ncvis-examples

Examples for NCVis Python wrapper.

Notebook	Contents
sample.ipynb	Introduction to NCVis
big-data.ipynb	Large-scale application case

Setup

Conda [recommended]

You do not need to setup the environment if using conda, all dependencies are installed automatically.

 $ conda install --file requirements-conda.txt

Pip [not recommended]

Important: be sure to have a compiler with OpenMP support. GCC has it by default, which is not the case with clang. You may need to install llvm-openmp library beforehand.

1. Install numpy and cython packages (compile-time dependencies):

   $ pip install numpy cython

2. Install other packages:

   $ pip install -r requirements-pip.txt

Popular Datasets

Datasets can be dowloaded by using the download.sh script:

$ bash data/download.sh <dataset>

Replace <dataset> with corresponding entry from the table. You can also download all of them at once:

$ bash data/download.sh

The datasets can be then accessed by using interfaces from the data Python module.

Dataset	<dataset>	Dataset Class
MNIST	mnist	MNIST
Fashion MNIST	fmnist	FMNIST
Iris	iris	Iris
Handwritten Digits	pendigits	PenDigits
COIL-20	coil20	COIL20
COIL-100	coil100	COIL100
Mouse scRNA-seq	scrna	ScRNA
Statlog (Shuttle)	shuttle	Shuttle

Each dataset can be used in the following way:

Sample Code	Action
d = data.MNIST()	Load the dataset.
ds.X	Get the samples as numpy array of shape (n_samples, n_dimensions). If samples have more than one dimension they are all flattened.
ds.y	Get the labels of the samples.
len(ds)	Get total number of samples.
ds[0]	Get 0-th pair (sample, label) from the dataset.
ds.shape	Get the original shape of the samples. For example, it equals to (28, 28) for MNIST.