Of course, all software has bugs, neither Octave or Matlab (yes, Matlab too) are safe from them. So the answer to your first question is yes in theory.
The different backend can be used for inline In theory, all code that runs in Matlab should run in Octave and Octave developers treat incompatibility with Matlab as bugs. The inline toolkit is the graphics_toolkit used to generate plots for the inlineīackend. Init file is explicitly called after the kernel has set more off to preventĪ lockup when the pager is invoked in ~/.octaverc. The cli options be appended to theĭefault opions of -interactive -quiet -no-init-file. The command line options to Octave can also be specified with an The path to the Octave kernel JSON file can also be specified by creating an # use Qt as the default backend for plotsĬ.ot_settings = dict(backend= 'qt ')
#Scilab vs octave install#
Python -m octave_kernel install -help for available options. Octave kernel, and install using python -m octave_kernel install. If the default location is not desired, remove the directory for the This location can be found using jupyter kernelspec list. We automatically install a Jupyter kernelspec when installing the
Note that on Octave 5 on Windows, the executable is in "Octave-5.x.x.x\mingw64\bin". We require the octave executable to run the kernel.Īdd that executable's directory to the PATH environment variable or create theĮnvironment variable OCTAVE_EXECUTABLE to point to the executable itself. To install using conda: conda config -add channels conda-forgeĬonda install texinfo # For the inline documentation (shift-tab) to appear. To install using pip: pip install octave_kernelĪdd -user to install in the user-level environment instead of the system environment. An Octave kernel for Jupyter Prerequisites
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