A scripted control system for autonomous hardware-timed experiments.

We present the labscript suite, an open-source experiment control system for automating shot-based experiments and their analysis. Experiments are composed as Python code, which is used to produce low-level hardware instructions. They are queued up and executed on the hardware in real time, synchronized by a pseudoclock. Experiment parameters are manipulated graphically, and analysis routines are run as new data are acquired. With this system, we can easily automate exploration of parameter spaces, including closed-loop optimization.

Relation between night visit rates and deprivation measures in one general practice.

OBJECTIVE: To compare night visit rates in different electoral wards of one general practice with the Jarman and Townsend deprivation scores and unemployment rates. DESIGN: Analysis of computerised workload data. SETTING: General practice in centre of Mansfield, Nottinghamshire. OUTCOME MEASURE: Visits made in 588 nights to the 11,998 patients on the practice list. RESULTS: Night visit rates in 15 electoral wards varied from 19.6 to 55.3 visits per 1000 patients per year. The rates showed a significant association with the Townsend score (p = 0.004) and the unemployment rate (p = 0.03) but not with the Jarman score (p = 0.3). The Townsend score explained 49% of the variability; unemployment explained 31% and the Jarman score explained 9%. CONCLUSIONS: Even in a general practice not eligible for deprivation payments there was a 2.8-fold variation in night visit rates between wards. In this practice the Townsend score was significantly better at predicting night visit rates than the Jarman score. This method of looking at internal variation in workloads in computerised practices could give more direct data on the relation between deprivation and general practice workload than has previously been available.