Welcome to the MPL Plotter documentation!
Making plots for technical documents can be a time sink. MPL Plotter aims to reduce that overhead by allowing you to effortlessly and concisely
Generate publication quality figures with a single call
Compare data by plotting different curves in a single plot
Visualize different kinds of data in figures with many plots
It is opinionated but built with flexibility in mind, which practically means that no default can’t be changed, and any and all further customization with Matplotlib is compatible. From ticks to legends to extra axes to whatever suits your needs. There’s two ways to use MPL Plotter:
Calls to the 2D and 3D plotting functions
Using presets, either those shipped with the library, or custom ones
It does the job for me and I expand it when it can’t. Hope you find some use in it!
- 2D
- Plotting Methods
plot
line
scatter
heatmap
contour
quiver
streamline
fill_area
- Composition:
comparison
comparison()
- Composition:
panes
panes()
- Placeholders
diff_field()
spirograph()
waterdrop()
boltzmann()
- 3D
- Plotting Methods
plot
line
scatter
surface
- Placeholders
hill()
- Presets
- Preset
preset
two_d
three_d
- Precision
- Publication
- Colors
- Color Maps
custom()
mapstack()
- Color Schemes
colorscheme_one()
- Methods
complementary()
delta()
- Internal Methods
- Common
method_backend()
method_figure()
method_colorbar()
method_fonts()
method_workspace_style()
method_background_color()
method_subplots_adjust()
method_save()
method_show()
- 2D Methods
method_setup()
method_spines()
method_resize_axes()
method_grid()
method_legend()
method_tick_locs()
method_tick_labels()
method_title()
method_axis_labels()
- 3D Methods
method_setup()
method_spines()
method_pane_fill()
method_remove_axes()
method_scale()
method_resize_axes()
method_grid()
method_legend()
method_tick_locs()
method_tick_labels()
method_title()
method_axis_labels()