semvec/pypi-packages huggingface dataset:
pose-openvr-wrapper 0.3.12
PyOpenvr Library convenience wrapper for recovery of pose data
Keywords: vive,tracking

### A convenient pose wrapper

#### Requirements

You need steamVR running to use it.

#### Usage
Simple sampling example, return dictionnary poses values converted to different
useful formats.
```
"""Example script using pose_openvr_wrapper."""
import pose_openvr_wrapper

pyopenvr_wrapper = pose_openvr_wrapper.OpenvrWrapper('cfg/config.json')
print(pyopenvr_wrapper.devices)

samples = pyopenvr_wrapper.sample('tracker_0', samples_count=10)
print(samples)
```
 it's also possible to get relative poses, from choosen reference device to
 target device.

```
relative_samples = pyopenvr_wrapper.sample(
       ref_device_key='tracking_reference_1',
       target_device_key='tracker_0', samples_count=10)

print(relative_samples)
```


#### Example config file :
 It require a config file to always keep same tracker/lighthouses names.
```
{
    "devices":[
        {
          "name": "tracking_reference_0",
          "type": "tracking_reference",
          "serial":"LHB-02F97E98"
        },
        {
          "name": "tracking_reference_1",
          "type": "tracking_reference",
          "serial":"LHB-431A55FD"
        },
        {
          "name": "tracker_0",
          "type": "tracker",
          "serial":"LHR-3CD1A9DA"
        },
        {
          "name": "tracker_1",
          "type": "tracker",
          "serial":"LHR-25865D81"
        },
        {
          "name": "tracker_2",
          "type": "tracker",
          "serial":"LHR-4359D2B6"
        }
    ]
}
```
lib-b 1.0.3
A library contains implements of factorization supporting multiple methods and data types
Requires Python: >=3.4.0

# LIB-B

A library contains implements of factorization supporting multiple methods and data types.

- LU Factorization
- Schmidt Decomposition (classical/modified)
- Householder Reduction
- Givens Reduction

## Environment

    Python 3.4 or higher

## Install

```sh
pip install lib-b
```

## Usage


```sh
# libb -h
```

If you have some matrix file which is split by white space:

```sh
# libb -f matrix lu|cs|ms|h|g
```

## Usage in script

Import it:

```python
import libb
```

Load matrix(from stdin or opened file):
```python
A_matrix, row_num, col_num = libb.LoadMatrix(src=stdin)
```

Apply methods on matrix (any struct that supports index operator `[]`) and fetch the result:

```python
P, L, U = libb.LUFactorization(A=A_matrix)
Q, R = libb.ClassicalSchmidtDecomposition(A=A_matrix)
Q, R = libb.ModifiedSchmidtDecomposition(A=A_matrix)
Q, R = libb.HouseholderReduction(A=A_matrix)
Q, R = libb.GivensReduction(A=A_matrix)
```