def ellipses(sizes, correlations, mean, variance):
correlation = Correlation()
for size in sizes:
for rho in correlations:
x, y = correlation.multivariate_normal(mean, variance, rho, size)
ellipse = Ellipse(x, y, size, rho)
ellipse.plot()
def selective_correlation(sizes, n, correlations, mean, variance):
correlation = Correlation()
for size in sizes:
for rho in correlations:
correlation_pearson_sample = []
correlation_square_sample = []
correlation_spearman_sample = []
for _ in range(0, n):
x, y = correlation.multivariate_normal(mean, variance, rho,
size)
correlation_pearson_sample.append(
Correlation.pearson_correlation(x, y))
correlation_square_sample.append(
Correlation.square_correlation(x, y))
correlation_spearman_sample.append(
Correlation.spearman_correlation(x, y))
print_correlations([
correlation_pearson_sample, correlation_spearman_sample,
correlation_square_sample
], size, rho)
for size in sizes:
correlation_pearson_sample = []
correlation_square_sample = []
correlation_spearman_sample = []
for _ in range(0, n):
x, y = correlation.mixed_multivariate_normal(size)
correlation_pearson_sample.append(
Correlation.pearson_correlation(x, y))
correlation_square_sample.append(
Correlation.square_correlation(x, y))
correlation_spearman_sample.append(
Correlation.spearman_correlation(x, y))
print_correlations([
correlation_pearson_sample, correlation_spearman_sample,
correlation_square_sample
], size, -1)
