# SpaceMap¶

API Reference

Note

This plot can be saved in an interactive form, see Saving plots

Spatially map a categorical variable onto a projection of a Sample’s image sequence

Note

Image produced from the following dataset: Garner, Aleena (2014): In vivo calcium imaging of layer 4 cells in the mouse using sinusoidal grating stimuli. CRCNS.org. http://dx.doi.org/10.6080/K0C8276G

## Controls¶

Parameter Description
Patch labels Categorical column to use for the patch labels
Image Colormap Colormap for the image
Patches Colormap Colormap for the patches
Projection Show the image as a “Max” or “Standard Deviation” projection
Fill Patches Fill the patches
Line width Line width of the patches
Alpha Alpha level of the patches
Samples Click on the sample to plot
Save Save the plot data and state in an interactive form
Load Load a plot that has been saved as a “.ptrn” file.

## Console¶

See also

API Reference

### Namespace¶

reference Description
this The SpaceMapWidget instance, i.e. the entire widget
this.transmission Current input Transmission
get_plot() Returns the plot area
get_plot().fig Returns the matplotlib Figure instance
get_plot().ax Returns the Axes for the current plot matplotlib Axes

### Examples¶

#### Export¶

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 # Desired size (width, height) size = (6,5) # Get the figure fig = get_plot().fig # original size to reset the figure after we save it orig_size = fig.get_size_inches() #Set the desired size fig.set_size_inches(size) # Save the figure as a png file with 600 dpi fig.savefig('/share/data/temp/kushal/spacemap.png', dpi=600, bbox_inches='tight', pad_inches=0) # Reset to original size and draw fig.set_size_inches(orig_size) get_plot().draw() 

Note

The entire plot area might go gray after the figure is reset to the original size. I think this is a Qt-matplotlib issue. Just resize the window a bit and the plot will be visible again!

#### Legend Title¶

See also

matplotlib API for matplotlib.axes.Axes.get_legend

get_plot().ax.get_legend().set_title('New Title')
get_plot().draw()


#### Hide Axis Borders¶

See also

matplotlib API for matplotlib.axes.Axes.axis

get_plot().ax.axis('off')
get_plot().draw()