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inverted axis and box zoom #198

ih64 opened this issue May 18, 2014 · 6 comments


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commented May 18, 2014

mpld3 is great and I've been having a lot of fun with it. I have a question about box zoom. Currently, I'm making some plots where the Y axis must be inverted (I'm plotting light curves in units of magnitude). I do this the traditional matplotlib way of doing ax.axes.invert_yaxis(). The plot renders fine. However, when I use the box zoom to zoom in on a certain part of my scatter plot, the Y axis switches to being uninverted again. Do you know if there is a way to for the axis to stay inverted?


@jakevdp jakevdp added the bug label May 18, 2014


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commented May 18, 2014

That looks like a bug that will have to be fixed in the javascript side of things. I imagine that d3 automatically returns the box zoom limits sorted, and we need to detect when the axis is already inverted and flip those limits.


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commented Aug 19, 2015

Related behaviour is present when zooming imshow plots. Here the DATA stays in place, but the Y-axis inverts.
Before zoom:

After zoom:

Notice that the red and blue box stay on the same coordinates, whereas the data stays at the same position.


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commented Jul 14, 2016

+1 - same issue experienced with IMSHOW


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commented Aug 6, 2016

+1 - same issue here. I am inverting both axis and when I zoom the scaling returns back to the initial order. Any help how to fix this?


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commented Oct 17, 2016

yup, some workaround in the meantime would be great :)


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commented Jun 6, 2017

Has there been any motion on this? I'm using mpld3 version 0.3, and I've been having trouble with matplotlib.pyplot.imshow() of a numpy.histogram2d object. Using mpld3 on the figure does not register the origin = 'lower' keyword argument, so my image is flipped. The code snippet here was used to generate a .html and .png version of the images listed. Basically,

H, xe, ye = np.histogram2d(x, y, bins = 30)
ex = [xe[0], xe[-1], ye[0], ye[-1]]
fig, ax = plt.subplots()
ax.imshow(H.T, extent = ex, origin = 'lower')
ax.plot(x, y, '.', ms = 3, color = 'r')

However, the same code using will flip the image back (leaving the scatter points in the right spot):
My workaround is to traverse the 2D matrix in the reverse direction along the column:

ax.imshow(H.T[::-1], extent = ex, origin = 'lower')

or else use:

ax.imshow(H.T, extent = ex, origin = 'upper')

However, the last one will only work if the plot axis already has the ~ax.ylim() set in the right way.

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