SciPy 1.0: fundamental algorithms for scientific computing in Python.

SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments

No Effect of Interstimulus Interval on Acoustic Reflex Thresholds

The acoustic reflex (AR), a longstanding component of the audiological test battery, has received renewed attention in the context of noise-induced cochlear synaptopathy-the destruction of synapses between inner hair cells and auditory nerve fibers. Noninvasive proxy measures of synaptopathy are widely sought, and AR thresholds (ARTs) correlate closely with synaptic survival in rodents. However, measurement in humans at high stimulus frequencies-likely important when testing for noise-induced pathology-can be challenging; reflexes at 4 kHz are frequently absent or occur only at high stimulus levels, even in young people with clinically normal audiograms. This phenomenon may partly reflect differences across stimulus frequency in the temporal characteristics of the response; later onset of the response, earlier onset of adaptation, and higher rate of adaptation have been observed at 4 kHz than at 1 kHz. One temporal aspect of the response that has received little attention is the interstimulus interval (ISI); inadequate duration of ISI might lead to incomplete recovery of the response between successive presentations and consequent response fatigue. This research aimed to test for effects of ISI on ARTs in normally hearing young humans, measured at 1 and 4 kHz. Contrary to our hypotheses, increasing ISIs from 2.5 to 8.5 s did not reduce ART level, nor raise ART reliability. Results confirm that clinically measured ARTs-including those at 4 kHz-can exhibit excellent reliability and that relatively short (2.5 s) ISIs are adequate for the measurement of sensitive and reliable ARTs

Changing computational research. The challenges ahead

EDITORIAL The past year has been an interesting one for those interested in reproducible research. There have been great examples of replicability [1, 2] in research communication, and examples of horrifying failure of reproducibility (as described in [3]) with serious questions being raised on the ability of our current system of research communication to guarantee, or even encourage, that published research be reproducible or replicable. When we launched the call for papers for Open Research Computation in late 2010 we saw a clear need for higher standards. Computational research should stand out as an exemplar of just how reproducible research can be, yet it falls short more often than not. With modern computational tools it is entirely possible to provide packages which allow direct replication of results. It is possible to provide data and code in the form of a functional virtual machine image along with automated tests to ensure everything is working as expected. But alongside this we can support the reader’s ability to modify and re-purpose tools, to run them against new data, indeed to support efforts to deliberately break the system to identify its limitations. In short, to do what we are supposed to do as scientists – replicate, reproduce, and test the limits of our models and understanding