SyntheticGen 0.1.1
Synthetic dataset creator/augmentor for machine learning applications.
License: MIT
Keywords: python, machine learning, data augmentation, sythetic datasets


# SyntheticGen v0.1.1



This is a Python package available on PyPi that creates synthetic datasets for various dataset types.



**SyntheticGen currently supports:**

 - Linear Synthetic Datasets

 - Linear Augmentations



# Installation

    pip install syntheticgen



# Usage

In v0.1.1 there is only a linear augmentor available however, image and experimental augmentation techniques will be available soon.

```

#Import a dataset as a numpy array (in this example it is named dataset)

#Create an augmentor object and initialize it with the dataset

aug = linearAugmentor(dataset)





#addMatrix() and setPowerRange() will configure the augmentor with custom specifications.

aug.addMatrix(.25)

aug.setPowerRange(2,2)



#performOperations() will run the augmentation operations with the set configuration.

aug.performOperation()



#Returns the augmented dataset

dataset = aug.getCombinedSet()

```



# Object and Method Details

**linearAugmentor(dataset):**\

This is the augmentor object for psuedo-linear datasets.

>Dataset Specifications For Proper Function:

 - Must be a numpy array with sub-lists holding inputs and outputs in the same order every line.

 - Each sub-list in the dataset must be of equal length to one another





**linearAugmentor.addMatrix(percentAdded):**\

This method will randomly add a custom percentage of the inputed dataset into a matrix to then be augmented.

>Parameters:

 - percentAdded

    - This is a float value that determines the percentage of the inputted dataset that will be augmented.

    - Minimum to function: whatever float equates to 2 lines of the dataset.

    - Maximum is 1.0, the entire dataset.



**linearAugmentor.setIntRange(lowerBound, upperBound):**\

This method will set an integer range for the number of operations to be performed on the matrix.

>Parameters:

 - lowerBound

   - This is the fewest possible operations to be performed on the inputted dataset's matrix.

   - Minimum: 0

   - No Maximum

 - upperBound

   - This is the maximum number of possible operations to be performed on the inputted dataset's matrix.

   - Minimum: 0

   - No Maximum



**linearAugmentor.setPowerRange(lowerBound, upperBound):**\

This method will set a range for the number of operations to be performed on the matrix based on the length of the matrix raised to a power (the bounds).

>Parameters:

 - lowerBound

   - This is the value the length of the matrix will be raised by creating the fewest possible operations to be performed.

   - Minimum: 0

   - No Maximum

 - upperBound

   - This is the value the length of the matrix will be raised by creating the maximum number of possible operations to be performed.

   - Minimum: 0

   - No Maximum

     

**linearAugmentor.performOperations():**\

This is the method that will perform the operations on the matrix given the inputted specifications. 

   

**linearAugmentor.getCombinedSet():**\

This method returns the original dataset randomly combined with the newly created augmented data.



**linearAugmentor.getSyntheticData()**\

This method returns only the augmented data creating a fully synthetic dataset.



**linearAugmentor.getInitialDataset()**\

This method returns the originally inputted, unchanged dataset. 



# Roadmap

>Linear Augmentor

 - Add additional customization options pertaining to the type of operations performed

 - Add more advanced augmentation techniques utilizing eingenvectors.

>Image Augmentor

 - Add an image augmentor that performs multiple augmentation techniques. 

>Differential Augmentor

 - Experimental augmentor that's currently in production utilizing differential calculus.



# Recent Changes

v0.1.1

  - README changes.



v0.1.0

  - Created package and added the linear augmentor.