Hello everyone,
this is the third post about the progress in my GSoC project and I want to present new changes in the handling of the external packages in Cantor.
The biggest changes done recently happened for Python. We now properly support integrated plots created with matplotlib.
Cantor intercepts the creation of plots and embedds the result into its worksheet.
This also works if multiple plots are created in one step the order of plots is preserved.
Also, text results between plots are also supported.
Besides matplotlib, we also properly handle Plot.ly - another popular graphing library for Python and R. This package has some requirements
that have to be fulfilled first. The user is notified about these requirements in case they are not fulfilled.
Similar implementation was also done for Julia and Octave, but to a smaller extent.
Though many preparational changes were done in the code for this, the only visible result for the user
are at the moment the new messages about unfulfited requirements of graphing packages.
Especially for Julia this is imprortannt now since for graphing the package GR was hard-coded in the past and there was no notification to the user
if this package was not installed and it was not immediately clear to the user why the creation of plots fails.
With this improvements Cantor is doing the next steps to become more user friendly.
There is another important change - the settings for graphing packages become dynamic.
The user can now change them on the fly without having to restart the session.
Also, the plot menu was extended. Julia and Python now can produce code for multiple packages - the prefered package can be choosen in settings.
In the next post I plan to show how the usability of Cantor panels is going to be improved.
this is the third post about the progress in my GSoC project and I want to present new changes in the handling of the external packages in Cantor.
The biggest changes done recently happened for Python. We now properly support integrated plots created with matplotlib.
Cantor intercepts the creation of plots and embedds the result into its worksheet.
This also works if multiple plots are created in one step the order of plots is preserved.
Also, text results between plots are also supported.
Besides matplotlib, we also properly handle Plot.ly - another popular graphing library for Python and R. This package has some requirements
that have to be fulfilled first. The user is notified about these requirements in case they are not fulfilled.
Similar implementation was also done for Julia and Octave, but to a smaller extent.
Though many preparational changes were done in the code for this, the only visible result for the user
are at the moment the new messages about unfulfited requirements of graphing packages.
Especially for Julia this is imprortannt now since for graphing the package GR was hard-coded in the past and there was no notification to the user
if this package was not installed and it was not immediately clear to the user why the creation of plots fails.
With this improvements Cantor is doing the next steps to become more user friendly.
There is another important change - the settings for graphing packages become dynamic.
The user can now change them on the fly without having to restart the session.
Also, the plot menu was extended. Julia and Python now can produce code for multiple packages - the prefered package can be choosen in settings.
In the next post I plan to show how the usability of Cantor panels is going to be improved.
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