Python Package

Installation

The latest stable release can be installed from PyPi:

#TensorFlow 2 packages require a pip version >19.0.
pip install --upgrade pip
pip install ivis[cpu]

If you have CUDA installed and want ivis to use the tensorflow-gpu package, instead run pip install ivis[gpu].

Note

ZSH users. If you’re running ZSH, square brackets are used for globbing / pattern matching. That means ivis should be installed as pip install 'ivis[cpu]' or pip install 'ivis[gpu]'

Alternatively, you can use pip to install the development version directly from github:

pip install git+https://github.com/beringresearch/ivis.git

Another option would be to clone the github repository and install from your local copy:

git clone https://github.com/beringresearch/ivis
cd ivis
pip install -e '.[cpu]'

Dependencies

  • Python 3.5+
  • tensorflow
  • numpy>1.14.2
  • scikit-learn>0.20.0
  • tqdm
  • annoy
from ivis import Ivis
from sklearn.preprocessing import MinMaxScaler
from sklearn import datasets

iris = datasets.load_iris()
X = iris.data

# Scale the data to [0, 1]
X_scaled = MinMaxScaler().fit_transform(X)

# Set ivis parameters
model = Ivis(embedding_dims=2, k=15)

# Generate embeddings
embeddings = model.fit_transform(X_scaled)

# Export model
model.save_model('iris.ivis')

Getting Started

from ivis import Ivis
from sklearn.preprocessing import MinMaxScaler
from sklearn import datasets

iris = datasets.load_iris()
X = iris.data

# Scale the data to [0, 1]
X_scaled = MinMaxScaler().fit_transform(X)

# Set ivis parameters
model = Ivis(embedding_dims=2, k=15)

# Generate embeddings
embeddings = model.fit_transform(X_scaled)

# Export model
model.save_model('iris.ivis')

Bugs

Please report any bugs you encounter through the github issue tracker. It will be most helpful to include a reproducible example.