PyCharm 2019.2 Help

Scientific mode

Scientific mode in PyCharm provides support for interactive scientific computing and data visualization. The following packages must be properly installed:

To learn how to install packages to your PyCharm interpreter, read the section Install, uninstall, and upgrade packages.

When a numpy import is detected, PyCharm shows the banner that suggests you to enable the Scientific mode:

Enable the scientific view

Scientific mode

With this mode enabled, the following changes are introduced to the UI:

In the Scientific mode, a graph opens in its own tab in the SciView window, allowing you to resize it, zoom in and out, and so on. You can alter this behavior by toggling the Show plots in tool window checkbox (Settings/Preferences | Tools | Python Scientific).

Scientific project

You can get all the Scientific mode settings predefined by choosing the corresponding project type in the New Project wizard.

creating a new scientific project in PyCharm

When choosing the Scientific project type, you need to ensure that you have Conda interpreter installed. Once this is done, all you need is to specify the project name. You can also alter the name of the data folder if needed.

Matplotlib in the console

Matplotlib is available also in console. See the Running in console section of the Scientific Mode tutorial.

With Matplotlib imported, the following happens:

  • When you open SciView tool window with the debug session stopped, an empty tab is shown, where you can type the variables from the console:

    SciView tab

    In the Format field, one can specify the format of representing the output.

    Note that when you launch your files in the SciView mode, the command line is automatically shown after the script execution.

  • When stopping on a breakpoint, a tab appears in the SciView with the graph being debugged:

    Matplotlib debuggin

    See the Debug section of the Scientific Mode tutorial.

When starting a Python console (Tools | Python Console...), one can import Matplotlib, and build graphs as required:

building graphs with matplotlib

The Python console is accessible for further inputs.

Last modified: 14 October 2019