Skip to main content

Exosomians

Getting Started

Installation

Installation with pip

To install the latest version from PyPI, simply use the following bash script:

pip install exosomians

or you can clone this repository and install via setup.py file:

git clone https://github.com/Exosomians/exosomians
cd exosomians
python setup.py -q

Examples

Inference

You can use pre-trained models to make predictions on your own datasets

import exopy as exo

# Load the pre-trained model
model = exo.ml.ExoGRU.load('./saved_models/ExoGRU/exogru_best-v2.ckpt')

# Prepare dataset
data = model.prepare_data('/path/to/fasta/data.fasta', seq_key='seq')

# Get the predictions 
df_results = model.predict(data, batch_size=128)  # Results will be stored in a pandas dataframe 

Train from scratch

import exopy as exo

exo.ml.ExoGRU.setup_dataset(path='/path/to/dataset/design.mat.csv',
                            seq_key='seq',
                            target_key='label',
                            fraction=1.0)

config = {
    'activation_fn': 'relu',
    'batch_size': 32,
    'bidirectional': False,
    'dropout_rate': 0.1,
    'lr': 0.00011342016019358544,
    'n_head_hidden': 512, 'n_head_layers': 2,
    'n_hidden': 1024,
    'n_layers': 1,
    'network': 'exogru',
    'use_batch_norm': True,
    'use_layer_norm': False
}

model = exo.ml.ExoGRU(**config)

model.fit(max_epochs=2000,
          train_size=0.8,
          batch_size=128,
          early_stopping_patience=5,
          check_val_every_n_epoch=3,
          save_path='./saved_models/ExoGRU/',
          )

Sample Notebooks

Model Path
ExoGRU notebooks/training_demos/ExoGRU.ipynb
ExoCNN notebooks/training_demos/ExoCNN.ipynb
ExoLSTM notebooks/training_demos/ExoLSTM.ipynb

Metadata

Release files for exosomians 0.1.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for exosomians 0.1.1
File Size Uploaded
exosomians-0.1.1.tar.gz 30.0 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for exosomians 0.1.1
File Interpreter ABI Platform
exosomians-0.1.1-py3-none-any.whl Python 3 none any Details

Total release size: 48.1 kB

Release files / exosomians-0.1.1.tar.gz

Download URL exosomians-0.1.1.tar.gz
Size 30.0 kB
Tags Source
SHA-256 checksum
How to use checksums
4704da2407b589817081964864033a4d1fbacfc736c81689d2f513f5b6ef0b58
BLAKE2b-256 checksum
How to use checksums
f3e6782459d73ad4f4eb4bdfe82e9943c7fed633b5f10196b9c72a98e1bf6d69
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via poetry/1.4.1 CPython/3.9.13 Linux/5.4.0-132-generic

Release files / exosomians-0.1.1-py3-none-any.whl

Download URL exosomians-0.1.1-py3-none-any.whl
Size 18.1 kB
Tags Python 3
SHA-256 checksum
How to use checksums
877f44c73d82ddcc9c3ee6c146cd7502e404823442f6f92f441b51419f316d29
BLAKE2b-256 checksum
How to use checksums
660971dab6960fe4bea394fed73526598b9a69c02702f066fbab9bf8a5945e4e
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via poetry/1.4.1 CPython/3.9.13 Linux/5.4.0-132-generic

Release history Release notifications | RSS feed

This release

0.1.1 This release

2 release files

0.1.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page