ModelVisualizer

class medigan.model_visualizer.ModelVisualizer(model_executor, config: None)[source]

Bases: object

ModelVisualizer class: Visualises synthetic data through a user interface. Depending on a model, it is possible to control the input latent vector values and conditional input.

Parameters

model_executor (ModelExecutor) – The generative model’s executor object
config (dict) – The config dict containing the model metadata

model_executor

The generative model’s executor object

Type: ModelExecutor

input_latent_vector_size

Size of the latent vector used as an input for generation

Type: int

conditional

Flag for models with conditional input

Type: bool

condition

Value of the conditinal input to the model

Type: Union[int, float]

max_input_value

Absolute value used for setting latent values input range

Type: float

Methods Summary

visualize([slider_grouper, auto_close])

Visualize the model's output.

Methods Documentation

visualize(slider_grouper: int = 10, auto_close=False)[source]

Visualize the model’s output. This method is called by the user. It opens up a user interface with available controls.

Parameters

slider_grouper (int) – Number of input parameters to group together within one slider.
auto_close (bool) – Flag for closing the user interface automatically after time. Used while testing.

Return type

None