geotrupede

Few questions, if anyone happens to be around please knock : )

What is the most efficient way to import x y z data into max to produce cloud of points? I am using a mixture of text parsing and jit.gl.mesh but seems not that scalable. Any other route? files are just ascii sequences of x y z values.

If the data is not centred in the origin (3400 200 100 etc. etc,), is there any simple way to create something fit, pan and zoom around the jit.world scene? The handle seems a little tricky to use in a very large dataset.

Finger crossed somebody has a minute to help out,

Few questions, if anyone happens to be around please knock : )

What is the most efficient way to import x y z data into max to produce cloud of points? I am using a mixture of text parsing and jit.gl.mesh but seems not that scalable. Any other route?   files are just ascii sequences of x y z values.

If the data is not centred in the origin (3400 200 100 etc. etc,), is there any simple way to create something  fit, pan and zoom around the jit.world scene? The handle seems a little tricky to use in a very large dataset.


Finger crossed somebody has a minute to help out,
Thank you in advance.
G>

Few questions, if anyone happens to be around please knock : )

What is the most efficient way to import x y z data into max to produce clou

large-point-clouds-far-from-the-origin

parsing out text files to fill matrices seems like a fine solution. once it's imported you could then save the matrix as a jit-matrix binary file to use the data without re-parsing (see the jit.matrix "write" message).

you could use some math with jit.3m to find the center of the data ((max - min) / 2 + min or something similar) and then use this as an offset for the position attribute. you can also scale the data down with the scale attribute and increase the size of the jit.gl.handle with the radius attribute.

alternatively you can use jit.anim.drive with jit.gl.camera to navigate through the points.

you could use some math with jit.3m to find the center of the data ((max - min) / 2 + min or something similar) and then use this as an offset for the position attribute. you can also scale the data down with the scale attribute and increase the size of the jit.gl.handle with the radius attribute. 

thanks, I did have a go and found good tips from you in earlier posts.

it does work but to me is surprising that there is not a more immediate way, like a' fit_all' message to the pwindow or something similar... maybe for max 9?

Anyhow, thank you once more for answering me.

thanks, I did have a go and found good tips from you in earlier posts.
it does work but to me is surprising that there is not a more immediate way, like a' fit_all' message to the pwindow or something similar... maybe for max 9?
Anyhow, thank you once more for answering me.
G>


large point clouds far from the origin