pygan.noisesampler package

Submodules

pygan.noisesampler.gauss_noise_sampler module

class pygan.noisesampler.gauss_noise_sampler.GaussNoiseSampler(mu, sigma, output_shape)[source]

Bases: pygan.noise_sampler.NoiseSampler

Generate samples based on the noise prior by Gauss distribution.

generate()[source]

Generate noise samples.

Returns:np.ndarray of samples.
get_output_shape()[source]

getter

output_shape

getter

set_output_shape(value)[source]

setter

pygan.noisesampler.image_noise_sampler module

class pygan.noisesampler.image_noise_sampler.ImageNoiseSampler(batch_size, image_dir, seq_len=None, gray_scale_flag=True, wh_size_tuple=(100, 100), norm_mode='z_score')[source]

Bases: pygan.noise_sampler.NoiseSampler

Sampler which draws samples from the noise prior of images.

generate()[source]

Draws samples from the true distribution.

Returns:np.ndarray of samples.

pygan.noisesampler.sine_wave_noise_sampler module

class pygan.noisesampler.sine_wave_noise_sampler.SineWaveNoiseSampler(batch_size, seq_len, dim=1, amp=0.5, sampling_freq=8000, freq=440, sec=5, mu=0.0, sigma=1.0, norm_mode='z_score')[source]

Bases: pygan.noise_sampler.NoiseSampler

Generate samples based on the noise prior by sine wave distribution.

generate()[source]

Generate noise samples.

Returns:np.ndarray of samples.

pygan.noisesampler.uniform_noise_sampler module

class pygan.noisesampler.uniform_noise_sampler.UniformNoiseSampler(low, high, output_shape)[source]

Bases: pygan.noise_sampler.NoiseSampler

Generate samples based on the noise prior by Uniform distribution.

generate()[source]

Generate noise samples.

Returns:np.ndarray of samples.
get_output_shape()[source]

getter

output_shape

getter

set_output_shape(value)[source]

setter

Module contents