# ISX Algorithms

The library includes an `ISXModule` that allows running the main algorithms for calcium imaging video analysis.\
Each function in the module represents a **step** that can be added to the pipeline and executed in order.

***

#### Available Functions

Each ISX function receives the pipeline inputs and has specific parameters, which can be overwritten for each step call.

**Main functions and their purpose:**

* `preprocess_videos()`: Preprocesses videos applying temporal and spatial downsampling, cropping, and defective pixel correction.
* `bandpass_filter_videos()`: Applies a spatial bandpass filter to the videos.
* `motion_correction_videos()`: Corrects motion in the videos and generates auxiliary outputs (translations, crop rects, mean images).
* `normalize_dff_videos()`: Normalizes fluorescence data for each cell (dF/F).
* `extract_neurons_pca_ica()`: Extracts neuronal signals using PCA and ICA.
* `detect_events_in_cells()`: Detects neuronal events in the extracted cells.
* `auto_accept_reject_cells()`: Automatically filters cells based on detected events.
* `export_movie_to_tiff()`: Exports processed videos to TIFF.
* `export_movie_to_nwb()`: Exports processed videos to NWB.

***

#### Example of Overwriting Parameters

```python
pipeline.set_defaults(
    isx_bp_subtract_global_minimum=False,
    isx_mc_max_translation=25,
    isx_acr_filters=[('SNR', '>', 3), ('Event Rate', '>', 0), ('# Comps', '=', 1)]
)

pipeline.isx.motion_correction_videos(isx_mc_series_name="series1")
```

In this example, the `isx_mc_series_name` parameter is overwritten for this step only, while the other values are taken from the pipeline defaults.

***

#### Executing Multiple Steps

Steps can be chained to run the full ISX analysis sequence cumulatively:

```
pipeline
    .set_defaults(isx_bp_subtract_global_minimum=False, isx_mc_max_translation=25, isx_acr_filters=[('SNR', '>', 3), ('Event Rate', '>', 0), ('# Comps', '=', 1)])
    .isx.preprocess_videos()
    .isx.bandpass_filter_videos()
    .isx.motion_correction_videos(isx_mc_series_name="series1")
    .isx.normalize_dff_videos()
    .isx.extract_neurons_pca_ica()
    .isx.detect_events_in_cells()
    .isx.auto_accept_reject_cells()

```

Each function generates its outputs, which are stored in folders inside the pipeline `output_directory` (as described in the **Step Execution and Structure** section) with the following naming convention:\
`<branch_name> - Step <number> - <function_name>`

Inside each folder, the files produced by the corresponding step are stored (one or multiple, depending on the function).


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