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load political compass data for uk in uk analysis

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Hannes Kuchelmeister
2021-05-20 13:36:13 +02:00
parent ee7480e53a
commit 7fd22ccbc6
1 changed files with 5 additions and 3 deletions
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8
uk_analysis.py
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@@ -5,6 +5,7 @@
import voting_lib.load_data as ld import voting_lib.load_data as ld
import voting_lib.voting_analysis as va import voting_lib.voting_analysis as va
import voting_lib.political_compass as pc
import numpy as np import numpy as np
import pandas as pd import pandas as pd
import os import os
@@ -16,14 +17,15 @@ grid_h = 30 # Grid height
grid_w = 30 # Grid width grid_w = 30 # Grid width
radius = 3 # Neighbour radius radius = 3 # Neighbour radius
step = 0.5 step = 0.5
ep = 100 # No of epochs ep = 1 # No of epochs
period_to_compass_year = {'2015_uk':2015, '2017_uk':2017, '2019_uk':2019}
main_directory = 'uk/csv' main_directory = 'uk/csv'
for dirname, _, filenames in os.walk(main_directory): for dirname, _, filenames in os.walk(main_directory):
if dirname == main_directory: #to skip main directory path if dirname == main_directory: #to skip main directory path
continue continue
else: elif os.path.isdir(dirname):
# Load data # Load data
data = ld.load_uk_data(dirname).to_numpy() data = ld.load_uk_data(dirname).to_numpy()
@@ -31,4 +33,4 @@ for dirname, _, filenames in os.walk(main_directory):
model = va.train_model(X, grid_h, grid_w, radius, step, ep) model = va.train_model(X, grid_h, grid_w, radius, step, ep)
# Predict and visualize output # Predict and visualize output
va.predict(model, data, grid_h, grid_w) va.predict(model, data, grid_h, grid_w, pc.get_compass_parties(year=period_to_compass_year[dirname.split('/')[-1]], country='uk'))