Metadata-Version: 2.1
Name: mc-uncertainty
Version: 0.1.1
Summary: Calculate uncertainty measures from Monte Carlo sampled model outputs.
Home-page: https://github.com/tayden/mc-uncertainty
Author: Taylor Denouden
Author-email: taylordenouden@gmail.com
License: MIT
Description: # MC Uncertainty
        Uncertainty estimation functions for use with Monte Carlo sampled model outputs.
        
        ## Installation
        
        `pip install mc-uncertainty`
        
        ## Usage
        
        ```python
        # All functions accept data with shape (mc_samples, n, classes)
        data = np.array(...
        
        # Variance
        from mc_uncertainty import variance
        print(variance(data))  # shape: [n, classes]
        
        # Entropy
        from mc_uncertainty import entropy
        print(entropy(data))  # shape: [mc_samples, n]
        
        # Predicted entropy
        from mc_uncertainty import predicted_entropy
        print(predicted_entropy(data))  # shape: [n,]
        
        # Mutual information
        from mc_uncertainty import mutual_information
        print(mutual_information(data))  # shape: [n,]
        ```
Platform: UNKNOWN
Description-Content-Type: text/markdown
