Clean git history #136
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Clean git history #136
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ladybugbot
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Apr 30, 2019
Pull Request Test Coverage Report for Build 567
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Pull Request Test Coverage Report for Build 567
💛 - Coveralls |
mostaphaRoudsari
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Apr 30, 2019
* Deleted Unnecessary Code * feat(skymodel): Added Perez Luminous Efficacy Model This commit adds the Perez model for luminaious efficacy of the sky, which seems to be the state-of-the-art model for deriving illuminance values from irradiance values. More info on the model can be found in [this paper](http://www.cuepe.ch/html/biblio/pdf/perez-ineichen%201990%20-%20modelling%20daylight%20(se).pdf) and credit is due to @hansukyang for pointing me towards a Python implementation of this model. With this commit, the Ladybug core now possesses enough climate models to make fully-simulate-able EPWs (for both daylight and energy) with only the following: * dry bulb temperature * dew point temperature * atmospheric pressure * sky cover * wind speed * wind direction * Fixing docstring of luminous efficacy * 0.3.0 Automatically generated by python-semantic-release * fix(deploy): use javascript semantic-release package for deployment Using the "pure" javascript implementation of semantic-release makes it a bit more flexible to set up custom scripts to run at different stages of the semantic release process. The packages used as well as scripts to run at different stages are specified in the .releaserc.json file. In this case we use standard semantic-release and add a custom deploy script on top of the normal github release setup. The custom deploy script is the new 'deploy.sh' file which takes the new version number as an argument to deploy the package to PyPi and build the documentation. #125 build(pytest): add pytest-cov deps to dev-requirements.txt build(euclid): add euclid to dev-requirements.txt * build(requirements): cleanup dev-requirements.txt and make python2 compatible * ci(travis): use python image to deploy with semantic-release Seems it's easy enough to install node on a python image but the node image's python distro doesn't play well with https. #125 * fix(deploy): fix travis file for docs deployment #125 * Create .nojekyll see here: https://github.blog/2009-12-29-bypassing-jekyll-on-github-pages/ * fix(init): fix isplus assignment * Update skymodel.py * fix(legendparam): fix import for Python 3 * fix(init): fix conflicts not really! GitHub being crazy. there is no conflicts. * Clean git history (#136) * feat(skymodel): Added Perez Luminous Efficacy Model See 5e0a32c * fix(travis): fix travis file for docs deployment and build
mostaphaRoudsari
added a commit
that referenced
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Apr 30, 2019
* feat(skymodel): Added Perez Luminous Efficacy Model * Deleted Unnecessary Code * feat(skymodel): Added Perez Luminous Efficacy Model This commit adds the Perez model for luminaious efficacy of the sky, which seems to be the state-of-the-art model for deriving illuminance values from irradiance values. More info on the model can be found in [this paper](http://www.cuepe.ch/html/biblio/pdf/perez-ineichen%201990%20-%20modelling%20daylight%20(se).pdf) and credit is due to @hansukyang for pointing me towards a Python implementation of this model. With this commit, the Ladybug core now possesses enough climate models to make fully-simulate-able EPWs (for both daylight and energy) with only the following: * dry bulb temperature * dew point temperature * atmospheric pressure * sky cover * wind speed * wind direction * Fixing docstring of luminous efficacy * 0.3.0 Automatically generated by python-semantic-release * fix(deploy): use javascript semantic-release package for deployment Using the "pure" javascript implementation of semantic-release makes it a bit more flexible to set up custom scripts to run at different stages of the semantic release process. The packages used as well as scripts to run at different stages are specified in the .releaserc.json file. In this case we use standard semantic-release and add a custom deploy script on top of the normal github release setup. The custom deploy script is the new 'deploy.sh' file which takes the new version number as an argument to deploy the package to PyPi and build the documentation. #125 build(pytest): add pytest-cov deps to dev-requirements.txt build(euclid): add euclid to dev-requirements.txt * build(requirements): cleanup dev-requirements.txt and make python2 compatible * ci(travis): use python image to deploy with semantic-release Seems it's easy enough to install node on a python image but the node image's python distro doesn't play well with https. #125 * fix(deploy): fix travis file for docs deployment #125 * Create .nojekyll see here: https://github.blog/2009-12-29-bypassing-jekyll-on-github-pages/ * fix(init): fix isplus assignment * Update skymodel.py * fix(legendparam): fix import for Python 3 * fix(init): fix conflicts not really! GitHub being crazy. there is no conflicts. * Clean git history (#136) * feat(skymodel): Added Perez Luminous Efficacy Model See 5e0a32c * fix(travis): fix travis file for docs deployment and build * docs(conf.py): set version to ''
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