# {py:mod}`elasticai.preprocessor.waveform_generator`

```{py:module} elasticai.preprocessor.waveform_generator
```

```{autodoc2-docstring} elasticai.preprocessor.waveform_generator
:allowtitles:
```

## Module Contents

### Classes

````{list-table}
:class: autosummary longtable
:align: left

* - {py:obj}`WaveformSignal <elasticai.preprocessor.waveform_generator.WaveformSignal>`
  - ```{autodoc2-docstring} elasticai.preprocessor.waveform_generator.WaveformSignal
    :summary:
    ```
* - {py:obj}`WaveformGenerator <elasticai.preprocessor.waveform_generator.WaveformGenerator>`
  - ```{autodoc2-docstring} elasticai.preprocessor.waveform_generator.WaveformGenerator
    :summary:
    ```
````

### API

`````{py:class} WaveformSignal
:canonical: elasticai.preprocessor.waveform_generator.WaveformSignal

```{autodoc2-docstring} elasticai.preprocessor.waveform_generator.WaveformSignal
```

````{py:attribute} time
:canonical: elasticai.preprocessor.waveform_generator.WaveformSignal.time
:type: numpy.ndarray
:value: >
   None

```{autodoc2-docstring} elasticai.preprocessor.waveform_generator.WaveformSignal.time
```

````

````{py:attribute} signal
:canonical: elasticai.preprocessor.waveform_generator.WaveformSignal.signal
:type: numpy.ndarray
:value: >
   None

```{autodoc2-docstring} elasticai.preprocessor.waveform_generator.WaveformSignal.signal
```

````

````{py:attribute} fs
:canonical: elasticai.preprocessor.waveform_generator.WaveformSignal.fs
:type: float
:value: >
   None

```{autodoc2-docstring} elasticai.preprocessor.waveform_generator.WaveformSignal.fs
```

````

````{py:attribute} rms
:canonical: elasticai.preprocessor.waveform_generator.WaveformSignal.rms
:type: float
:value: >
   None

```{autodoc2-docstring} elasticai.preprocessor.waveform_generator.WaveformSignal.rms
```

````

`````

`````{py:class} WaveformGenerator(sampling_rate: float)
:canonical: elasticai.preprocessor.waveform_generator.WaveformGenerator

```{autodoc2-docstring} elasticai.preprocessor.waveform_generator.WaveformGenerator
```

```{rubric} Initialization
```

```{autodoc2-docstring} elasticai.preprocessor.waveform_generator.WaveformGenerator.__init__
```

````{py:method} check_charge_balancing(signal: numpy.ndarray) -> float
:canonical: elasticai.preprocessor.waveform_generator.WaveformGenerator.check_charge_balancing

```{autodoc2-docstring} elasticai.preprocessor.waveform_generator.WaveformGenerator.check_charge_balancing
```

````

````{py:method} get_dictionary_classes() -> list
:canonical: elasticai.preprocessor.waveform_generator.WaveformGenerator.get_dictionary_classes

```{autodoc2-docstring} elasticai.preprocessor.waveform_generator.WaveformGenerator.get_dictionary_classes
```

````

````{py:method} generate_waveform(time_points: list, time_duration: list, waveform_select: list, polarity_cathodic: list) -> elasticai.preprocessor.waveform_generator.WaveformSignal
:canonical: elasticai.preprocessor.waveform_generator.WaveformGenerator.generate_waveform

```{autodoc2-docstring} elasticai.preprocessor.waveform_generator.WaveformGenerator.generate_waveform
```

````

````{py:method} generate_waveform_quant_fxp(time_points: list, time_duration: list, waveform_select: list, polarity_cathodic: list, bitwidth: int, bitfrac: int, signed: bool, do_opt: bool = False) -> elasticai.preprocessor.waveform_generator.WaveformSignal
:canonical: elasticai.preprocessor.waveform_generator.WaveformGenerator.generate_waveform_quant_fxp

```{autodoc2-docstring} elasticai.preprocessor.waveform_generator.WaveformGenerator.generate_waveform_quant_fxp
```

````

````{py:method} generate_biphasic_waveform(anodic_wvf: str, anodic_duration: float, cathodic_wvf: str, cathodic_duration: float, intermediate_duration: float = 0.0, do_cathodic_first: bool = False, do_charge_balancing: bool = False) -> dict
:canonical: elasticai.preprocessor.waveform_generator.WaveformGenerator.generate_biphasic_waveform

```{autodoc2-docstring} elasticai.preprocessor.waveform_generator.WaveformGenerator.generate_biphasic_waveform
```

````

````{py:method} build_random_timestamps(count: int, min_gap: float = 0.002, max_gap: float = 0.01) -> list
:canonical: elasticai.preprocessor.waveform_generator.WaveformGenerator.build_random_timestamps
:staticmethod:

```{autodoc2-docstring} elasticai.preprocessor.waveform_generator.WaveformGenerator.build_random_timestamps
```

````

````{py:method} create_design(waveform: str, num_params: int, is_signed: bool, target: str, bitwidth: int, id: str, path2save: pathlib.Path, use_bram: bool = False, do_opt: bool = False) -> list[int]
:canonical: elasticai.preprocessor.waveform_generator.WaveformGenerator.create_design

```{autodoc2-docstring} elasticai.preprocessor.waveform_generator.WaveformGenerator.create_design
```

````

`````