On Sep 1, 2016, at 11:59 AM, Marcus Donnelly <[email protected]> wrote:

That explains it, thanks Bryan. I did notice the when auto-ranging included in the reference for the DataRange1d flipped attribute, but didn't realise I'd turned it off!

Marcus.

On Thursday, September 1, 2016 at 5:46:12 PM UTC+1, Bryan Van de ven wrote:

To elaborate, there's actually two considerations.

For the image itself, I believe there is a bug relating to flipped ranges specifically relating to images. The reason for this is that unlike every other kind of glyph that depends mapping individual coordinates from data to screen space, an image has to be flipped "as a whole". There is no code that does this yet, AFAIK. For now your best bet is to "flip" the image yourself as suggested by Raphael.

For the axes, the reason they are not flipped it because you are setting start and end values yourself. Setting flipped=True means that the axis orientation should be flipped *when auto-ranging is happening* But by setting start and end manually, you are overriding any auto-ranging. So, if you want the axes flipped, but want to set values yourself, then simply swap what you set for start/end. Of course, if you always want to set things yourself, and not rely on auto-ranging, then a simple Range1d will also suffice.

Bryan

> On Sep 1, 2016, at 10:44 AM, Raphael Walker <[email protected]> wrote:

>

> Hi Marcus,

>

> z = numpy.flipud(z) will do the trick for you.

>

> Raphael

> On 2016-09-01 17:30, Marcus Donnelly wrote:

>> Hi,

>>

>> I've been trying to display an image and flip the axes using the DataRange1d 'flipped' attribute. It isn't working, don't know if that's just because I'm not using it properly. Here's the code...

>>

>> -----

>>

>> from bokeh.io import show

>> from bokeh.models.ranges import DataRange1d

>> from bokeh.plotting import Figure

>> from bokeh.models.mappers import LinearColorMapper

>> from bokeh.palettes import RdYlBu11

>> import numpy

>>

>> # Test data

>> x = numpy.linspace(1,2,4)

>> y = numpy.linspace(2,4,6)

>> z = numpy.zeros([x.size,y.size])

>> for i in range(x.size):

>> for j in range(y.size):

>> z[i,j] = (x[i]*y[j])**2

>>

>> # Flipped ranges

>> xr = DataRange1d(start = x[0],end = x[-1])

>> xr.flipped = True

>> yr = DataRange1d(start = y[0],end = y[-1])

>> yr.flipped = True

>>

>> # Plot

>> f = Figure(x_range = xr,y_range = yr)

>> cm = LinearColorMapper(palette = RdYlBu11)

>> f.image([z.T],x[0],y[0],dw=x[-1]-x[0],dh=y[-1]-y[0],color_mapper=cm)

>>

>> show(f)

>>

>> -----

>>

>> The result is in the attached file test_image.png. I was expecting the image to be flipped in x and y (i.e. the red colour should be in the bottom-left hand corner) and the axes labels flipped accordingly, but this didn't happen. Any advice gratefully received,

>>

>> Marcus.

>>

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>

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