Plot Gallery#

Pyopenms-viz plotting occurs by calling the .plot() method on a pandas dataframe. Mandatory Types include has several built in plots which can be set using the “kind” attribute

BOKEH Plots#

These examples are generated if backend=’ms_bokheh’. Interactive plots are supported and rendering is typically faster than the PLOTLY backend.

PeakMap ms_bokeh

Chromatogram ms_bokeh

Mobilogram ms_bokeh

Spectrum ms_bokeh

Spectrum of Extracted DIA Data ms_bokeh

Plot Spyogenes subplots ms_bokeh

MATPLOTLIB Plots#

These plots can be generated by setting the backend=’ms_matplotlib’. Matplotlib is useful for generating static publication quality plots.

PeakMap ms_matplotlib

Extracted PeakMap 3D ms_matplotlib

PeakMap ms_matplotlib

Chromatogram ms_matplotlib

Mobilogram ms_matplotlib

Spectrum of Extracted DIA Data ms_matplotlib

Spectrum ms_matplotlib

Color Targeted Peptide PeakMap 3D ms_matplotlib

Investigate Spctrum Binning ms_matplotlib

Plot Spyogenes subplots ms_matplotlib

Manuscript d Fructose Example ms_matplotlib

PLOTLY Plots#

These plots can be generated by setting the backend=’ms_plotly’. PLOTLY plots inferfances well with StreamLit WebApps and allow for interactive 3D plots. Rendering is typically slower than the BOKEH backend.