Data split based on election period and model is trained on each set, closes #15

german_analysis.py

@@ -3,19 +3,29 @@
 
 import voting_lib.load_data as ld
 import voting_lib.voting_analysis as va
+import numpy as np
 
-# Load data
-data = ld.load_german_data().to_numpy()
-X = data[:,2:]
-
-# Train model
-grid_h = 10       # Grid height
-grid_w = 10       # Grid width
+# Training Paramters
+grid_h = 2       # Grid height
+grid_w = 2       # Grid width
 radius = 2        # Neighbour radius
 step = 0.5
 ep = 300          # No of epochs
 
-model = va.train_model(X, grid_h, grid_w, radius, step, ep)
+# Load data
+dataset = ld.load_german_data()
+
+
+for period, df in dataset.items():
+
+    print("Election Period ", period)
+    data = df.to_numpy()
+    
+    X = data[:,2:]
+
+    # Train model
+    model = va.train_model(X, grid_h, grid_w, radius, step, ep)
+
+    # Predict and visualize output
+    va.predict(model, data, grid_h, grid_w)
 
-# Predict and visualize output
-va.predict(model, data, grid_h, grid_w)