{"version":"1.0","type":"rich","title":"Simple functions to calculate expected number of failures and workload in systems that can process a given number of subscribers in parallel, using a binomial distribution model to simulate subscriber behavior. Applicable e.g. to web servers & cellphone base stations.","description":"This example demonstrates how to estimate the expected workload and number of processing failures for a system with limited parallel capacity, such as a web server or cellphone base station. The code uses `scipy.stats.binom` to calculate the binomial probability mass function for each possible number of concurrent subscribers, then sums weighted contributions to derive the two metrics. The `workload` function computes the average percentage of capacity utilized, while `failures` sums the excess subscribers beyond the capacity limit. Both functions iterate over subscriber counts, applying the binomial distribution to model subscriber behavior at a given call probability.","provider_name":"VizHub AI Studio","provider_url":"https://next.vizhub.com","html":"<iframe src=\"https://next.vizhub.com/viz/gist-6104997?mode=embed\" width=\"960\" height=\"500\" scrolling=\"no\" frameborder=\"1\"></iframe>","width":960,"height":500,"cache_age":3600}