semvec/pypi-packages huggingface dataset:
isensing 0.1.1
Intelligent Sensing Toolbox for Multivariate Time Series

# intelligent-sensing-toolbox

Intelligent Sensing Toolbox (Isensing) is a Python package that focuses on multivariate time series analysis. This toolbox includes multiple open-source machine learning algorithms and statistic calculations.

In data analytics, making sense of massive numbers of data requires machine learning to work on datasets from different multiple sources in order to generate insights. For situation where a node that generates data points of multiple features in time series, massive number of nodes will make analysis more challenging.

Isensing provides a list of algorithms that does features extraction, decomposition and anomaly detections.

### Installation

Isensing is built upon Python 3. To install Isensing, make sure Python 3 and pip is installed.

```python
pip install isensing
```

### Dependencies
```
pandas
numpy
scipy
sklearn
statsmodels
matplotlib
plotly
shapely
```
These dependencies will be installed automatically using pip.

### Modules
#### anomaly
```python
# class
AlphaHull
HDR

# functions
outlier_detection()
isensing_anomalies()
```

#### decomposition
```python
# class
RobustPCA
```

#### features_extraction
```python
# functions
multiple_regression()
fast_DTW()
pearsonr_correlation()
```

### Tutorial
[Link](https://gitlab.com/imda-dsl/intelligent-sensing-toolbox/blob/master/demo/Intelligent%20Sensing%20Toolkit%20Tutorial/Intelligent%20Sensing%20Toolbox%20Tutorial.md)

### References
* https://github.com/robjhyndman/anomalous-acm
* http://blog.thehumangeo.com/2014/05/12/drawing-boundaries-in-python/
* https://feb.kuleuven.be/public/u0017833/Programs/pca/robpca.txt

### License
Apache License 2.0
drivefiller 3.0.1
A Python 3 library that makes very large files very quickly. Can also return file size.

# DriveFiller(dot)py
A python library that creates very large files very quickly.
Please DO NOT use in any malicious form. This has been made for the sole purpose of testing on systems you have the
permission to break. We (Conor and Ben) accept no responsibility for any consequences you may recieve or damage you
may cause.

## Examples
To write 500 lines in the file 'text.txt' stored in 'C:\Documents\' with the text 'Hello World!' and check size in bytes:
```
import drivefiller as df
Filler_Object = df.filler('C:\Documents\', 'text', 'Hello World!', 500)
Filler_Object.fill()
print(Filler_Object.checkSize())
```

To write approx. 10,000 bytes in the file'text.txt' stored in 'C:\Documents\' with the text 'Hello World!' and check size in bytes:
```
import drivefiller as df
Filler_Object = df.filler('C:\Documents\', 'text', 'Hello World!', 0, 10000)
Filler_Object.fill()
print(Filler_Object.checkSize())
```