# Python API

## <mark style="color:purple;">catch22\_all</mark>

Extract the *catch22* feature set from an input time series.

### **Syntax**

<pre class="language-python"><code class="lang-python"><strong>pycatch22.catch22_all(data, catch24=False, short_names=False)
</strong></code></pre>

### Parameters

| Parameter     | Type                                                                                    | Description                                                                                              |
| ------------- | --------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------- |
| `data`        | [array-like](https://numpy.org/doc/stable/user/basics.creation.html#array-like-objects) | Input time-series data.                                                                                  |
| `catch24`     | [bool](https://docs.python.org/3/library/stdtypes.html#boolean-values)                  | If True, include the two catch24 features (mean and standard deviation) in the output. Default is False. |
| `short_names` | [bool](https://docs.python.org/3/library/stdtypes.html#boolean-values)                  | If True, also include the short names of the features in the output. Default is False.                   |

***

### Return Value

The function returns a [dictionary](https://docs.python.org/3/library/stdtypes.html#dict) with the following keys:

| Key             | Type                                                         | Description                                          |
| --------------- | ------------------------------------------------------------ | ---------------------------------------------------- |
| `'names'`       | [list](https://docs.python.org/3/library/stdtypes.html#list) | List of feature names.                               |
| `'values'`      | [list](https://docs.python.org/3/library/stdtypes.html#list) | List of corresponding feature values.                |
| `'short_names'` | [list](https://docs.python.org/3/library/stdtypes.html#list) | List of short feature names (if `short_names=True`). |

***

### Example Usage

```python
import numpy as np
import pycatch22 as catch22

data = np.random.rand(100)
features = catch22_all(data)
print(features['names'])
# Output: ['DN_HistogramMode_5', 'DN_HistogramMode_10', 'CO_f1ecac', ..., 'SP_Summaries_welch_rect_centroid', 'FC_LocalSimple_mean3_stderr']
print(features['values'])
# Output: [0.23, 0.18, 1.52, ..., 0.04, 0.67]

features_with_catch24 = catch22_all(data, catch24=True)
print(features_with_catch24['names'][-2:])
# Output: ['DN_Mean', 'DN_Spread_Std']

features_with_short_names = catch22_all(data, short_names=True)
print(features_with_short_names['short_names'])
# Output: ['mode_5', 'mode_10', 'acf_timescale', ..., 'low_freq_power', 'forecast_error']

```

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## Individual Feature Methods

The `catch22` module provides direct access to the individual feature extraction methods implemented in C. These methods can be called directly using `pycatch22.{name}`, where `{name}` is the name of the feature method (as given by the **long** name in the [table of features](https://time-series-features.gitbook.io/catch22/information-about-catch22/feature-descriptions/feature-overview-table)).&#x20;

### Syntax

```python
pycatch22.DN_Mean(data)
```

### Parameters

| Parameter | Type                                                                                                                             | Description             |
| --------- | -------------------------------------------------------------------------------------------------------------------------------- | ----------------------- |
| `data`    | ([list](https://docs.python.org/3/library/stdtypes.html#list) or [tuple](https://docs.python.org/3/library/stdtypes.html#tuple)) | Input time-series data. |

### Return Values

| Value     | Type                                                                                                                             | Description                                                                        |
| --------- | -------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------- |
| `feature` | ([Int](https://docs.python.org/3/library/functions.html#int) or [Float](https://docs.python.org/3/library/functions.html#float)) | Individual feature value. Either integer or float depending on the feature method. |

### Example Usage

```python
import numpy as np
from pycatch22 import DN_Mean

data = list(np.random.randn(100))
individual_feature = DN_Mean(data)
print(individual_feature)
# Output: -0.11125506527054776
```

***