Merge branch 'pcmdi_master'

.travis.yml

@@ -1,31 +1,26 @@
 os:
  - linux
-
 language: python
- - "2.7"
+ - "2.7"
+
+sudo: false
 
 before_install:
- - if [ "$TRAVIS_OS_NAME" = "linux" ]; then sudo apt-get update -qq; sudo apt-get install -y gfortran xvfb; fi
+ - export UVCDAT_FEATURE=""
+ - if [ "$TRAVIS_OS_NAME" = "linux" ]; then export UVCDAT_FEATURE="-nox"; fi
  - if [ "$TRAVIS_OS_NAME" = "linux" ] && ! [ -d ${HOME}/miniconda] ; then wget https://repo.continuum.io/miniconda/Miniconda-latest-Linux-x86_64.sh -O miniconda.sh; fi
- - if [ "$TRAVIS_OS_NAME" = "osx" ]; then brew update ; fi 
- - if [ "$TRAVIS_OS_NAME" = "osx" ] && ! [ -d ${HOME}/miniconda ]; then wget https://repo.continuum.io/miniconda/Miniconda-latest-MacOSX-x86_64.sh -O miniconda.sh; fi
- - if [ "$TRAVIS_OS_NAME" = "osx" ] && ! [ -d /usr/local/gfortran ]; then wget https://github.com/UV-CDAT/uvcdat/releases/download/v2.4.1/gfortran-4.9.2-Mac.tar.gz -O ~/gfortran-4.9.2-Mac.tar.gz ; pushd / ; sudo tar xzvf ~/gfortran-4.9.2-Mac.tar.gz ; pushd ; fi
  - export PATH="$HOME/miniconda/bin:$PATH"
- - if [ ! -d ${HOME}/miniconda ]; then bash miniconda.sh -b -p $HOME/miniconda ; conda install --yes --channel uvcdat python=2.7 setuptools cdms2 cdutil genutil unidata cdtime vcs ; fi
+ - if [ ! -d ${HOME}/miniconda ]; then bash miniconda.sh -b -p $HOME/miniconda ; conda install --yes --channel uvcdat/label/nightly -c uvcdat uvcdat${UVCDAT_FEATURE} hdf5==1.8.16  ; fi
  - hash -r
  - conda config --set always_yes yes --set changeps1 no
  - conda update -q conda
- - conda update -q cdms2 cdutil genutil unidata cdtime vcs -c uvcdat
  - conda install openssl=1.0.2d
- - conda update -f -c doutriaux1/label/doutriaux1 -c cdoutrix -c uvcdat --show-channel-urls -q -y vtk
  # Useful for debugging any issues with conda
  - conda info -a
 
 install:
  - python setup.py install
 
-before_script:
- - if [ "$TRAVIS_OS_NAME" = "linux" ]; then export DISPLAY=:99.0 ; sh -e /etc/init.d/xvfb start ; sleep 3 ; fi
-
 script:
+ - export HDF5_DISABLE_VERSION_CHECK=1
  - python test/test_suite.py # --no-graphics

README.md

@@ -1,16 +1,14 @@
 PCMDI metrics package (PMP)
 ======
-[![stable version](http:https://img.shields.io/badge/stable version-1.0-brightgreen.svg)](https://github.com/PCMDI/pcmdi_metrics/releases/tag/1.0)
+[![stable version](http:https://img.shields.io/badge/stable version-1.1-brightgreen.svg)](https://github.com/PCMDI/pcmdi_metrics/releases/tag/1.1)
 ![repo size](https://reposs.herokuapp.com/?path=PCMDI/pcmdi_metrics)
 ![platforms](http:https://img.shields.io/badge/platforms-linux | osx-lightgrey.svg)
-[![DOI](http:https://img.shields.io/badge/DOI-10.5281/zenodo.13952-orange.svg)](http:https://doi.org/10.5281/zenodo.13952)
-[![Anaconda-Server
-Badge](https://anaconda.org/pcmdi/pcmdi_metrics/badges/installer/conda.svg)](https://conda.anaconda.org/pcmdi)
-[![Anaconda-Server
-Badge](https://anaconda.org/pcmdi/pcmdi_metrics/badges/downloads.svg)](https://anaconda.org/pcmdi/pcmdi_metrics)
+[![DOI](http:https://img.shields.io/badge/DOI-10.5281/zenodo.58439-orange.svg)](http:https://doi.org/10.5281/zenodo.58439)
+[![Anaconda-Server Badge](https://anaconda.org/pcmdi/pcmdi_metrics/badges/installer/conda.svg)](https://conda.anaconda.org/pcmdi)
+[![Anaconda-Server Badge](https://anaconda.org/pcmdi/pcmdi_metrics/badges/downloads.svg)](https://anaconda.org/pcmdi/pcmdi_metrics)
 
 
-The PCMDI metrics package is used to objectively compare results from climate models with observations using well-established statistical tests. Results are produced in the context of all model simulations contributed to CMIP5 and earlier CMIP phases. Among other purposes, this enables modeling groups to evaluate changes during the development cycle in the context of the structural error distribution of the multi-model ensemble. Currently, the comparisons emphasize large- to global-scale annual cycle performance metrics, although there are v1.1x branches soon be committed to master that include established statistics for ENSO, regional monsoon precipitation, and the diurnal cycle of preciptation.
+The PCMDI metrics package is used to objectively compare results from climate models with observations using well-established statistical tests. Results are produced in the context of all model simulations contributed to CMIP5 and earlier CMIP phases. Among other purposes, this enables modeling groups to evaluate changes during the development cycle in the context of the structural error distribution of the multi-model ensemble. Currently, the comparisons emphasize large- to global-scale annual cycle performance metrics. Current work in v1.x development branches include established statistics for ENSO, regional monsoon precipitation, and the diurnal cycle of precipitation. These diagnostics will be included in a future PMP release.
 
 The metrics package consists of four parts: 1) Analysis software, 2) an observationally-based database of global (or near global, land or ocean) annual cycle climatologies, 3) a database of performance metrics computed for CMIP models and 4) package documentation.
 The package expects model data to be [CF-compliant](http:https://cfconventions.org/). To successfully use the package some input data "conditioning" may be required. We provide several demo scripts within the package to facilitate new users.
@@ -31,11 +29,6 @@ Some installation support for CMIP participating modeling groups is available: p
 PMP versions
 ------------
 
-v1.0 - prototype version of the PMP
-
-v1.1 - First public release, emphasizing climatological statistics, with development branch for ENSO and regional monsoon precipitation indices.
-
-
-
-
+v1.0 - Prototype version of the PMP
 
+v1.1 - First public release, emphasizing climatological statistics, with development branches for ENSO and regional monsoon precipitation indices

conda-recipes/pcmdi_metrics/meta.yaml

@@ -1,9 +1,9 @@
 package:
  name: pcmdi_metrics
- version: 1.0.5
+ version: 1.1
 
 source:
- git_rev: master
+ git_rev: 1.1
  git_url: git:https://github.com/PCMDI/pcmdi_metrics
 
 build:
@@ -16,9 +16,9 @@ requirements:
  - setuptools
  - numpy <=1.9.2
  run:
- - vcs
+ - vcs >=2.6
  - vcsaddons
- - cdms2
+ - cdms2 >=2.6
  - genutil
  - cdutil
  - unidata