feat: update analysis server to return computed steady state frequenc…

…y averages
NEUROFUSIONInc · Dec 21, 2023 · 3367bd7 · 3367bd7
1 parent aafc39c
commit 3367bd7
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Showing 2 changed files with 22 additions and 12 deletions.
diff --git a/analysis_server/app.py b/analysis_server/app.py
@@ -7,12 +7,19 @@
 import time
 from PIL import Image
 from flask_cors import CORS
+import base64
 
 import eeg
 
 app = Flask(__name__)
 CORS(app, resources={r"/api/*": {"origins": "*"}})
 
+
+def encode_image_to_base64(image_path):
+    with open(image_path, "rb") as image_file:
+        encoded_string = base64.b64encode(image_file.read()).decode('utf-8')
+    return encoded_string
+
 # TODO: handle multiple files
 @app.route('/api/v1/process_eeg', methods=['POST'])
 def process():
@@ -66,14 +73,23 @@ def process():
             powerComparisonImage = Image.fromarray(powerComparisonData)
             powerComparisonImage.save("powerComparisons.png")
 
+            powerDistributionBase64= encode_image_to_base64("powerDistributions.png")
+            powerComparisonBase64 = encode_image_to_base64("powerComparisons.png")
 
-            # remember to delete folder after processing
-            return jsonify({"files": os.listdir(temp_dir)}), 200
+            # do foof analysis and display that
+
+            # # remember to delete folder after processing
+            return jsonify({"images": {
+                "powerDistribution": powerDistributionBase64,
+                "powerComparison": powerComparisonBase64
+            }, "summary": "Steady State Frequency Averages from Recordings"}), 200
 
     except Exception as e:
         print("error", e)
         return jsonify({'error': str(e)}), 500
 
+# TODO: endpoint for ERP analysis
+
 
 if __name__ == '__main__':
     app.run(debug=True, port=8000)

diff --git a/analysis_server/eeg.py b/analysis_server/eeg.py
@@ -299,7 +299,7 @@ def load_session_epochs(files: dict, _on: set, _channels: list = [],qualityCutof
 
     return on
 
-def load_session_summery(files: dict, _channels: list = [], qualityCutoffFilter: int = 0, epochSize: int = -1, returnEpoched = False, debug=False) -> dict:
+def load_session_summary(files: dict, _channels: list = [], qualityCutoffFilter: int = 0, epochSize: int = -1, returnEpoched = False, debug=False) -> dict:
     """
     Takes a session of EEG data, computes some metrics, and returns them.
     
@@ -457,10 +457,10 @@ def __init__(self,fileBundles: dict,epochSize=5, qualityCutoffFilter=0.95, debug
             if bundleType == "tags": # this means it's a dict of datasets based on tags
                 # this means it's an array of datasets based on tags
                 for y in self.fileBundles[x]:
-                    self.fileBundleSummeries[x].append(load_session_summery(self.fileBundles[x][y],qualityCutoffFilter=qualityCutoffFilter,epochSize=epochSize,returnEpoched=True,debug=debug))
+                    self.fileBundleSummeries[x].append(load_session_summary(self.fileBundles[x][y],qualityCutoffFilter=qualityCutoffFilter,epochSize=epochSize,returnEpoched=True,debug=debug))
                     sum += len(self.fileBundleSummeries[x][-1])
             elif bundleType == "ids":
-                self.fileBundleSummeries[x].append(load_session_summery(self.fileBundles[x],qualityCutoffFilter=qualityCutoffFilter,epochSize=epochSize,returnEpoched=True,debug=debug))
+                self.fileBundleSummeries[x].append(load_session_summary(self.fileBundles[x],qualityCutoffFilter=qualityCutoffFilter,epochSize=epochSize,returnEpoched=True,debug=debug))
                 sum += len(self.fileBundleSummeries[x])
             else:
                 raise Exception("Invalid bundleType")
@@ -736,10 +736,4 @@ def load_fileset(
             continue
         *type, session = f.stem.split("_")
         sessions[session]["_".join(type)] = str(f)
-    return sessions
-
-
-if __name__ == "__main__":
-    df = load_data()
-    print(df)
-    print(df.describe())
+    return sessions