Image plot

import scipp as sc
import plopp as pp

Basic image plot

As with one-dimensional data, plotting two-dimensional data is done using the plot function.

da = pp.data.data2d()
da.plot()

Changing the colormap

da.plot(cmap='magma')

Hiding the colorbar

da.plot(cbar=False)

Logarithmic colormap

da.plot(logc=True)

Logarithmic axes

da.plot(logx=True)

Setting the axes limits

pp.plot(da, xmax=sc.scalar(25, unit='m'))

Note that if the unit in the supplied limits is not identical to the data units, an on-the-fly conversion is attempted. It is also possible to omit the units altogether, in which case it is assumed the unit is the same as the data unit.

pp.plot(da, xmax=25, ymin=10, ymax=30)

Setting the colorscale limits

Similarly to the axes limits, the colorscale limits are controlled via the cmin/cmax arguments:

da.plot(cmin=sc.scalar(0, unit='m/s'), cmax=0.5)

Masks on images

The masked data are by default represented using a grayscale colormap:

da.masks['yband'] = abs(da.coords['y'] - sc.scalar(20, unit='m')) < sc.scalar(
    5, unit='m'
)
da.plot()

The colormap for the masks can be changed using the mask_cmap argument:

da.plot(mask_cmap='hot')

Masks can also be a solid color:

da.plot(mask_color='magenta')

Using a non-dimension coordinate

For a dimension of name 'x', Plopp will use the corresponding coordinate of name 'x'. To use a different coordinate, use the coords argument.

da = pp.data.data2d()
da.coords['x2'] = da.coords['x'] ** 2
da.coords['y2'] = da.coords['y'] ** 2
pp.plot(da, coords=['x2', 'y2'])

Note that if no coordinate of name 'x' exists, a dummy one will be generated using scipp.arange.