semvec/pypi-packages huggingface dataset:
batchglm 0.7.4
Fast and scalable fitting of over-determined generalized-linear models (GLMs)


# Fast and scalable fitting of over-determined generalized-linear models (GLMs)

batchglm was developed in the context of [diffxpy](https://github.com/theislab/diffxpy) to allow fast model fitting for differential expression analysis for single-cell RNA-seq data. However, one can use batchglm or its concepts in other scenarios where over-determined GLMs are encountered. batchglm is based on TensorFlow 

# Installation
1. Install [tensorflow](https://www.tensorflow.org/install/), see below. Please use the pip installation if you are unsure.
2. Clone the GitHub repository of batchglm.
3. cd into the clone.
4. pip install -e .

## Tensorflow installation
Tensorflow can be installed like any other package or can be compiled from source to allow for optimization of the software to the given hardware. Compiling tensorflow from source can significantly improve the performance, since this allows tensorflow to make use of all available CPU-specific instructions. Hardware optimization takes longer but is only required once during installation and is recommended if batchglm is used often or on large data sets. We summarize a few key steps here, an extensive up-to-date installation guide can be found here: https://www.tensorflow.org/install/

### Out-of-the-box tensorflow installation
You can install [tensorflow](https://www.tensorflow.org/install/) via pip or via conda.

#### pip
- CPU-only: <br/>
  `pip install tensorflow`
- GPU: <br/>
  `pip install tensorflow-gpu`

### Hardware-optimized tensorflow installation (compiling from source)
Please refer to https://www.tensorflow.org/install/.
VL53L1X 0.0.5
vl53l1x distance sensor driver for Raspberry Pi

# vl53l1x-python

Python library for the VL53L1X Laser Ranger.

https://shop.pimoroni.com/products/vl53l1x-breakout

# Installing

```
sudo pip install smbus2
sudo pip install vl53l1x
```

# Usage

```python
import VL53L1X

# Open and start the VL53L1X sensor.
# If you've previously used change-address.py then you
# should use the new i2c address here.
# If you're using a software i2c bus (ie: HyperPixel4) then
# you should `ls /dev/i2c-*` and use the relevant bus number.
tof = VL53L1X.VL53L1X(i2c_bus=1, i2c_address=0x29)
tof.open()

# Optionally set an explicit timing budget
# These values are measurement time in microseconds,
# and inter-measurement time in milliseconds.
# If you uncomment the line below to set a budget you
# should use `tof.start_ranging(0)`
# tof.set_timing(66000, 70)

tof.start_ranging(1)  # Start ranging
                      # 0 = Unchanged
                      # 1 = Short Range
                      # 2 = Medium Range
                      # 3 = Long Range

# Grab the range in mm, this function will block until
# a reading is returned.
distance_in_mm = tof.get_distance()

tof.stop_ranging()
```

See examples for more advanced usage.

0.0.5
-----

* Enhancement: support for ROI thanks to @jinnie

0.0.4
-----

* Enhancement: support for tca9548a, for #13
* Enhancement: support for i2c address change, for #14
* Enhancement: support for setting timing budget, for #16
* Synced API code with latest release from ST


0.0.3
-----

* Fix: Use i2c_bus param for use with alternate buses/soft i2c

0.0.2
-----

* Improved search for .so file to pick up arch-specific files

0.0.1
-----

* Initial release