2dc2c2564c24dc67d1b997a0e45674d85b43abb3,hyperspy/learn/mva.py,MVA,plot_explained_variance_ratio,#MVA#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,924

Before Change

        
        s = self.get_explained_variance_ratio()

        if n is None:
            n = len(self.learning_results.explained_variance_ratio)

        // Determine right number of components for signal and cutoff value
        if isinstance(threshold, float):
            if not 0 < threshold < 1:
                raise ValueError("Variance threshold should be between 0 and"
                                 " 1")

After Change

        s = self.get_explained_variance_ratio()

        n_max = len(self.learning_results.explained_variance_ratio)
        if n is None:
            n = n_max
        elif n > n_max:
            _logger.info("n is too large, setting n to its maximal value.")
            n = n_max

        // Determine right number of components for signal and cutoff value
        if isinstance(threshold, float):
            if not 0 < threshold < 1:
                raise ValueError("Variance threshold should be between 0 and"
                                 " 1")

Instances