pygan.truesampler package

Submodules

pygan.truesampler.conditional_true_sampler module

class pygan.truesampler.conditional_true_sampler.ConditionalTrueSampler[source]

Bases: pygan.true_sampler.TrueSampler

Sampler which draws samples from the conditional true distribution.

add_condition(observed_arr)[source]

Add condtion.

Parameters:observed_arr – np.ndarray of samples.
Returns:np.ndarray of samples.

pygan.truesampler.gauss_true_sampler module

class pygan.truesampler.gauss_true_sampler.GaussTrueSampler(mu, sigma, output_shape)[source]

Bases: pygan.true_sampler.TrueSampler

Sampler which draws samples from the true Gauss distribution.

draw()[source]

Draws samples from the true distribution.

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

getter

output_shape

getter

set_output_shape(value)[source]

setter

pygan.truesampler.image_true_sampler module

class pygan.truesampler.image_true_sampler.ImageTrueSampler(batch_size, image_dir, seq_len=None, gray_scale_flag=True, wh_size_tuple=(100, 100), norm_mode='z_score')[source]

Bases: pygan.true_sampler.TrueSampler

Sampler which draws samples from the true distribution of images.

draw()[source]

Draws samples from the true distribution.

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

getter

seq_len

getter

set_readonly(value)[source]

setter

pygan.truesampler.sine_wave_true_sampler module

class pygan.truesampler.sine_wave_true_sampler.SineWaveTrueSampler(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.true_sampler.TrueSampler

Sampler which draws samples from the true sine wave distribution.

draw()[source]

Draws samples from the true distribution.

Returns:np.ndarray of samples.

pygan.truesampler.uniform_true_sampler module

class pygan.truesampler.uniform_true_sampler.UniformSampler(low, high, output_shape)[source]

Bases: pygan.true_sampler.TrueSampler

Generate samples based on the noise prior by Uniform distribution.

draw()[source]

Draws samples from the true distribution.

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

getter

output_shape

getter

set_output_shape(value)[source]

setter

Module contents