Data

Tools

Indexes

Applications

Experiments

Open Source Science

utm

Bidirectional UTM-WGS84 converter for python

https://github.com/turbo87/utm

Science Score: 36.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    2 of 25 committers (8.0%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (9.9%) to scientific vocabulary

Keywords from Contributors

documents zsh-plugin converter png
Last synced: 10 months ago · JSON representation

Repository

Bidirectional UTM-WGS84 converter for python

Basic Info
Statistics
  • Stars: 523
  • Watchers: 13
  • Forks: 103
  • Open Issues: 10
  • Releases: 14
Created over 13 years ago · Last pushed 10 months ago
Metadata Files
Readme Changelog Funding License

README.rst 

utm
===

Bidirectional UTM-WGS84 converter for python

Usage
-----

.. code-block:: python

  >>> import utm

Latitude/Longitude to UTM
^^^^^^^^^^^^^^^^^^^^^^^^^

Convert a ``(latitude, longitude)`` tuple into an UTM coordinate:

.. code-block:: python

  >>> utm.from_latlon(51.2, 7.5)
  (395201.3103811303, 5673135.241182375, 32, 'U')

The syntax is ``utm.from_latlon(LATITUDE, LONGITUDE)``.

The return has the form ``(EASTING, NORTHING, ZONE_NUMBER, ZONE_LETTER)``.

You can also use NumPy arrays for ``LATITUDE`` and ``LONGITUDE``. In the
result ``EASTING`` and ``NORTHING`` will have the same shape.  ``ZONE_NUMBER``
and ``ZONE_LETTER`` are scalars and will be calculated for the first point of
the input. All other points will be set into the same UTM zone.  Therefore
it's a good idea to make sure all points are near each other.

.. code-block:: python

  >>> utm.from_latlon(np.array([51.2, 49.0]), np.array([7.5, 8.4]))
  (array([395201.31038113, 456114.59586214]),
   array([5673135.24118237, 5427629.20426126]),
   32,
   'U')


UTM to Latitude/Longitude
^^^^^^^^^^^^^^^^^^^^^^^^^

Convert an UTM coordinate into a ``(latitude, longitude)`` tuple:

.. code-block:: python

  >>> utm.to_latlon(340000, 5710000, 32, 'U')
  (51.51852098408468, 6.693872395145327)

The syntax is ``utm.to_latlon(EASTING, NORTHING, ZONE_NUMBER, ZONE_LETTER)``.

The return has the form ``(LATITUDE, LONGITUDE)``.

You can also use NumPy arrays for ``EASTING`` and ``NORTHING``. In the result
``LATITUDE`` and ``LONGITUDE`` will have the same shape.  ``ZONE_NUMBER`` and
``ZONE_LETTER`` are scalars.

.. code-block:: python

    >>> utm.to_latlon(np.array([395200, 456100]), np.array([5673100, 5427600]), 32, 'U')
    (array([51.19968297, 48.99973627]), array([7.49999141, 8.3998036 ]))


Since the zone letter is not strictly needed for the conversion you may also
the ``northern`` parameter instead, which is a named parameter and can be set
to either ``True`` or ``False``. Have a look at the unit tests to see how it
can be used.

The UTM coordinate system is explained on
`this `_
Wikipedia page.

Speed
-----

The library has been compared to the more generic pyproj library by running
the unit test suite through pyproj instead of utm. These are the results:

* with pyproj (without projection cache): 4.0 - 4.5 sec
* with pyproj (with projection cache): 0.9 - 1.0 sec
* with utm: 0.4 - 0.5 sec

NumPy arrays bring another speed improvement (on a different computer than the
previous test). Using ``utm.from_latlon(x, y)`` to convert one million points:

* one million calls (``x`` and ``y`` are floats): 1,000,000 × 90µs = 90s
* one call (``x`` and ``y`` are numpy arrays of one million points): 0.26s

Development
-----------

Create a new ``virtualenv`` and install the library via ``pip install -e .``.
After that install the ``pytest`` package via ``pip install pytest`` and run
the unit test suite by calling ``pytest``.

Changelog
---------

see `CHANGELOG.rst `_ file

Authors
-------

* Bart van Andel 
* Tobias Bieniek 
* Torstein I. Bø

License
-------

Copyright (C) 2012 Tobias Bieniek 

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Owner

  • Name: Tobias Bieniek
  • Login: Turbo87
  • Kind: user
  • Location: Aachen, Germany
  • Company: @rustfoundation

🛩️ glider pilot – 🦀 crates.io team co-lead – 🐹 Ember CLI team emeritus

GitHub Events

Total
  • Create event: 18
  • Release event: 7
  • Issues event: 18
  • Watch event: 29
  • Delete event: 18
  • Issue comment event: 44
  • Push event: 35
  • Pull request review comment event: 1
  • Pull request review event: 4
  • Pull request event: 40
  • Fork event: 4
Last Year
  • Create event: 18
  • Release event: 7
  • Issues event: 18
  • Watch event: 29
  • Delete event: 18
  • Issue comment event: 44
  • Push event: 35
  • Pull request review comment event: 1
  • Pull request review event: 4
  • Pull request event: 40
  • Fork event: 4

Committers

Last synced: about 1 year ago

All Time
  • Total Commits: 166
  • Total Committers: 25
  • Avg Commits per committer: 6.64
  • Development Distribution Score (DDS): 0.542
Past Year
  • Commits: 22
  • Committers: 7
  • Avg Commits per committer: 3.143
  • Development Distribution Score (DDS): 0.636
Top Committers
Name Email Commits
Tobias Bieniek T****k@g****e 76
renovate[bot] 2****] 21
Bart van Andel b****l@g****m 13
Miroslav Šedivý 6****o 7
Juan Luis Cano Rodríguez j****u@s****m 6
Heath Henley h****y@g****m 6
Paarth Shah m****l@s****m 5
Alan D. Snow a****w@u****l 4
Pablo Sotres p****s@t****s 4
Torstein I. Bø t****r 3
Eivind Fonn e****n@g****m 2
Arnaldo Russo a****o@g****m 2
JamesParrott 8****t 2
Richard Barnes r****s@u****u 2
Steven Hiscocks s****s@d****k 2
Paul Hovey p****y@s****m 2
Chencheng Zhang 4****g 1
Christian Ewald v****b@y****m 1
David Hotham d****m@b****k 1
Lipeng Guo i@g****i 1
Renovate Bot b****t@r****m 1
chlxt 5****t 1
unknown l****e@M****k 1
JackKiefer j****r@g****m 1
hogend r****n@r****l 1
Committer Domains (Top 20 + Academic)
rmer.nl: 1 mhp538.ad.nerc.ac.uk: 1 renovateapp.com: 1 glp.ai: 1 blueyonder.co.uk: 1 smart-ag.com: 1 dstl.gov.uk: 1 umn.edu: 1 tlmat.unican.es: 1 usace.army.mil: 1 shahpaarth.com: 1 satellogic.com: 1 gmx.de: 1

Issues and Pull Requests

Last synced: 10 months ago

All Time
  • Total issues: 51
  • Total pull requests: 92
  • Average time to close issues: over 1 year
  • Average time to close pull requests: 7 months
  • Total issue authors: 49
  • Total pull request authors: 26
  • Average comments per issue: 2.39
  • Average comments per pull request: 1.41
  • Merged pull requests: 69
  • Bot issues: 1
  • Bot pull requests: 40
Past Year
  • Issues: 1
  • Pull requests: 24
  • Average time to close issues: 2 days
  • Average time to close pull requests: 13 days
  • Issue authors: 1
  • Pull request authors: 5
  • Average comments per issue: 6.0
  • Average comments per pull request: 0.63
  • Merged pull requests: 18
  • Bot issues: 0
  • Bot pull requests: 14
View more stats
Top Authors
Issue Authors
  • exfizik (2)
  • senyai (2)
  • geoffleyland (1)
  • psotres (1)
  • emakarov (1)
  • camillechasset (1)
  • greatvovan (1)
  • m4mlo (1)
  • astrojuanlu (1)
  • SimoneRaponi (1)
  • m-sasha (1)
  • BenCrittenden (1)
  • renovate[bot] (1)
  • jgodwin (1)
  • lbillingham (1)
Pull Request Authors
  • renovate[bot] (55)
  • bartvanandel (11)
  • eumiro (9)
  • Turbo87 (5)
  • heathhenley (4)
  • JamesParrott (3)
  • sdhiscocks (3)
  • PaarthShah (2)
  • TheBB (2)
  • astrojuanlu (2)
  • fudanglp (2)
  • rtechencheng (2)
  • LuxMiranda (2)
  • saty9 (2)
  • dimbleby (2)
Top Labels
Issue Labels
enhancement (6) question (3) invalid (2) bug (2) duplicate (1) meta (1)
Pull Request Labels
enhancement (7) internal (4) bug (2) documentation (1) breaking (1)

Packages

  • Total packages: 4
  • Total downloads:
    • pypi 455,460 last-month
  • Total docker downloads: 12,878
  • Total dependent packages: 80
    (may contain duplicates)
  • Total dependent repositories: 768
    (may contain duplicates)
  • Total versions: 55
  • Total maintainers: 1
pypi.org: utm

Bidirectional UTM-WGS84 converter for python

  • Versions: 17
  • Dependent Packages: 70
  • Dependent Repositories: 736
  • Downloads: 455,460 Last month
  • Docker Downloads: 12,878
Rankings
Dependent packages count: 0.3%
Downloads: 0.4%
Dependent repos count: 0.4%
Docker downloads count: 1.5%
Average: 1.7%
Stargazers count: 3.0%
Forks count: 4.7%
Maintainers (1)
Tobias.Bieniek
Last synced: 10 months ago
proxy.golang.org: github.com/Turbo87/utm
  • Versions: 17
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 7.0%
Average: 8.2%
Dependent repos count: 9.3%
Last synced: 10 months ago
proxy.golang.org: github.com/turbo87/utm
  • Versions: 17
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 7.0%
Average: 8.2%
Dependent repos count: 9.3%
Last synced: 10 months ago
conda-forge.org: utm

Bidirectional UTM-WGS84 converter for python.

  • Versions: 4
  • Dependent Packages: 10
  • Dependent Repositories: 32
Rankings
Dependent packages count: 5.9%
Dependent repos count: 6.5%
Average: 12.9%
Stargazers count: 19.4%
Forks count: 19.6%
Last synced: 10 months ago

Dependencies

numpy-requirements.txt pypi
  • numpy ==1.16.6
requirements.txt pypi
  • pytest ==4.6.11
  • pytest-cov ==2.11.1
.github/workflows/ci.yml actions
  • actions/checkout v3 composite
  • actions/setup-python v4 composite
  • pypa/gh-action-pypi-publish v1.5.1 composite
setup.py pypi