Skip to main content

svVascularize

Version PyPI downloads Platform Latest Release codecov DOI Docs Telemetry Basic smoke test

The svVascularize (svv) is an open-source API for automated vascular generation and multi-fidelity hemodynamic simulation written in Python. Often small-caliber vessels are difficult or infeasible to obtain from experimental data sources despite playing important roles in blood flow regulation and cell microenvironments. svVascularize aims to provide tissue engineers and computational hemodynamic scientists with de novo vasculature that can easily be applied in biomanufacturing applications or computational fluid dynamic (CFD) analysis.

Installation

The package is published on PyPI as svv:

pip install svv

If you are installing into an existing environment and hit NumPy ABI errors such as _ARRAY_API not found or numpy.core.multiarray failed to import, recreate the environment with a NumPy version supported by your Python version. For Python 3.9–3.12, use NumPy 1.x:

python -m pip install --upgrade pip
python -m pip install --force-reinstall "numpy<2" svv

Python 3.13 requires NumPy 2.1 or newer:

python -m pip install --upgrade pip
python -m pip install --force-reinstall "numpy>=2.1" svv

On clusters / HPC systems (for example Stanford Sherlock), use a recent Python (3.9–3.13) and pip, and install into a clean virtual environment or user site-packages.

Basic usage

Import the primary classes from the root package and supporting types from their public subpackages:

from svv import Domain, Forest, Simulation, Tree
from svv.domain import Patch
from svv.tree import TreeParameters, UnitSystem

dir(svv) lists the curated root API. Explicit imports are recommended for application code, and existing deep import paths remain supported for compatibility.

Metadata

Release files for svv 0.0.53

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

Source distribution (sdist)

Source distribution for svv 0.0.53
File Size Uploaded
svv-0.0.53.tar.gz 4.1 MB Details

Built distributions (wheels)

Table of built distributions (wheels) for svv 0.0.53
File
svv-0.0.53-py3-none-win_amd64.whl Python 3 none Windows x86-64 Details
svv-0.0.53-py3-none-musllinux_1_2_x86_64.whl Python 3 none Linux musl 1.2+ x86-64 Details
svv-0.0.53-py3-none-musllinux_1_2_aarch64.whl Python 3 none Linux musl 1.2+ ARM64 Details
svv-0.0.53-py3-none-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl Python 3 none Linux glibc 2.28+ x86-64, Linux glibc 2.24+ x86-64 Details
svv-0.0.53-py3-none-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl Python 3 none Linux glibc 2.24+ ARM64, Linux glibc 2.28+ ARM64 Details
svv-0.0.53-py3-none-macosx_11_0_universal2.whl Python 3 none macOS 11.0+ universal2 (ARM64, x86-64) Details

Total release size: 20.3 MB

Release files / svv-0.0.53.tar.gz

Download URL svv-0.0.53.tar.gz
Size 4.1 MB
Tags Source
SHA-256 checksum
How to use checksums
cdae6d374707aee2869ca8e4d320a4eb1bb1314249943180632cd138a0e15648
BLAKE2b-256 checksum
How to use checksums
b1d9ad2353c6bf1906ab03591a67e06aa5aa4aa6f6d4dc73002240b9a9f7214a
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.14

Release files / svv-0.0.53-py3-none-win_amd64.whl

Download URL svv-0.0.53-py3-none-win_amd64.whl
Size 1.9 MB
Tags Python 3 Windows x86-64
SHA-256 checksum
How to use checksums
78540ccfc0e827229f9325dc8564ca282384370f8a6506f28b7ebe30d5232725
BLAKE2b-256 checksum
How to use checksums
1cd21d86bcc61eb2739597173ecae51e037a5349cfc9efdb0333a2692ead0f88
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.14

Release files / svv-0.0.53-py3-none-musllinux_1_2_x86_64.whl

Download URL svv-0.0.53-py3-none-musllinux_1_2_x86_64.whl
Size 3.3 MB
Tags Linux musl 1.2+ x86-64 Python 3
SHA-256 checksum
How to use checksums
47ce3781862a112bd265b6ce032a8f3d6e195bf8cb958e82c84b9cc04dd25c19
BLAKE2b-256 checksum
How to use checksums
bdf328a6c83c32a1acc007ff6ab0fd57706542e3e9b5b2420ae9cf7eb9791017
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.14

Release files / svv-0.0.53-py3-none-musllinux_1_2_aarch64.whl

Download URL svv-0.0.53-py3-none-musllinux_1_2_aarch64.whl
Size 3.2 MB
Tags Linux musl 1.2+ ARM64 Python 3
SHA-256 checksum
How to use checksums
0762bf5824f1f67d331dc04d72c0e2f09894dc92841d179cd9e6972f7f5d6959
BLAKE2b-256 checksum
How to use checksums
badc83d53dd4df5476b3d7d318a527223bb01318f42db1de2dce8e96b266208c
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.14

Release files / svv-0.0.53-py3-none-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl

Download URL svv-0.0.53-py3-none-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl
Size 2.2 MB
Tags Linux glibc 2.24+ x86-64 Linux glibc 2.28+ x86-64 Python 3
SHA-256 checksum
How to use checksums
fd1ef8c52c772c2ea2b4737b3fd0ef06760f457821021476e59dfa71b24abdc9
BLAKE2b-256 checksum
How to use checksums
0203403f9710e28e961728b6f9584a3529bdefff49454116dc9c3afbb2df3d03
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.14

Release files / svv-0.0.53-py3-none-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl

Download URL svv-0.0.53-py3-none-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl
Size 2.2 MB
Tags Linux glibc 2.24+ ARM64 Linux glibc 2.28+ ARM64 Python 3
SHA-256 checksum
How to use checksums
ba00f8df92c93b685c29f043933c9fd454968aa6cf352f8183005487bbb63e7c
BLAKE2b-256 checksum
How to use checksums
f49485980946acf62497357b0beb6a48573b10b319511fc64eda984ec4e429be
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.14

Release files / svv-0.0.53-py3-none-macosx_11_0_universal2.whl

Download URL svv-0.0.53-py3-none-macosx_11_0_universal2.whl
Size 3.4 MB
Tags Python 3 macOS 11.0+ universal2 (ARM64, x86-64)
SHA-256 checksum
How to use checksums
a9b4447cdb8e2d8eb78e850d60405ca06f7b09e48a7d9e380d9d75950a1e9225
BLAKE2b-256 checksum
How to use checksums
bc03c9f9915ecbd49e154fe833df892a1bc596343ea9caed4e0eb8a356ef8b2c
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.14

Release history Release notifications | RSS feed

0.0.57

7 release files

0.0.56

7 release files

0.0.55

7 release files

0.0.54

7 release files

This release

0.0.53 This release

7 release files

0.0.50

7 release files

0.0.49

7 release files

0.0.48

7 release files

0.0.47

7 release files

0.0.46

7 release files

0.0.45

7 release files

0.0.44

7 release files

0.0.43

2 release files

0.0.42

2 release files

0.0.41

2 release files

0.0.40

2 release files

0.0.39

2 release files

0.0.34

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