49 lines
1.2 KiB
Python
49 lines
1.2 KiB
Python
import csv
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import matplotlib.pyplot as plt
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from scipy import stats
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import pandas as pd
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def plot(l):
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labels = ['0-10k', '10k-20k,', '20k-30k', '30k-40k', '40k-50k', '50k-60k', '60k-70k']
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l = [i/15625 for i in l]
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l = l[:7]
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plt.bar(labels, l)
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plt.savefig('plot.png')
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def analyse(filename):
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l = [0 for i in range(10)]
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scores = []
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count = 0
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best_value = -1
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with open(filename) as file:
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reader = csv.reader(file)
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header = next(reader)
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data = [row for row in reader]
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for row in data:
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score = row[0]
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best_value = max(best_value, float(score))
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# print(score)
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ind = float(score) // 10000
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ind = int(ind)
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l[ind] += 1
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acc = row[1]
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index = row[2]
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datas = list(zip(score, acc, index))
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scores.append(score)
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print(max(scores))
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results = pd.DataFrame(datas, columns=['swap_score', 'valid_acc', 'index'])
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print(results['swap_score'].max())
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print(best_value)
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plot(l)
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return stats.spearmanr(results.swap_score, results.valid_acc)[0]
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if __name__ == '__main__':
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print(analyse('output/swap_results.csv'))
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