines the type of noise used for the
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turbulence, see L{NoiseTypes}.
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@rtype: float
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@return: the generated value.
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"""
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def ridgedMFractal (xyz, H, lacunarity, octaves, offset, gain,
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basis = NoiseTypes['STDPERLIN']):
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"""
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Returns Ridged Multifractal value.
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@type xyz: 3-float tuple
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@param xyz: (x,y,z) float values.
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@type H: float
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@param H: fractal dimension of the roughest areas.
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@type lacunarity: float
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@param lacunarity: gap between successive frequencies.
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@type octaves: float
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@param octaves: number of frequencies in the fBm.
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@type offset: float
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@param offset: it raises the terrain from 'sea level'.
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@type gain: float
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@param gain: scale factor.
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@type basis: int
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@param basis: noise basis determines the type of noise used for the
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turbulence, see L{NoiseTypes}.
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@rtype: float
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@return: the generated value.
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"""
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def voronoi(xyz, distance_metric = DistanceMetrics['DISTANCE'], exponent = 2.5):
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"""
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Returns Voronoi diagrams-related data.
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@type xyz: 3-float tuple
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@param xyz: (x,y,z) float values.
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@type distance_metric: int
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@param distance_metric: see L{DistanceMetrics}
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@type exponent: float
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@param exponent: only used with MINKOVSKY, default is 2.5.
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@rtype: list
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@return: a list containing a list of distances in order of closest feature,
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and a list containing the positions of the four closest features.
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"""
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def cellNoise (xyz):
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"""
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Returns cellnoise.
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@type xyz: 3-float tuple
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@param xyz: (x,y,z) float values.
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@rtype: float
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@return: the generated value.
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"""
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def cellNoiseV (xyz):
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"""
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Returns cellnoise vector/point/color.
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@type xyz: 3-float tuple
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@param xyz: (x,y,z) float values.
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@rtype: 3-float list
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@return: the generated vector.
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"""
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