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import numpy as np |
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def calculate_gini_simpson(dictionary): |
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""" |
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Function to Calculate Gini Simpson's Diversity Index |
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""" |
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total = sum(dictionary.values()) |
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sum_squares = sum((n / total) ** 2 for n in dictionary.values()) |
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return 1 - sum_squares |
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def calculate_gini(frequencies): |
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""" |
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Function to Calculate Gini's Diversity Index |
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""" |
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frequencies = np.array(frequencies) |
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if len(frequencies) == 0 or np.mean(frequencies) == 0: |
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return None |
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total = sum( |
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np.sum(np.abs(xi - frequencies[i:])) |
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for i, xi in enumerate(frequencies[:-1], 1) |
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) |
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return total / (len(frequencies) ** 2 * np.mean(frequencies)) |
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