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---
license: mit
language:
- en
pretty_name: iDATA-Capcitance Dataset
size_categories:
- 100M<n<1B
---
# 3D Capacitance Dataset #
This project serves as the submodule of [PC-Cap](https://gitee.com/oscc-project/pct-cap).
The dataset generation is briefly shown in <a href="#fig_we_dataset">Fig. 1</a>.
## Dataset Description ##
### Directory Descriptions ###
The complete directory structure is as follows:
```txt
dataset
├── pc
├── pc_annotation_coupling_test_clean.csv
├── pc_annotation_coupling_test.csv
├── pc_annotation_coupling_train_clean.csv
├── pc_annotation_coupling_train.csv
├── pc_annotation.csv
├── pc_annotation_total_test_clean.csv
├── pc_annotation_total_test.csv
├── pc_annotation_total_train_clean.csv
└── pc_annotation_total_train.csv
```
The directory **dataset/pc** contains all information of the point cloud.
### File descriptions ###
- **pc_annotation.csv** - records some information from the original **3D Capacitance Sample** of the point cloud
|column name | description |
| --- | --- |
| point_cloud_path | point cloud file path |
| conductor_num | the number of conductors that the original sample contains |
| point_num | the size of point cloud |
| electrode1_point_num | points generated based on the master conductor |
| electrode2_point_num | points generated based on the target environment conductor |
| cap_type | total or coupling capacitance |
| cap | reference capacitance value, the label |
| v1_x | the absolute coordinate-low-x of the original sample in the layout |
| v1_y | the absolute coordinate-low-y of the original sample in the layout |
| v1_z | the absolute coordinate-low-z of the original sample in the layout |
| dx | the size of the original sample along direction-x |
| dy | the size of the original sample along direction-y |
| dz | the size of the original sample along direction-z |
| timestamp | timestamp of the point cloud file generation |
| solver_time | the calculation time that the solver takes to get the capacitance result |
- **pc_annotation_xxx.csv** - part of records from pc_annotation.csv
The details of dataset partition and data cleaning are available at [PC-Cap repository](https://gitee.com/oscc-project/pct-cap)
|sub-dataset used in our research | descriptions |
| --- | --- |
| pc_annotation_coupling_train_clean.csv | the training set for coupling capacitance task |
| pc_annotation_coupling_test_clean.csv | the testing set for coupling capacitance task |
| pc_annotation_total_train_clean.csv | the training set for total capacitance task |
| pc_annotation_total_test_clean.csv | the testing set for total capacitance task |
- **w500l2_1_C_0_0.txt** - example of a point cloud file
- file name format
- w500l2:
The 3D sampling window is height-adaptive and can accommodate 2 layers above and 2 layers below.
5 metal layers in maximum: Routing-Via-Routing-Via-Routing or Via-Routing-Via-Routing-Via.
The 3D sampling window project to XOY-plane with an area sized $500 nm \times 500nm$.
- 1:
the sample id when generation
- C_0_0:
the position in the sample capacitance matrix
- content format: point cloud file format that [CloudCompare](https://www.cloudcompare.org/) can read directly.
| symbol | descriptions |
| --- | --- |
| $x$ | coordinate-x |
| $y$ | coordinate-y |
| $z$ | coordinate-z |
| $n_x$ | component-x of normal vector |
| $n_y$ | component-y of normal vector |
| $n_z$ | component-z of normal vector |
| $\varepsilon_r$ | the dielectric channel, relative permittivity |
| class | a point belongs to a class that relates to its generation |
| $\Phi$ | the selecting channel |
- line 1 : 432.715, 171.114, 0.5879, 1, 0, 0, 4.06, 1, 0
A point with coordinates **(432.715, 171.114, 0.5879)** in layout.
This point is generated on the surface of a region whose local normal vector is **(1, 0, 0)**.
This local region is full of dielectric with a relative permittivity of **4.06**, except the region inner the conductor.
The id of this region equals **1**.
The selecting channel value of this point is **0**, such as non-target environment conductors. The details of the setting are related to the **Gauss Law-based Point Cloud feature**. |