![]() To turn them back on, check Settings > Preferences > Elements > Show CSS documentation tooltip.ĭevTools pulls the descriptions for tooltips from VS Code Custom Data.Ĭhromium issue: 1401107. ![]() If you know CSS well, you might find the tooltips bothersome. The tooltip also has a Learn more link that takes you to an MDN CSS Reference on this property. How many times a day do you look up documentation on CSS properties? The Elements > Styles pane now shows you a short description when you hover over a property. # Elements > Styles updates # CSS documentation We look forward to seeing yours on the list!Ĭhromium issues: 1417104, 1413168. Get extensions for the Recorder by clicking the Export > Get extensions in a recording.įeel free to add your own extension to the list of Recorder Extensions. # Get extensionsĮxplore options to customize your recorder experience, for example, with custom export options. Run the Puppeteer script to get a Lighthouse report in a file. Open your recording, click Export, select the new option, and save the. With Lighthouse, you can capture and improve your website's performance. With Puppeteer, you can automate and control Chrome. The Recorder introduces a new export option: Puppeteer (including Lighthouse analysis). # Export as a Puppeteer script with Lighthouse analysis Record your interaction with elements in the shadow DOM and inspect the corresponding step.Ĭhromium issue: 1411188. Start a new recording on a page with shadow DOM and check Pierce in Selector types to record. These selectors behave like CSS ones but can also pierce through shadow roots. In addition to custom, CSS, ARIA, text, and XPath selectors, you can now record using pierce selectors. To customize the Recorder to your needs and integrate it with your tools, consider developing your own extension: explore the API and check out more extension examples.Ĭhromium issue: 1400243. Select the new custom replay option to open the custom replay UI. The Recorder introduces support for custom replay options that you can embed into DevTools with an extension. ![]() The resulting LFI framework is applicable to population-level inference problems with selection effects across astrophysics.# Recorder updates # Replay extensions support Marginalizing over the bias increases the H 0 uncertainty by only 6% for training sets consisting of O ( 10 4 ) populations. We demonstrate that LFI yields statistically unbiased estimates of H 0 in the presence of selection effects, with precision matching that of sampling the full Bayesian hierarchical model. Here, we use density-estimation LFI, coupled to neural-network-based data compression, to infer H 0 from mock catalogues of binary neutron star mergers, given noisy redshift, distance and peculiar velocity estimates for each object. This calculation can, however, be bypassed completely by performing the inference in a framework in which the likelihood is never explicitly calculated, but instead fit using forward simulations of the data, which naturally include the selection. In the traditional Bayesian framework, accounting for selection effects in the likelihood requires calculation of the expected number (or fraction) of detections as a function of the parameters describing the population and cosmology a potentially costly and/or inaccurate process. Multimessenger observations of binary neutron star mergers offer a promising path toward resolution of the Hubble constant ( H 0) tension, provided their constraints are shown to be free from systematics such as the Malmquist bias.
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