![]() ![]() Note that once we’ve used %matplotlib inline, any Matplotlib plots that we create in any future cells in the notebook will also be displayed and store within the notebook. Notice that the code runs without any errors again and the plot is displayed inline in the notebook. Fresh PBMCs were stimulated with overlapping peptide pools (PepTivator peptide pools Miltenyi Biotec, Cologne, Germany) covering the complete sequence of proteins M and N or the immunodominant sequence domains of protein S. To fix this, we can use the %matplotlib inline command before we create the line plot: %matplotlib inline The code runs without any errors, but no line plot is displayed inline with the code. ![]() Here’s what the output looks like in the Jupyter notebook: Suppose we attempt to use the following code to create a Matplotlib line plot in a Jupyter notebook: import matplotlib. The following example shows how to use this code in practice. GNU TeXmacs is a free wysiwyw (what you see is what you want) editing platform with special features for scientists. The resulting plots will then also be stored in the notebook document.” “With this backend, the output of plotting commands is displayed inline within frontends like the Jupyter notebook, directly below the code cell that produced it. Here’s how this code is described within the documentation page: You can use the following code to display and store Matplotlib plots within a Python Jupyter notebook: %matplotlib inline The remaining 1413 cells, 685 irradiated and 728 controls, are plotted in Figure 2. ![]()
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