Update docs; and readme

MANIFEST.in

@@ -5,4 +5,5 @@ include ./ethome/data/sample_nwb_.nwb
 include ./ethome/data/videos/m3v1mp4.mp4
 recursive-include ./ethome/data/dlc *.csv
 recursive-include ./ethome/data/boris *.csv
+recursive-include ./ethome/data/sleap *.h5
 recursive-include ./ethome/features/pretrained_models *

README.md

@@ -160,6 +160,14 @@ Sample notebooks are available ([here](https://github.com/benlansdell/ethome/tre
 
 Refer to `CONTRIBUTING.md` for guidelines on how to contribute to the project, and report bugs, etc.
 
+## Development
+
+You can setup your dev environment using the conda `yaml` file provided. Compiling the docs requires the following packages are also installed:
+
+```
+pip install mkdocs-material mkdocs-awesome-pages-plugin twine build
+```
+
 ## Animal data
 
 Sample data was obtained from resident-intruder open field recordings performed as part of on going social memory studies performed in the Zakharenko lab at St Jude Children's Research Hospital (e.g. [1,2]). All animal experiments were reviewed and approved by the Institutional Animal Care & Use Committee of St. Jude Children’s Research Hospital.

docs/api-docs/README.md

@@ -4,8 +4,8 @@
 
 ## Modules
 
-- [`interpolation`](./interpolation.md#module-interpolation)
-- [`io`](./io.md#module-io): Loading and saving tracking and behavior annotation files
+- [`interpolation`](./interpolation.md#module-interpolation): Interpolate over low confidence data
+- [`io`](./io.md#module-io): Loading and saving tracking and behavior annotation files 
 - [`utils`](./utils.md#module-utils): Small helper utilities
 - [`video`](./video.md#module-video): Basic video tracking and behavior class that houses data
 
@@ -29,6 +29,7 @@
 - [`io.get_sample_data`](./io.md#function-get_sample_data): Load a sample dataset of 5 mice social interaction videos. Each video is approx. 5 minutes in duration
 - [`io.get_sample_data_paths_dlcboris`](./io.md#function-get_sample_data_paths_dlcboris): Get path to sample data files provided with package.
 - [`io.get_sample_nwb_paths`](./io.md#function-get_sample_nwb_paths): Get path to a sample NWB file with tracking data for testing and dev purposes.
+- [`io.get_sample_sleap_paths`](./io.md#function-get_sample_sleap_paths): Get path to a sample SLEAP h5 file with tracking data for testing and dev purposes.
 - [`io.load_data`](./io.md#function-load_data): Load an object from a pickle file
 - [`io.load_sklearn_model`](./io.md#function-load_sklearn_model): Load sklearn model from file
 - [`io.read_DLC_tracks`](./io.md#function-read_dlc_tracks): Read in tracks from DLC.

docs/api-docs/interpolation.md

@@ -3,14 +3,12 @@
 <a href="https://github.com/benlansdell/ethome/blob/master/ethome/interpolation.py#L0"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>
 
 # <kbd>module</kbd> `interpolation`
-
-
-
+Interpolate over low confidence data 
 
 
 ---
 
-<a href="https://github.com/benlansdell/ethome/blob/master/ethome/interpolation.py#L4"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>
+<a href="https://github.com/benlansdell/ethome/blob/master/ethome/interpolation.py#L7"><img align="right" style="float:right;" src="https://img.shields.io/badge/-source-cccccc?style=flat-square"></a>
 
 ## <kbd>function</kbd> `interpolate_lowconf_points`
 
@@ -24,22 +22,22 @@ interpolate_lowconf_points(
 ) → DataFrame
 ```
 
-Interpolate raw tracking points if their probabilities are available.
+Interpolate raw tracking points if their probabilities are available. 
 
 
 
 **Args:**
-
- - <b>`edf`</b>:  pandas DataFrame containing the tracks to interpolate
- - <b>`conf_threshold`</b>:  default 0.9. Confidence below which to count as uncertain, and to interpolate its value instead
- - <b>`in_place`</b>:  default True. Whether to replace data in place
- - <b>`rolling_window`</b>:  default True. Whether to use a rolling window to interpolate
- - <b>`window_size`</b>:  default 3. The size of the rolling window to use
+ 
+ - <b>`edf`</b>:  pandas DataFrame containing the tracks to interpolate 
+ - <b>`conf_threshold`</b>:  default 0.9. Confidence below which to count as uncertain, and to interpolate its value instead 
+ - <b>`in_place`</b>:  default True. Whether to replace data in place 
+ - <b>`rolling_window`</b>:  default True. Whether to use a rolling window to interpolate 
+ - <b>`window_size`</b>:  default 3. The size of the rolling window to use 
 
 
 
 **Returns:**
- Pandas dataframe with the filtered raw columns. Returns None if opted for in_place modification
+ Pandas dataframe with the filtered raw columns. Returns None if opted for in_place modification