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First, users coming to KiCad from other tools have to adjust working with the new coordinate system. After years of a bottom-left coordinate system, getting used to top right is easier said then done (example: I still used Netlists in KiCad 5 because muscle memory is hard to forget).
Second, interoperability with other drawing tools is much harder when coordinate systems don't agree. At the very least, it will cost you a bit of time to translate X and Y numbers. At the worst, you could crash your robotic probe to Mars (doh!).
At the top of the KiCad 6 Pcbnew context menu is the Select item, which contains a few sub-functions including the selection filter (that is also accessible via the Appearance pane in the right toolset). It is interesting to note that the Select item is present in KiCad 5, but is found towards the middle of the context menu.
The last three tools allow you to quickly propagate pad properties across your PCB. This was not possible prior to KiCad 6, and you would need to manually reset pad properties if you needed to make changes.
The KiCad 6 Footprint editor has also received several upgrades. Both user interface elements, as well as drawing tools and how those apply to footprint design have received a lot of attention from the developers.
The most notable change in KiCad 6's Footprint Editor is the right toolset. It contains most of the familiar elements of the Pcbnew right toolset. To avoid repetition, I will not repeat the details of how each of these elements work here (please reffer to the Pcbnew segment for the details).
The CASA 6.x series is also available as modular packages, giving users the flexibility to build CASA tools and tasks in their own Python environment. This includes the casatools, casatasks, and casampi modules, allowing for core data processing capabilities in parallel.
Pip wheels for casatools and casatasks are available as Python 3 modules from the public PyPI server casa-pip.nrao.edu. This allows simple installation and import in to standard Python 3.6 environments. The casatools wheel is necessarily a binary wheel so there may be some compatibility issues for some time as we work toward making wheels available for important Python configurations. Initially, we are targeting Python 3.6 as provided by RedHat for our wheelproduction, with RH6 and RH7 as official supported platforms. We have had some success on other Linux-based platforms as well, but we do not recommend the use of Conda until compatibility with Conda is better understood. The modular pip-wheel version is also available for Mac OSX, but has not yet been as extensively tested as the Mac OS tarfile distribution or modular Linux RedHat version.
By default, pip will install the latest released version of the casatools and casatasks modules. An earlier released version of the pip wheels can be installed by adding the version number to the casatools and casatasks, e.g., casatools==126.96.36.199 (see this example). Adding casatools== (i.e., without version number) to the pip install command will list all available version numbers in the terminal.
WARNING: The pip-wheel modules for CASAviewer and CASAplotms, as well as other GUIs, are unvalidated. They are included in the full tar-file distribution, and we recommend to use of the tar-file for these GUIs. For the CASAviewer, specifically use the tasks imview (for images) and msview (for MSs). We also recommend to use the tar-file for add-on ALMA tools/tasks, such as wvrgcal. Additional testing is being performed to ensure that the pip-wheels for the GUIs and add-on ALMA tools/tasks canbe reliably offered as stand-alone modules in a subsequent CASA 6 release.
For the modular installation of individual packages in to a standard python environment, ensure that openmpi is installed on the host machine (RHEL: yum install openmpi-devel, Ubuntu: apt-get install libopenmpi-dev), then perform the following commands(from the venv in a Linux terminal after the previous installation of casatools and casatasks):
Jupyter notebooks are ideally suited for code tutorials, exploration, and collaborative development. Together with Google Colaboratory, which hosts Jupyter notebooks on free virtual hardware in the cloud, the door is opened to powerful new ways of developing and sharing software. CASA 6 casatools and casatasks modules are compatible with the Google Colab environment. The CASA team is working towards making additional modules compatible in the future as well as introducing new Jupyter-basedCASAguide tutorials.
All tasks throw exceptions as normal Python functions (the one or more top level try/except blocks that would trap all exceptions in 1/3+ of tasks have been removed or replaced in favor of finally blocks that clean up tools, etc. resources, see documentation on Python clean-up actions and the finally clause.
Amazon Web Services (AWS) is a collection of physical assets and software tools for using ad hoc computing resources (aka Cloud Computing) within Amazon. The combination of a wide range of processing hardware, network speeds, storage media and tools allows users to create virtual computing platforms tailored to specific problem sizes with discrete durations. 2b1af7f3a8