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rename german analysis to match uk
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@@ -12,12 +12,12 @@ grid_h = 11 # Grid height
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grid_w = 11 # Grid width
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radius = 2 # Neighbour radius
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step = 0.5
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ep = 300 # No of epochs
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ep = 100 # No of epochs
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# Load data
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dataset = ld.load_german_data()
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years = {17:2005, 18:2013, 19:2017}
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period_to_compass_year = {17:2005, 18:2013, 19:2017}
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for period, df in dataset.items():
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@@ -30,5 +30,5 @@ for period, df in dataset.items():
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model = va.train_model(X, grid_h, grid_w, radius, step, ep)
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# Predict and visualize output
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va.predict(model, data, grid_h, grid_w, pc.get_compass_parties(year=years[period], country='de'))
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va.predict(model, data, grid_h, grid_w, pc.get_compass_parties(year=period_to_compass_year[period], country='de'))
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