Skip to main content

Calculate uncertainty measures from Monte Carlo sampled model outputs.

Project description

MC Uncertainty

Uncertainty estimation functions for use with Monte Carlo sampled model outputs.

Installation

pip install mc-uncertainty

Usage

import mc_uncertainty as mcu

# All functions accept data with shape (mc_samples, n, classes)
data = np.array(...

# Variance
print(mcu.variance(data).shape)  # [n, classes]

# Entropy
print(mcu.entropy(data).shape)  # [mc_samples, n]

# Predicted entropy
print(mcu.predicted_entropy(data).shape)  # [n,]

# Mutual information
print(mcu.mutual_information(data).shape)  # [n,]

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for mc-uncertainty, version 0.1.3
Filename, size File type Python version Upload date Hashes
Filename, size mc-uncertainty-0.1.3.tar.gz (1.5 kB) File type Source Python version None Upload date Hashes View

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring DigiCert DigiCert EV certificate Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page