From fc0071fd55a6906ee7271bc550198a86a97a2916 Mon Sep 17 00:00:00 2001 From: Liam Arbuckle Date: Thu, 4 Jul 2024 11:24:30 +0200 Subject: [PATCH] =?UTF-8?q?=F0=9F=A4=AD=F0=9F=8C=8A=20=E2=86=9D=20[GP-44?= =?UTF-8?q?=20GP-45]:=20Pipeline=20for=20new=20anomalies=20AND=20all=20ima?= =?UTF-8?q?ges?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- base.png | Bin 21312 -> 0 bytes binned.png | Bin 40014 -> 0 bytes {views => galaxy/views}/Unity/retrieveData.cs | 0 {views => galaxy/views}/Unity/tests/get.py | 0 .../views}/Unity/unity-integration.py | 0 {views => galaxy/views}/Unity/unitySetup.sql | 0 {views => galaxy/views}/__init__.py | 0 {views => galaxy/views}/lightkurve.py | 0 phased.png | Bin 21524 -> 0 bytes snippets/createAnomalies.py | 23 ++++++++++++------ snippets/output/binned_light_curves.png | Bin 0 -> 26584 bytes snippets/output/individual_light_curves.png | Bin 0 -> 30966 bytes snippets/output/smoothed_light_curves.png | Bin 0 -> 109719 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Client +import re # Import the regex library # Initialize Supabase client supabase_url = 'https://hlufptwhzkpkkjztimzo.supabase.co' @@ -16,6 +17,13 @@ def upload_to_supabase(filepath, bucket_name, folder_name, file_name): # Function to insert a new anomaly and get its ID def insert_anomaly(tic_id): + # Extract the numeric part of the TIC ID for use as the id + match = re.search(r'\d+', tic_id) + tic_id_numeric = int(match.group()) if match else None + + if tic_id_numeric is None: + raise ValueError("TIC ID must contain a numeric value to be used as the anomaly ID.") + configuration = { "mass": None, "ticId": tic_id, @@ -28,6 +36,7 @@ def insert_anomaly(tic_id): } data = { + "id": tic_id_numeric, # Use the numeric part of the TIC ID as the primary key "content": tic_id, "ticId": tic_id, "anomalytype": "planet", @@ -35,7 +44,7 @@ def insert_anomaly(tic_id): "configuration": configuration } - response = supabase.table("anomalies").insert(data).execute() + response = supabase.table("anomalies").upsert(data).execute() anomaly_id = response.data[0]['id'] return anomaly_id @@ -47,8 +56,8 @@ def generate_lightcurves(tic_id, output_dir): lc_collection = select_sector.download_all() # Plot individual light curves - lc = select_sector.download_all() fig1, ax1 = plt.subplots() + lc = select_sector.download_all() lc.plot(ax=ax1, linewidth=0, marker='.', markersize=1, color='midnightblue', alpha=0.3) fig1.savefig(os.path.join(output_dir, 'individual_light_curves.png')) plt.close(fig1) @@ -61,7 +70,7 @@ def generate_lightcurves(tic_id, output_dir): plt.close(fig2) # Bin the light curves with a larger bin time - bin_time = 1 / 24 # 1-hour binning + bin_time = 15 / 24 / 60 # 15-minute binning lc_collection_binned = lc_collection_stitched.bin(bin_time) fig3, ax3 = plt.subplots() lc_collection_binned.plot(ax=ax3, linewidth=0, marker='o', markersize=4, color='red', alpha=0.7) @@ -76,11 +85,11 @@ def generate_lightcurves(tic_id, output_dir): fig4.savefig(os.path.join(output_dir, 'stitched_and_binned_light_curves.png')) plt.close(fig4) - # Optional: Zoom in on a specific time range to highlight transits + # Zoom in on a specific time range to highlight transits fig5, ax5 = plt.subplots(figsize=(10, 5)) lc_collection_stitched.plot(ax=ax5, linewidth=0, marker='.', markersize=1, color='midnightblue', alpha=0.3, label='Unbinned') lc_collection_binned.plot(ax=ax5, linewidth=0, marker='o', markersize=4, color='red', alpha=0.7, label='Binned') - ax5.set_xlim(lc_collection_stitched.time.min().value, lc_collection_stitched.time.min().value + 10) # Example zoom range + ax5.set_xlim(lc_collection_stitched.time.min().value, lc_collection_stitched.time.min().value + 5) # Adjust zoom range here ax5.legend() fig5.savefig(os.path.join(output_dir, 'zoomed_light_curves.png')) plt.close(fig5) @@ -112,5 +121,5 @@ def main(tic_ids): print(f"Processed TIC ID {tic_id}, Anomaly ID: {anomaly_id}") if __name__ == "__main__": - tic_ids_list = 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