Commit 15547208 authored by Hugh Brown's avatar Hugh Brown

Add documentation for polaris batch + minor editing

Signed-off-by: Hugh Brown's avatarHugh Brown (Saint Aardvark the Carpeted) <[email protected]>
parent bc9605d9
......@@ -19,9 +19,11 @@ If you want to **know more**:
contrib/ - code that is not directly dependent on Polaris, but is used in the project
docs/ - Some documentation on the project (though more is in the wiki)
polaris/ - Project source code
common/ - Modules common to all of Polaris
fetch/ - Module to fetch and prepare data for the analysis
viz/ - Module to visualize the analysis results
learn/ - Module to perform the data analysis
batch/ - Module to perform batch operations
polaris.py - Polaris entry point
tests/ - Project unit tests
......@@ -59,10 +61,10 @@ Options:
--help Show this message and exit.
Commands:
fetch Download data set(s)
learn Analyze data
viz Display results
batch Run polaris commands in batch mode
fetch Download data set(s)
learn Analyze data
viz Displaying results
# To fetch and decode data from the SatNOGS network, run:
$ (.venv) polaris fetch -s 2019-08-10 -e 2019-10-5 LightSail-2 /tmp/
......@@ -91,11 +93,27 @@ $ (.venv) polaris learn -g /tmp/new_graph.json /tmp/normalized_frames.json
$ (.venv) polaris viz /tmp/new_graph.json
# Then visit http://localhost:8080 in your browser
```
## Batch operations
Batch operations allow automation of repeated steps. For example:
- running `polaris fetch` so that it fetches the latest data for a particular satellite, then running `polaris learn` to update the model
- running `polaris fetch`, `polaris learn` and `polaris viz` as part of an integration test
The `polaris batch` command is controlled by a JSON configuration file; an example can be found at `polaris/common/polaris_config.json.EXAMPLE`.
```bash
$ (.venv) polaris batch --config_file polaris/common/polaris_config.json.EXAMPLE
```
## MLflow
Installing Polaris will install MLflow as a dependency. At this time Polaris is using MLflow during the cross check dependencies process and the database is stored in the current working directory under the mlruns folder.
Installing Polaris will install MLflow as a dependency. At this time Polaris is using MLflow during the cross check dependencies process, and the database is stored in the current working directory under the mlruns folder.
To view the logs in MLflow, run this command in the directory that holds the `mlruns` folder (by default, this is the project root directory):
To view the logs into MLflow, you have to run that command line from where the mlruns folder is located :
```bash
$ mlflow ui
```
......
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