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https://github.com/claygregory/node-moves-cleaner
Node module to repair common quirks of Moves app location history
https://github.com/claygregory/node-moves-cleaner
location-history movesapp
Last synced: about 1 month ago
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Node module to repair common quirks of Moves app location history
- Host: GitHub
- URL: https://github.com/claygregory/node-moves-cleaner
- Owner: claygregory
- License: mit
- Created: 2017-05-31T23:26:49.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2018-12-31T00:34:57.000Z (about 6 years ago)
- Last Synced: 2024-11-10T04:57:10.740Z (about 2 months ago)
- Topics: location-history, movesapp
- Language: JavaScript
- Homepage:
- Size: 50.8 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
Awesome Lists containing this project
README
# Moves App Segment Cleaner
Having worked with data from the [Moves App](https://www.moves-app.com) —both from the API as well as manual JSON exports — I've noticed a few
recurring oddities I attempt to correct with this utility. Namely:
* Long stays at a single location (in excess of 24 hours) tend to get truncated, forming a time gap
* Occasionally a single stay or single move will get chopped into multiple segments
* Other time gaps inexplicably appear between segments, absent an 'off' segment
* Not specifically a problem, but multple consecutive movements (e.g. walking → transport → walking) are merged as activities under a single 'move' segment. I prefer these separated into separate segments to simplify analysis.
## Installation
```bash
npm install --save @claygregory/moves-cleaner
```
## Usage
For most applications, just call the single `apply` method on an array of segments. This will apply all of the normalization
functions in one go.
```javascript
const MovesCleaner = require('@claygregory/moves-cleaner');
const movesCleaner = new MovesCleaner();
const normalizedSegments = movesCleaner.apply([
{ type: 'move', activities: […], … },
{ type: 'place', activities: […], … },
…
]);
```
### Additional Methods
Normalization steps can also be applied individually. These include:
#### Close Gaps
Collapses the gap between two segments so long as no `off` segments are logged and the distance between the shoulder segments is within
a given threshold.
```javascript
movesCleaner.close_gaps([…]);
```
#### Filter Off Segments
Removes segments with a `type` value of `off`. The gaps in time remain, only the segments are removed.
```javascript
movesCleaner.filter_off_segments([…]);
```
#### Flatten Move Segments
Bubbles the individual activities of `move` segments up as standalone move segments.
```javascript
movesCleaner.flatten_move_segments([…]);
```
#### Merge Move Segments
Merges consecutive move segments of same type into a single segment. Track points are merged and start/end time, duration, and distance are corrected.
```javascript
movesCleaner.merge_move_segments([…]);
```
#### Merge Place Segments
Merges consecutive place segments with same place ID into a single segment. Start/end times are corrected.
```javascript
movesCleaner.merge_place_segments([…]);
```
#### Sort
Orders segments according to time. Many of the above methods assume time-ordered segments are provided.
```javascript
movesCleaner.sort_segments([…]);
```
### Options
Currently only one configuration option is available: `near_threshold_m` is used in gap detection to determine when the end of one segment is close enough to the beginning of next. Gaps are only closed between if endpoints are within threshold. The default is 100 meters.
```javascript
const MovesCleaner = require('@claygregory/moves-cleaner');
const movesCleaner = new MovesCleaner({
near_threshold_m: 250
});
```
## License
See the included [LICENSE](LICENSE.md) for rights and limitations under the terms of the MIT license.