sdf | Parallelized triangle mesh -- > continuous signed distance
kandi X-RAY | sdf Summary
kandi X-RAY | sdf Summary
In robust mode (default) we use raytracing (parity count) to check containment. Currently the ray tracing has the same limitation as embree, that is when ray exactly hits an edge the intersection gets double counted, inverting the sign of the distance function. This is theoretically unlikely for random points but can occur either due to floating point error or if points and mesh vertices are both taken from a grid. In practice, we (1) randomize the ray tracing direction and (2) trace 3 rays along different axes and take majority to decrease the likelihood of this occurring. In non-robust mode we use nearest surface normal to check containment. The contains check (and SDF sign) will be wrong under self-intersection or if normals are incorrectly oriented.
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sdf Key Features
sdf Examples and Code Snippets
from pysdf import SDF
# Load some mesh (don't necessarily need trimesh)
import trimesh
o = trimesh.load('some.obj')
f = SDF(o.vertices, o.faces); # (num_vertices, 3) and (num_faces, 3)
# Compute some SDF values (negative outside);
# takes a (num_po
sdf::SDF sdf(verts, faces); // verts (n, 3) float, faces (m, 3) float
// SDF. points (k, 3) float; return (k) float
Eigen::Vector3f sdf_at_points = sdf(points);
// Containment test, equal (but maybe faster) than sdf >= 0.
// points (k, 3) float;
Community Discussions
Trending Discussions on sdf
QUESTION
I have a dataset sdf and I am trying to get a groupby-rollup of the summary statitics. I am using rollup from data.table, but the problem is when a certain value is missing in the grouping, or lets say has the count 0, no statistics is given for it.
Output of dput(as.data.frame(sdf)
:
ANSWER
Answered 2022-Mar-29 at 14:10One approach (similar to as suggested in comments) is to join on a look up table of all the unique combinations of the three grouping variables:
QUESTION
I have a following query like this
...ANSWER
Answered 2022-Mar-23 at 17:20If there's only one row of data, then you can use
QUESTION
sdf = df.to_sparse()
has been deprecated. What's the updated way to convert to a sparse DataFrame?
ANSWER
Answered 2022-Mar-15 at 22:18You can use scipy to create sparse matrix:
QUESTION
For example I can build a model using functions like AddRigidbody and AddJoint. After the model is built, can I save the model into a URDF file or other xml type file? Drake can load model from URDF or SDF using parser but I haven't find function for saving the MultibodyPlant into URDF or SDF. Thank you for your answer!
...ANSWER
Answered 2022-Mar-14 at 02:31I'm afraid Drake doesn't offer that capability (at least not yet). Contributions are always welcome!
QUESTION
I've got the following BarEntry
List:
ANSWER
Answered 2022-Feb-12 at 16:13Use numbers 1,2,3,4,5 etc. as the x value instead of date. Each number should represend a date:
QUESTION
I am trying to use RDKit to enumerate large libraries of compounds and output the result as a single column of SMILES strings in a CSV file. I was able to use the following code successfully:
...ANSWER
Answered 2022-Jan-29 at 19:07EnumerateLibraryFromReaction
expects a list
.
So this should work:
QUESTION
What's the problem in my code?
Uncaught TypeError: Cannot read properties of undefined (reading 'remove')
and
...Uncaught TypeError: Cannot read properties of undefined (reading 'add')
ANSWER
Answered 2022-Jan-16 at 11:51JavaScript is case-sensitive
Changeclasslist
to classList
(l
→ L
)
QUESTION
I have a vector of strings:
...ANSWER
Answered 2022-Jan-06 at 13:30A possible solution, using stringr::str_remove
:
QUESTION
I have a spark dataframe that looks something like below.
date ID window_size qty 01/01/2020 1 2 1 02/01/2020 1 2 2 03/01/2020 1 2 3 04/01/2020 1 2 4 01/01/2020 2 3 1 02/01/2020 2 3 2 03/01/2020 2 3 3 04/01/2020 2 3 4I'm trying to apply a rolling window of size window_size to each ID in the dataframe and get the rolling sum. Basically I'm calculating a rolling sum (pd.groupby.rolling(window=n).sum()
in pandas) where the window size (n) can change per group.
Expected output
date ID window_size qty rolling_sum 01/01/2020 1 2 1 null 02/01/2020 1 2 2 3 03/01/2020 1 2 3 5 04/01/2020 1 2 4 7 01/01/2020 2 3 1 null 02/01/2020 2 3 2 null 03/01/2020 2 3 3 6 04/01/2020 2 3 4 9I'm struggling to find a solution that works and is fast enough on a large dataframe (+- 350M rows).
What I have tried
I tried the solution in the below thread:
The idea is to first use sf.collect_list
and then slice the ArrayType
column correctly.
ANSWER
Answered 2022-Jan-04 at 17:50About the errors you get:
- The first one means you can't pass a column to
slice
using DataFrame API function (unless you have Spark 3.1+). But you already got it as you tried using it within SQL expression. - Second error occurs because you pass column names quoted in your
expr
. It should beslice(qty_list, count, window_size)
otherwise Spark is considering them as strings hence the error message.
That said, you almost got it, you need to change the expression for slicing to get the correct size of array, then use aggregate
function to sum up the values of the resulting array. Try with this:
QUESTION
I see issues in the Spring cloud config server (Springboot) logs when connecting to the repo where configs are stored. I'm not sure if it's unable to clone because of credentials or something else (git-upload-pack not permitted). Any pointers to this would be great.
...ANSWER
Answered 2021-Oct-28 at 00:08Github token needs to be passed as username which I was configuring against the password property for the spring boot app. The password property needs to be left empty and the Github-token needs to be assigned to the username like below-
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