The development version of yt has a function called toggle_right_handed that might be useful here.
Take a look at the following example: https://gist.github.com/ 2937442f997bb16f5505fa470edb2480
Unfortunately you need to be using the development version to do this, there's no workaround for the version you're using, since the call to `invert_xaxis` needs to happen while the plot is getting set up. There are instructions on how to build yt from source here:
Alternatively if you're using conda you can use the nightly conda builds:
Hope that's helpful,
On Tue, Apr 11, 2017 at 12:00 AM, Greta Zhong firstname.lastname@example.org wrote:
I’m trying to invert the horizontal axis on some simple projection plots. I’m trying to get a projection along the x axis, with y as the vertical and z as the horizontal axis where the horizontal/z axis is inverted, with the horizontal/z axis decreasing from left to right. Here’s the relevant code:
ds.coordinates.x_axis = 2 ds.coordinates.x_axis['x'] = 2 ds.coordinates.y_axis = 1 ds.coordinates.y_axis['x'] = 1
This is just assigning the z axis (2) to the horizontal axis and the y axis (1) to the vertical axis.
plot1 = yt.ProjectionPlot(ds,"x","velocity_x",weight_field='density') #plot1.plots["velocity_x"].axes.invert_xaxis() plot1.save()
plot12 = yt.ProjectionPlot(ds,"x","density") #plot12.plots["density"].axes.invert_xaxis() plot12.save()
And then I just use ProjectionPlot to make the plots. As you can see, I commented out a sort of matplotlib-y attempt to invert the horizontal axis, to no effect.
I’ve attached two files: the first is what I’m getting with the above code (‘Projection_x_density_actual'), and the second illustrates the orientation I’d like (‘Projection_x_density_rotated'). Unfortunately, I got to the desired orientation by swapping my vertical/horizontal axes like this:
ds.coordinates.x_axis = 1 ds.coordinates.x_axis['x'] = 1 ds.coordinates.y_axis = 2 ds.coordinates.y_axis['x'] = 2
and then just rotating the png in preview.
I can’t find anything in the documentation about this besides the fact that we can use matplotlib objects to customize plots. I’d really appreciate any help on this!
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