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

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

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

## Module Contents

### Classes

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

* - {py:obj}`SettingsResampler <elasticai.preprocessor.adc.adc.SettingsResampler>`
  - ```{autodoc2-docstring} elasticai.preprocessor.adc.adc.SettingsResampler
    :summary:
    ```
* - {py:obj}`TransientResampler <elasticai.preprocessor.adc.adc.TransientResampler>`
  - ```{autodoc2-docstring} elasticai.preprocessor.adc.adc.TransientResampler
    :summary:
    ```
````

### API

`````{py:class} SettingsResampler
:canonical: elasticai.preprocessor.adc.adc.SettingsResampler

```{autodoc2-docstring} elasticai.preprocessor.adc.adc.SettingsResampler
```

````{py:attribute} total_bits
:canonical: elasticai.preprocessor.adc.adc.SettingsResampler.total_bits
:type: int
:value: >
   None

```{autodoc2-docstring} elasticai.preprocessor.adc.adc.SettingsResampler.total_bits
```

````

````{py:attribute} frac_bits
:canonical: elasticai.preprocessor.adc.adc.SettingsResampler.frac_bits
:type: int
:value: >
   None

```{autodoc2-docstring} elasticai.preprocessor.adc.adc.SettingsResampler.frac_bits
```

````

````{py:attribute} is_signed
:canonical: elasticai.preprocessor.adc.adc.SettingsResampler.is_signed
:type: bool
:value: >
   None

```{autodoc2-docstring} elasticai.preprocessor.adc.adc.SettingsResampler.is_signed
```

````

````{py:attribute} srate_orig
:canonical: elasticai.preprocessor.adc.adc.SettingsResampler.srate_orig
:type: float
:value: >
   None

```{autodoc2-docstring} elasticai.preprocessor.adc.adc.SettingsResampler.srate_orig
```

````

````{py:attribute} srate_new
:canonical: elasticai.preprocessor.adc.adc.SettingsResampler.srate_new
:type: float
:value: >
   None

```{autodoc2-docstring} elasticai.preprocessor.adc.adc.SettingsResampler.srate_new
```

````

````{py:attribute} vneg
:canonical: elasticai.preprocessor.adc.adc.SettingsResampler.vneg
:type: float
:value: >
   None

```{autodoc2-docstring} elasticai.preprocessor.adc.adc.SettingsResampler.vneg
```

````

````{py:attribute} vpos
:canonical: elasticai.preprocessor.adc.adc.SettingsResampler.vpos
:type: float
:value: >
   None

```{autodoc2-docstring} elasticai.preprocessor.adc.adc.SettingsResampler.vpos
```

````

````{py:property} vcm
:canonical: elasticai.preprocessor.adc.adc.SettingsResampler.vcm
:type: float

```{autodoc2-docstring} elasticai.preprocessor.adc.adc.SettingsResampler.vcm
```

````

````{py:property} lsb
:canonical: elasticai.preprocessor.adc.adc.SettingsResampler.lsb
:type: float

```{autodoc2-docstring} elasticai.preprocessor.adc.adc.SettingsResampler.lsb
```

````

`````

`````{py:class} TransientResampler(settings: elasticai.preprocessor.adc.adc.SettingsResampler)
:canonical: elasticai.preprocessor.adc.adc.TransientResampler

```{autodoc2-docstring} elasticai.preprocessor.adc.adc.TransientResampler
```

```{rubric} Initialization
```

```{autodoc2-docstring} elasticai.preprocessor.adc.adc.TransientResampler.__init__
```

````{py:method} do_cut_transient(data: numpy.ndarray, t_range_sec: list[float], use_srate_orig: bool = True) -> numpy.ndarray
:canonical: elasticai.preprocessor.adc.adc.TransientResampler.do_cut_transient

```{autodoc2-docstring} elasticai.preprocessor.adc.adc.TransientResampler.do_cut_transient
```

````

````{py:method} do_cut_labels(label_id: numpy.ndarray, label_pos: numpy.ndarray, t_range_sec: list[float], use_srate_orig: bool = True) -> tuple[numpy.ndarray, numpy.ndarray]
:canonical: elasticai.preprocessor.adc.adc.TransientResampler.do_cut_labels

```{autodoc2-docstring} elasticai.preprocessor.adc.adc.TransientResampler.do_cut_labels
```

````

````{py:method} redefine_from_voltage(data: numpy.ndarray, is_int_output: bool = True) -> numpy.ndarray
:canonical: elasticai.preprocessor.adc.adc.TransientResampler.redefine_from_voltage

```{autodoc2-docstring} elasticai.preprocessor.adc.adc.TransientResampler.redefine_from_voltage
```

````

````{py:method} redefine_from_fxp(data: numpy.ndarray, is_int_output: bool = True) -> numpy.ndarray
:canonical: elasticai.preprocessor.adc.adc.TransientResampler.redefine_from_fxp

```{autodoc2-docstring} elasticai.preprocessor.adc.adc.TransientResampler.redefine_from_fxp
```

````

````{py:method} redefine_from_int(data: numpy.ndarray, is_int_output: bool = True) -> numpy.ndarray
:canonical: elasticai.preprocessor.adc.adc.TransientResampler.redefine_from_int

```{autodoc2-docstring} elasticai.preprocessor.adc.adc.TransientResampler.redefine_from_int
```

````

````{py:method} create_verilog_design(id: str, path2save: pathlib.Path, data: numpy.ndarray, trgg: list = []) -> None
:canonical: elasticai.preprocessor.adc.adc.TransientResampler.create_verilog_design

```{autodoc2-docstring} elasticai.preprocessor.adc.adc.TransientResampler.create_verilog_design
```

````

`````