I think you're asking how to blend a custom intensity image with an rgb
image. (I'm traveling and just have my phone, so you'll have to excuse my
lack of examples.)
There are several ways to do this. Basically, it's analogous to "blend
modes" in Photoshop etc.
Have a look at the matplotlib.colors.LightSource.blend_overlay and
blend_soft_light functions in the current github head. (And also
http://matplotlib.org/devdocs/examples/specialty_plots/topographic_hillshading.html
)
If you're working with 1.4.x, though, you won't have those functions.
However, the math is very simple. Have a look at the code in those
functions in the github head. It's basically a one liner.
You'll need both the 4-band rgba image and the 1 band intensity/hillshade
image to be floating point arrays scaled from 0-1. However, this is the
default in matplotlib.
How that helps a bit, and sorry again for the lack of examples!
Joe
OK, I understand.
Could you suggest a way to reduce that 3D array to a 2D array and plot it
with a specific colormap, while preserving the shading?
I did something similar in Matlab
https://mycarta.wordpress.com/2012/04/05/visualization-tips-for-geoscientists-matlab-part-ii/
But it took using some custom functions and a ton of asking and tinkering,
and I'm not quite at that level with matplotlib, so any suggestion would
be appreciated
Thanks,
Matteo
On Thu, May 21, 2015 4:10 pm, Eric Firing wrote:
>
> Colormapping occurs only when you give imshow a 2-D array of numbers to
> be mapped; when you feed it a 3-D array of RGB values, it simply shows
> those colors. For colormapping to occur, it must be done on a 2-D array
> as a step leading up to the generation of your img_array.
>
> Eric
> On 2015/05/21 5:50 AM, Matteo Niccoli wrote:
>
>> I posted a question on stackoverflow about creating with making my own
>> shading effect (I want to use horizontal gradient for the shading).
>> http://stackoverflow.com/questions/30310002/issue-creating-map-shading-
>> in-matplotlib-imshow-by-setting-opacity-to-data-gradi
>>
>>
>> Unfortunately I cannot share the data because I am using it for a
>> manuscripts, but my notebook with full code listing and plots, here:
>> http://nbviewer.ipython.org/urls/dl.dropbox.com/s/2pfhla9rn66lsbv/surfa
>> ce_shading.ipynb/%3Fdl%3D0
>>
>> The shading using gradient is implemented in two ways as suggested in
>> the answer. What I do not understand is why the last plot comes out with
>> a rainbow-like colors, when I did specify cubehelix as colormap.
>>
>> hsv = cl.rgb_to_hsv(img_array[:, :, :3]) hsv[:, :, 2] = tdx_n
>> rgb = cl.hsv_to_rgb(hsv) plt.imshow(rgb[4:-3,4:-3], cmap='cubehelix')
>> plt.show()
>>
>>
>> Am I doing something wrong or is this unexpected behavior; is there a
>> workaround?
>
>>
>> Thanks
>> Matteo
>>
>>
>
>
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