Plotting directly to movie with numpy and mencoder

I think you're getting confused on what the uint32 represents. It's 4 bands of uint8 integers.

If you have floating point data, and want to represent it in grayscale, you don't want to rescale it to a full 32 bit range, you want to rescale it to an 8-bit range, and repeat that for the red, green, and blue bands (and then presumably put in a constant alpha band).

You could also just use a different byteorder. Y8 is just a single grayscale, 8-bit band, and Y16 is a single, grayscale 16-bit band. (Have a look at the output of mencoder -rawvideo format=help for a full (though somewhat confusing) listing.)

Just to illustrate using numpy for view a 32-bit integer as four bands of 8-bit integers:

import numpy as npheight, width = 20,20# Make an array with 4 bands of uint8 integersimage = np.zeros((height, width, 4), dtype=np.uint8)# Filling a single band (red) b,g,r,a = image.Tr.fill(255) # Fill the image with yellow and leave alpha aloneimage[...,:3] = (255, 255, 0) # Then when we want to view it as a single, 32-bit band:image32bit = image.reshape(-1).view(np.uint32).reshape(height, width)# (Note that this is a view. In other words,  we could change "b" above #  and it would change "image32bit")

In your case, however, you probably want to do something more like this:

import numpy as npfrom videosink import VideoSinkheight, width = 20,20numframes = 1000data = np.random.random((height, width, numframes))# Rescale your data into 0-255, 8-bit integers # (This could be done in-place if you need to conserve memory)d    ata_rescaled = 255.0 / (data.max() - data.min()) * (data - data.min())data_rescaled = data_rescaled.astype(np.uint8)# The key here is the "Y8" format. It's 8-bit grayscale.video = VideoSink((height,width), "test", rate=20, byteorder="Y8")# Iterate over last axisfor frame in data.T:    video.run(frame.T)video.close()