27 lines
1.5 KiB
Python
Executable File
27 lines
1.5 KiB
Python
Executable File
from scipy import stats
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import numpy as np
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# siemens_froc = [1.68,1.81,1.44,1.55]
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# b400_froc = [3.4,3.93,2.82,]
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# b800_froc = [1.58,1.99,1.36,1.6]
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# siemens_roc = [0.782, 0.732, 0.775, 0.854]
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b400_roc = [0.746, 0.814, 0.789, 0.763]
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b800_roc = [0.786, 0.731, 0.67, 0.782]
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# stat_test = stats.wilcoxon(siemens_froc,b800_froc,alternative='less')
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# print('froc stats siemens > b400',stat_test)
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# print(' Mean and std siemens froc:', np.mean(siemens_froc),'+-',np.std(siemens_froc))
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# print(' Mean and std b400 froc:', np.mean(b400_froc),'+-',np.std(b400_froc))
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# print(' Mean and std b800 froc:', np.mean(b800_froc),'+-',np.std(b800_froc))
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# print(' Mean and std siemens roc:', np.mean(siemens_roc),'+-',np.std(siemens_roc))
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print(' Mean and std b400 roc:', np.mean(b400_roc),'+-',np.std(b400_roc))
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print(' Mean and std b800 roc:', np.mean(b800_roc),'+-',np.std(b800_roc))
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# The test has been introduced in [4]. Given n independent samples (xi, yi) from a bivariate distribution
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# (i.e. paired samples), it computes the differences di = xi - yi. One assumption of the test is that the
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# differences are symmetric, see [2]. The two-sided test has the null hypothesis that the median of the
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# differences is zero against the alternative that it is different from zero. The one-sided test has the
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# null hypothesis that the median is positive against the alternative that it is negative
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# (alternative == 'less'), or vice versa (alternative == 'greater.'). |