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""" |
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This module provides advanced noise generation. |
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Noise is sometimes used for over-world generation, height-maps, and |
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cloud/mist/smoke effects among other things. |
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You can see examples of the available noise algorithms in the libtcod |
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documentation `here |
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<http://doryen.eptalys.net/data/libtcod/doc/1.5.1/html2/noise.html>`_. |
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""" |
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import random as _random |
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from tcod import ffi as _ffi |
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from tcod import lib as _lib |
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import tdl as _tdl |
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from . import style as _style |
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_MERSENNE_TWISTER = 1 |
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_CARRY_WITH_MULTIPLY = 2 |
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_MAX_DIMENSIONS = 4 |
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_MAX_OCTAVES = 128 |
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_NOISE_TYPES = {'PERLIN': 1, 'SIMPLEX': 2, 'WAVELET': 4} |
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_NOISE_MODES = {'FLAT': _lib.TCOD_noise_get, |
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'FBM': _lib.TCOD_noise_get_fbm, |
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'TURBULENCE': _lib.TCOD_noise_get_turbulence} |
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class Noise(object): |
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"""An advanced noise generator. |
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.. deprecated:: 3.2 |
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This class has been replaced by :any:`tcod.noise.Noise`. |
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Args: |
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algorithm (Text): The primary noise algorithm to be used. |
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Can be one of 'PERLIN', 'SIMPLEX', 'WAVELET' |
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- 'PERLIN' - |
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A popular noise generator. |
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- 'SIMPLEX' - |
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In theory this is a slightly faster generator with |
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less noticeable directional artifacts. |
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- 'WAVELET' - |
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A noise generator designed to reduce aliasing and |
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not lose detail when summed into a fractal |
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(as with the 'FBM' and 'TURBULENCE' modes.) |
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This works faster at higher dimensions. |
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mode (Text): A secondary parameter to determine how noise is generated. |
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Can be one of 'FLAT', 'FBM', 'TURBULENCE' |
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- 'FLAT' - |
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Generates the simplest form of noise. |
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This mode does not use the hurst, lacunarity, |
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and octaves parameters. |
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- 'FBM' - |
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Generates fractal brownian motion. |
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- 'TURBULENCE' - |
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Generates detailed noise with smoother and more |
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natural transitions. |
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hurst (float): The hurst exponent. |
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This describes the raggedness of the resultant noise, |
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with a higher value leading to a smoother noise. |
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It should be in the 0.0-1.0 range. |
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This is only used in 'FBM' and 'TURBULENCE' modes. |
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lacunarity (float): A multiplier that determines how quickly the |
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frequency increases for each successive octave. |
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The frequency of each successive octave is equal to |
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the product of the previous octave's frequency and |
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the lacunarity value. |
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This is only used in 'FBM' and 'TURBULENCE' modes. |
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octaves (float): Controls the amount of detail in the noise. |
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This is only used in 'FBM' and 'TURBULENCE' modes. |
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seed (Hashable): You can use any hashable object to be a seed for the |
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noise generator. |
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If None is used then a random seed will be generated. |
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""" |
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def __init__(self, algorithm='PERLIN', mode='FLAT', |
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hurst=0.5, lacunarity=2.0, octaves=4.0, seed=None, dimensions=4): |
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if algorithm.upper() not in _NOISE_TYPES: |
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raise _tdl.TDLError('No such noise algorithm as %s' % algorithm) |
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self._algorithm = algorithm.upper() |
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if mode.upper() not in _NOISE_MODES: |
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raise _tdl.TDLError('No such mode as %s' % mode) |
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self._mode = mode.upper() |
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if seed is None: |
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seed = _random.getrandbits(32) |
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try: |
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seed = int(seed) |
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except TypeError: |
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seed = hash(seed) |
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self._seed = seed |
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# convert values into ctypes to speed up later functions |
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self._dimensions = min(_MAX_DIMENSIONS, int(dimensions)) |
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if self._algorithm == 'WAVELET': |
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self._dimensions = min(self._dimensions, 3) # Wavelet only goes up to 3 |
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self._random = _lib.TCOD_random_new_from_seed( |
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_MERSENNE_TWISTER, |
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_ffi.cast('uint32_t', self._seed), |
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) |
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self._hurst = hurst |
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self._lacunarity = lacunarity |
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self._noise = _lib.TCOD_noise_new(self._dimensions, self._hurst, |
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self._lacunarity, self._random) |
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_lib.TCOD_noise_set_type(self._noise, _NOISE_TYPES[self._algorithm]) |
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self._noiseFunc = _NOISE_MODES[self._mode] |
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self._octaves = octaves |
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self._useOctaves = (self._mode != 'FLAT') |
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self._arrayType = 'float[%i]' % self._dimensions |
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#self._cFloatArray = _ctypes.c_float * self._dimensions |
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#self._array = self._cFloatArray() |
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def __copy__(self): |
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# using the pickle method is a convenient way to clone this object |
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return self.__class__(*self.__getstate__()) |
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def __getstate__(self): |
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return (self._algorithm, self._mode, |
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self._hurst, self._lacunarity, self._octaves, |
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self._seed, self._dimensions) |
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def __setstate__(self, state): |
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self.__init__(*state) |
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def get_point(self, *position): |
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"""Return the noise value of a specific position. |
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Example usage: value = noise.getPoint(x, y, z) |
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Args: |
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position (Tuple[float, ...]): The point to sample at. |
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Returns: |
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float: The noise value at position. |
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This will be a floating point in the 0.0-1.0 range. |
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""" |
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#array = self._array |
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#for d, pos in enumerate(position): |
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# array[d] = pos |
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#array = self._cFloatArray(*position) |
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array = _ffi.new(self._arrayType, position) |
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if self._useOctaves: |
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return (self._noiseFunc(self._noise, array, self._octaves) + 1) * 0.5 |
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return (self._noiseFunc(self._noise, array) + 1) * 0.5 |
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__all__ = [_var for _var in locals().keys() if _var[0] != '_'] |
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Noise.getPoint = _style.backport(Noise.get_point) |
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python-tdl
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