Hello Ben,

Thank you very much, this works perfectly for me!

Best,

Will.

On 01/10/2018 21:10, Benjamin Root wrote:

> ```

> x = np.arange(256)

> y = np.arange(256)

> xx, yy = np.meshgrid(x, y)

> ```

> Then your `xx` and `yy` will be 2D, just like your `ll` variable. Then,

> you pass the flattened versions of those three variables (i.e.,

> `xx.flatten()` or `xx.flat`) to the 3d scatter call.

>

> I hope that helps!

> Ben Root

>

>

> On Mon, Oct 1, 2018 at 3:47 PM Will Furnell <

[hidden email]
> <mailto:

[hidden email]>> wrote:

>

> Hey everyone,

>

> I'm looking into a 3D scatter plot - basically converting a NumPy array

> to a 3D plot, where X and Y correspond to the X and Y co-ordinates on

> the graph and the Z values corresponds to a particular height on the

> graph.

>

> This is how I'm generating the lists:

>

>

> x = list(range(0, 256))

> y = list(range(0, 256))

> z = []

>

> for i in range(0, 255):

> for j in range(0, 255):

> z.append(ll[i][j])

>

> where ll is my 2D array...

>

> I've seen the scatter function with 3d projection, but this requires the

> Z array length to be the same length as the X and Y lengths, whereas

> I'll need to be plotting X*Y points (256*256). Is there some way that I

> could achieve this?

>

> Thanks,

>

> Will.

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