Hi,
After much deliberation, I found a passable solution:
distances = np.abs(np.arange(0,resolution,1)+0.5-(resolution/2.0))
x_gradient = np.tile(distances,(resolution,1))
y_gradient = np.copy(x_gradient)
y_gradient = np.swapaxes(y_gradient,0,1)
distances_to_center = np.hypot(x_gradient,y_gradien
Am 25.07.10 06:38, schrieb Ian Mallett:
> Hi,
>
> So I have a square 2D array, and I want to fill the array with sine
> values. The values need to be generated by their coordinates within the
> array.
>
> The center of the array should be treated as the angle 90 degrees. Each
> of the four edges
Hi,
So I have a square 2D array, and I want to fill the array with sine values.
The values need to be generated by their coordinates within the array.
The center of the array should be treated as the angle 90 degrees. Each of
the four edges should be 0 degrees. The corners, therefore, ought to
