Merge pull request #7 from uwescience/exporting_results

Exporting results

.github/workflows/noise_processing.yml

@@ -3,6 +3,11 @@ name: Ambient Sound Processing
 on:
   # To run manually
   workflow_dispatch:
+  push: 
+    branches:
+     - main
+     - exporting_results
+
   # schedule:
   #  - cron: '9 * * * *'
 
@@ -33,7 +38,22 @@ jobs:
       run: |
         python ambient_sound_analysis/noise_processing.py
 
-    - uses: stefanzweifel/git-auto-commit-action@v5
+    - name: Upload to GitHub repo
+      uses: stefanzweifel/git-auto-commit-action@v5
       with:
           commit_message: Commit to Github
           file_pattern: 'ambient_sound_analysis/img/*.png'
+
+    - name: Upload as artifact
+      uses: actions/upload-artifact@v4
+      with:
+        name: ambient_sound_plots
+        path: ambient_sound_analysis/img/*.png
+
+    - name: Upload to Google Drive
+      uses: AnimMouse/setup-rclone@v1
+      with:
+        rclone_config: ${{secrets.RCLONE_CONFIG}}
+
+    - run: |
+        rclone copy ambient_sound_analysis/img/broadband.png mydrive:rclone_uploads/

.github/workflows/test_rclone.yml

@@ -0,0 +1,26 @@
+name: Test Rclone
+
+on:
+  # To run manually
+  workflow_dispatch:
+#  push: 
+#    branches:
+#     - main
+#     - exporting_results
+
+  # schedule:
+  #  - cron: '9 * * * *'
+
+jobs:
+  process:
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v4
+
+    - name: Upload to Google Drive
+      uses: AnimMouse/setup-rclone@v1
+      with:
+        rclone_config: ${{secrets.RCLONE_CONFIG}}
+
+    - run: |
+        rclone copy ambient_sound_analysis/img/broadband.png mydrive:rclone_uploads/

ambient_sound_analysis/noise_processing.py

@@ -15,7 +15,7 @@
 # Set Location and Resolution
 # Port Townsend, 1 Hz Frequency, 60-second samples
 if __name__ == '__main__':
-    pipeline = NoiseAnalysisPipeline(Hydrophone.PORT_TOWNSEND,
+    pipeline = NoiseAnalysisPipeline(Hydrophone.ORCASOUND_LAB,
                                      delta_f=10, bands=None,
                                      delta_t=60, mode='safe')
 
@@ -25,8 +25,8 @@
 # Generate parquet dataframes with noise levels for a time period
 
 now = dt.datetime.now(pytz.timezone('US/Pacific'))
-psd_path, broadband_path = pipeline.generate_parquet_file(now - dt.timedelta(hours = 6), 
-                                                          now - dt.timedelta(hours = 1), 
+psd_path, broadband_path = pipeline.generate_parquet_file(now - dt.timedelta(hours = 9), 
+                                                          now - dt.timedelta(hours = 8), 
                                                           upload_to_s3=False)
 
 # Read the parquet files