# Real-time accuracy of trigger output generation

For each behavioral session with real-time trigger generation, we created a single DeepLabCut project dedicated for _post hoc_ estimation of whisker tips to use it as the "ground-truth" data.

Based on this ground-truth dataset, we computed the conditional probability of trigger generation for the whiskers being located at each position to characterize the accuracy of trigger output signals.

## 1. Analyzed data

The `analyzed-data.h5` HDF5 file contains infomation on each video.

### 1-1. Code

The code to generate this dataset is found in `01_data-formatting.ipynb`, and the panels generated during the procedures are in:

- `F01_trace-comparison`: comparison of traces between real-time and post-hoc estimation.
- `F02_densities`: plots of dwell-time histograms used in the paper.
- `F03_conditional-probability`: plots of conditional probability densities used in the paper.

### 1-2. Entries in `analyzed-data.h5`

Each video comprises one entry under the root, numbered as 001, 002, etc.

#### Attributes

Attributes of each entry contains the information of the video, such as:

- `subject`: name of the animal.
-  `session`: name of the behavioral session.
-  `run`: the index / starting time stamp of the video.
- `expression`: the expression used to turn the positions of whisker tips into the status of trigger output.
- `px_per_mm`: the scale information computed from the video.

#### Subgroups

1. **"pose"** group store the estimation of each whisker-tip positions. It contains two subgroups corresponding to `realtime` and `posthoc` estimations.
2. **"evaluation"** group store the result of evaluation. Traces in `realtime` and `posthoc` store the values of `expression` at given `time`. The `trigger` data holds the output of the evaluation.
3. **"densities"** group stores the dwell-time histograms generated using the kernel-density estimation method.
   - `kernel`: the attributes contain the information of the Gaussian kernel (in pixels) used for kernel density estimation.
   - `positions`: the list of positions (in pixels) used to estimate the dwell-time density.
   - `all`: the values of dwell-time densities, during the whole recording period of the video, based on the _post hoc_ estimation.
   - `triggered`: the values of dwell-time densities, when the real-time trigger was active, based on the _post hoc_ estimation.
4. **"conditional"** group stores the information on conditional probability of trigger generation.
   - `positions`: the list of positions (in pixels) used to compute conditional probability.
   - `probability`: the values of conditional probability at given `position`.
   - `sigmoid`: the attributes (in pixels) contain the information on the sigmoid curve (we used the cumulative of Gaussian) fitted to the trace of conditional probability distribution.

## 2. Summary data

Several types of summary data are found here:

- `02_summary.ipynb` is the Jupyter notebook used to summarize the data in `analyzed-data.h5`.
- `F04_summary` contains the panels generated by the above notebook (and used in the paper).
- `stats.md` stores the statistical information analyzed in the above notebook.