| Name | scikit-fmm JSON |
| Version |
2024.9.16
JSON |
| download |
| home_page | None |
| Summary | An extension module implementing the fast marching method |
| upload_time | 2024-09-16 14:08:25 |
| maintainer | None |
| docs_url | https://pythonhosted.org/scikit-fmm/ |
| author | None |
| requires_python | >=3.9 |
| license | Unless otherwise specified by LICENSE.txt files in individual directories, all code is Copyright (C) 2024 the scikit-fmm team All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither the name of scikit-fmm nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
| keywords |
fast marching method
eikonal equation
interface
boundary
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
  [](http://pypi.python.org/pypi/scikit-fmm)[](https://scikit-fmm.readthedocs.io/en/latest/?badge=latest) <a href="https://pepy.tech/project/scikit-fmm"><img alt="Downloads" src="https://pepy.tech/badge/scikit-fmm"></a>
# scikit-fmm: the fast marching method for Python
`scikit-fmm` is a Python extension module which implements the fast marching method.
The fast marching method is used to model the evolution of boundaries
and interfaces in a variety of application areas. More specifically,
the fast marching method is a numerical technique for finding
approximate solutions to boundary value problems of the Eikonal
equation:
F(x) | grad T(x) | = 1
Typically, such a problem describes the evolution of a closed curve as
a function of time T with speed F(x)>0 in the normal direction at a
point x on the curve. The speed function is specified, and the time at
which the contour crosses a point x is obtained by solving the
equation.
scikit-fmm is a simple module which provides functions to calculate
the signed distance and travel time to an interface described by the
zero contour of the input array phi.
```python
import skfmm
import numpy as np
phi = np.ones((3, 3))
phi[1, 1] = -1
skfmm.distance(phi)
```
```python
array([[ 1.20710678, 0.5 , 1.20710678],
[ 0.5 , -0.35355339, 0.5 ],
[ 1.20710678, 0.5 , 1.20710678]])
```
---
```python
skfmm.travel_time(phi, speed = 3.0 * np.ones_like(phi))
```
```python
array([[ 0.40236893, 0.16666667, 0.40236893],
[ 0.16666667, 0.11785113, 0.16666667],
[ 0.40236893, 0.16666667, 0.40236893]])
```
---
The input array can be of 1, 2, 3 or higher dimensions and can be a
masked array. A function is provided to compute extension velocities.
### Documentation
* http://scikit-fmm.readthedocs.org/en/master/
### PyPI
* http://pypi.python.org/pypi/scikit-fmm
### Requirements
* Numpy >= 1.0.2
* Building requires the pypa/build module
(https://github.com/pypa/build) and a C/C++ compiler
### Bugs, questions, patches, feature requests, discussion & cetera
* Open a GitHub pull request or a GitHub issue
* Email list: http://groups.google.com/group/scikit-fmm
* Send an email to scikit-fmm+subscribe@googlegroups.com to subscribe.
### Installing
* Via pip: `pip install scikit-fmm`
* Anaconda linux-64 and linux-ppc64le packages:
* `conda install scikit-fmm`
* Ubuntu PPA
* https://launchpad.net/~nvidia-digits/+archive/ubuntu/dev
* Debian
* https://tracker.debian.org/pkg/scikit-fmm
### Building and installing from Source
* `pip install build`
* `python -m build`
* `pip install .`
### Running Tests
* `python -c "import skfmm; skfmm.test(True)"` (Do not run the tests from the source directory.)
* Tests are doctests in `skfmm/__init__.py`
### Building documentation
* Requires sphinx and numpydoc
* `make html`
### Publications using scikit-fmm
* Akinola, I., J Varley, B. Chen, and P.K. Allen
(2018) "Workspace Aware Online Grasp Planning" arXiv:1806.11402v1
[cs.RO] 29 Jun 2018 https://arxiv.org/pdf/1806.11402.pdf
* Bortolussi, V., B. Figliuzzi, F. Willot, M.
Faessel, M. Jeandin (2018) "Morphological modeling of cold spray
coatings" Image Anal Stereol 2018;37:145-158 doi:10.5566/ias.1894
https://hal.archives-ouvertes.fr/hal-01837906/document
* Chalmers, S., C.D. Saunter, J.M. Girkin and J.G. McCarron (2016)
"Age decreases mitochondrial motility and increases mitochondrial
size in vascular smooth muscle." Journal of Physiology, 594.15 pp
4283–4295.
* Diogo Brandão Amorim (2014) "Efficient path planning of a mobile
robot on rough terrain" Master's Thesis, Department of Aerospace
Engineering, University of Lisbon.
* Giometto, A., D.R. Nelson, and A.W. Murray (2018)
"Physical interactions reduce the power of natural selection in
growing yeast colonies", PNAS November 6, 2018 115 (45) 11448-11453;
published ahead of print October 23, 2018
https://doi.org/10.1073/pnas.1809587115
* Joshua A. Taillon, Christopher Pellegrinelli, Yilin Huang, Eric D.
Wachsman, and Lourdes G. Salamanca-Riba (2014) "Three Dimensional
Microstructural Characterization of Cathode Degradation in SOFCs
Using Focused Ion Beam and SEM" ECS Trans. 2014 61(1): 109-120;
https://www.joshuataillon.com/pdfs/2015-08-06%20jtaillon%203D%20SOFC%20cathode%20degradation.pdf
* Marshak, C., I. Yanovsky, and L. Vese (2017) "Energy
Minimization for Cirrus and Cumulus Cloud Separation in Atmospheric
Images" IGARSS 2018 - 2018 IEEE International Geoscience and Remote
Sensing Symposium DOI: 10.1109/IGARSS.2018.8517940
ftp://ftp.math.ucla.edu/pub/camreport/cam17-68.pdf
* Moon, K. R., V. Delouille, J.J. Li, R. De Visscher, F. Watson and
A.O. Hero III (2016) "Image patch analysis of sunspots and active
regions." J. Space Weather Space Clim., 6, A3, DOI:
10.1051/swsc/2015043.
* Tao, M., J. Solomon and A. Butscher (2016) "Near-Isometric Level Set
Tracking." in Eurographics Symposium on Geometry Processing 2016
Eds: M. Ovsjanikov and D. Panozzo. Volume 35 (2016), Number 5
* Thibaut, R., Laloy, E., Hermans, T., 2021. A new framework for
experimental design using Bayesian Evidential Learning: The
case of wellhead protection area. J. Hydrol. 603, 126903.
https://doi.org/10.1016/j.jhydrol.2021.126903
* Vargiu, Antioco, M. Marrocu, L. Massidda (2015) "Implementazione e
valutazione su un caso reale del servizio di Cloud Computing per la
simulazione di incendi boschivi in Sardegna" (Implementation and
evaluation on a real case of Cloud computing service for simulation
of Forest fires in Sardinia). Sardinia Department of Energy and
Environment. CRS4 PIA 2010 D5.4.
* Wronkiewicz, M. (2018) "Mapping buildings with help from machine
learning" Medium article, June 29th 2018
https://medium.com/devseed/mapping-buildings-with-help-from-machine-learning-f8d8d221214a
* Makki, K., Ben Salem, D., Ben Amor, B. (2021) "Toward the Assessment
of Intrinsic Geometry of Implicit Brain MRI Manifolds" IEEE Access,
volume 9, pages 131054 - 131071 (September 2021)
DOI: 10.1109/ACCESS.2021.3113611
https://ieeexplore.ieee.org/abstract/document/9540688
### Version History:
* 0.0.1: February 13 2012
* Initial release
* 0.0.2: February 26th 2012
* Including tests and docs in source distribution. Minor changes to
documentation.
* 0.0.3: August 4th 2012
* Extension velocities.
* Fixes for 64 bit platforms.
* Optional keyword argument for point update order.
* Bug reports and patches from three contributors.
* 0.0.4: October 15th 2012
* Contributions from Daniel Wheeler:
* Bug fixes in extension velocity.
* Many additional tests and migration to doctest format.
* Additional optional input to extension_velocities() for FiPy compatibly.
* 0.0.5: May 12th 2014
* Fix for building with MSVC (Jan Margeta).
* Corrected second-order point update.
* 0.0.6: February 20th 2015
* Documentation clarification (Geordie McBain).
* Python 3 port (Eugene Prilepin).
* Python wrapper for binary min-heap.
* Freeze equidistant narrow-band points simultaneously.
* 0.0.7: October 21st 2015
* Bug fix to upwind finite difference approximation for negative
phi from Lester Hedges.
* 0.0.8: March 9th 2016
* Narrow band capability: an optional "narrow" keyword argument
limits the extent of the marching algorithm (Adrian Butscher).
* 0.0.9: August 5th 2016
* Periodic boundaries: an optional "periodic" keyword argument
enables periodic boundaries in one or more directions (Wolfram Moebius).
* 2019.1.30 January 30th 2019
* Abrupt change to version numbering scheme.
* Bugfix in setup.py to allow installing via pip with numpy (ManifoldFR).
* Handle C++ exceptions during fast marching (Jens Glaser).
* Accept a zero discriminant in travel time point update.
* 2021.1.20 January 20th 2021
* Fix divide by zero bugs in travel_time and extension_velocities
* Contributions from Murray Cutforth, f-fanni, and okonrad
* 2021.1.21 January 21st 2021
* Minor C++ change (removed the auto keyword) to fix the compile on TravisCI.
* 2021.2.2 February 2nd 2021
* Add a pyproject.toml file to specify numpy as a build
requirement, this is needed to build with new version of pip
(David Parsson).
* 2021.7.8 July 8th 2021
* Add a pyproject.toml file to the MANIFEST.in file to fix the
numpy build dependency (David Parsson). Fix numpy deprecation
warnings and improve source code formatting (Robin Thibaut).
* 2021.9.23 September 23rd 2021
* Make the pyproject.toml file specify the oldest supported
numpy as a build requirement, to allow using wheels with any
numpy version.
(David Parsson).
* 2021.10.29 October 29th 2021
* Fix for point update discriminant exactly equal to zero
* Fall back calculation for point update when discriminant becomes negative
* (Joshua Gehre)
* 2022.02.02 February 2nd 2022
* Fixes for Python 3.10 compatibility
* (Amin Sadeghi, Xylar Asay-Davis, David Parsson)
* 2022.03.26 March 26th 2022
* Following the breaking changes in setuptools v61.0.0 it is
suggested to set py_modules to disable auto-discovery behavior.
* (Daniel Ammar)
* 2022.08.15 August 15th 2022
* Following the breaking changes in setuptools v65 pin setuptools
to v64
* (DorSSS)
* 2022.04.02 April 2nd 2023
* Build fixes for Python 3.11 (update pheap cython wrapper)
* No solver changes
* 2024.05.29 May 29th 2024
* Update build system to use meson
* Python 3.12 support
* No solver changes
* 2024.09.16 September 16th 2024
* Update build to use NumPy 2.0
* Known issue: Windows tests failing with NumPy 2.0
* No solver changes
Copyright 2024 The scikit-fmm team.
BSD-style license. See LICENSE.txt in the source directory.
Raw data
{
"_id": null,
"home_page": null,
"name": "scikit-fmm",
"maintainer": null,
"docs_url": "https://pythonhosted.org/scikit-fmm/",
"requires_python": ">=3.9",
"maintainer_email": null,
"keywords": "fast marching method, Eikonal equation, interface, boundary",
"author": null,
"author_email": "Jason Furtney <jkfurtney@gmail.com>",
"download_url": "https://files.pythonhosted.org/packages/03/7e/484f704353b19a1cdbe92409def6f06635ae6d7fef9148bda6a5e962ed7b/scikit_fmm-2024.9.16.tar.gz",
"platform": null,
"description": "  [](http://pypi.python.org/pypi/scikit-fmm)[](https://scikit-fmm.readthedocs.io/en/latest/?badge=latest) <a href=\"https://pepy.tech/project/scikit-fmm\"><img alt=\"Downloads\" src=\"https://pepy.tech/badge/scikit-fmm\"></a>\n\n# scikit-fmm: the fast marching method for Python\n\n`scikit-fmm` is a Python extension module which implements the fast marching method.\nThe fast marching method is used to model the evolution of boundaries\nand interfaces in a variety of application areas. More specifically,\nthe fast marching method is a numerical technique for finding\napproximate solutions to boundary value problems of the Eikonal\nequation:\n\nF(x) | grad T(x) | = 1\n\nTypically, such a problem describes the evolution of a closed curve as\na function of time T with speed F(x)>0 in the normal direction at a\npoint x on the curve. The speed function is specified, and the time at\nwhich the contour crosses a point x is obtained by solving the\nequation.\n\nscikit-fmm is a simple module which provides functions to calculate\nthe signed distance and travel time to an interface described by the\nzero contour of the input array phi.\n\n```python\nimport skfmm\nimport numpy as np\nphi = np.ones((3, 3))\nphi[1, 1] = -1\nskfmm.distance(phi)\n```\n\n ```python\n array([[ 1.20710678, 0.5 , 1.20710678],\n [ 0.5 , -0.35355339, 0.5 ],\n [ 1.20710678, 0.5 , 1.20710678]])\n ```\n---\n```python\nskfmm.travel_time(phi, speed = 3.0 * np.ones_like(phi))\n```\n\n ```python\n array([[ 0.40236893, 0.16666667, 0.40236893],\n [ 0.16666667, 0.11785113, 0.16666667],\n [ 0.40236893, 0.16666667, 0.40236893]])\n ```\n---\n\nThe input array can be of 1, 2, 3 or higher dimensions and can be a\nmasked array. A function is provided to compute extension velocities.\n\n### Documentation\n* http://scikit-fmm.readthedocs.org/en/master/\n\n### PyPI\n* http://pypi.python.org/pypi/scikit-fmm\n\n### Requirements\n* Numpy >= 1.0.2\n* Building requires the pypa/build module\n (https://github.com/pypa/build) and a C/C++ compiler\n### Bugs, questions, patches, feature requests, discussion & cetera\n* Open a GitHub pull request or a GitHub issue\n* Email list: http://groups.google.com/group/scikit-fmm\n * Send an email to scikit-fmm+subscribe@googlegroups.com to subscribe.\n\n### Installing\n* Via pip: `pip install scikit-fmm`\n* Anaconda linux-64 and linux-ppc64le packages:\n * `conda install scikit-fmm`\n* Ubuntu PPA\n * https://launchpad.net/~nvidia-digits/+archive/ubuntu/dev\n* Debian\n * https://tracker.debian.org/pkg/scikit-fmm\n\n### Building and installing from Source\n* `pip install build`\n* `python -m build`\n* `pip install .`\n\n\n### Running Tests\n* `python -c \"import skfmm; skfmm.test(True)\"` (Do not run the tests from the source directory.)\n* Tests are doctests in `skfmm/__init__.py`\n\n### Building documentation\n* Requires sphinx and numpydoc\n* `make html`\n\n### Publications using scikit-fmm\n\n* Akinola, I., J Varley, B. Chen, and P.K. Allen\n (2018) \"Workspace Aware Online Grasp Planning\" arXiv:1806.11402v1\n [cs.RO] 29 Jun 2018 https://arxiv.org/pdf/1806.11402.pdf\n\n* Bortolussi, V., B. Figliuzzi, F. Willot, M.\n Faessel, M. Jeandin (2018) \"Morphological modeling of cold spray\n coatings\" Image Anal Stereol 2018;37:145-158 doi:10.5566/ias.1894\n https://hal.archives-ouvertes.fr/hal-01837906/document\n\n* Chalmers, S., C.D. Saunter, J.M. Girkin and J.G. McCarron (2016)\n \"Age decreases mitochondrial motility and increases mitochondrial\n size in vascular smooth muscle.\" Journal of Physiology, 594.15 pp\n 4283\u20134295.\n\n* Diogo Brand\u00e3o Amorim (2014) \"Efficient path planning of a mobile\n robot on rough terrain\" Master's Thesis, Department of Aerospace\n Engineering, University of Lisbon.\n\n* Giometto, A., D.R. Nelson, and A.W. Murray (2018)\n \"Physical interactions reduce the power of natural selection in\n growing yeast colonies\", PNAS November 6, 2018 115 (45) 11448-11453;\n published ahead of print October 23, 2018\n https://doi.org/10.1073/pnas.1809587115\n\n* Joshua A. Taillon, Christopher Pellegrinelli, Yilin Huang, Eric D.\n Wachsman, and Lourdes G. Salamanca-Riba (2014) \"Three Dimensional\n Microstructural Characterization of Cathode Degradation in SOFCs\n Using Focused Ion Beam and SEM\" ECS Trans. 2014 61(1): 109-120;\n https://www.joshuataillon.com/pdfs/2015-08-06%20jtaillon%203D%20SOFC%20cathode%20degradation.pdf\n\n* Marshak, C., I. Yanovsky, and L. Vese (2017) \"Energy\n Minimization for Cirrus and Cumulus Cloud Separation in Atmospheric\n Images\" IGARSS 2018 - 2018 IEEE International Geoscience and Remote\n Sensing Symposium DOI: 10.1109/IGARSS.2018.8517940\n ftp://ftp.math.ucla.edu/pub/camreport/cam17-68.pdf\n\n* Moon, K. R., V. Delouille, J.J. Li, R. De Visscher, F. Watson and\n A.O. Hero III (2016) \"Image patch analysis of sunspots and active\n regions.\" J. Space Weather Space Clim., 6, A3, DOI:\n 10.1051/swsc/2015043.\n\n* Tao, M., J. Solomon and A. Butscher (2016) \"Near-Isometric Level Set\n Tracking.\" in Eurographics Symposium on Geometry Processing 2016\n Eds: M. Ovsjanikov and D. Panozzo. Volume 35 (2016), Number 5\n\n* Thibaut, R., Laloy, E., Hermans, T., 2021. A new framework for\n experimental design using Bayesian Evidential Learning: The\n case of wellhead protection area. J. Hydrol. 603, 126903.\n https://doi.org/10.1016/j.jhydrol.2021.126903\n\n* Vargiu, Antioco, M. Marrocu, L. Massidda (2015) \"Implementazione e\n valutazione su un caso reale del servizio di Cloud Computing per la\n simulazione di incendi boschivi in Sardegna\" (Implementation and\n evaluation on a real case of Cloud computing service for simulation\n of Forest fires in Sardinia). Sardinia Department of Energy and\n Environment. CRS4 PIA 2010 D5.4.\n\n* Wronkiewicz, M. (2018) \"Mapping buildings with help from machine\n learning\" Medium article, June 29th 2018\n https://medium.com/devseed/mapping-buildings-with-help-from-machine-learning-f8d8d221214a\n\n* Makki, K., Ben Salem, D., Ben Amor, B. (2021) \"Toward the Assessment\n of Intrinsic Geometry of Implicit Brain MRI Manifolds\" IEEE Access,\n volume 9, pages 131054 - 131071 (September 2021)\n DOI: 10.1109/ACCESS.2021.3113611\n https://ieeexplore.ieee.org/abstract/document/9540688\n\n### Version History:\n* 0.0.1: February 13 2012\n * Initial release\n* 0.0.2: February 26th 2012\n * Including tests and docs in source distribution. Minor changes to\n documentation.\n* 0.0.3: August 4th 2012\n * Extension velocities.\n * Fixes for 64 bit platforms.\n * Optional keyword argument for point update order.\n * Bug reports and patches from three contributors.\n* 0.0.4: October 15th 2012\n * Contributions from Daniel Wheeler:\n * Bug fixes in extension velocity.\n * Many additional tests and migration to doctest format.\n * Additional optional input to extension_velocities() for FiPy compatibly.\n* 0.0.5: May 12th 2014\n * Fix for building with MSVC (Jan Margeta).\n * Corrected second-order point update.\n* 0.0.6: February 20th 2015\n * Documentation clarification (Geordie McBain).\n * Python 3 port (Eugene Prilepin).\n * Python wrapper for binary min-heap.\n * Freeze equidistant narrow-band points simultaneously.\n* 0.0.7: October 21st 2015\n * Bug fix to upwind finite difference approximation for negative\n phi from Lester Hedges.\n* 0.0.8: March 9th 2016\n * Narrow band capability: an optional \"narrow\" keyword argument\n limits the extent of the marching algorithm (Adrian Butscher).\n* 0.0.9: August 5th 2016\n * Periodic boundaries: an optional \"periodic\" keyword argument\n enables periodic boundaries in one or more directions (Wolfram Moebius).\n* 2019.1.30 January 30th 2019\n * Abrupt change to version numbering scheme.\n * Bugfix in setup.py to allow installing via pip with numpy (ManifoldFR).\n * Handle C++ exceptions during fast marching (Jens Glaser).\n * Accept a zero discriminant in travel time point update.\n* 2021.1.20 January 20th 2021\n * Fix divide by zero bugs in travel_time and extension_velocities\n * Contributions from Murray Cutforth, f-fanni, and okonrad\n* 2021.1.21 January 21st 2021\n * Minor C++ change (removed the auto keyword) to fix the compile on TravisCI.\n* 2021.2.2 February 2nd 2021\n * Add a pyproject.toml file to specify numpy as a build\n requirement, this is needed to build with new version of pip\n (David Parsson).\n* 2021.7.8 July 8th 2021\n * Add a pyproject.toml file to the MANIFEST.in file to fix the\n numpy build dependency (David Parsson). Fix numpy deprecation\n warnings and improve source code formatting (Robin Thibaut).\n* 2021.9.23 September 23rd 2021\n * Make the pyproject.toml file specify the oldest supported\n numpy as a build requirement, to allow using wheels with any\n numpy version.\n (David Parsson).\n* 2021.10.29 October 29th 2021\n * Fix for point update discriminant exactly equal to zero\n * Fall back calculation for point update when discriminant becomes negative\n * (Joshua Gehre)\n* 2022.02.02 February 2nd 2022\n * Fixes for Python 3.10 compatibility\n * (Amin Sadeghi, Xylar Asay-Davis, David Parsson)\n* 2022.03.26 March 26th 2022\n * Following the breaking changes in setuptools v61.0.0 it is\n suggested to set py_modules to disable auto-discovery behavior.\n * (Daniel Ammar)\n* 2022.08.15 August 15th 2022\n * Following the breaking changes in setuptools v65 pin setuptools\n to v64\n * (DorSSS)\n* 2022.04.02 April 2nd 2023\n * Build fixes for Python 3.11 (update pheap cython wrapper)\n * No solver changes\n* 2024.05.29 May 29th 2024\n * Update build system to use meson\n * Python 3.12 support\n * No solver changes\n* 2024.09.16 September 16th 2024\n * Update build to use NumPy 2.0\n * Known issue: Windows tests failing with NumPy 2.0\n * No solver changes\n\n\nCopyright 2024 The scikit-fmm team.\n\nBSD-style license. See LICENSE.txt in the source directory.\n",
"bugtrack_url": null,
"license": "Unless otherwise specified by LICENSE.txt files in individual directories, all code is Copyright (C) 2024 the scikit-fmm team All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither the name of scikit-fmm nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.",
"summary": "An extension module implementing the fast marching method",
"version": "2024.9.16",
"project_urls": null,
"split_keywords": [
"fast marching method",
" eikonal equation",
" interface",
" boundary"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "037e484f704353b19a1cdbe92409def6f06635ae6d7fef9148bda6a5e962ed7b",
"md5": "f11bf1a1f297ef74d15ae45b4e165296",
"sha256": "aba86ab5e5efeb4d221fbc6908a1e044b909612a72f6121ffd09e5b1823e8e1e"
},
"downloads": -1,
"filename": "scikit_fmm-2024.9.16.tar.gz",
"has_sig": false,
"md5_digest": "f11bf1a1f297ef74d15ae45b4e165296",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.9",
"size": 465925,
"upload_time": "2024-09-16T14:08:25",
"upload_time_iso_8601": "2024-09-16T14:08:25.533094Z",
"url": "https://files.pythonhosted.org/packages/03/7e/484f704353b19a1cdbe92409def6f06635ae6d7fef9148bda6a5e962ed7b/scikit_fmm-2024.9.16.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-09-16 14:08:25",
"github": false,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"lcname": "scikit-fmm"
}
