Mercurial > repos > ecology > xarray_netcdf2netcdf
changeset 0:b0780241f916 draft
"planemo upload for repository https://github.com/galaxyecology/tools-ecology/tree/master/tools/data_manipulation/xarray/ commit 57b6d23e3734d883e71081c78e77964d61be82ba"
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/README.md Sun Jun 06 08:50:11 2021 +0000 @@ -0,0 +1,8 @@ +# Xarray tools for netCDF +## netCDF metadata information + +The first tool `xarray_metadata_info ` uses xarray to provide users with general information about variable names, dimensions +and attributes. +Variables that can be extracted and dimensions available are printed in a tabular file. + +The tool also print a general information file. It's the result of the xarray method info().
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/macros.xml Sun Jun 06 08:50:11 2021 +0000 @@ -0,0 +1,185 @@ +<macros> + <token name="@TOOL_VERSION@">0.18.2</token> + <token name="@VERSION_SUFFIX@">0</token> + <xml name="edam_ontology"> + <edam_topics> + <edam_topic>topic_0610</edam_topic> + <edam_topic>topic_3050</edam_topic> + </edam_topics> + </xml> + <xml name="citations"> + <citations> + <citation type="bibtex"> + @article{hoyer2017xarray, + title = {xarray: {N-D} labeled arrays and datasets in {Python}}, + author = {Hoyer, S. and J. Hamman}, + journal = {Journal of Open Research Software}, + volume = {5}, + number = {1}, + year = {2017}, + publisher = {Ubiquity Press}, + doi = {10.5334/jors.148}, + url = {http://doi.org/10.5334/jors.148} + } + </citation> + </citations> + </xml> + <xml name="customize_appearance_plots"> + <param name="borders" type="float" optional="true" label="Add country borders with alpha value [0-1] (optional)" /> + <param name="coastline" type="float" optional="true" label="Add coastline with alpha value [0-1] (optional)" /> + <param name="ocean" type="float" optional="true" label="Add ocean with alpha value [0-1] (optional)" /> + <param name="land" type="float" optional="true" label="Add land with alpha value [0-1] (optional)" /> + <param name="title" type="text" optional="true" label="Specify plot title (optional)" /> + <param name="colorbar_label" type="text" optional="true" label="Set a label for colormap (optional)" /> + <param name="cmap" type="select" optional="true" label="Specify which colormap to use for plotting (optional)"> + <option value="cm.batlow">batlow</option> + <option value="cm.batlowW">batlowW</option> + <option value="cm.batlowK">batlowK</option> + <option value="cm.devon">devon</option> + <option value="cm.davos">davos</option> + <option value="cm.oslo">oslo</option> + <option value="cm.lapaz">lapaz</option> + <option value="cm.acton">acton</option> + <option value="cm.lajolla">lajolla</option> + <option value="cm.bilbao">bilbao</option> + <option value="cm.grayC">grayC</option> + <option value="cm.tokyo">tokyo</option> + <option value="cm.turku">turku</option> + <option value="cm.bamako">bamako</option> + <option value="cm.nuuk">nuuk</option> + <option value="cm.hawaii">hawaii</option> + <option value="cm.buda">buda</option> + <option value="cm.imola">imola</option> + <option value="cm.broc">broc</option> + <option value="cm.lisbon">lisbon</option> + <option value="cm.roma">roma</option> + <option value="cm.cork">cork</option> + <option value="cm.tofino">tofino</option> + <option value="cm.bam">bam</option> + <option value="cm.vik">vik</option> + <option value="cm.berlin">berlin</option> + <option value="cm.vanimo">vanimo</option> + <option value="cm.oleron">oleron</option> + <option value="cm.bukavu">bukavu</option> + <option value="cm.fes">fes</option> + <option value="cm.romaO">romaO</option> + <option value="cm.bamO">bamO</option> + <option value="cm.brocO">brocO</option> + <option value="cm.corkO">corkO</option> + <option value="cm.vikO">vikO</option> + <option value="cm.batlow_r">batlow_r</option> + <option value="cm.batlowW_r">batlowW_r</option> + <option value="cm.batlowK_r">batlowK_r</option> + <option value="cm.devon_r">devon_r</option> + <option value="cm.davos_r">davos_r</option> + <option value="cm.oslo_r">oslo_r</option> + <option value="cm.lapaz_r">lapaz_r</option> + <option value="cm.acton_r">acton_r</option> + <option value="cm.lajolla_r">lajolla_r</option> + <option value="cm.bilbao_r">bilbao_r</option> + <option value="cm.grayC_r">grayC_r</option> + <option value="cm.tokyo_r">tokyo_r</option> + <option value="cm.turku_r">turku_r</option> + <option value="cm.bamako_r">bamako_r</option> + <option value="cm.nuuk_r">nuuk_r</option> + <option value="cm.hawaii_r">hawaii_r</option> + <option value="cm.buda_r">buda_r</option> + <option value="cm.imola_r">imola_r</option> + <option value="cm.broc_r">broc_r</option> + <option value="cm.lisbon_r">lisbon_r</option> + <option value="cm.roma_r">roma_r</option> + <option value="cm.cork_r">cork_r</option> + <option value="cm.tofino_r">tofino_r</option> + <option value="cm.bam_r">bam_r</option> + <option value="cm.vik_r">vik_r</option> + <option value="cm.berlin_r">berlin_r</option> + <option value="cm.vanimo_r">vanimo_r</option> + <option value="cm.oleron_r">oleron_r</option> + <option value="cm.bukavu_r">bukavu_r</option> + <option value="cm.fes_r">fes_r</option> + <option value="cm.romaO_r">romaO_r</option> + <option value="cm.bamO_r">bamO_r</option> + <option value="cm.brocO_r">brocO_r</option> + <option value="cm.corkO_r">corkO_r</option> + <option value="cm.vikO_r">vikO_r</option> + <option value="Accent">Accent</option> + <option value="Blues">Blues</option> + <option value="BrBG">BrBG</option> + <option value="BuGn">BuGn</option> + <option value="BuPu">BuPu</option> + <option value="CMRmap">CMRmap</option> + <option value="Dark2">Dark2</option> + <option value="GnBu">GnBu</option> + <option value="Greens">Greens</option> + <option value="Greys">Greys</option> + <option value="OrRd">OrRd</option> + <option value="Oranges">Oranges</option> + <option value="PRGn">PRGn</option> + <option value="Paired">Paired</option> + <option value="Pastel1">Pastel1</option> + <option value="Pastel2">Pastel2</option> + <option value="PiYG">PiYG</option> + <option value="PuBu">PuBu</option> + <option value="PuBuGn">PuBuGn</option> + <option value="PuOr">PuOr</option> + <option value="PuRd">PuRd</option> + <option value="Purples">Purples</option> + <option value="RdBu">RdBu</option> + <option value="RdGy">RdGy</option> + <option value="RdPu">RdPu</option> + <option value="RdBu_r">RdBu_r</option> + <option value="RdGy_r">RdGy_r</option> + <option value="RdPu_r">RdPu_r</option> + <option value="RdYlBu">RdYlBu</option> + <option value="RdYlGn">RdYlGn</option> + <option value="Reds">Reds</option> + <option value="Set1">Set1</option> + <option value="Set2">Set2</option> + <option value="Set3">Set3</option> + <option value="Spectral">Spectral</option> + <option value="Wistia">Wistia</option> + <option value="YlGn">YlGn</option> + <option value="YlGnBu">YlGnBu</option> + <option value="YlOrBr">YlOrBr</option> + <option value="YlOrRd">YlOrRd</option> + <option value="afmhot">afmhot</option> + <option value="autumn">autumn</option> + <option value="binary">binary</option> + <option value="bone">bone</option> + <option value="brg">brg</option> + <option value="bwr">bwr</option> + <option value="cool">cool</option> + <option value="coolwarm" selected="true">coolwarm</option> + <option value="copper">copper</option> + <option value="cubehelix">cubehelix</option> + <option value="flag">flag</option> + <option value="gist_earth">gist_earth</option> + <option value="gist_gray">gist_gray</option> + <option value="gist_heat">gist_heat</option> + <option value="gist_ncar">gist_ncar</option> + <option value="gist_rainbow">gist_rainbow</option> + <option value="gist_stern">gist_stern</option> + <option value="gist_yarg">gist_yarg</option> + <option value="gnuplot">gnuplot</option> + <option value="gnuplot2">gnuplot2</option> + <option value="gray">gray</option> + <option value="hot">hot</option> + <option value="hsv">hsv</option> + <option value="jet">jet</option> + <option value="nipy_spectral">nipy_spectral</option> + <option value="ocean">ocean</option> + <option value="pink">pink</option> + <option value="prism">prism</option> + <option value="rainbow">rainbow</option> + <option value="seismic">seismic</option> + <option value="spring">spring</option> + <option value="summer">summer</option> + <option value="tab10">tab10</option> + <option value="tab20">tab20</option> + <option value="tab20b">tab20b</option> + <option value="tab20c">tab20c</option> + <option value="terrain">terrain</option> + <option value="winter">winter</option> + </param> + </xml> +</macros>
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/Metadata_infos_from_dataset-ibi-reanalysis-bio-005-003-monthly-regulargrid_1510914389133.nc.Variables.tab Sun Jun 06 08:50:11 2021 +0000 @@ -0,0 +1,8 @@ +VariableName NumberOfDimensions Dim0Name Dim0Size Dim1Name Dim1Size Dim2Name Dim2Size Dim3Name Dim3Size +phy 4 time 145 depth 1 latitude 97 longitude 103 +chl 4 time 145 depth 1 latitude 97 longitude 103 +nh4 4 time 145 depth 1 latitude 97 longitude 103 +time 1 time 145 +longitude 1 longitude 103 +latitude 1 latitude 97 +depth 1 depth 1
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/Test1.tabular Sun Jun 06 08:50:11 2021 +0000 @@ -0,0 +1,146 @@ + time depth longitude latitude phy +0 2002-12-15 0.5057600140571594 -2.0000007 44.0 1.0500183 +1 2003-01-15 0.5057600140571594 -2.0000007 44.0 1.25 +2 2003-02-15 0.5057600140571594 -2.0000007 44.0 1.3000183 +3 2003-03-15 0.5057600140571594 -2.0000007 44.0 6.0599976 +4 2003-04-15 0.5057600140571594 -2.0000007 44.0 2.25 +5 2003-05-15 0.5057600140571594 -2.0000007 44.0 0.6499939 +6 2003-06-15 0.5057600140571594 -2.0000007 44.0 0.42999268 +7 2003-07-15 0.5057600140571594 -2.0000007 44.0 0.42999268 +8 2003-08-15 0.5057600140571594 -2.0000007 44.0 0.480011 +9 2003-09-15 0.5057600140571594 -2.0000007 44.0 0.45999146 +10 2003-10-15 0.5057600140571594 -2.0000007 44.0 0.5 +11 2003-11-15 0.5057600140571594 -2.0000007 44.0 0.9299927 +12 2003-12-15 0.5057600140571594 -2.0000007 44.0 1.3900146 +13 2004-01-15 0.5057600140571594 -2.0000007 44.0 1.7400208 +14 2004-02-15 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2005-07-15 0.5057600140571594 -2.0000007 44.0 0.6700134 +32 2005-08-15 0.5057600140571594 -2.0000007 44.0 0.4500122 +33 2005-09-15 0.5057600140571594 -2.0000007 44.0 0.45999146 +34 2005-10-15 0.5057600140571594 -2.0000007 44.0 0.45999146 +35 2005-11-15 0.5057600140571594 -2.0000007 44.0 0.6199951 +36 2005-12-15 0.5057600140571594 -2.0000007 44.0 1.1499939 +37 2006-01-15 0.5057600140571594 -2.0000007 44.0 3.5299988 +38 2006-02-15 0.5057600140571594 -2.0000007 44.0 7.1799927 +39 2006-03-15 0.5057600140571594 -2.0000007 44.0 6.5599976 +40 2006-04-15 0.5057600140571594 -2.0000007 44.0 3.8000183 +41 2006-05-15 0.5057600140571594 -2.0000007 44.0 0.95999146 +42 2006-06-15 0.5057600140571594 -2.0000007 44.0 1.5 +43 2006-07-15 0.5057600140571594 -2.0000007 44.0 1.0299988 +44 2006-08-15 0.5057600140571594 -2.0000007 44.0 0.480011 +45 2006-09-15 0.5057600140571594 -2.0000007 44.0 0.49002075 +46 2006-10-15 0.5057600140571594 -2.0000007 44.0 0.480011 +47 2006-11-15 0.5057600140571594 -2.0000007 44.0 0.9299927 +48 2006-12-15 0.5057600140571594 -2.0000007 44.0 1.2099915 +49 2007-01-15 0.5057600140571594 -2.0000007 44.0 1.1499939 +50 2007-02-15 0.5057600140571594 -2.0000007 44.0 1.7000122 +51 2007-03-15 0.5057600140571594 -2.0000007 44.0 5.230011 +52 2007-04-15 0.5057600140571594 -2.0000007 44.0 3.8600159 +53 2007-05-15 0.5057600140571594 -2.0000007 44.0 0.83999634 +54 2007-06-15 0.5057600140571594 -2.0000007 44.0 0.6799927 +55 2007-07-15 0.5057600140571594 -2.0000007 44.0 0.45999146 +56 2007-08-15 0.5057600140571594 -2.0000007 44.0 0.45999146 +57 2007-09-15 0.5057600140571594 -2.0000007 44.0 0.5 +58 2007-10-15 0.5057600140571594 -2.0000007 44.0 0.89001465 +59 2007-11-15 0.5057600140571594 -2.0000007 44.0 2.0299988 +60 2007-12-15 0.5057600140571594 -2.0000007 44.0 1.8399963 +61 2008-01-15 0.5057600140571594 -2.0000007 44.0 1.3399963 +62 2008-02-15 0.5057600140571594 -2.0000007 44.0 3.149994 +63 2008-03-15 0.5057600140571594 -2.0000007 44.0 4.5899963 +64 2008-04-15 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2009-09-15 0.5057600140571594 -2.0000007 44.0 0.5800171 +82 2009-10-15 0.5057600140571594 -2.0000007 44.0 0.6499939 +83 2009-11-15 0.5057600140571594 -2.0000007 44.0 0.8999939 +84 2009-12-15 0.5057600140571594 -2.0000007 44.0 1.3099976 +85 2010-01-15 0.5057600140571594 -2.0000007 44.0 1.5299988 +86 2010-02-15 0.5057600140571594 -2.0000007 44.0 2.9599915 +87 2010-03-15 0.5057600140571594 -2.0000007 44.0 5.450012 +88 2010-04-15 0.5057600140571594 -2.0000007 44.0 7.5899963 +89 2010-05-15 0.5057600140571594 -2.0000007 44.0 1.8000183 +90 2010-06-15 0.5057600140571594 -2.0000007 44.0 0.480011 +91 2010-07-15 0.5057600140571594 -2.0000007 44.0 0.5 +92 2010-08-15 0.5057600140571594 -2.0000007 44.0 0.45999146 +93 2010-09-15 0.5057600140571594 -2.0000007 44.0 0.49002075 +94 2010-10-15 0.5057600140571594 -2.0000007 44.0 0.45999146 +95 2010-11-15 0.5057600140571594 -2.0000007 44.0 0.9299927 +96 2010-12-15 0.5057600140571594 -2.0000007 44.0 1.1499939 +97 2011-01-15 0.5057600140571594 -2.0000007 44.0 2.4900208 +98 2011-02-15 0.5057600140571594 -2.0000007 44.0 5.1799927 +99 2011-03-15 0.5057600140571594 -2.0000007 44.0 7.029999 +100 2011-04-15 0.5057600140571594 -2.0000007 44.0 2.4900208 +101 2011-05-15 0.5057600140571594 -2.0000007 44.0 0.6499939 +102 2011-06-15 0.5057600140571594 -2.0000007 44.0 0.52001953 +103 2011-07-15 0.5057600140571594 -2.0000007 44.0 0.5 +104 2011-08-15 0.5057600140571594 -2.0000007 44.0 0.75 +105 2011-09-15 0.5057600140571594 -2.0000007 44.0 0.45999146 +106 2011-10-15 0.5057600140571594 -2.0000007 44.0 0.480011 +107 2011-11-15 0.5057600140571594 -2.0000007 44.0 0.730011 +108 2011-12-15 0.5057600140571594 -2.0000007 44.0 1.0299988 +109 2012-01-15 0.5057600140571594 -2.0000007 44.0 3.149994 +110 2012-02-15 0.5057600140571594 -2.0000007 44.0 2.3099976 +111 2012-03-15 0.5057600140571594 -2.0000007 44.0 5.5200195 +112 2012-04-15 0.5057600140571594 -2.0000007 44.0 3.399994 +113 2012-05-15 0.5057600140571594 -2.0000007 44.0 3.7000122 +114 2012-06-15 0.5057600140571594 -2.0000007 44.0 2.5899963 +115 2012-07-15 0.5057600140571594 -2.0000007 44.0 0.45999146 +116 2012-08-15 0.5057600140571594 -2.0000007 44.0 0.4500122 +117 2012-09-15 0.5057600140571594 -2.0000007 44.0 0.45999146 +118 2012-10-15 0.5057600140571594 -2.0000007 44.0 0.61001587 +119 2012-11-15 0.5057600140571594 -2.0000007 44.0 2.0299988 +120 2012-12-15 0.5057600140571594 -2.0000007 44.0 1.4200134 +121 2013-01-15 0.5057600140571594 -2.0000007 44.0 2.2700195 +122 2013-02-15 0.5057600140571594 -2.0000007 44.0 7.0 +123 2013-03-15 0.5057600140571594 -2.0000007 44.0 10.550018 +124 2013-04-15 0.5057600140571594 -2.0000007 44.0 5.8399963 +125 2013-05-15 0.5057600140571594 -2.0000007 44.0 1.2400208 +126 2013-06-15 0.5057600140571594 -2.0000007 44.0 4.1700134 +127 2013-07-15 0.5057600140571594 -2.0000007 44.0 3.2099915 +128 2013-08-15 0.5057600140571594 -2.0000007 44.0 0.45999146 +129 2013-09-15 0.5057600140571594 -2.0000007 44.0 0.480011 +130 2013-10-15 0.5057600140571594 -2.0000007 44.0 0.49002075 +131 2013-11-15 0.5057600140571594 -2.0000007 44.0 0.7799988 +132 2013-12-15 0.5057600140571594 -2.0000007 44.0 1.4500122 +133 2014-01-15 0.5057600140571594 -2.0000007 44.0 0.95999146 +134 2014-02-15 0.5057600140571594 -2.0000007 44.0 1.3900146 +135 2014-03-15 0.5057600140571594 -2.0000007 44.0 5.779999 +136 2014-04-15 0.5057600140571594 -2.0000007 44.0 5.4299927 +137 2014-05-15 0.5057600140571594 -2.0000007 44.0 1.1799927 +138 2014-06-15 0.5057600140571594 -2.0000007 44.0 0.730011 +139 2014-07-15 0.5057600140571594 -2.0000007 44.0 0.45999146 +140 2014-08-15 0.5057600140571594 -2.0000007 44.0 0.45999146 +141 2014-09-15 0.5057600140571594 -2.0000007 44.0 0.5 +142 2014-10-15 0.5057600140571594 -2.0000007 44.0 0.6199951 +143 2014-11-15 0.5057600140571594 -2.0000007 44.0 0.480011 +144 2014-12-15 0.5057600140571594 -2.0000007 44.0 0.55999756
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/Test2.tabular Sun Jun 06 08:50:11 2021 +0000 @@ -0,0 +1,25 @@ + time depth latitude longitude nh4 +0 2003-12-15 0.5057600140571594 45.166664123535156 -0.6666674017906189 81.27 +1 2003-12-15 0.5057600140571594 45.416664123535156 -0.8333340883255005 78.08 +2 2003-12-15 0.5057600140571594 45.5 -0.9166674017906189 55.149998 +3 2004-01-15 0.5057600140571594 45.166664123535156 -0.6666674017906189 65.2 +4 2004-01-15 0.5057600140571594 45.416664123535156 -0.8333340883255005 64.11 +5 2004-02-15 0.5057600140571594 45.166664123535156 -0.6666674017906189 51.0 +6 2004-02-15 0.5057600140571594 45.416664123535156 -0.8333340883255005 51.32 +7 2004-05-15 0.5057600140571594 45.166664123535156 -0.6666674017906189 54.53 +8 2004-06-15 0.5057600140571594 45.166664123535156 -0.6666674017906189 79.79 +9 2004-06-15 0.5057600140571594 45.416664123535156 -0.8333340883255005 61.52 +10 2004-07-15 0.5057600140571594 45.166664123535156 -0.6666674017906189 99.159996 +11 2004-07-15 0.5057600140571594 45.416664123535156 -0.8333340883255005 77.93 +12 2004-08-15 0.5057600140571594 45.166664123535156 -0.6666674017906189 110.149994 +13 2004-08-15 0.5057600140571594 45.416664123535156 -0.8333340883255005 86.759995 +14 2004-09-15 0.5057600140571594 45.166664123535156 -0.6666674017906189 112.369995 +15 2004-09-15 0.5057600140571594 45.416664123535156 -0.8333340883255005 91.979996 +16 2004-10-15 0.5057600140571594 45.166664123535156 -0.6666674017906189 109.63 +17 2004-10-15 0.5057600140571594 45.416664123535156 -0.8333340883255005 95.509995 +18 2004-11-15 0.5057600140571594 45.166664123535156 -0.6666674017906189 98.45 +19 2004-11-15 0.5057600140571594 45.416664123535156 -0.8333340883255005 93.11 +20 2004-11-15 0.5057600140571594 45.5 -0.9166674017906189 56.78 +21 2004-12-15 0.5057600140571594 45.166664123535156 -0.6666674017906189 84.25 +22 2004-12-15 0.5057600140571594 45.416664123535156 -0.8333340883255005 81.83 +23 2004-12-15 0.5057600140571594 45.5 -0.9166674017906189 57.07
Binary file test-data/dataset-ibi-reanalysis-bio-005-003-monthly-regulargrid_1510914389133.nc has changed
Binary file test-data/dataset-ibi-reanalysis-bio-005-003-monthly-regulargrid_1510914389133_time0.png has changed
Binary file test-data/dataset-ibi-reanalysis-bio-005-003-monthly-regulargrid_1510914389133_time1.png has changed
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/depth.tabular Sun Jun 06 08:50:11 2021 +0000 @@ -0,0 +1,1 @@ +0 0.50576
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/info_file.txt Sun Jun 06 08:50:11 2021 +0000 @@ -0,0 +1,74 @@ +xarray.Dataset { +dimensions: + depth = 1 ; + latitude = 97 ; + longitude = 103 ; + time = 145 ; + +variables: + float32 phy(time, depth, latitude, longitude) ; + phy:_CoordinateAxes = time depth latitude longitude ; + phy:long_name = Mole Concentration of Phytoplankton expressed as carbon in sea water ; + phy:standard_name = mole_concentration_of_phytoplankton_expressed_as_carbon_in_sea_water ; + phy:units = mmol.m-3 ; + phy:unit_long = mole_concentration_of_phytoplankton_expressed_as_carbon_in_sea_water ; + datetime64[ns] time(time) ; + time:standard_name = time ; + time:long_name = time ; + time:_CoordinateAxisType = Time ; + time:axis = T ; + float32 chl(time, depth, latitude, longitude) ; + chl:_CoordinateAxes = time depth latitude longitude ; + chl:long_name = Mass Concentration of Chlorophyll in Sea Water ; + chl:standard_name = mass_concentration_of_chlorophyll_in_sea_water ; + chl:units = mg.m-3 ; + chl:unit_long = milligram of chlorophyll per cubic meter ; + float32 nh4(time, depth, latitude, longitude) ; + nh4:_CoordinateAxes = time depth latitude longitude ; + nh4:long_name = Mole Concentration of Ammonium in Sea Water ; + nh4:standard_name = mole_concentration_of_ammonium_in_sea_water ; + nh4:units = mmol.m-3 ; + nh4:unit_long = millimoles of Ammonium per cubic meter ; + float32 longitude(longitude) ; + longitude:long_name = Longitude ; + longitude:units = degrees_east ; + longitude:standard_name = longitude ; + longitude:axis = X ; + longitude:unit_long = Degrees East ; + longitude:step = 0.08333f ; + longitude:_CoordinateAxisType = Lon ; + float32 latitude(latitude) ; + latitude:long_name = Latitude ; + latitude:units = degrees_north ; + latitude:standard_name = latitude ; + latitude:axis = Y ; + latitude:unit_long = Degrees North ; + latitude:step = 0.08333f ; + latitude:_CoordinateAxisType = Lat ; + float32 depth(depth) ; + depth:long_name = Depth ; + depth:units = m ; + depth:axis = Z ; + depth:positive = down ; + depth:unit_long = Meters ; + depth:standard_name = depth ; + depth:_CoordinateAxisType = Height ; + depth:_CoordinateZisPositive = down ; + +// global attributes: + :title = CMEMS IBI REANALYSIS: MONTHLY BIOGEOCHEMICAL PRODUCTS (REGULAR GRID) ; + :institution = Puertos del Estado (PdE) - Mercator-Ocean (MO) ; + :references = http://marine.copernicus.eu ; + :source = CMEMS IBI-MFC ; + :Conventions = CF-1.0 ; + :history = Data extracted from dataset http://puertos2.cesga.es:8080/thredds/dodsC/dataset-ibi-reanalysis-bio-005-003-monthly-regulargrid ; + :time_min = 7272.0 ; + :time_max = 112464.0 ; + :julian_day_unit = Hours since 2002-02-15 ; + :z_min = 0.5057600140571594 ; + :z_max = 0.5057600140571594 ; + :latitude_min = 43.0 ; + :latitude_max = 51.0 ; + :longitude_min = -6.000000476837158 ; + :longitude_max = 2.4999990463256836 ; +} \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/latitude.tabular Sun Jun 06 08:50:11 2021 +0000 @@ -0,0 +1,97 @@ +0 43.0 +1 43.083332 +2 43.166664 +3 43.25 +4 43.333332 +5 43.416664 +6 43.5 +7 43.583332 +8 43.666664 +9 43.75 +10 43.833332 +11 43.916664 +12 44.0 +13 44.083332 +14 44.166664 +15 44.25 +16 44.333332 +17 44.416664 +18 44.5 +19 44.583332 +20 44.666664 +21 44.75 +22 44.833332 +23 44.916664 +24 45.0 +25 45.083332 +26 45.166664 +27 45.25 +28 45.333332 +29 45.416664 +30 45.5 +31 45.583332 +32 45.666664 +33 45.75 +34 45.833332 +35 45.916664 +36 46.0 +37 46.083332 +38 46.166664 +39 46.25 +40 46.333332 +41 46.416664 +42 46.5 +43 46.583332 +44 46.666664 +45 46.75 +46 46.833332 +47 46.916664 +48 47.0 +49 47.083332 +50 47.166664 +51 47.25 +52 47.333332 +53 47.416664 +54 47.5 +55 47.583332 +56 47.666664 +57 47.75 +58 47.833332 +59 47.916664 +60 48.0 +61 48.083332 +62 48.166664 +63 48.25 +64 48.333332 +65 48.416664 +66 48.5 +67 48.583332 +68 48.666664 +69 48.75 +70 48.833332 +71 48.916664 +72 49.0 +73 49.083332 +74 49.166664 +75 49.25 +76 49.333332 +77 49.416664 +78 49.5 +79 49.583332 +80 49.666664 +81 49.75 +82 49.833332 +83 49.916664 +84 50.0 +85 50.083332 +86 50.166664 +87 50.25 +88 50.333332 +89 50.416664 +90 50.5 +91 50.583332 +92 50.666664 +93 50.75 +94 50.833332 +95 50.916664 +96 51.0
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/longitude.tabular Sun Jun 06 08:50:11 2021 +0000 @@ -0,0 +1,103 @@ +0 -6.0000005 +1 -5.916667 +2 -5.833334 +3 -5.7500005 +4 -5.666667 +5 -5.583334 +6 -5.5000005 +7 -5.416667 +8 -5.333334 +9 -5.2500005 +10 -5.166667 +11 -5.083334 +12 -5.0000005 +13 -4.9166675 +14 -4.833334 +15 -4.7500005 +16 -4.6666675 +17 -4.583334 +18 -4.5000005 +19 -4.4166675 +20 -4.333334 +21 -4.2500005 +22 -4.1666675 +23 -4.083334 +24 -4.0000005 +25 -3.9166672 +26 -3.833334 +27 -3.7500007 +28 -3.6666672 +29 -3.583334 +30 -3.5000007 +31 -3.4166672 +32 -3.333334 +33 -3.2500007 +34 -3.1666672 +35 -3.083334 +36 -3.0000007 +37 -2.9166672 +38 -2.833334 +39 -2.7500007 +40 -2.6666672 +41 -2.583334 +42 -2.5000007 +43 -2.4166672 +44 -2.333334 +45 -2.2500007 +46 -2.1666672 +47 -2.083334 +48 -2.0000007 +49 -1.9166673 +50 -1.833334 +51 -1.7500007 +52 -1.6666673 +53 -1.5833341 +54 -1.5000007 +55 -1.4166673 +56 -1.3333341 +57 -1.2500007 +58 -1.1666673 +59 -1.0833341 +60 -1.0000007 +61 -0.9166674 +62 -0.8333341 +63 -0.7500007 +64 -0.6666674 +65 -0.5833341 +66 -0.5000007 +67 -0.4166674 +68 -0.3333341 +69 -0.25000075 +70 -0.16666742 +71 -0.08333409 +72 -7.6e-07 +73 0.08333257 +74 0.1666659 +75 0.24999923 +76 0.33333257 +77 0.41666588 +78 0.49999923 +79 0.58333254 +80 0.66666585 +81 0.7499992 +82 0.83333254 +83 0.91666585 +84 0.9999992 +85 1.0833325 +86 1.1666659 +87 1.2499992 +88 1.3333325 +89 1.4166658 +90 1.4999992 +91 1.5833325 +92 1.6666658 +93 1.7499992 +94 1.8333325 +95 1.9166658 +96 1.9999992 +97 2.0833325 +98 2.1666658 +99 2.249999 +100 2.3333325 +101 2.4166658 +102 2.499999
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/time.tabular Sun Jun 06 08:50:11 2021 +0000 @@ -0,0 +1,145 @@ +0 2002-12-15 +1 2003-01-15 +2 2003-02-15 +3 2003-03-15 +4 2003-04-15 +5 2003-05-15 +6 2003-06-15 +7 2003-07-15 +8 2003-08-15 +9 2003-09-15 +10 2003-10-15 +11 2003-11-15 +12 2003-12-15 +13 2004-01-15 +14 2004-02-15 +15 2004-03-15 +16 2004-04-15 +17 2004-05-15 +18 2004-06-15 +19 2004-07-15 +20 2004-08-15 +21 2004-09-15 +22 2004-10-15 +23 2004-11-15 +24 2004-12-15 +25 2005-01-15 +26 2005-02-15 +27 2005-03-15 +28 2005-04-15 +29 2005-05-15 +30 2005-06-15 +31 2005-07-15 +32 2005-08-15 +33 2005-09-15 +34 2005-10-15 +35 2005-11-15 +36 2005-12-15 +37 2006-01-15 +38 2006-02-15 +39 2006-03-15 +40 2006-04-15 +41 2006-05-15 +42 2006-06-15 +43 2006-07-15 +44 2006-08-15 +45 2006-09-15 +46 2006-10-15 +47 2006-11-15 +48 2006-12-15 +49 2007-01-15 +50 2007-02-15 +51 2007-03-15 +52 2007-04-15 +53 2007-05-15 +54 2007-06-15 +55 2007-07-15 +56 2007-08-15 +57 2007-09-15 +58 2007-10-15 +59 2007-11-15 +60 2007-12-15 +61 2008-01-15 +62 2008-02-15 +63 2008-03-15 +64 2008-04-15 +65 2008-05-15 +66 2008-06-15 +67 2008-07-15 +68 2008-08-15 +69 2008-09-15 +70 2008-10-15 +71 2008-11-15 +72 2008-12-15 +73 2009-01-15 +74 2009-02-15 +75 2009-03-15 +76 2009-04-15 +77 2009-05-15 +78 2009-06-15 +79 2009-07-15 +80 2009-08-15 +81 2009-09-15 +82 2009-10-15 +83 2009-11-15 +84 2009-12-15 +85 2010-01-15 +86 2010-02-15 +87 2010-03-15 +88 2010-04-15 +89 2010-05-15 +90 2010-06-15 +91 2010-07-15 +92 2010-08-15 +93 2010-09-15 +94 2010-10-15 +95 2010-11-15 +96 2010-12-15 +97 2011-01-15 +98 2011-02-15 +99 2011-03-15 +100 2011-04-15 +101 2011-05-15 +102 2011-06-15 +103 2011-07-15 +104 2011-08-15 +105 2011-09-15 +106 2011-10-15 +107 2011-11-15 +108 2011-12-15 +109 2012-01-15 +110 2012-02-15 +111 2012-03-15 +112 2012-04-15 +113 2012-05-15 +114 2012-06-15 +115 2012-07-15 +116 2012-08-15 +117 2012-09-15 +118 2012-10-15 +119 2012-11-15 +120 2012-12-15 +121 2013-01-15 +122 2013-02-15 +123 2013-03-15 +124 2013-04-15 +125 2013-05-15 +126 2013-06-15 +127 2013-07-15 +128 2013-08-15 +129 2013-09-15 +130 2013-10-15 +131 2013-11-15 +132 2013-12-15 +133 2014-01-15 +134 2014-02-15 +135 2014-03-15 +136 2014-04-15 +137 2014-05-15 +138 2014-06-15 +139 2014-07-15 +140 2014-08-15 +141 2014-09-15 +142 2014-10-15 +143 2014-11-15 +144 2014-12-15
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/var_tab_dataset-ibi Sun Jun 06 08:50:11 2021 +0000 @@ -0,0 +1,7 @@ +time 1 time 145 +chl 4 time 145 depth 1 latitude 97 longitude 103 +nh4 4 time 145 depth 1 latitude 97 longitude 103 +longitude 1 longitude 103 +latitude 1 latitude 97 +depth 1 depth 1 +phy 4 time 145 depth 1 latitude 97 longitude 103
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/version.tabular Sun Jun 06 08:50:11 2021 +0000 @@ -0,0 +1,1 @@ +Galaxy xarray version 0.18.2
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/xarray_mapplot.py Sun Jun 06 08:50:11 2021 +0000 @@ -0,0 +1,457 @@ +#!/usr/bin/env python3 +# +# +# usage: xarray_mapplot.py [-h] [--proj PROJ] +# [--cmap CMAP] +# [--output OUTPUT] +# [--time TIMES] +# [--nrow NROW] +# [--ncol NCOL] +# [--title title] +# [--latitude LATITUDE] +# [--longitude LONGITUDE] +# [--land ALPHA-LAND] +# [--ocean ALPHA-OCEAN] +# [--coastline ALPHA-COASTLINE] +# [--borders ALPHA-BORDERS] +# [--xlim "x1,x2"] +# [--ylim "y1,y2"] +# [--range "valmin,valmax"] +# [--threshold VAL] +# [--label label-colorbar] +# [--shift] +# [-v] +# input varname +# +# positional arguments: +# input input filename with geographical coordinates (netCDF +# format) +# varname Specify which variable to plot (case sensitive) +# +# optional arguments: +# -h, --help show this help message and exit +# --proj PROJ Specify the projection on which we draw +# --cmap CMAP Specify which colormap to use for plotting +# --output OUTPUT output filename to store resulting image (png format) +# --time TIMES time index from the file for multiple plots ("0 1 2 3") +# --title plot or subplot title +# --latitude variable name for latitude +# --longitude variable name for longitude +# --land add land on plot with alpha value [0-1] +# --ocean add oceans on plot with alpha value [0-1] +# --coastline add coastline with alpha value [0-1] +# --borders add country borders with alpha value [0-1] +# --xlim limited geographical area longitudes "x1,x2" +# --ylim limited geographical area latitudes "y1,y2" +# --range "valmin,valmax" for plotting +# --threshold do not plot values below threshold +# --label set a label for colormap +# --shift shift longitudes if specified +# -v, --verbose switch on verbose mode +# + +import argparse +import ast +import warnings +from pathlib import Path + +import cartopy.crs as ccrs +import cartopy.feature as feature + +from cmcrameri import cm + +import matplotlib as mpl +mpl.use('Agg') +from matplotlib import pyplot # noqa: I202,E402 + +import xarray as xr # noqa: E402 + + +class MapPlotXr (): + def __init__(self, input, proj, varname, cmap, output, verbose=False, + time=[], title="", latitude="latitude", + longitude="longitude", land=0, ocean=0, + coastline=0, borders=0, xlim=[], ylim=[], + threshold="", label="", shift=False, + range_values=[]): + self.input = input + print("PROJ", proj) + if proj != "" and proj is not None: + self.proj = proj.replace('X', ':') + else: + self.proj = proj + self.varname = varname + self.get_cmap(cmap) + self.time = time + self.latitude = latitude + self.longitude = longitude + self.land = land + self.ocean = ocean + self.coastline = coastline + self.borders = borders + self.xlim = xlim + self.ylim = ylim + self.range = range_values + self.threshold = threshold + self.shift = shift + self.xylim_supported = False + self.colorbar = True + self.title = title + if output is None: + self.output = Path(input).stem + '.png' + else: + self.output = output + self.verbose = verbose + self.dset = xr.open_dataset(self.input, use_cftime=True) + + self.label = {} + if label != "" and label is not None: + self.label['label'] = label + if verbose: + print("input: ", self.input) + print("proj: ", self.proj) + print("varname: ", self.varname) + print("time: ", self.time) + print("minval, maxval: ", self.range) + print("title: ", self.title) + print("output: ", self.output) + print("label: ", self.label) + print("shift: ", self.shift) + print("ocean: ", self.ocean) + print("land: ", self.land) + print("coastline: ", self.coastline) + print("borders: ", self.borders) + print("latitude: ", self.latitude) + print("longitude: ", self.longitude) + print("xlim: ", self.xlim) + print("ylim: ", self.ylim) + + def get_cmap(self, cmap): + if cmap[0:3] == 'cm.': + self.cmap = cm.__dict__[cmap[3:]] + else: + self.cmap = cmap + + def projection(self): + if self.proj is None: + return ccrs.PlateCarree() + + proj_dict = ast.literal_eval(self.proj) + + user_proj = proj_dict.pop("proj") + if user_proj == 'PlateCarree': + self.xylim_supported = True + return ccrs.PlateCarree(**proj_dict) + elif user_proj == 'AlbersEqualArea': + return ccrs.AlbersEqualArea(**proj_dict) + elif user_proj == 'AzimuthalEquidistant': + return ccrs.AzimuthalEquidistant(**proj_dict) + elif user_proj == 'EquidistantConic': + return ccrs.EquidistantConic(**proj_dict) + elif user_proj == 'LambertConformal': + return ccrs.LambertConformal(**proj_dict) + elif user_proj == 'LambertCylindrical': + return ccrs.LambertCylindrical(**proj_dict) + elif user_proj == 'Mercator': + return ccrs.Mercator(**proj_dict) + elif user_proj == 'Miller': + return ccrs.Miller(**proj_dict) + elif user_proj == 'Mollweide': + return ccrs.Mollweide(**proj_dict) + elif user_proj == 'Orthographic': + return ccrs.Orthographic(**proj_dict) + elif user_proj == 'Robinson': + return ccrs.Robinson(**proj_dict) + elif user_proj == 'Sinusoidal': + return ccrs.Sinusoidal(**proj_dict) + elif user_proj == 'Stereographic': + return ccrs.Stereographic(**proj_dict) + elif user_proj == 'TransverseMercator': + return ccrs.TransverseMercator(**proj_dict) + elif user_proj == 'UTM': + return ccrs.UTM(**proj_dict) + elif user_proj == 'InterruptedGoodeHomolosine': + return ccrs.InterruptedGoodeHomolosine(**proj_dict) + elif user_proj == 'RotatedPole': + return ccrs.RotatedPole(**proj_dict) + elif user_proj == 'OSGB': + self.xylim_supported = False + return ccrs.OSGB(**proj_dict) + elif user_proj == 'EuroPP': + self.xylim_supported = False + return ccrs.EuroPP(**proj_dict) + elif user_proj == 'Geostationary': + return ccrs.Geostationary(**proj_dict) + elif user_proj == 'NearsidePerspective': + return ccrs.NearsidePerspective(**proj_dict) + elif user_proj == 'EckertI': + return ccrs.EckertI(**proj_dict) + elif user_proj == 'EckertII': + return ccrs.EckertII(**proj_dict) + elif user_proj == 'EckertIII': + return ccrs.EckertIII(**proj_dict) + elif user_proj == 'EckertIV': + return ccrs.EckertIV(**proj_dict) + elif user_proj == 'EckertV': + return ccrs.EckertV(**proj_dict) + elif user_proj == 'EckertVI': + return ccrs.EckertVI(**proj_dict) + elif user_proj == 'EqualEarth': + return ccrs.EqualEarth(**proj_dict) + elif user_proj == 'Gnomonic': + return ccrs.Gnomonic(**proj_dict) + elif user_proj == 'LambertAzimuthalEqualArea': + return ccrs.LambertAzimuthalEqualArea(**proj_dict) + elif user_proj == 'NorthPolarStereo': + return ccrs.NorthPolarStereo(**proj_dict) + elif user_proj == 'OSNI': + return ccrs.OSNI(**proj_dict) + elif user_proj == 'SouthPolarStereo': + return ccrs.SouthPolarStereo(**proj_dict) + + def plot(self, ts=None): + if self.shift: + if self.longitude == 'longitude': + self.dset = self.dset.assign_coords( + longitude=((( + self.dset[self.longitude] + + 180) % 360) - 180)) + elif self.longitude == 'lon': + self.dset = self.dset.assign_coords( + lon=(((self.dset[self.longitude] + + 180) % 360) - 180)) + + pyplot.figure(1, figsize=[20, 10]) + + # Set the projection to use for plotting + ax = pyplot.subplot(1, 1, 1, projection=self.projection()) + if self.land: + ax.add_feature(feature.LAND, alpha=self.land) + + if self.ocean: + ax.add_feature(feature.OCEAN, alpha=self.ocean) + if self.coastline: + ax.coastlines(resolution='10m', alpha=self.coastline) + if self.borders: + ax.add_feature(feature.BORDERS, linestyle=':', alpha=self.borders) + + if self.xlim: + min_lon = min(self.xlim[0], self.xlim[1]) + max_lon = max(self.xlim[0], self.xlim[1]) + else: + min_lon = self.dset[self.longitude].min() + max_lon = self.dset[self.longitude].max() + + if self.ylim: + min_lat = min(self.ylim[0], self.ylim[1]) + max_lat = max(self.ylim[0], self.ylim[1]) + else: + min_lat = self.dset[self.latitude].min() + max_lat = self.dset[self.latitude].max() + + if self.xylim_supported: + pyplot.xlim(min_lon, max_lon) + pyplot.ylim(min_lat, max_lat) + + # Fix extent + if self.threshold == "" or self.threshold is None: + threshold = self.dset[self.varname].min() + else: + threshold = float(self.threshold) + + if self.range == []: + minval = self.dset[self.varname].min() + maxval = self.dset[self.varname].max() + else: + minval = self.range[0] + maxval = self.range[1] + + if self.verbose: + print("minval: ", minval) + print("maxval: ", maxval) + + # pass extent with vmin and vmax parameters + proj_t = ccrs.PlateCarree() + if ts is None: + self.dset.where( + self.dset[self.varname] > threshold + )[self.varname].plot(ax=ax, + vmin=minval, + vmax=maxval, + transform=proj_t, + cmap=self.cmap, + cbar_kwargs=self.label + ) + if self.title != "" and self.title is not None: + pyplot.title(self.title) + pyplot.savefig(self.output) + else: + if self.colorbar: + self.dset.where( + self.dset[self.varname] > threshold + )[self.varname].isel(time=ts).plot(ax=ax, + vmin=minval, + vmax=maxval, + transform=proj_t, + cmap=self.cmap, + cbar_kwargs=self.label + ) + else: + self.dset.where( + self.dset[self.varname] > minval + )[self.varname].isel(time=ts).plot(ax=ax, + vmin=minval, + vmax=maxval, + transform=proj_t, + cmap=self.cmap, + add_colorbar=False) + if self.title != "" and self.title is not None: + pyplot.title(self.title + "(time = " + str(ts) + ')') + pyplot.savefig(self.output[:-4] + "_time" + str(ts) + + self.output[-4:]) # assume png format + + +if __name__ == '__main__': + warnings.filterwarnings("ignore") + parser = argparse.ArgumentParser() + parser.add_argument( + 'input', + help='input filename with geographical coordinates (netCDF format)' + ) + + parser.add_argument( + '--proj', + help='Specify the projection on which we draw' + ) + parser.add_argument( + 'varname', + help='Specify which variable to plot (case sensitive)' + ) + parser.add_argument( + '--cmap', + help='Specify which colormap to use for plotting' + ) + parser.add_argument( + '--output', + help='output filename to store resulting image (png format)' + ) + parser.add_argument( + '--time', + help='list of times to plot for multiple plots' + ) + parser.add_argument( + '--title', + help='plot title' + ) + parser.add_argument( + '--latitude', + help='variable name for latitude' + ) + parser.add_argument( + '--longitude', + help='variable name for longitude' + ) + parser.add_argument( + '--land', + help='add land on plot with alpha value [0-1]' + ) + parser.add_argument( + '--ocean', + help='add oceans on plot with alpha value [0-1]' + ) + parser.add_argument( + '--coastline', + help='add coastline with alpha value [0-1]' + ) + parser.add_argument( + '--borders', + help='add country borders with alpha value [0-1]' + ) + parser.add_argument( + '--xlim', + help='limited geographical area longitudes "x1,x2"' + ) + parser.add_argument( + '--ylim', + help='limited geographical area latitudes "y1,y2"' + ) + parser.add_argument( + '--range', + help='min and max values for plotting "minval,maxval"' + ) + parser.add_argument( + '--threshold', + help='do not plot values below threshold' + ) + parser.add_argument( + '--label', + help='set a label for colorbar' + ) + parser.add_argument( + '--shift', + help='shift longitudes if specified', + action="store_true" + ) + parser.add_argument( + "-v", "--verbose", + help="switch on verbose mode", + action="store_true") + args = parser.parse_args() + + if args.time is None: + time = [] + else: + time = list(map(int, args.time.split(","))) + if args.xlim is None: + xlim = [] + else: + xlim = list(map(float, args.xlim.split(","))) + if args.ylim is None: + ylim = [] + else: + ylim = list(map(float, args.ylim.split(","))) + if args.range is None: + range_values = [] + else: + range_values = list(map(float, args.range.split(","))) + if args.latitude is None: + latitude = "latitude" + else: + latitude = args.latitude + if args.longitude is None: + longitude = "longitude" + else: + longitude = args.longitude + if args.land is None: + land = 0 + else: + land = float(args.land) + if args.ocean is None: + ocean = 0 + else: + ocean = float(args.ocean) + if args.coastline is None: + coastline = 0 + else: + coastline = float(args.coastline) + if args.borders is None: + borders = 0 + else: + borders = float(args.borders) + + dset = MapPlotXr(input=args.input, proj=args.proj, varname=args.varname, + cmap=args.cmap, output=args.output, verbose=args.verbose, + time=time, title=args.title, + latitude=latitude, longitude=longitude, land=land, + ocean=ocean, coastline=coastline, borders=borders, + xlim=xlim, ylim=ylim, threshold=args.threshold, + label=args.label, shift=args.shift, + range_values=range_values) + + if dset.time == []: + dset.plot() + else: + for t in dset.time: + dset.plot(t) + dset.shift = False # only shift once + dset.colorbar = True
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/xarray_netcdf2netcdf.py Sun Jun 06 08:50:11 2021 +0000 @@ -0,0 +1,133 @@ +#!/usr/bin/env python3 +# +# Apply operations on selected variables +# - scale +# one can also select the range of time (for timeseries) +# to apply these operations over the range only +# when a range of time is selected and when scaling, one +# can choose to save the entire timeseries or +# the selected range only. +# when scaling, one can add additional filters on dimensions +# (typically used to filter over latitudes and longitudes) + + +import argparse +import warnings + +import xarray as xr # noqa: E402 + + +class netCDF2netCDF (): + def __init__(self, infile, varname, scale="", + output="output.netcdf", + write_all=False, + filter_list="", + verbose=False): + self.infile = infile + self.verbose = verbose + self.varname = varname + self.write_all = write_all + self.filter = filter_list + self.selection = {} + if scale == "" or scale is None: + self.scale = 1 + else: + self.scale = float(scale) + if output is None: + self.output = "output.netcdf" + else: + self.output = output + # initialization + self.dset = None + self.subset = None + if self.verbose: + print("infile: ", self.infile) + print("varname: ", self.varname) + print("filter_list: ", self.filter) + print("scale: ", self.scale) + print("write_all: ", self.write_all) + print("output: ", self.output) + + def dimension_selection(self, single_filter): + split_filter = single_filter.split('#') + dimension_varname = split_filter[0] + op = split_filter[1] + ll = int(split_filter[2]) + if (op == 'sl'): + rl = int(split_filter[3]) + self.selection[dimension_varname] = slice(ll, rl) + elif (op == 'to'): + self.selection[dimension_varname] = slice(None, ll) + elif (op == 'from'): + self.selection[dimension_varname] = slice(ll, None) + elif (op == 'is'): + self.selection[dimension_varname] = ll + + def filter_selection(self): + for single_filter in self.filter: + self.dimension_selection(single_filter) + if self.write_all: + self.ds[self.varname] = \ + self.ds[self.varname].isel(self.selection)*self.scale + else: + self.dset = \ + self.ds[self.varname].isel(self.selection)*self.scale + + def compute(self): + if self.dset is None: + self.ds = xr.open_dataset(self.infile) + if self.filter: + self.filter_selection() + if self.verbose: + print(self.selection) + elif self.write_all is not None: + self.dset = self.ds[self.varname] + + def save(self): + if self.write_all: + self.ds.to_netcdf(self.output) + else: + self.dset.to_netcdf(self.output) + + +if __name__ == '__main__': + warnings.filterwarnings("ignore") + parser = argparse.ArgumentParser() + parser.add_argument( + 'input', + help='input filename in netCDF format' + ) + parser.add_argument( + 'varname', + help='Specify which variable to plot (case sensitive)' + ) + parser.add_argument( + '--filter', + nargs="*", + help='Filter list variable#operator#value_s#value_e' + ) + parser.add_argument( + '--output', + help='Output filename to store the resulting netCDF file' + ) + parser.add_argument( + '--scale', + help='scale factor to apply to selection (float)' + ) + parser.add_argument( + "--write_all", + help="write all data to netCDF", + action="store_true") + parser.add_argument( + "-v", "--verbose", + help="switch on verbose mode", + action="store_true") + args = parser.parse_args() + + dset = netCDF2netCDF(infile=args.input, varname=args.varname, + scale=args.scale, output=args.output, + filter_list=args.filter, + write_all=args.write_all, + verbose=args.verbose) + dset.compute() + dset.save()
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/xarray_netcdf2netcdf.xml Sun Jun 06 08:50:11 2021 +0000 @@ -0,0 +1,190 @@ +<tool id="xarray_netcdf2netcdf" name="NetCDF xarray operations" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@"> + <description>manipulate xarray from netCDF and save back to netCDF</description> + <macros> + <import>macros.xml</import> + </macros> + <expand macro="edam_ontology"/> + <requirements> + <requirement type="package" version="3">python</requirement> + <requirement type="package" version="1.5.6">netcdf4</requirement> + <requirement type="package" version="@TOOL_VERSION@">xarray</requirement> + </requirements> + <command detect_errors="exit_code"><![CDATA[ + mkdir output_dir && + python '$__tool_directory__/xarray_netcdf2netcdf.py' '$input' '$var' + --filter + #for $i,$uc in enumerate($user_choice) + #if $uc.condi_between.comparator=="sl" + '${uc.dim}#${uc.condi_between.comparator}#${uc.condi_between.t1}#${uc.condi_between.t2}' + #else + '${uc.dim}#${uc.condi_between.comparator}#${uc.condi_between.value}' + #end if + #end for + #if $scale + --scale '$scale' + #end if + #if $write_all + --write_all + #end if + --verbose + --output '$output_netcdf' + ]]></command> + <inputs> + <param type="data" name="input" label="Input netcdf file" format="netcdf"/> + <param type="data" label="Tabular of variables" name="var_tab" format="tabular" help="Select the tabular file which summarize the available variables and dimensions."/> + + <param name="var" type="select" label="Choose the variable to extract"> + <options from_dataset="var_tab"> + <column name="name" index="0"/> + <column name="value" index="0"/> + </options> + </param> + + <repeat name="user_choice" title="additional filter" min="0" max="20" help="Use this option to filter on the selected dataset"> + <param name="dim" type="select" label="Dimensions"> + <options from_dataset="var_tab"> + <column name="value" index="0"/> + </options> + </param> + <param type="data" label="Tabular containing values of this dimension" name="dim_tab" format="tabular" help="File containing values for this dimension."/> + <conditional name="condi_between"> + <param name="comparator" type="select" label="Comparator"> + <option value="is">is</option> + <option value="from">from</option> + <option value="to">to</option> + <option value="sl">slice(threshold1,threshold2)</option> + </param> + <when value="sl"> + <param name="t1" type="select" multiple="false" label="Choose the start value for slice"> + <options from_dataset="dim_tab"> + <column name="name" index="1"/> + <column name="value" index="0"/> + </options> + </param> + <param name="t2" type="select" multiple="false" label="Choose the end value for slice"> + <options from_dataset="dim_tab"> + <column name="name" index="1"/> + <column name="value" index="0"/> + </options> + </param> + </when> + <when value="is"> + <param name="value" type="select" multiple="false" label="Choose the value to select"> + <options from_dataset="dim_tab"> + <column name="name" index="1"/> + <column name="value" index="0"/> + </options> + </param> + </when> + <when value="to"> + <param name="value" type="select" multiple="false" label="Choose the end value"> + <options from_dataset="dim_tab"> + <column name="name" index="1"/> + <column name="value" index="0"/> + </options> + </param> + </when> + <when value="from"> + <param name="value" type="select" multiple="false" label="Choose the start value"> + <options from_dataset="dim_tab"> + <column name="name" index="1"/> + <column name="value" index="0"/> + </options> + </param> + </when> + </conditional> + </repeat> + <param type="float" name="scale" optional="true" help="scale factor (float) to apply to selection (optional)"/> + + <param name="write_all" type="boolean" value="false" label="Write all variables to new netCDF file"/> + </inputs> + <outputs> + <data name="output_netcdf" format="netcdf"/> + </outputs> + <tests> + <test> + <param name="input" value="dataset-ibi-reanalysis-bio-005-003-monthly-regulargrid_1510914389133.nc"/> + <param name="var_tab" value="var_tab_dataset-ibi"/> + <param name="var" value="chl"/> + <repeat name="user_choice"> + <param name="dim" value="time"/> + <conditional name="condi_between"> + <param name="comparator" value="sl"/> + <param name="t1" value="10"/> + <param name="t2" value="12"/> + </conditional> + </repeat> + <repeat name="user_choice"> + <param name="dim" value="latitude"/> + <param name="dim_tab" value="latitude.tabular"/> + <conditional name="condi_between"> + <param name="comparator" value="sl"/> + <param name="t1" value="5"/> + <param name="t2" value="10"/> + </conditional> + </repeat> + <repeat name="user_choice"> + <param name="dim" value="longitude"/> + <param name="dim_tab" value="longitude.tabular"/> + <conditional name="condi_between"> + <param name="comparator" value="sl"/> + <param name="t1" value="4"/> + <param name="t2" value="10"/> + </conditional> + </repeat> + <param name="scale" value="1000.5"/> + <output name="output_netcdf" file="small.netcdf" compare="sim_size" delat="1000"/> + </test> + <test> + <param name="input" value="dataset-ibi-reanalysis-bio-005-003-monthly-regulargrid_1510914389133.nc"/> + <param name="var_tab" value="var_tab_dataset-ibi"/> + <param name="var" value="chl"/> + <repeat name="user_choice"> + <param name="dim" value="time"/> + <conditional name="condi_between"> + <param name="comparator" value="sl"/> + <param name="t1" value="10"/> + <param name="t2" value="12"/> + </conditional> + </repeat> + <repeat name="user_choice"> + <param name="dim" value="latitude"/> + <param name="dim_tab" value="latitude.tabular"/> + <conditional name="condi_between"> + <param name="comparator" value="sl"/> + <param name="t1" value="5"/> + <param name="t2" value="10"/> + </conditional> + </repeat> + <repeat name="user_choice"> + <param name="dim" value="longitude"/> + <param name="dim_tab" value="longitude.tabular"/> + <conditional name="condi_between"> + <param name="comparator" value="sl"/> + <param name="t1" value="4"/> + <param name="t2" value="10"/> + </conditional> + </repeat> + <param name="scale" value="1000.5"/> + <param name="write_all" value="Yes"/> + <output name="output_netcdf" file="all.netcdf" compare="sim_size" delat="1000"/> + </test> + </tests> + <help><![CDATA[ +**What it does** + +Select a variable ans can restrict over any of its dimension and apply a scaling (1 by default). +the result is stored in a new netCDF file. +One can also select the range of time (for timeseries) to apply these operations over the range only +when a range of time is selected and when scaling, one can choose to save the entire timeseries or +the selected range only. +when scaling, one can add additional filters on dimensions (typically used to filter +over latitudes and longitudes) + + +------------------------------------------------- + +The xarray select tool can be used after the xarray Info and xarray Coord. + ]]></help> + <expand macro="citations"/> +</tool>
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/xarray_tool.py Sun Jun 06 08:50:11 2021 +0000 @@ -0,0 +1,365 @@ +# xarray tool for: +# - getting metadata information +# - select data and save results in csv file for further post-processing + +import argparse +import csv +import os +import warnings + +import geopandas as gdp + +import pandas as pd + +from shapely.geometry import Point +from shapely.ops import nearest_points + +import xarray as xr + + +class XarrayTool (): + def __init__(self, infile, outfile_info="", outfile_summary="", + select="", outfile="", outputdir="", latname="", + latvalN="", latvalS="", lonname="", lonvalE="", + lonvalW="", filter_list="", coords="", time="", + verbose=False, no_missing=False, coords_info=None, + tolerance=None): + self.infile = infile + self.outfile_info = outfile_info + self.outfile_summary = outfile_summary + self.select = select + self.outfile = outfile + self.outputdir = outputdir + self.latname = latname + if tolerance != "" and tolerance is not None: + self.tolerance = float(tolerance) + else: + self.tolerance = -1 + if latvalN != "" and latvalN is not None: + self.latvalN = float(latvalN) + else: + self.latvalN = "" + if latvalS != "" and latvalS is not None: + self.latvalS = float(latvalS) + else: + self.latvalS = "" + self.lonname = lonname + if lonvalE != "" and lonvalE is not None: + self.lonvalE = float(lonvalE) + else: + self.lonvalE = "" + if lonvalW != "" and lonvalW is not None: + self.lonvalW = float(lonvalW) + else: + self.lonvalW = "" + self.filter = filter_list + self.time = time + self.coords = coords + self.verbose = verbose + self.no_missing = no_missing + # initialization + self.dset = None + self.gset = None + self.coords_info = coords_info + if self.verbose: + print("infile: ", self.infile) + print("outfile_info: ", self.outfile_info) + print("outfile_summary: ", self.outfile_summary) + print("outfile: ", self.outfile) + print("select: ", self.select) + print("outfile: ", self.outfile) + print("outputdir: ", self.outputdir) + print("latname: ", self.latname) + print("latvalN: ", self.latvalN) + print("latvalS: ", self.latvalS) + print("lonname: ", self.lonname) + print("lonvalE: ", self.lonvalE) + print("lonvalW: ", self.lonvalW) + print("filter: ", self.filter) + print("time: ", self.time) + print("coords: ", self.coords) + print("coords_info: ", self.coords_info) + + def info(self): + f = open(self.outfile_info, 'w') + ds = xr.open_dataset(self.infile) + ds.info(f) + f.close() + + def summary(self): + f = open(self.outfile_summary, 'w') + ds = xr.open_dataset(self.infile) + writer = csv.writer(f, delimiter='\t') + header = ['VariableName', 'NumberOfDimensions'] + for idx, val in enumerate(ds.dims.items()): + header.append('Dim' + str(idx) + 'Name') + header.append('Dim' + str(idx) + 'Size') + writer.writerow(header) + for name, da in ds.data_vars.items(): + line = [name] + line.append(len(ds[name].shape)) + for d, s in zip(da.shape, da.sizes): + line.append(s) + line.append(d) + writer.writerow(line) + for name, da in ds.coords.items(): + line = [name] + line.append(len(ds[name].shape)) + for d, s in zip(da.shape, da.sizes): + line.append(s) + line.append(d) + writer.writerow(line) + f.close() + + def rowfilter(self, single_filter): + split_filter = single_filter.split('#') + filter_varname = split_filter[0] + op = split_filter[1] + ll = float(split_filter[2]) + if (op == 'bi'): + rl = float(split_filter[3]) + if filter_varname == self.select: + # filter on values of the selected variable + if op == 'bi': + self.dset = self.dset.where( + (self.dset <= rl) & (self.dset >= ll) + ) + elif op == 'le': + self.dset = self.dset.where(self.dset <= ll) + elif op == 'ge': + self.dset = self.dset.where(self.dset >= ll) + elif op == 'e': + self.dset = self.dset.where(self.dset == ll) + else: # filter on other dimensions of the selected variable + if op == 'bi': + self.dset = self.dset.sel({filter_varname: slice(ll, rl)}) + elif op == 'le': + self.dset = self.dset.sel({filter_varname: slice(None, ll)}) + elif op == 'ge': + self.dset = self.dset.sel({filter_varname: slice(ll, None)}) + elif op == 'e': + self.dset = self.dset.sel({filter_varname: ll}, + method='nearest') + + def selection(self): + if self.dset is None: + self.ds = xr.open_dataset(self.infile) + self.dset = self.ds[self.select] # select variable + if self.time: + self.datetime_selection() + if self.filter: + self.filter_selection() + + self.area_selection() + if self.gset.count() > 1: + # convert to dataframe if several rows and cols + self.gset = self.gset.to_dataframe().dropna(how='all'). \ + reset_index() + self.gset.to_csv(self.outfile, header=True, sep='\t') + else: + data = { + self.latname: [self.gset[self.latname].values], + self.lonname: [self.gset[self.lonname].values], + self.select: [self.gset.values] + } + + df = pd.DataFrame(data, columns=[self.latname, self.lonname, + self.select]) + df.to_csv(self.outfile, header=True, sep='\t') + + def datetime_selection(self): + split_filter = self.time.split('#') + time_varname = split_filter[0] + op = split_filter[1] + ll = split_filter[2] + if (op == 'sl'): + rl = split_filter[3] + self.dset = self.dset.sel({time_varname: slice(ll, rl)}) + elif (op == 'to'): + self.dset = self.dset.sel({time_varname: slice(None, ll)}) + elif (op == 'from'): + self.dset = self.dset.sel({time_varname: slice(ll, None)}) + elif (op == 'is'): + self.dset = self.dset.sel({time_varname: ll}, method='nearest') + + def filter_selection(self): + for single_filter in self.filter: + self.rowfilter(single_filter) + + def area_selection(self): + + if self.latvalS != "" and self.lonvalW != "": + # Select geographical area + self.gset = self.dset.sel({self.latname: + slice(self.latvalS, self.latvalN), + self.lonname: + slice(self.lonvalW, self.lonvalE)}) + elif self.latvalN != "" and self.lonvalE != "": + # select nearest location + if self.no_missing: + self.nearest_latvalN = self.latvalN + self.nearest_lonvalE = self.lonvalE + else: + # find nearest location without NaN values + self.nearest_location() + if self.tolerance > 0: + self.gset = self.dset.sel({self.latname: self.nearest_latvalN, + self.lonname: self.nearest_lonvalE}, + method='nearest', + tolerance=self.tolerance) + else: + self.gset = self.dset.sel({self.latname: self.nearest_latvalN, + self.lonname: self.nearest_lonvalE}, + method='nearest') + else: + self.gset = self.dset + + def nearest_location(self): + # Build a geopandas dataframe with all first elements in each dimension + # so we assume null values correspond to a mask that is the same for + # all dimensions in the dataset. + dsel_frame = self.dset + for dim in self.dset.dims: + if dim != self.latname and dim != self.lonname: + dsel_frame = dsel_frame.isel({dim: 0}) + # transform to pandas dataframe + dff = dsel_frame.to_dataframe().dropna().reset_index() + # transform to geopandas to collocate + gdf = gdp.GeoDataFrame(dff, + geometry=gdp.points_from_xy(dff[self.lonname], + dff[self.latname])) + # Find nearest location where values are not null + point = Point(self.lonvalE, self.latvalN) + multipoint = gdf.geometry.unary_union + queried_geom, nearest_geom = nearest_points(point, multipoint) + self.nearest_latvalN = nearest_geom.y + self.nearest_lonvalE = nearest_geom.x + + def selection_from_coords(self): + fcoords = pd.read_csv(self.coords, sep='\t') + for row in fcoords.itertuples(): + self.latvalN = row[0] + self.lonvalE = row[1] + self.outfile = (os.path.join(self.outputdir, + self.select + '_' + + str(row.Index) + '.tabular')) + self.selection() + + def get_coords_info(self): + ds = xr.open_dataset(self.infile) + for c in ds.coords: + filename = os.path.join(self.coords_info, + c.strip() + + '.tabular') + pd = ds.coords[c].to_pandas() + pd.index = range(len(pd)) + pd.to_csv(filename, header=False, sep='\t') + + +if __name__ == '__main__': + warnings.filterwarnings("ignore") + parser = argparse.ArgumentParser() + + parser.add_argument( + 'infile', + help='netCDF input filename' + ) + parser.add_argument( + '--info', + help='Output filename where metadata information is stored' + ) + parser.add_argument( + '--summary', + help='Output filename where data summary information is stored' + ) + parser.add_argument( + '--select', + help='Variable name to select' + ) + parser.add_argument( + '--latname', + help='Latitude name' + ) + parser.add_argument( + '--latvalN', + help='North latitude value' + ) + parser.add_argument( + '--latvalS', + help='South latitude value' + ) + parser.add_argument( + '--lonname', + help='Longitude name' + ) + parser.add_argument( + '--lonvalE', + help='East longitude value' + ) + parser.add_argument( + '--lonvalW', + help='West longitude value' + ) + parser.add_argument( + '--tolerance', + help='Maximum distance between original and selected value for ' + ' inexact matches e.g. abs(index[indexer] - target) <= tolerance' + ) + parser.add_argument( + '--coords', + help='Input file containing Latitude and Longitude' + 'for geographical selection' + ) + parser.add_argument( + '--coords_info', + help='output-folder where for each coordinate, coordinate values ' + ' are being printed in the corresponding outputfile' + ) + parser.add_argument( + '--filter', + nargs="*", + help='Filter list variable#operator#value_s#value_e' + ) + parser.add_argument( + '--time', + help='select timeseries variable#operator#value_s[#value_e]' + ) + parser.add_argument( + '--outfile', + help='csv outfile for storing results of the selection' + '(valid only when --select)' + ) + parser.add_argument( + '--outputdir', + help='folder name for storing results with multiple selections' + '(valid only when --select)' + ) + parser.add_argument( + "-v", "--verbose", + help="switch on verbose mode", + action="store_true" + ) + parser.add_argument( + "--no_missing", + help="""Do not take into account possible null/missing values + (only valid for single location)""", + action="store_true" + ) + args = parser.parse_args() + + p = XarrayTool(args.infile, args.info, args.summary, args.select, + args.outfile, args.outputdir, args.latname, + args.latvalN, args.latvalS, args.lonname, + args.lonvalE, args.lonvalW, args.filter, + args.coords, args.time, args.verbose, + args.no_missing, args.coords_info, args.tolerance) + if args.info: + p.info() + if args.summary: + p.summary() + if args.coords: + p.selection_from_coords() + elif args.select: + p.selection() + elif args.coords_info: + p.get_coords_info()