Skip to main content

Hierarchical Manifold Approximation and Projection for Single Cell Data

Project description

HMAP: Hierarchical Manifold Approximation and Projection

HMAP develop a hierarchical deep generative topographic mapping algorithm to realize the recovery of both global and local manifolds underlying single-cell data.

Installation

  1. Create a virtual environment and activate it
conda create -n HMAP python=3.10 scipy numpy pandas scikit-learn && conda activate HMAP
  1. Install PyTorch following the official instruction.
pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu126
  1. Install HMAP
pip3 install HMAP-tool

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

hmap_tool-1.0.4.tar.gz (21.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

hmap_tool-1.0.4-py3-none-any.whl (22.4 kB view details)

Uploaded Python 3

File details

Details for the file hmap_tool-1.0.4.tar.gz.

File metadata

  • Download URL: hmap_tool-1.0.4.tar.gz
  • Upload date:
  • Size: 21.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.18

File hashes

Hashes for hmap_tool-1.0.4.tar.gz
Algorithm Hash digest
SHA256 58ab3515949deba0395bf4a915d4d0de66730c8ffe620fdb9b45d8913ea73791
MD5 287bccbce46a2487b565268d1607f59d
BLAKE2b-256 e09e25f214942fe5a6fcc24750397fa9721c5d77dc3cf378c7e96fcbe83c880a

See more details on using hashes here.

File details

Details for the file hmap_tool-1.0.4-py3-none-any.whl.

File metadata

  • Download URL: hmap_tool-1.0.4-py3-none-any.whl
  • Upload date:
  • Size: 22.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.18

File hashes

Hashes for hmap_tool-1.0.4-py3-none-any.whl
Algorithm Hash digest
SHA256 1c79ef02c86676d3599597978d2370bc45194b496fb979504a96948ff207ae30
MD5 26c9ac9b7dbf8fe4445530daa11270c5
BLAKE2b-256 b3279803aadfc8368ffdac8ab34050cbe5f653e6ba8e19e069a87357019bbff6

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page