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feat: Warning added when trying to estimate a covariance matrix from
observables with too few samples.
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@ -1354,6 +1354,11 @@ def covariance(obs, visualize=False, correlation=False, **kwargs):
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'''
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'''
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length = len(obs)
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length = len(obs)
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max_samples = np.max([o.N for o in obs])
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if max_samples <= length:
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warnings.warn(f"The dimension of the covariance matrix ({length}) is larger or equal to the number of samples ({max_samples}). This will result in a rank deficient matrix.", RuntimeWarning)
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cov = np.zeros((length, length))
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cov = np.zeros((length, length))
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for i in range(length):
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for i in range(length):
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for j in range(i, length):
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for j in range(i, length):
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