changeset 3:bf595d613af4 draft

"planemo upload for repository https://github.com/galaxyecology/tools-ecology/tree/master/tools/data_manipulation/xarray/ commit 2166974df82f97557b082a9e55135098e61640c4"
author ecology
date Thu, 20 Jan 2022 17:07:19 +0000
parents 123a9a629bef
children b393815e4cb7
files README.md macros.xml macros_mapplot.xml macros_netcdf2netcdf.xml macros_tests_netcdf2netcdf.xml test-data/all.netcdf test-data/chl_alltimes.nc test-data/chl_nh4.netcdf test-data/chl_phy_where.netcdf test-data/chl_where_drop.netcdf test-data/data_from_20040615.nc test-data/data_to_20040615.nc test-data/dataset-ibi-reanalysis-bio-005-003-monthly-regulargrid_1510914389133_time0.png test-data/dataset-ibi-reanalysis-bio-005-003-monthly-regulargrid_1510914389133_time0_title.png test-data/dataset-ibi-reanalysis-bio-005-003-monthly-regulargrid_1510914389133_time1.png test-data/dataset-ibi-reanalysis-bio-005-003-monthly-regulargrid_1510914389133_time50.png test-data/info_file.txt test-data/select_by_values.netcdf test-data/small.netcdf test-data/small_all_variables.netcdf test-data/version.tabular test-data/where_condition.txt test-data/where_condition_simple.txt xarray_mapplot.py xarray_netcdf2netcdf.py xarray_select.xml xarray_tool.py
diffstat 27 files changed, 2012 insertions(+), 1467 deletions(-) [+]
line wrap: on
line diff
--- a/README.md	Sun Jun 06 08:51:41 2021 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,8 +0,0 @@
-# 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().
--- a/macros.xml	Sun Jun 06 08:51:41 2021 +0000
+++ b/macros.xml	Thu Jan 20 17:07:19 2022 +0000
@@ -1,185 +1,28 @@
-<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>
+<macros>
+    <token name="@TOOL_VERSION@">0.20.2</token>
+    <token name="@VERSION_SUFFIX@">0</token>
+    <token name="@PROFILE@">20.05</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>
+</macros>
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/macros_mapplot.xml	Thu Jan 20 17:07:19 2022 +0000
@@ -0,0 +1,213 @@
+<macros>
+    <xml name="config_map">
+        <configfiles>
+            <configfile name="map_customization"><![CDATA[
+{
+#if $condi_datetime.datetime=="yes"
+"time":"$condi_datetime.time_values",
+#end if
+"latitude":'$lat_dim',
+"longitude":'$lon_dim',
+#if $colorbar_label
+"label":'$colorbar_label',
+#end if
+#if $title
+"title":"$title",
+#end if
+#if $cmap
+"cmap":'$cmap',
+#end if
+#if $land
+"land":'$land',
+#end if
+#if $ocean
+"ocean":'$ocean',
+#end if
+#if $coastline
+"coastline":'$coastline',
+#end if
+#if $borders
+"borders":'$borders',
+#end if
+#if $threshold
+"threshold":'$threshold',
+#end if
+#if $range
+"range":'$range',
+#end if
+#if $xlim
+"xlim":'$xlim',
+#end if
+#if $ylim
+"ylim":'$ylim',
+#end if
+}
+            ]]>
+            </configfile>
+            <configfile name="map_projection"><![CDATA[
+#if $proj
+'$proj'
+#end if 
+            ]]>
+            </configfile>
+        </configfiles>
+    </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/macros_netcdf2netcdf.xml	Thu Jan 20 17:07:19 2022 +0000
@@ -0,0 +1,143 @@
+<macros>
+    <xml name="coord_range">
+        <repeat name="user_choice" title="Filter by coordinate values" min="0" max="20" help="Use this option to filter on the values of the selected coordinate">
+            <param name="dim" type="select" label="Dimensions">
+                <options from_dataset="var_tab">
+                    <column name="value" index="0"/>
+                </options>
+            </param>
+            <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="text" value="" label="Choose the start value for slice"/>
+                    <param name="t2" type="text" value="" label="Choose the end value for slice"/>
+                </when>
+                <when value="to">
+                    <param name="value" type="text" value="" label="Choose the end value"/>
+                </when>
+                <when value="from">
+                    <param name="value" type="text" value="" label="Choose the start value"/>
+                </when>
+                <when value="is">
+                    <param name="value" type="text" value="" label="Choose the value to select"/>
+                    <yield />
+                </when>
+            </conditional>
+        </repeat>
+    </xml>
+    <xml name="section_variables">
+        <section name="variable" title="Select variables">
+            <param name="var" type="select" multiple="true" label="Choose variables to extract">
+                <options from_dataset="var_tab">
+                    <column name="name" index="0"/>
+                    <column name="value" index="0"/>
+                </options>
+            </param>
+            <param type="float" name="scale" optional="true" help="scale factor (float) to apply to the selected variable (optional and only if a variable is selected)"/>
+            <param name="write_all" type="boolean" checked="false" label="Write all variables to new netCDF file (only if a variable is selected)"/>
+            <param name="keep_attributes" type="boolean" checked="true" label="Keep all attributes (only if a variable is selected)"/>
+        </section>
+    </xml>
+    <xml name="section_coords">
+        <section name="subset_coords" title="Subset by coordinates">
+            <conditional name="tsel">
+                <param name="by_click" type="select" optional="true" label="Coordinate values">
+                    <option value="sel">Coordinate values (sel)</option>
+                    <option value="isel">Coordinate indices (isel)</option>
+                    <option value="isel_list" selected="true">Coordinate values from list</option>
+                </param>
+                <when value="sel">
+                    <expand macro="coord_range">
+                        <param name="method" type="select" multiple="false" label="Choose selection method">
+                            <option value="None">only exact matches</option>
+                            <option value="nearest">use nearest valid index value</option>
+                            <option value="pad">propagate last valid index value forward</option>
+                            <option value="backfill">propagate next valid index value backward</option>
+                        </param>
+                    </expand>
+                </when>
+                <when value="isel">
+                    <expand macro="coord_range"/>
+                </when>
+                <when value="isel_list">
+                    <repeat name="user_choice" title="Filter by coordinate values" min="0" max="20" help="Use this option to filter on the values of the selected coordinate">
+                        <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>
+                </when>
+            </conditional>
+        </section>
+    </xml>
+    <xml name="section_where">
+        <section name="mask_values" title="Advanced options to mask by values">
+            <conditional name="mask_condi">
+                <param name="mask_option" type="select" multiple="false" label="Option for masked values">
+                    <option value="keep" selected="true">Fill with NA</option>
+                    <option value="drop">Drop values</option>
+                    <option value="other">Set constant</option>
+                </param>
+                <when value="keep"/>
+                <when value="drop"/>
+                <when value="other">
+                    <param name="set_other" type="float" value="0" label="Value to use for locations in this object where cond is False." />
+                </when>
+            </conditional>
+            <param name="where_condition" type="data" optional="true" format="txt" label="file containing a where expression" />
+        </section>
+    </xml>
+</macros>
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/macros_tests_netcdf2netcdf.xml	Thu Jan 20 17:07:19 2022 +0000
@@ -0,0 +1,263 @@
+<macros>
+    <xml name="section_tests">
+        <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"/>
+                <section name="variable">
+                    <param name="var" value="chl"/>
+                    <param name="scale" value="1000.5"/>
+                </section>
+                <section name="subset_coords">
+                    <conditional name="tsel">
+                        <param name="by_click" value="isel_list"/>
+                        <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>
+                    </conditional>
+                </section>
+                <output name="output_netcdf" file="small.netcdf" compare="sim_size" delta="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"/>
+                <section name="variable">
+                    <param name="var" value="chl"/>
+                    <param name="scale" value="1000.5"/>
+                    <param name="write_all" value="true"/>
+                    <param name="keep_attribute" value="false"/>
+                </section>
+                <section name="subset_coords">
+                    <conditional name="tsel">
+                        <param name="by_click" value="isel_list"/>
+                        <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>
+                    </conditional>
+                </section>
+                <output name="output_netcdf" file="all.netcdf" compare="sim_size" delta="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"/>
+                <section name="subset_coords">
+                    <conditional name="tsel">
+                        <param name="by_click" value="isel_list"/>
+                        <repeat name="user_choice">
+                            <param name="dim" value="time"/>
+                            <param name="dim_tab" value="time.tabular"/>
+                            <conditional name="condi_between">
+                                <param name="comparator" value="to"/>
+                                <param name="value" 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="is"/>
+                                <param name="value" value="5"/>
+                            </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="is"/>
+                                <param name="value" value="4"/>
+                            </conditional>
+                        </repeat>
+                    </conditional>
+                </section>
+                <output name="output_netcdf" file="small_all_variables.netcdf" compare="sim_size" delta="500"/>
+            </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"/>
+                <section name="subset_coords">
+                    <conditional name="tsel">
+                        <param name="by_click" value="isel"/>
+                        <repeat name="user_choice">
+                            <param name="dim" value="time"/>
+                            <param name="dim_tab" value="time.tabular"/>
+                            <conditional name="condi_between">
+                                <param name="comparator" value="to"/>
+                                <param name="value" 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="is"/>
+                                <param name="value" value="5"/>
+                            </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="is"/>
+                                <param name="value" value="4"/>
+                            </conditional>
+                        </repeat>
+                    </conditional>
+                </section>
+                <output name="output_netcdf" file="small_all_variables.netcdf" compare="sim_size" delta="500"/>
+            </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"/>
+                <section name="variable">
+                    <param name="var" value="chl,nh4"/>
+                </section>
+                <output name="output_netcdf" file="chl_nh4.netcdf" compare="sim_size" delta="500"/>
+            </test>
+            <test>
+                <param name="input" value="data_to_20040615.nc,data_from_20040615.nc"/>
+                <param name="var_tab" value="var_tab_dataset-ibi"/>
+                <section name="variable">
+                    <param name="var" value="nh4"/>
+                </section>
+                <output name="output_netcdf" file="chl_alltimes.nc" compare="sim_size" delta="500"/>
+            </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"/>
+                <section name="subset_coords">
+                    <conditional name="tsel">
+                        <param name="by_click" value="sel"/>
+                        <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="44.5"/>
+                                <param name="t2" value="45.0"/>
+                            </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="is"/>
+                                <param name="value" value="-3.5"/>
+                                <param name="method" value="nearest"/>
+                            </conditional>
+                        </repeat>
+                    </conditional>
+                </section>
+                <output name="output_netcdf" file="select_by_values.netcdf" compare="sim_size" delta="500"/>
+            </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"/>
+                <section name="variable">
+                    <param name="var" value="chl,phy"/>
+                </section>
+                <section name="mask_values">
+                    <conditional name="mask_condi">
+                        <param name="mask_option" value="other"/>
+                        <param name="set_other" value="1000"/>
+                    </conditional>
+                    <param name="where_condition" ftype="txt" value="where_condition.txt"/>
+                </section>
+                <output name="output_netcdf" file="chl_phy_where.netcdf" compare="sim_size" delta="500"/>
+            </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"/>
+                <section name="variable">
+                    <param name="var" value="chl"/>
+                    <param name="scale" value="1000.5"/>
+                    <param name="write_all" value="true"/>
+                    <param name="keep_attribute" value="true"/>
+                </section>
+                <section name="subset_coords">
+                    <conditional name="tsel">
+                        <param name="by_click" value="isel_list"/>
+                        <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="0"/>
+                                <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="1"/>
+                                <param name="t2" value="20"/>
+                            </conditional>
+                        </repeat>
+                    </conditional>
+                </section>
+                <section name="mask_values">
+                    <conditional name="mask_condi">
+                        <param name="mask_option" value="drop"/>
+                    </conditional>
+                    <param name="where_condition" ftype="txt" value="where_condition_simple.txt"/>
+                </section>
+                <output name="output_netcdf" file="chl_where_drop.netcdf" compare="sim_size" delta="500"/>
+            </test>
+        </tests>
+    </xml>
+</macros>
Binary file test-data/all.netcdf has changed
Binary file test-data/chl_alltimes.nc has changed
Binary file test-data/chl_nh4.netcdf has changed
Binary file test-data/chl_phy_where.netcdf has changed
Binary file test-data/chl_where_drop.netcdf has changed
Binary file test-data/data_from_20040615.nc has changed
Binary file test-data/data_to_20040615.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_time0_title.png has changed
Binary file test-data/dataset-ibi-reanalysis-bio-005-003-monthly-regulargrid_1510914389133_time1.png has changed
Binary file test-data/dataset-ibi-reanalysis-bio-005-003-monthly-regulargrid_1510914389133_time50.png has changed
--- a/test-data/info_file.txt	Sun Jun 06 08:51:41 2021 +0000
+++ b/test-data/info_file.txt	Thu Jan 20 17:07:19 2022 +0000
@@ -1,9 +1,9 @@
 xarray.Dataset {
 dimensions:
+	time = 145 ;
 	depth = 1 ;
 	latitude = 97 ;
 	longitude = 103 ;
-	time = 145 ;
 
 variables:
 	float32 phy(time, depth, latitude, longitude) ;
Binary file test-data/select_by_values.netcdf has changed
Binary file test-data/small.netcdf has changed
Binary file test-data/small_all_variables.netcdf has changed
--- a/test-data/version.tabular	Sun Jun 06 08:51:41 2021 +0000
+++ b/test-data/version.tabular	Thu Jan 20 17:07:19 2022 +0000
@@ -1,1 +1,1 @@
-Galaxy xarray version 0.18.2
+Galaxy xarray version 0.20.2
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/where_condition.txt	Thu Jan 20 17:07:19 2022 +0000
@@ -0,0 +1,1 @@
+((chl > 1) | (chl < 45)) & (nh4 > 1)
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/where_condition_simple.txt	Thu Jan 20 17:07:19 2022 +0000
@@ -0,0 +1,1 @@
+nh4 > 5.15
--- a/xarray_mapplot.py	Sun Jun 06 08:51:41 2021 +0000
+++ b/xarray_mapplot.py	Thu Jan 20 17:07:19 2022 +0000
@@ -1,457 +1,411 @@
-#!/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
+#!/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]
+#                               [--config config-file]
+#                               [--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
+#  --config          plotting parameters are passed via a config file
+#                    (overwrite other plotting options)
+#  --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, varname, output, verbose=False,
+                 config_file="", proj="", shift=False):
+
+        li = list(input.split(","))
+        if len(li) > 1:
+            self.input = li
+        else:
+            self.input = input
+
+        if proj != "" and proj is not None and Path(proj).exists():
+            f = open(proj)
+            sdict = ''.join(
+                f.read().replace("\n", "").split('{')[1].split('}')[0]
+                )
+            self.proj = '{' + sdict.strip() + '}'
+        else:
+            self.proj = None
+        self.varname = varname
+        self.shift = shift
+        self.xylim_supported = False
+        self.colorbar = True
+        if output is None:
+            if type(self.input) is list:
+                self.output = Path(self.input[0]).stem + '.png'
+            else:
+                self.output = Path(self.input).stem + '.png'
+        else:
+            self.output = output
+        self.verbose = verbose
+        self.label = {}
+        self.time = []
+        self.xlim = []
+        self.ylim = []
+        self.range = []
+        self.latitude = "latitude"
+        self.longitude = "longitude"
+        self.land = 0
+        self.ocean = 0
+        self.coastline = 0
+        self.borders = 0
+        self.cmap = "coolwarm"
+        self.threshold = ""
+        self.title = ""
+
+        if config_file != "" and config_file is not None:
+            with open(config_file) as f:
+                sdict = ''.join(
+                    f.read().replace("\n", "").split('{')[1].split('}')[0]
+                    )
+                tmp = ast.literal_eval('{' + sdict.strip() + '}')
+                for key in tmp:
+                    if key == 'time':
+                        time = tmp[key]
+                        self.time = list(map(int, time.split(",")))
+                    if key == 'cmap':
+                        self.get_cmap(tmp[key])
+                    if key == 'latitude':
+                        self.latitude = tmp[key]
+                    if key == 'longitude':
+                        self.longitude = tmp[key]
+                    if key == 'land':
+                        self.land = float(tmp[key])
+                    if key == 'ocean':
+                        self.ocean = float(tmp[key])
+                    if key == 'coastline':
+                        self.coastline = float(tmp[key])
+                    if key == 'borders':
+                        self.borders = float(tmp[key])
+                    if key == 'xlim':
+                        xlim = tmp[key]
+                        self.xlim = list(map(float, xlim.split(",")))
+                    if key == 'ylim':
+                        ylim = tmp[key]
+                        self.ylim = list(map(float, ylim.split(",")))
+                    if key == 'range':
+                        range_values = tmp[key]
+                        self.range = list(map(float, range_values.split(",")))
+                    if key == 'threshold':
+                        self.threshold = float(tmp[key])
+                    if key == 'label':
+                        self.label['label'] = tmp[key]
+                    if key == 'title':
+                        self.title = tmp[key]
+
+        if type(self.input) is list:
+            self.dset = xr.open_mfdataset(self.input, use_cftime=True)
+        else:
+            self.dset = xr.open_dataset(self.input, use_cftime=True)
+
+        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='Config file with the projection on which we draw'
+    )
+    parser.add_argument(
+        'varname',
+        help='Specify which variable to plot (case sensitive)'
+    )
+    parser.add_argument(
+        '--output',
+        help='output filename to store resulting image (png format)'
+    )
+    parser.add_argument(
+        '--config',
+        help='pass plotting parameters via a config file'
+    )
+    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()
+
+    dset = MapPlotXr(input=args.input, varname=args.varname,
+                     output=args.output, verbose=args.verbose,
+                     config_file=args.config, proj=args.proj,
+                     shift=args.shift)
+
+    if dset.time == []:
+        dset.plot()
+    else:
+        for t in dset.time:
+            dset.plot(t)
+            dset.shift = False   # only shift once
+            dset.colorbar = True
--- a/xarray_netcdf2netcdf.py	Sun Jun 06 08:51:41 2021 +0000
+++ b/xarray_netcdf2netcdf.py	Thu Jan 20 17:07:19 2022 +0000
@@ -1,133 +1,268 @@
-#!/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()
+#!/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 re
+import warnings
+from pathlib import Path
+
+import xarray as xr  # noqa: E402
+
+
+class netCDF2netCDF ():
+    def __init__(self, infile, varname, scale="",
+                 output="output.netcdf",
+                 write_all=False,
+                 keep_attributes=True,
+                 filter_list="",
+                 where_config="",
+                 other="",
+                 sel=False,
+                 drop=False,
+                 verbose=False):
+        self.drop = drop
+        if Path(where_config).exists():
+            f = open(where_config)
+            self.where = f.read().replace("\n", "")
+        else:
+            self.where = ""
+        self.other = other
+        self.sel = sel
+        li = list(infile.split(","))
+        if len(li) > 1:
+            self.infile = li
+        else:
+            self.infile = infile
+        self.verbose = verbose
+        if varname == 'None' or varname is None:
+            self.varname = varname
+        else:
+            li = list(varname.split(","))
+            self.varname = li
+        self.write_all = write_all
+        self.keep_attributes = keep_attributes
+        if self.keep_attributes:
+            xr.set_options(keep_attrs=True)
+        self.filter = filter_list
+        self.selection = {}
+        self.method = {}
+        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("keep_attributes: ", self.keep_attributes)
+            print("sel: ", self.sel)
+            print("output: ", self.output)
+
+    def apply_selection(self):
+        self.dset = self.ds
+        for key in self.selection:
+            if 'slice' in str(self.selection[key]):
+                self.dset = self.dset.sel(
+                    {key: self.selection[key]}
+                    )
+            else:
+                self.dset = self.dset.sel(
+                    {key: self.selection[key]},
+                    method=self.method[key]
+                    )
+
+    def dimension_selection(self, single_filter):
+        split_filter = single_filter.split('#')
+        dimension_varname = split_filter[0]
+        op = split_filter[1]
+        if self.sel:
+            ll = float(split_filter[2])
+        else:
+            ll = int(split_filter[2])
+        if (op == 'sl'):
+            if self.sel:
+                rl = float(split_filter[3])
+            else:
+                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
+            if self.sel:
+                rl = split_filter[3]
+                if 'None' in rl:
+                    self.method[dimension_varname] = None
+                else:
+                    self.method[dimension_varname] = rl
+
+    def filter_selection(self):
+        for single_filter in self.filter:
+            self.dimension_selection(single_filter)
+
+        if self.sel:
+            self.apply_selection()
+        else:
+            self.dset = \
+                self.ds.isel(self.selection)
+
+        if self.varname != 'None' and self.varname is not None:
+            for var in self.varname:
+                self.dset[var] = \
+                    self.dset[var]*self.scale
+
+    def compute(self):
+        if self.dset is None:
+            if type(self.infile) is list:
+                self.ds = xr.open_mfdataset(self.infile)
+            else:
+                self.ds = xr.open_dataset(self.infile)
+            if self.where != "":
+                if self.drop:
+                    if self.verbose:
+                        print("Where with drop=True")
+                    self.ds = self.ds.where(
+                        self.eval_where(self.where),
+                        drop=True
+                        )
+                elif self.other is not None and self.other != "":
+                    if self.verbose:
+                        print("Where with  other=", float(self.other))
+                    self.ds = self.ds.where(
+                        self.eval_where(self.where),
+                        other=float(self.other)
+                        )
+                else:
+                    self.ds = self.ds.where(
+                        self.eval_where(self.where)
+                        )
+            self.filter_selection()
+            if self.verbose:
+                print(self.selection)
+
+    def save(self):
+        if self.varname != 'None' and \
+            self.varname is not None and \
+                not self.write_all:
+            self.dset[self.varname].to_netcdf(self.output)
+        else:
+            self.dset.to_netcdf(self.output)
+
+    def is_float(self, element) -> bool:
+        try:
+            float(element)
+            return True
+        except ValueError:
+            return False
+
+    def eval_where(self, where_condition):
+        eval_cond = None
+        list_names = list(set(
+                        list(self.ds.keys()) +
+                        list(self.ds.coords.keys()))
+                        )
+        wcond = where_condition
+        check_cond = where_condition
+        for var in list_names:
+            wcond = wcond.replace(var, ' self.ds.' + var + ' ')
+            check_cond = check_cond.replace(var, '')
+        to_remove = "[><=&|()]"
+        check_cond = re.sub(to_remove, "", check_cond).replace("!", "")
+        check_cond = re.sub(' +', ' ', check_cond).strip()
+        list_flt = check_cond.split(" ")
+        no_convert = False
+        for num in list_flt:
+            if not self.is_float(num):
+                no_convert = True
+        if not no_convert:
+            eval_cond = eval(wcond)
+        return eval_cond
+
+
+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(
+        '--where',
+        help='filename with where condition to be evaluated'
+    )
+    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(
+        '--other',
+        help='Value to use for locations where condition is False (float)'
+    )
+    parser.add_argument(
+        "--write_all",
+        help="write all data to netCDF",
+        action="store_true")
+    parser.add_argument(
+        "--keep_attributes",
+        help="Keep all attributes",
+        action="store_true")
+    parser.add_argument(
+        "-v", "--verbose",
+        help="switch on verbose mode",
+        action="store_true")
+    parser.add_argument(
+        "--selection",
+        help="select by values",
+        action="store_true")
+    parser.add_argument(
+        "--drop",
+        help="drop values where condition is not met",
+        action="store_true")
+    args = parser.parse_args()
+
+    print("args.selection", args.selection)
+    dset = netCDF2netCDF(infile=args.input, varname=args.varname,
+                         scale=args.scale, output=args.output,
+                         write_all=args.write_all,
+                         sel=args.selection,
+                         keep_attributes=args.keep_attributes,
+                         filter_list=args.filter,
+                         where_config=args.where,
+                         drop=args.drop, other=args.other,
+                         verbose=args.verbose)
+    dset.compute()
+    dset.save()
--- a/xarray_select.xml	Sun Jun 06 08:51:41 2021 +0000
+++ b/xarray_select.xml	Thu Jan 20 17:07:19 2022 +0000
@@ -1,317 +1,317 @@
-<tool id="xarray_select" name="NetCDF xarray Selection" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@">
-    <description>extracts variable values with custom conditions on dimensions</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>
-        <requirement type="package" version="0.9.0">geopandas</requirement>
-        <requirement type="package" version="1.7.1">shapely</requirement>
-    </requirements>
-    <command detect_errors="exit_code"><![CDATA[
-    mkdir output_dir &&
-    #if $condi_source_coord.coord_source=="coord_from_file"
-       echo "Galaxy xarray version @TOOL_VERSION@" > output_dir/version.tabular &&
-    #end if
-    python '$__tool_directory__/xarray_tool.py' '$input' --select '$var'
-           --verbose
-           --filter
-    #for $i,$uc in enumerate($user_choice)
-        #if $uc.condi_between.comparator=="bi"
-             '${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 $time.condi_datetime.datetime=="yes"
-         --time
-        #if $time.condi_datetime.condi_between.comparator=="sl"
-             '${time.condi_datetime.dim}#${time.condi_datetime.condi_between.comparator}#${time.condi_datetime.condi_between.t1}#${time.condi_datetime.condi_between.t2}'
-        #else
-             '${time.condi_datetime.dim}#${time.condi_datetime.condi_between.comparator}#${time.condi_datetime.condi_between.t1}'
-        #end if
-    #end if
-
-    #if $condi_source_coord.coord_source=="coord_from_file"
-         --coords '$coord_tabular'
-         --latname '$condi_source_coord.lat_dim' --lonname '$condi_source_coord.lon_dim'
-         --outputdir output_dir
-         #if $condi_source_coord.tolerance
-             --tolerance '$condi_source_coord.tolerance'
-         #end if
-    #else
-         --outfile 'final.tabular'
-        #if $condi_source_coord.condi_coord.coord=='single'
-           --latname $condi_source_coord.condi_coord.lat_dim
-           --latvalN $condi_source_coord.condi_coord.lat_val
-           --lonname $condi_source_coord.condi_coord.lon_dim
-           --lonvalE $condi_source_coord.condi_coord.lon_val
-	    #if $condi_source_coord.condi_coord.no_missing
-	        --no_missing
-	    #end if
-            #if $condi_source_coord.condi_coord.tolerance
-                --tolerance '$condi_source_coord.condi_coord.tolerance'
-            #end if
-        #elif $condi_source_coord.condi_coord.coord=='subregion'
-           --latname $condi_source_coord.condi_coord.lat_dim
-           --latvalN $condi_source_coord.condi_coord.lat_valN
-           --latvalS $condi_source_coord.condi_coord.lat_valS
-           --lonname $condi_source_coord.condi_coord.lon_dim
-           --lonvalE $condi_source_coord.condi_coord.lon_valE
-           --lonvalW $condi_source_coord.condi_coord.lon_valW
-        #end if
-    #end if
-    ]]></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>
-
-        <conditional name="condi_source_coord">
-            <param name="coord_source" type="select" label="Source of coordinates">
-                <option value="coord_from_stdin">Manually enter coordinates</option>
-                <option value="coord_from_file">Use coordinates from input file</option>
-            </param>
-
-            <when value="coord_from_file">
-                <param type="data" label="Tabular of coord" name="coord_tabular" format="tabular" help="Format : Latitude	Longitude"/>
-                <param name="lat_dim" type="select" label="Name of latitude coordinate" >
-                    <options from_dataset="var_tab">
-                        <column name="value" index="0"/>
-                    </options>
-                </param>
-                <param name="lon_dim" type="select" label="Name of longitude coordinate" >
-                    <options from_dataset="var_tab">
-                        <column name="value" index="0"/>
-                    </options>
-                </param>
-                <param type="float" name="tolerance" optional="true" label="Maximum distance between original and selected value for inexact matches e.g. abs(original, index) is lower or equal to tolerance"/>
-            </when>
-
-            <when value="coord_from_stdin">
-                <conditional name="condi_coord">
-                    <param name="coord" type="select" label="Geographical area" help="Use this option to get valid values at your custom coordinates.">
-                        <option value="global">Whole available region</option>
-                        <option value="single">Single location</option>
-                        <option value="subregion">Sub-region extraction</option>
-                    </param>
-                    <when value="single">
-                        <param name="lat_dim" type="select" label="Name of latitude coordinate" >
-                            <options from_dataset="var_tab">
-                                <column name="value" index="0"/>
-                            </options>
-                        </param>
-                        <param name="lat_val" type="float" value="0" label="Latitude"/>
-                        <param name="lon_dim" type="select" label="Name of longitude coordinate" >
-                            <options from_dataset="var_tab">
-                                <column name="value" index="0"/>
-                            </options>
-                        </param>
-                        <param name="lon_val" type="float" value="0" label="Longitude"/>
-                        <param name="no_missing" type="boolean" value="false" label="Do not handle null/missing values (only valid for single location and multiple columns)"/>
-                        <param name="tolerance" type="float" optional="true" label="Maximum distance between original and selected value for inexact matches e.g. abs(original, index) is lower or equal to tolerance"/>
-                    </when>
-                    <when value="subregion">
-                        <param name="lat_dim" type="select" label="Name of latitude coordinate" >
-                            <options from_dataset="var_tab">
-                                <column name="value" index="0"/>
-                            </options>
-                        </param>
-                        <param name="lat_valN" type="float" value="0" label="Latitude North"/>
-                        <param name="lat_valS" type="float" value="0" label="Latitude South"/>
-                        <param name="lon_dim" type="select" label="Name of longitude coordinate" >
-                            <options from_dataset="var_tab">
-                                <column name="value" index="0"/>
-                            </options>
-                        </param>
-                        <param name="lon_valE" type="float" value="0" label="Longitude East"/>
-                        <param name="lon_valW" type="float" value="0" label="Longitude West"/>
-                    </when>
-                    <when value="global"></when>
-                </conditional>
-            </when>
-
-        </conditional>
-
-        <section name="time" title="Select Time series" expanded="false">
-            <conditional name="condi_datetime">
-                <param name="datetime" type="select" label="Datetime selection" help="Use this option to extract timeseries from your dataset">
-                    <option value="no">No</option>
-                    <option value="yes">Yes</option>
-                </param>
-                <when value="no"></when>
-                <when value="yes">
-                    <param name="dim" type="select" label="Select datetime dimension" help="Use this option only if your dataset contains a date/time dimension">
-                        <options from_dataset="var_tab">
-                            <column name="value" index="0"/>
-                        </options>
-                    </param>
-                    <conditional name="condi_between">
-                        <param name="comparator" type="select" label="date/Time selection">
-                            <option value="is">is</option>
-                            <option value="sl">slice</option>
-                            <option value="ne">nearest</option>
-                            <option value="to">to</option>
-                            <option value="from">from</option>
-                        </param>
-                        <when value="sl">
-                            <param name="t1" type="text" value="" label="Start date/time"/>
-                            <param name="t2" type="text" value="" label="End date/time"/>
-                        </when>
-                        <when value="is">
-                            <param name="t1" type="text" value="" label="date/time"/>
-                        </when>
-                        <when value="ne">
-                            <param name="t1" type="text" value="" label="date/time"/>
-                        </when>
-                        <when value="to">
-                            <param name="t1" type="text" value="" label="date/time"/>
-                        </when>
-                        <when value="from">
-                            <param name="t1" type="text" value="" label="date/time"/>
-                        </when>
-                    </conditional>
-                </when>
-            </conditional>
-        </section>
-        <repeat name="user_choice" title="additional filter" 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>
-            <conditional name="condi_between">
-                <param name="comparator" type="select" label="Comparator">
-                    <option value="e">Equal</option>
-                    <option value="ge">Greater or equal</option>
-                    <option value="le">Less or equal</option>
-                    <option value="bi">Between-include [threshold1,threshold2]</option>
-                </param>
-                <when value="bi">
-                    <param name="t1" type="text" value="0" label="Inferior threshold"/>
-                    <param name="t2" type="text" value="0" label="Superior threshold"/>
-                </when>
-                <when value="e">
-                    <param name="value" type="text" value="0" label="Value"/>
-                </when>
-                <when value="ge">
-                    <param name="value" type="text" value="0" label="Value"/>
-                </when>
-                <when value="le">
-                    <param name="value" type="text" value="0" label="Value"/>
-                </when>
-            </conditional>
-        </repeat>
-    </inputs>
-    <outputs>
-        <collection type="list" name="output">
-            <discover_datasets pattern="__designation_and_ext__" visible="false" format="tabular" directory="output_dir"/>
-            <filter>condi_source_coord['coord_source'] == 'coord_from_file'</filter>
-        </collection>
-        <data name="simpleoutput" from_work_dir="final.tabular" format="tabular">
-            <filter>condi_source_coord['coord_source'] == 'coord_from_stdin'</filter>
-        </data>
-    </outputs>
-    <tests>
-        <test>
-             <param name="input" value="dataset-ibi-reanalysis-bio-005-003-monthly-regulargrid_1510914389133.nc"/>
-             <param name="var" value="phy"/>
-             <param name="var_tab" value="var_tab_dataset-ibi"/>
-             <conditional name="condi_source_coord">
-                 <param name="coord_source" value="coord_from_stdin"/>
-                 <conditional name="condi_coord">
-                     <param name="coord" value="single"/>
-                     <param name="lat_dim" value="latitude"/>
-                     <param name="lat_val" value="44.0"/>
-                     <param name="lon_dim" value="longitude"/>
-                     <param name="lon_val" value="-2.0"/>
-                 </conditional>
-             </conditional>
-             <output name="simpleoutput" value="Test1.tabular">
-                 <assert_contents>
-                     <has_text_matching expression="0\t2002-12-15\t0.5"/>
-                     <has_text_matching expression="144\t2014-12-15\t0.5"/>
-                 </assert_contents>
-             </output>
-        </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="nh4"/>
-
-             <conditional name="condi_source_coord">
-                 <param name="coord_source" value="coord_from_stdin"/>
-                 <conditional name="condi_coord">
-                     <param name="coord" value="global"/>
-                 </conditional>
-             </conditional>
-             <section name="time">
-                 <conditional name="condi_datetime">
-                     <param name="datetime" value="yes"/>
-                     <conditional name="condi_between">
-                         <param name="comparator" value="sl"/>
-                         <param name="t1" value="2003-12-15" />
-                         <param name="t2" value="2004-12-15" />
-                     </conditional>
-                 </conditional>
-             </section>
-             <repeat name="user_choice">
-                 <param name="dim" value="nh4"/>
-                 <conditional name="condi_between">
-                     <param name="comparator" value="ge"/>
-                     <param name="value" value="50."/>
-                 </conditional>
-             </repeat>
-             <output name="simpleoutput" value="Test2.tabular">
-                 <assert_contents>
-                     <has_text_matching expression="0\t2003-12-15\t0.5"/>
-                     <has_text_matching expression="23\t2004-12-15\t0.5"/>
-                 </assert_contents>
-             </output>
-        </test>
-    </tests>
-    <help><![CDATA[
-**What it does**
-
-This tool extracts variable values with custom conditions on dimensions.
-
-It can use manualy given coordinates or automaticaly take them from a tabular file to filter informations.
-
-If no values are availables at a coordinate X, the tool will search the closest coordinate with a non NA value.
-
-Filter can be set on every dimension. Available filtering operations are : =, >, <, >=, <=, [interval], ]interval[.
-
-
-
-**Input**
-
-A netcdf file (.nc).
-
-Variable tabular file from 'Netcdf Metadate Info'.
-
-Tabular file with coordinates (only coordinates, no header!) and the following structure : 'lat'	'lon'.
-
-
-**Outputs**
-
-A single output with values for the wanted variable if there is only one coordinate.
-
-A data collection where one file is created for every coordinate, if multiple coordinates from tabular file.
-
-
--------------------------------------------------
-
-The xarray select tool can be used after the xarray Info.
-    ]]></help>
-    <expand macro="citations"/>
-</tool>
+<tool id="xarray_select" name="NetCDF xarray Selection" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="@PROFILE@">
+    <description>extracts variable values with custom conditions on dimensions</description>
+    <macros>
+        <import>macros.xml</import>
+    </macros>
+    <expand macro="edam_ontology"/>
+    <requirements>
+        <requirement type="package" version="@TOOL_VERSION@">xarray</requirement>
+        <requirement type="package" version="3">python</requirement>
+        <requirement type="package" version="1.5.6">netcdf4</requirement>
+        <requirement type="package" version="0.9.0">geopandas</requirement>
+        <requirement type="package" version="1.7.1">shapely</requirement>
+    </requirements>
+    <command detect_errors="exit_code"><![CDATA[
+    mkdir output_dir &&
+    #if $condi_source_coord.coord_source=="coord_from_file"
+       echo "Galaxy xarray version @TOOL_VERSION@"> output_dir/version.tabular &&
+    #end if
+    python '$__tool_directory__/xarray_tool.py' '$input' --select '$var'
+           --verbose
+           --filter
+    #for $i,$uc in enumerate($user_choice)
+        #if $uc.condi_between.comparator=="bi"
+             '${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 $time.condi_datetime.datetime=="yes"
+         --time
+        #if $time.condi_datetime.condi_between.comparator=="sl"
+             '${time.condi_datetime.dim}#${time.condi_datetime.condi_between.comparator}#${time.condi_datetime.condi_between.t1}#${time.condi_datetime.condi_between.t2}'
+        #else
+             '${time.condi_datetime.dim}#${time.condi_datetime.condi_between.comparator}#${time.condi_datetime.condi_between.t1}'
+        #end if
+    #end if
+
+    #if $condi_source_coord.coord_source=="coord_from_file"
+         --coords '$coord_tabular'
+         --latname '$condi_source_coord.lat_dim' --lonname '$condi_source_coord.lon_dim'
+         --outputdir output_dir
+         #if $condi_source_coord.tolerance
+             --tolerance '$condi_source_coord.tolerance'
+         #end if
+    #else
+         --outfile 'final.tabular'
+        #if $condi_source_coord.condi_coord.coord=='single'
+           --latname $condi_source_coord.condi_coord.lat_dim
+           --latvalN $condi_source_coord.condi_coord.lat_val
+           --lonname $condi_source_coord.condi_coord.lon_dim
+           --lonvalE $condi_source_coord.condi_coord.lon_val
+	    #if $condi_source_coord.condi_coord.no_missing
+	        --no_missing
+	    #end if
+            #if $condi_source_coord.condi_coord.tolerance
+                --tolerance '$condi_source_coord.condi_coord.tolerance'
+            #end if
+        #elif $condi_source_coord.condi_coord.coord=='subregion'
+           --latname $condi_source_coord.condi_coord.lat_dim
+           --latvalN $condi_source_coord.condi_coord.lat_valN
+           --latvalS $condi_source_coord.condi_coord.lat_valS
+           --lonname $condi_source_coord.condi_coord.lon_dim
+           --lonvalE $condi_source_coord.condi_coord.lon_valE
+           --lonvalW $condi_source_coord.condi_coord.lon_valW
+        #end if
+    #end if
+    ]]>    </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>
+
+        <conditional name="condi_source_coord">
+            <param name="coord_source" type="select" label="Source of coordinates">
+                <option value="coord_from_stdin">Manually enter coordinates</option>
+                <option value="coord_from_file">Use coordinates from input file</option>
+            </param>
+
+            <when value="coord_from_file">
+                <param type="data" label="Tabular of coord" name="coord_tabular" format="tabular" help="Format : Latitude	Longitude"/>
+                <param name="lat_dim" type="select" label="Name of latitude coordinate">
+                    <options from_dataset="var_tab">
+                        <column name="value" index="0"/>
+                    </options>
+                </param>
+                <param name="lon_dim" type="select" label="Name of longitude coordinate">
+                    <options from_dataset="var_tab">
+                        <column name="value" index="0"/>
+                    </options>
+                </param>
+                <param type="float" name="tolerance" optional="true" label="Maximum distance between original and selected value for inexact matches e.g. abs(original, index) is lower or equal to tolerance"/>
+            </when>
+
+            <when value="coord_from_stdin">
+                <conditional name="condi_coord">
+                    <param name="coord" type="select" label="Geographical area" help="Use this option to get valid values at your custom coordinates.">
+                        <option value="global">Whole available region</option>
+                        <option value="single">Single location</option>
+                        <option value="subregion">Sub-region extraction</option>
+                    </param>
+                    <when value="single">
+                        <param name="lat_dim" type="select" label="Name of latitude coordinate">
+                            <options from_dataset="var_tab">
+                                <column name="value" index="0"/>
+                            </options>
+                        </param>
+                        <param name="lat_val" type="float" value="0" label="Latitude"/>
+                        <param name="lon_dim" type="select" label="Name of longitude coordinate">
+                            <options from_dataset="var_tab">
+                                <column name="value" index="0"/>
+                            </options>
+                        </param>
+                        <param name="lon_val" type="float" value="0" label="Longitude"/>
+                        <param name="no_missing" type="boolean" value="false" label="Do not handle null/missing values (only valid for single location and multiple columns)"/>
+                        <param name="tolerance" type="float" optional="true" label="Maximum distance between original and selected value for inexact matches e.g. abs(original, index) is lower or equal to tolerance"/>
+                    </when>
+                    <when value="subregion">
+                        <param name="lat_dim" type="select" label="Name of latitude coordinate">
+                            <options from_dataset="var_tab">
+                                <column name="value" index="0"/>
+                            </options>
+                        </param>
+                        <param name="lat_valN" type="float" value="0" label="Latitude North"/>
+                        <param name="lat_valS" type="float" value="0" label="Latitude South"/>
+                        <param name="lon_dim" type="select" label="Name of longitude coordinate">
+                            <options from_dataset="var_tab">
+                                <column name="value" index="0"/>
+                            </options>
+                        </param>
+                        <param name="lon_valE" type="float" value="0" label="Longitude East"/>
+                        <param name="lon_valW" type="float" value="0" label="Longitude West"/>
+                    </when>
+                    <when value="global"></when>
+                </conditional>
+            </when>
+
+        </conditional>
+
+        <section name="time" title="Select Time series" expanded="false">
+            <conditional name="condi_datetime">
+                <param name="datetime" type="select" label="Datetime selection" help="Use this option to extract timeseries from your dataset">
+                    <option value="no">No</option>
+                    <option value="yes">Yes</option>
+                </param>
+                <when value="no"></when>
+                <when value="yes">
+                    <param name="dim" type="select" label="Select datetime dimension" help="Use this option only if your dataset contains a date/time dimension">
+                        <options from_dataset="var_tab">
+                            <column name="value" index="0"/>
+                        </options>
+                    </param>
+                    <conditional name="condi_between">
+                        <param name="comparator" type="select" label="date/Time selection">
+                            <option value="is">is</option>
+                            <option value="sl">slice</option>
+                            <option value="ne">nearest</option>
+                            <option value="to">to</option>
+                            <option value="from">from</option>
+                        </param>
+                        <when value="sl">
+                            <param name="t1" type="text" value="" label="Start date/time"/>
+                            <param name="t2" type="text" value="" label="End date/time"/>
+                        </when>
+                        <when value="is">
+                            <param name="t1" type="text" value="" label="date/time"/>
+                        </when>
+                        <when value="ne">
+                            <param name="t1" type="text" value="" label="date/time"/>
+                        </when>
+                        <when value="to">
+                            <param name="t1" type="text" value="" label="date/time"/>
+                        </when>
+                        <when value="from">
+                            <param name="t1" type="text" value="" label="date/time"/>
+                        </when>
+                    </conditional>
+                </when>
+            </conditional>
+        </section>
+        <repeat name="user_choice" title="additional filter" 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>
+            <conditional name="condi_between">
+                <param name="comparator" type="select" label="Comparator">
+                    <option value="e">Equal</option>
+                    <option value="ge">Greater or equal</option>
+                    <option value="le">Less or equal</option>
+                    <option value="bi">Between-include [threshold1,threshold2]</option>
+                </param>
+                <when value="bi">
+                    <param name="t1" type="text" value="0" label="Inferior threshold"/>
+                    <param name="t2" type="text" value="0" label="Superior threshold"/>
+                </when>
+                <when value="e">
+                    <param name="value" type="text" value="0" label="Value"/>
+                </when>
+                <when value="ge">
+                    <param name="value" type="text" value="0" label="Value"/>
+                </when>
+                <when value="le">
+                    <param name="value" type="text" value="0" label="Value"/>
+                </when>
+            </conditional>
+        </repeat>
+    </inputs>
+    <outputs>
+        <collection type="list" name="output">
+            <discover_datasets pattern="__designation_and_ext__" visible="false" format="tabular" directory="output_dir"/>
+            <filter>condi_source_coord['coord_source'] == 'coord_from_file'</filter>
+        </collection>
+        <data name="simpleoutput" from_work_dir="final.tabular" format="tabular">
+            <filter>condi_source_coord['coord_source'] == 'coord_from_stdin'</filter>
+        </data>
+    </outputs>
+    <tests>
+        <test>
+            <param name="input" value="dataset-ibi-reanalysis-bio-005-003-monthly-regulargrid_1510914389133.nc"/>
+            <param name="var" value="phy"/>
+            <param name="var_tab" value="var_tab_dataset-ibi"/>
+            <conditional name="condi_source_coord">
+                <param name="coord_source" value="coord_from_stdin"/>
+                <conditional name="condi_coord">
+                    <param name="coord" value="single"/>
+                    <param name="lat_dim" value="latitude"/>
+                    <param name="lat_val" value="44.0"/>
+                    <param name="lon_dim" value="longitude"/>
+                    <param name="lon_val" value="-2.0"/>
+                </conditional>
+            </conditional>
+            <output name="simpleoutput" value="Test1.tabular">
+                <assert_contents>
+                    <has_text_matching expression="0\t2002-12-15\t0.5"/>
+                    <has_text_matching expression="144\t2014-12-15\t0.5"/>
+                </assert_contents>
+            </output>
+        </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="nh4"/>
+
+            <conditional name="condi_source_coord">
+                <param name="coord_source" value="coord_from_stdin"/>
+                <conditional name="condi_coord">
+                    <param name="coord" value="global"/>
+                </conditional>
+            </conditional>
+            <section name="time">
+                <conditional name="condi_datetime">
+                    <param name="datetime" value="yes"/>
+                    <conditional name="condi_between">
+                        <param name="comparator" value="sl"/>
+                        <param name="t1" value="2003-12-15" />
+                        <param name="t2" value="2004-12-15" />
+                    </conditional>
+                </conditional>
+            </section>
+            <repeat name="user_choice">
+                <param name="dim" value="nh4"/>
+                <conditional name="condi_between">
+                    <param name="comparator" value="ge"/>
+                    <param name="value" value="50."/>
+                </conditional>
+            </repeat>
+            <output name="simpleoutput" value="Test2.tabular">
+                <assert_contents>
+                    <has_text_matching expression="0\t2003-12-15\t0.5"/>
+                    <has_text_matching expression="23\t2004-12-15\t0.5"/>
+                </assert_contents>
+            </output>
+        </test>
+    </tests>
+    <help><![CDATA[
+**What it does**
+
+This tool extracts variable values with custom conditions on dimensions.
+
+It can use manualy given coordinates or automaticaly take them from a tabular file to filter informations.
+
+If no values are availables at a coordinate X, the tool will search the closest coordinate with a non NA value.
+
+Filter can be set on every dimension. Available filtering operations are : =, >, <, >=, <=, [interval], ]interval[.
+
+
+
+**Input**
+
+A netcdf file (.nc).
+
+Variable tabular file from 'Netcdf Metadate Info'.
+
+Tabular file with coordinates (only coordinates, no header!) and the following structure : 'lat'	'lon'.
+
+
+**Outputs**
+
+A single output with values for the wanted variable if there is only one coordinate.
+
+A data collection where one file is created for every coordinate, if multiple coordinates from tabular file.
+
+
+-------------------------------------------------
+
+The xarray select tool can be used after the xarray Info.
+    ]]>    </help>
+    <expand macro="citations"/>
+</tool>
--- a/xarray_tool.py	Sun Jun 06 08:51:41 2021 +0000
+++ b/xarray_tool.py	Thu Jan 20 17:07:19 2022 +0000
@@ -1,365 +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()
+# 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()