changeset 0:810820a0d45c draft default tip

planemo upload for repository https://github.com/galaxyecology/tools-ecology/tree/master/tools/data_manipulation/xarray/ commit fd8ad4d97db7b1fd3876ff63e14280474e06fdf7
author ecology
date Sun, 31 Jul 2022 21:23:21 +0000
parents
children
files macros.xml macros_mapplot.xml macros_netcdf2netcdf.xml macros_tests_netcdf2netcdf.xml macros_timeseries.xml test-data/Metadata_infos_from_dataset-ibi-reanalysis-bio-005-003-monthly-regulargrid_1510914389133.nc.Variables.tab test-data/Test1.tabular test-data/Test2.tabular 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.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/depth.tabular test-data/info_file.txt test-data/latitude.tabular test-data/longitude.tabular test-data/select_by_values.netcdf test-data/small.netcdf test-data/small_all_variables.netcdf test-data/time.tabular test-data/time_series.png test-data/time_series.tabular test-data/time_series_customized.png test-data/time_series_customized.tabular test-data/var_tab_dataset-ibi test-data/version.tabular test-data/where_condition.txt test-data/where_condition_simple.txt timeseries.py timeseries_plot.xml xarray_info.py xarray_mapplot.py xarray_netcdf2netcdf.py xarray_select.py
diffstat 42 files changed, 2869 insertions(+), 0 deletions(-) [+]
line wrap: on
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/macros.xml	Sun Jul 31 21:23:21 2022 +0000
@@ -0,0 +1,28 @@
+<macros>
+    <token name="@TOOL_VERSION@">2022.3.0</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	Sun Jul 31 21:23:21 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	Sun Jul 31 21:23:21 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	Sun Jul 31 21:23:21 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>
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/macros_timeseries.xml	Sun Jul 31 21:23:21 2022 +0000
@@ -0,0 +1,47 @@
+<macros>
+    <xml name="config_series">
+        <configfiles>
+            <configfile name="series_customization"><![CDATA[
+{
+#if $condi_datetime.datetime=="yes"
+#if str($condi_datetime.time_name).strip()
+"time_name":'$condi_datetime.time_name',
+#end if
+#if str($condi_datetime.time_start_value).strip()
+"time_start_value":"$condi_datetime.time_start_value",
+#end if
+#if str($condi_datetime.time_end_value).strip()
+"time_end_value":"$condi_datetime.time_end_value",
+#end if
+#end if
+#if str($lon_value).strip()
+"lon_value":'$lon_value',
+#end if
+#if str($lat_value).strip()
+"lat_value":'$lat_value',
+#end if
+#if $lon_name
+"lon_name":'$lon_name',
+#end if
+#if $lat_name
+"lat_name":'$lat_name',
+#end if
+#if str($adv.format_date).strip()
+"format_date":'$adv.format_date',
+#end if
+#if str($adv.plot_title).strip()
+"title":'$adv.plot_title',
+#end if
+#if str($adv.xlabel).strip()
+"xlabel":'$adv.xlabel',
+#end if
+#if str($adv.ylabel).strip()
+"ylabel":'$adv.ylabel',
+#end if
+}
+            ]]>
+            </configfile>
+        </configfiles>
+   
+    </xml>
+</macros>
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/Metadata_infos_from_dataset-ibi-reanalysis-bio-005-003-monthly-regulargrid_1510914389133.nc.Variables.tab	Sun Jul 31 21:23:21 2022 +0000
@@ -0,0 +1,8 @@
+VariableName	NumberOfDimensions	Dim0Name	Dim0Size	Dim1Name	Dim1Size	Dim2Name	Dim2Size	Dim3Name	Dim3Size
+phy	4	time	145	depth	1	latitude	97	longitude	103
+chl	4	time	145	depth	1	latitude	97	longitude	103
+nh4	4	time	145	depth	1	latitude	97	longitude	103
+time	1	time	145
+longitude	1	longitude	103
+latitude	1	latitude	97
+depth	1	depth	1
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/Test1.tabular	Sun Jul 31 21:23:21 2022 +0000
@@ -0,0 +1,146 @@
+	time	depth	longitude	latitude	phy
+0	2002-12-15	0.5057600140571594	-2.0000007	44.0	1.0500183
+1	2003-01-15	0.5057600140571594	-2.0000007	44.0	1.25
+2	2003-02-15	0.5057600140571594	-2.0000007	44.0	1.3000183
+3	2003-03-15	0.5057600140571594	-2.0000007	44.0	6.0599976
+4	2003-04-15	0.5057600140571594	-2.0000007	44.0	2.25
+5	2003-05-15	0.5057600140571594	-2.0000007	44.0	0.6499939
+6	2003-06-15	0.5057600140571594	-2.0000007	44.0	0.42999268
+7	2003-07-15	0.5057600140571594	-2.0000007	44.0	0.42999268
+8	2003-08-15	0.5057600140571594	-2.0000007	44.0	0.480011
+9	2003-09-15	0.5057600140571594	-2.0000007	44.0	0.45999146
+10	2003-10-15	0.5057600140571594	-2.0000007	44.0	0.5
+11	2003-11-15	0.5057600140571594	-2.0000007	44.0	0.9299927
+12	2003-12-15	0.5057600140571594	-2.0000007	44.0	1.3900146
+13	2004-01-15	0.5057600140571594	-2.0000007	44.0	1.7400208
+14	2004-02-15	0.5057600140571594	-2.0000007	44.0	4.5
+15	2004-03-15	0.5057600140571594	-2.0000007	44.0	5.5500183
+16	2004-04-15	0.5057600140571594	-2.0000007	44.0	5.3099976
+17	2004-05-15	0.5057600140571594	-2.0000007	44.0	3.75
+18	2004-06-15	0.5057600140571594	-2.0000007	44.0	0.77001953
+19	2004-07-15	0.5057600140571594	-2.0000007	44.0	0.5
+20	2004-08-15	0.5057600140571594	-2.0000007	44.0	0.45999146
+21	2004-09-15	0.5057600140571594	-2.0000007	44.0	0.4500122
+22	2004-10-15	0.5057600140571594	-2.0000007	44.0	0.480011
+23	2004-11-15	0.5057600140571594	-2.0000007	44.0	0.83999634
+24	2004-12-15	0.5057600140571594	-2.0000007	44.0	1.7400208
+25	2005-01-15	0.5057600140571594	-2.0000007	44.0	1.7700195
+26	2005-02-15	0.5057600140571594	-2.0000007	44.0	1.5500183
+27	2005-03-15	0.5057600140571594	-2.0000007	44.0	7.149994
+28	2005-04-15	0.5057600140571594	-2.0000007	44.0	3.649994
+29	2005-05-15	0.5057600140571594	-2.0000007	44.0	2.5200195
+30	2005-06-15	0.5057600140571594	-2.0000007	44.0	0.45999146
+31	2005-07-15	0.5057600140571594	-2.0000007	44.0	0.6700134
+32	2005-08-15	0.5057600140571594	-2.0000007	44.0	0.4500122
+33	2005-09-15	0.5057600140571594	-2.0000007	44.0	0.45999146
+34	2005-10-15	0.5057600140571594	-2.0000007	44.0	0.45999146
+35	2005-11-15	0.5057600140571594	-2.0000007	44.0	0.6199951
+36	2005-12-15	0.5057600140571594	-2.0000007	44.0	1.1499939
+37	2006-01-15	0.5057600140571594	-2.0000007	44.0	3.5299988
+38	2006-02-15	0.5057600140571594	-2.0000007	44.0	7.1799927
+39	2006-03-15	0.5057600140571594	-2.0000007	44.0	6.5599976
+40	2006-04-15	0.5057600140571594	-2.0000007	44.0	3.8000183
+41	2006-05-15	0.5057600140571594	-2.0000007	44.0	0.95999146
+42	2006-06-15	0.5057600140571594	-2.0000007	44.0	1.5
+43	2006-07-15	0.5057600140571594	-2.0000007	44.0	1.0299988
+44	2006-08-15	0.5057600140571594	-2.0000007	44.0	0.480011
+45	2006-09-15	0.5057600140571594	-2.0000007	44.0	0.49002075
+46	2006-10-15	0.5057600140571594	-2.0000007	44.0	0.480011
+47	2006-11-15	0.5057600140571594	-2.0000007	44.0	0.9299927
+48	2006-12-15	0.5057600140571594	-2.0000007	44.0	1.2099915
+49	2007-01-15	0.5057600140571594	-2.0000007	44.0	1.1499939
+50	2007-02-15	0.5057600140571594	-2.0000007	44.0	1.7000122
+51	2007-03-15	0.5057600140571594	-2.0000007	44.0	5.230011
+52	2007-04-15	0.5057600140571594	-2.0000007	44.0	3.8600159
+53	2007-05-15	0.5057600140571594	-2.0000007	44.0	0.83999634
+54	2007-06-15	0.5057600140571594	-2.0000007	44.0	0.6799927
+55	2007-07-15	0.5057600140571594	-2.0000007	44.0	0.45999146
+56	2007-08-15	0.5057600140571594	-2.0000007	44.0	0.45999146
+57	2007-09-15	0.5057600140571594	-2.0000007	44.0	0.5
+58	2007-10-15	0.5057600140571594	-2.0000007	44.0	0.89001465
+59	2007-11-15	0.5057600140571594	-2.0000007	44.0	2.0299988
+60	2007-12-15	0.5057600140571594	-2.0000007	44.0	1.8399963
+61	2008-01-15	0.5057600140571594	-2.0000007	44.0	1.3399963
+62	2008-02-15	0.5057600140571594	-2.0000007	44.0	3.149994
+63	2008-03-15	0.5057600140571594	-2.0000007	44.0	4.5899963
+64	2008-04-15	0.5057600140571594	-2.0000007	44.0	5.080017
+65	2008-05-15	0.5057600140571594	-2.0000007	44.0	1.0
+66	2008-06-15	0.5057600140571594	-2.0000007	44.0	1.5299988
+67	2008-07-15	0.5057600140571594	-2.0000007	44.0	0.55999756
+68	2008-08-15	0.5057600140571594	-2.0000007	44.0	0.42999268
+69	2008-09-15	0.5057600140571594	-2.0000007	44.0	0.42999268
+70	2008-10-15	0.5057600140571594	-2.0000007	44.0	0.42999268
+71	2008-11-15	0.5057600140571594	-2.0000007	44.0	0.64001465
+72	2008-12-15	0.5057600140571594	-2.0000007	44.0	2.4200134
+73	2009-01-15	0.5057600140571594	-2.0000007	44.0	2.3900146
+74	2009-02-15	0.5057600140571594	-2.0000007	44.0	6.2099915
+75	2009-03-15	0.5057600140571594	-2.0000007	44.0	4.6799927
+76	2009-04-15	0.5057600140571594	-2.0000007	44.0	1.1100159
+77	2009-05-15	0.5057600140571594	-2.0000007	44.0	2.649994
+78	2009-06-15	0.5057600140571594	-2.0000007	44.0	1.4900208
+79	2009-07-15	0.5057600140571594	-2.0000007	44.0	0.5
+80	2009-08-15	0.5057600140571594	-2.0000007	44.0	0.45999146
+81	2009-09-15	0.5057600140571594	-2.0000007	44.0	0.5800171
+82	2009-10-15	0.5057600140571594	-2.0000007	44.0	0.6499939
+83	2009-11-15	0.5057600140571594	-2.0000007	44.0	0.8999939
+84	2009-12-15	0.5057600140571594	-2.0000007	44.0	1.3099976
+85	2010-01-15	0.5057600140571594	-2.0000007	44.0	1.5299988
+86	2010-02-15	0.5057600140571594	-2.0000007	44.0	2.9599915
+87	2010-03-15	0.5057600140571594	-2.0000007	44.0	5.450012
+88	2010-04-15	0.5057600140571594	-2.0000007	44.0	7.5899963
+89	2010-05-15	0.5057600140571594	-2.0000007	44.0	1.8000183
+90	2010-06-15	0.5057600140571594	-2.0000007	44.0	0.480011
+91	2010-07-15	0.5057600140571594	-2.0000007	44.0	0.5
+92	2010-08-15	0.5057600140571594	-2.0000007	44.0	0.45999146
+93	2010-09-15	0.5057600140571594	-2.0000007	44.0	0.49002075
+94	2010-10-15	0.5057600140571594	-2.0000007	44.0	0.45999146
+95	2010-11-15	0.5057600140571594	-2.0000007	44.0	0.9299927
+96	2010-12-15	0.5057600140571594	-2.0000007	44.0	1.1499939
+97	2011-01-15	0.5057600140571594	-2.0000007	44.0	2.4900208
+98	2011-02-15	0.5057600140571594	-2.0000007	44.0	5.1799927
+99	2011-03-15	0.5057600140571594	-2.0000007	44.0	7.029999
+100	2011-04-15	0.5057600140571594	-2.0000007	44.0	2.4900208
+101	2011-05-15	0.5057600140571594	-2.0000007	44.0	0.6499939
+102	2011-06-15	0.5057600140571594	-2.0000007	44.0	0.52001953
+103	2011-07-15	0.5057600140571594	-2.0000007	44.0	0.5
+104	2011-08-15	0.5057600140571594	-2.0000007	44.0	0.75
+105	2011-09-15	0.5057600140571594	-2.0000007	44.0	0.45999146
+106	2011-10-15	0.5057600140571594	-2.0000007	44.0	0.480011
+107	2011-11-15	0.5057600140571594	-2.0000007	44.0	0.730011
+108	2011-12-15	0.5057600140571594	-2.0000007	44.0	1.0299988
+109	2012-01-15	0.5057600140571594	-2.0000007	44.0	3.149994
+110	2012-02-15	0.5057600140571594	-2.0000007	44.0	2.3099976
+111	2012-03-15	0.5057600140571594	-2.0000007	44.0	5.5200195
+112	2012-04-15	0.5057600140571594	-2.0000007	44.0	3.399994
+113	2012-05-15	0.5057600140571594	-2.0000007	44.0	3.7000122
+114	2012-06-15	0.5057600140571594	-2.0000007	44.0	2.5899963
+115	2012-07-15	0.5057600140571594	-2.0000007	44.0	0.45999146
+116	2012-08-15	0.5057600140571594	-2.0000007	44.0	0.4500122
+117	2012-09-15	0.5057600140571594	-2.0000007	44.0	0.45999146
+118	2012-10-15	0.5057600140571594	-2.0000007	44.0	0.61001587
+119	2012-11-15	0.5057600140571594	-2.0000007	44.0	2.0299988
+120	2012-12-15	0.5057600140571594	-2.0000007	44.0	1.4200134
+121	2013-01-15	0.5057600140571594	-2.0000007	44.0	2.2700195
+122	2013-02-15	0.5057600140571594	-2.0000007	44.0	7.0
+123	2013-03-15	0.5057600140571594	-2.0000007	44.0	10.550018
+124	2013-04-15	0.5057600140571594	-2.0000007	44.0	5.8399963
+125	2013-05-15	0.5057600140571594	-2.0000007	44.0	1.2400208
+126	2013-06-15	0.5057600140571594	-2.0000007	44.0	4.1700134
+127	2013-07-15	0.5057600140571594	-2.0000007	44.0	3.2099915
+128	2013-08-15	0.5057600140571594	-2.0000007	44.0	0.45999146
+129	2013-09-15	0.5057600140571594	-2.0000007	44.0	0.480011
+130	2013-10-15	0.5057600140571594	-2.0000007	44.0	0.49002075
+131	2013-11-15	0.5057600140571594	-2.0000007	44.0	0.7799988
+132	2013-12-15	0.5057600140571594	-2.0000007	44.0	1.4500122
+133	2014-01-15	0.5057600140571594	-2.0000007	44.0	0.95999146
+134	2014-02-15	0.5057600140571594	-2.0000007	44.0	1.3900146
+135	2014-03-15	0.5057600140571594	-2.0000007	44.0	5.779999
+136	2014-04-15	0.5057600140571594	-2.0000007	44.0	5.4299927
+137	2014-05-15	0.5057600140571594	-2.0000007	44.0	1.1799927
+138	2014-06-15	0.5057600140571594	-2.0000007	44.0	0.730011
+139	2014-07-15	0.5057600140571594	-2.0000007	44.0	0.45999146
+140	2014-08-15	0.5057600140571594	-2.0000007	44.0	0.45999146
+141	2014-09-15	0.5057600140571594	-2.0000007	44.0	0.5
+142	2014-10-15	0.5057600140571594	-2.0000007	44.0	0.6199951
+143	2014-11-15	0.5057600140571594	-2.0000007	44.0	0.480011
+144	2014-12-15	0.5057600140571594	-2.0000007	44.0	0.55999756
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/Test2.tabular	Sun Jul 31 21:23:21 2022 +0000
@@ -0,0 +1,25 @@
+	time	depth	latitude	longitude	nh4
+0	2003-12-15	0.5057600140571594	45.166664123535156	-0.6666674017906189	81.27
+1	2003-12-15	0.5057600140571594	45.416664123535156	-0.8333340883255005	78.08
+2	2003-12-15	0.5057600140571594	45.5	-0.9166674017906189	55.149998
+3	2004-01-15	0.5057600140571594	45.166664123535156	-0.6666674017906189	65.2
+4	2004-01-15	0.5057600140571594	45.416664123535156	-0.8333340883255005	64.11
+5	2004-02-15	0.5057600140571594	45.166664123535156	-0.6666674017906189	51.0
+6	2004-02-15	0.5057600140571594	45.416664123535156	-0.8333340883255005	51.32
+7	2004-05-15	0.5057600140571594	45.166664123535156	-0.6666674017906189	54.53
+8	2004-06-15	0.5057600140571594	45.166664123535156	-0.6666674017906189	79.79
+9	2004-06-15	0.5057600140571594	45.416664123535156	-0.8333340883255005	61.52
+10	2004-07-15	0.5057600140571594	45.166664123535156	-0.6666674017906189	99.159996
+11	2004-07-15	0.5057600140571594	45.416664123535156	-0.8333340883255005	77.93
+12	2004-08-15	0.5057600140571594	45.166664123535156	-0.6666674017906189	110.149994
+13	2004-08-15	0.5057600140571594	45.416664123535156	-0.8333340883255005	86.759995
+14	2004-09-15	0.5057600140571594	45.166664123535156	-0.6666674017906189	112.369995
+15	2004-09-15	0.5057600140571594	45.416664123535156	-0.8333340883255005	91.979996
+16	2004-10-15	0.5057600140571594	45.166664123535156	-0.6666674017906189	109.63
+17	2004-10-15	0.5057600140571594	45.416664123535156	-0.8333340883255005	95.509995
+18	2004-11-15	0.5057600140571594	45.166664123535156	-0.6666674017906189	98.45
+19	2004-11-15	0.5057600140571594	45.416664123535156	-0.8333340883255005	93.11
+20	2004-11-15	0.5057600140571594	45.5	-0.9166674017906189	56.78
+21	2004-12-15	0.5057600140571594	45.166664123535156	-0.6666674017906189	84.25
+22	2004-12-15	0.5057600140571594	45.416664123535156	-0.8333340883255005	81.83
+23	2004-12-15	0.5057600140571594	45.5	-0.9166674017906189	57.07
Binary file test-data/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.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
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/depth.tabular	Sun Jul 31 21:23:21 2022 +0000
@@ -0,0 +1,1 @@
+0	0.50576
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/info_file.txt	Sun Jul 31 21:23:21 2022 +0000
@@ -0,0 +1,74 @@
+xarray.Dataset {
+dimensions:
+	time = 145 ;
+	depth = 1 ;
+	latitude = 97 ;
+	longitude = 103 ;
+
+variables:
+	float32 phy(time, depth, latitude, longitude) ;
+		phy:_CoordinateAxes = time depth latitude longitude  ;
+		phy:long_name = Mole Concentration of Phytoplankton expressed as carbon in sea water ;
+		phy:standard_name = mole_concentration_of_phytoplankton_expressed_as_carbon_in_sea_water ;
+		phy:units = mmol.m-3 ;
+		phy:unit_long = mole_concentration_of_phytoplankton_expressed_as_carbon_in_sea_water ;
+	datetime64[ns] time(time) ;
+		time:standard_name = time ;
+		time:long_name = time ;
+		time:_CoordinateAxisType = Time ;
+		time:axis = T ;
+	float32 chl(time, depth, latitude, longitude) ;
+		chl:_CoordinateAxes = time depth latitude longitude  ;
+		chl:long_name = Mass Concentration of Chlorophyll in Sea Water ;
+		chl:standard_name = mass_concentration_of_chlorophyll_in_sea_water ;
+		chl:units = mg.m-3 ;
+		chl:unit_long = milligram of chlorophyll per cubic meter ;
+	float32 nh4(time, depth, latitude, longitude) ;
+		nh4:_CoordinateAxes = time depth latitude longitude  ;
+		nh4:long_name = Mole Concentration of Ammonium in Sea Water ;
+		nh4:standard_name = mole_concentration_of_ammonium_in_sea_water ;
+		nh4:units = mmol.m-3 ;
+		nh4:unit_long = millimoles of Ammonium per cubic meter ;
+	float32 longitude(longitude) ;
+		longitude:long_name = Longitude ;
+		longitude:units = degrees_east ;
+		longitude:standard_name = longitude ;
+		longitude:axis = X ;
+		longitude:unit_long = Degrees East ;
+		longitude:step = 0.08333f ;
+		longitude:_CoordinateAxisType = Lon ;
+	float32 latitude(latitude) ;
+		latitude:long_name = Latitude ;
+		latitude:units = degrees_north ;
+		latitude:standard_name = latitude ;
+		latitude:axis = Y ;
+		latitude:unit_long = Degrees North ;
+		latitude:step = 0.08333f ;
+		latitude:_CoordinateAxisType = Lat ;
+	float32 depth(depth) ;
+		depth:long_name = Depth ;
+		depth:units = m ;
+		depth:axis = Z ;
+		depth:positive = down ;
+		depth:unit_long = Meters ;
+		depth:standard_name = depth ;
+		depth:_CoordinateAxisType = Height ;
+		depth:_CoordinateZisPositive = down ;
+
+// global attributes:
+	:title = CMEMS IBI REANALYSIS: MONTHLY BIOGEOCHEMICAL PRODUCTS (REGULAR GRID)  ;
+	:institution = Puertos del Estado (PdE) - Mercator-Ocean (MO)  ;
+	:references = http://marine.copernicus.eu ;
+	:source = CMEMS IBI-MFC ;
+	:Conventions = CF-1.0 ;
+	:history = Data extracted from dataset http://puertos2.cesga.es:8080/thredds/dodsC/dataset-ibi-reanalysis-bio-005-003-monthly-regulargrid ;
+	:time_min = 7272.0 ;
+	:time_max = 112464.0 ;
+	:julian_day_unit = Hours since 2002-02-15 ;
+	:z_min = 0.5057600140571594 ;
+	:z_max = 0.5057600140571594 ;
+	:latitude_min = 43.0 ;
+	:latitude_max = 51.0 ;
+	:longitude_min = -6.000000476837158 ;
+	:longitude_max = 2.4999990463256836 ;
+}
\ No newline at end of file
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/latitude.tabular	Sun Jul 31 21:23:21 2022 +0000
@@ -0,0 +1,97 @@
+0	43.0
+1	43.083332
+2	43.166664
+3	43.25
+4	43.333332
+5	43.416664
+6	43.5
+7	43.583332
+8	43.666664
+9	43.75
+10	43.833332
+11	43.916664
+12	44.0
+13	44.083332
+14	44.166664
+15	44.25
+16	44.333332
+17	44.416664
+18	44.5
+19	44.583332
+20	44.666664
+21	44.75
+22	44.833332
+23	44.916664
+24	45.0
+25	45.083332
+26	45.166664
+27	45.25
+28	45.333332
+29	45.416664
+30	45.5
+31	45.583332
+32	45.666664
+33	45.75
+34	45.833332
+35	45.916664
+36	46.0
+37	46.083332
+38	46.166664
+39	46.25
+40	46.333332
+41	46.416664
+42	46.5
+43	46.583332
+44	46.666664
+45	46.75
+46	46.833332
+47	46.916664
+48	47.0
+49	47.083332
+50	47.166664
+51	47.25
+52	47.333332
+53	47.416664
+54	47.5
+55	47.583332
+56	47.666664
+57	47.75
+58	47.833332
+59	47.916664
+60	48.0
+61	48.083332
+62	48.166664
+63	48.25
+64	48.333332
+65	48.416664
+66	48.5
+67	48.583332
+68	48.666664
+69	48.75
+70	48.833332
+71	48.916664
+72	49.0
+73	49.083332
+74	49.166664
+75	49.25
+76	49.333332
+77	49.416664
+78	49.5
+79	49.583332
+80	49.666664
+81	49.75
+82	49.833332
+83	49.916664
+84	50.0
+85	50.083332
+86	50.166664
+87	50.25
+88	50.333332
+89	50.416664
+90	50.5
+91	50.583332
+92	50.666664
+93	50.75
+94	50.833332
+95	50.916664
+96	51.0
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/longitude.tabular	Sun Jul 31 21:23:21 2022 +0000
@@ -0,0 +1,103 @@
+0	-6.0000005
+1	-5.916667
+2	-5.833334
+3	-5.7500005
+4	-5.666667
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+6	-5.5000005
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+22	-4.1666675
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+24	-4.0000005
+25	-3.9166672
+26	-3.833334
+27	-3.7500007
+28	-3.6666672
+29	-3.583334
+30	-3.5000007
+31	-3.4166672
+32	-3.333334
+33	-3.2500007
+34	-3.1666672
+35	-3.083334
+36	-3.0000007
+37	-2.9166672
+38	-2.833334
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+40	-2.6666672
+41	-2.583334
+42	-2.5000007
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+47	-2.083334
+48	-2.0000007
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+51	-1.7500007
+52	-1.6666673
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+54	-1.5000007
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+64	-0.6666674
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+66	-0.5000007
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+69	-0.25000075
+70	-0.16666742
+71	-0.08333409
+72	-7.6e-07
+73	0.08333257
+74	0.1666659
+75	0.24999923
+76	0.33333257
+77	0.41666588
+78	0.49999923
+79	0.58333254
+80	0.66666585
+81	0.7499992
+82	0.83333254
+83	0.91666585
+84	0.9999992
+85	1.0833325
+86	1.1666659
+87	1.2499992
+88	1.3333325
+89	1.4166658
+90	1.4999992
+91	1.5833325
+92	1.6666658
+93	1.7499992
+94	1.8333325
+95	1.9166658
+96	1.9999992
+97	2.0833325
+98	2.1666658
+99	2.249999
+100	2.3333325
+101	2.4166658
+102	2.499999
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
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/time.tabular	Sun Jul 31 21:23:21 2022 +0000
@@ -0,0 +1,145 @@
+0	2002-12-15
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+142	2014-10-15
+143	2014-11-15
+144	2014-12-15
Binary file test-data/time_series.png has changed
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/time_series.tabular	Sun Jul 31 21:23:21 2022 +0000
@@ -0,0 +1,38 @@
+time	longitude	latitude	depth	chl
+2010-12-15 00:00:00	-6.0000005	44.75	0.50576	0.31
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+2011-04-15 00:00:00	-6.0000005	44.75	0.50576	1.8399999
+2011-05-15 00:00:00	-6.0000005	44.75	0.50576	0.099999994
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+2012-03-15 00:00:00	-6.0000005	44.75	0.50576	1.5799999
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+2013-03-15 00:00:00	-6.0000005	44.75	0.50576	1.15
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+2013-09-15 00:00:00	-6.0000005	44.75	0.50576	0.01
+2013-10-15 00:00:00	-6.0000005	44.75	0.50576	0.01
+2013-11-15 00:00:00	-6.0000005	44.75	0.50576	0.12
+2013-12-15 00:00:00	-6.0000005	44.75	0.50576	0.34
Binary file test-data/time_series_customized.png has changed
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/time_series_customized.tabular	Sun Jul 31 21:23:21 2022 +0000
@@ -0,0 +1,146 @@
+time	longitude	latitude	depth	chl
+2002-12-15 00:00:00	-5.0000005	43.5	0.50576	0.34
+2003-01-15 00:00:00	-5.0000005	43.5	0.50576	0.41
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+2013-07-15 00:00:00	-5.0000005	43.5	0.50576	0.48
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+2013-12-15 00:00:00	-5.0000005	43.5	0.50576	0.59
+2014-01-15 00:00:00	-5.0000005	43.5	0.50576	0.56
+2014-02-15 00:00:00	-5.0000005	43.5	0.50576	0.90999997
+2014-03-15 00:00:00	-5.0000005	43.5	0.50576	1.3299999
+2014-04-15 00:00:00	-5.0000005	43.5	0.50576	1.09
+2014-05-15 00:00:00	-5.0000005	43.5	0.50576	0.37
+2014-06-15 00:00:00	-5.0000005	43.5	0.50576	0.11
+2014-07-15 00:00:00	-5.0000005	43.5	0.50576	0.02
+2014-08-15 00:00:00	-5.0000005	43.5	0.50576	0.02
+2014-09-15 00:00:00	-5.0000005	43.5	0.50576	0.11
+2014-10-15 00:00:00	-5.0000005	43.5	0.50576	0.02
+2014-11-15 00:00:00	-5.0000005	43.5	0.50576	0.07
+2014-12-15 00:00:00	-5.0000005	43.5	0.50576	0.17
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/var_tab_dataset-ibi	Sun Jul 31 21:23:21 2022 +0000
@@ -0,0 +1,7 @@
+time	1	time	145	 	 	 	 	 	 
+chl	4	time	145	depth	1	latitude	97	longitude	103
+nh4	4	time	145	depth	1	latitude	97	longitude	103
+longitude	1	longitude	103	 	 	 	 	 	 
+latitude	1	latitude	97	 	 	 	 	 	 
+depth	1	depth	1	 	 	 	 	 	 
+phy	4	time	145	depth	1	latitude	97	longitude	103
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/version.tabular	Sun Jul 31 21:23:21 2022 +0000
@@ -0,0 +1,1 @@
+Galaxy xarray version 2022.3.0
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/where_condition.txt	Sun Jul 31 21:23:21 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	Sun Jul 31 21:23:21 2022 +0000
@@ -0,0 +1,1 @@
+nh4 > 5.15
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/timeseries.py	Sun Jul 31 21:23:21 2022 +0000
@@ -0,0 +1,182 @@
+#!/usr/bin/env python3
+#
+#
+# usage:  netCDF_timeseries.py [-h] [--output output.png]
+#                               [--save timeseries.tabular]
+#                               [--config config-file]
+#                               [-v]
+#                               input varname
+# positional arguments:
+#  input            input filename with geographical coordinates (netCDF
+#                   format)
+#  varname          Specify which variable to extract (case sensitive)
+#
+# optional arguments:
+#  -h, --help                 show this help message and exit
+#  --output output.png        filename to store image (png format)
+#  --save timeseries.tabular  filename to store timeseries (tabular format)
+#  --config                   config file extract parameters
+#  -v, --verbose              switch on verbose mode
+#
+import argparse
+import ast
+import warnings
+
+import cftime  # noqa: F401
+
+import matplotlib as mpl
+mpl.use('Agg')
+
+import matplotlib.pyplot as plt   # noqa: I202,E402
+from matplotlib.dates import DateFormatter   # noqa: I202,E402
+
+import xarray as xr  # noqa: I202,E402
+
+
+class TimeSeries ():
+    def __init__(self, input, varname, output, save, verbose=False,
+                 config_file=""):
+
+        li = list(input.split(","))
+        if len(li) > 1:
+            self.input = li
+        else:
+            self.input = input
+
+        self.varname = varname
+        self.xylim_supported = True
+        if output == "" or output is None:
+            self.output = "Timeseries.png"
+        else:
+            self.output = output
+        if save == "" or save is None:
+            self.save = "Timeseries.tabular"
+        else:
+            self.save = save
+        self.verbose = verbose
+        self.time_start_value = ""
+        self.time_end_value = ""
+        self.lon_value = ""
+        self.lat_value = ""
+        self.lat_name = 'lat'
+        self.lon_name = 'lon'
+        self.time_name = 'time'
+        self.title = ''
+        self.xlabel = ''
+        self.ylabel = ''
+        self.format_date = ''
+        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_start_value':
+                        self.time_start_value = tmp[key]
+                    if key == 'time_end_value':
+                        self.time_end_value = tmp[key]
+                    if key == 'lon_value':
+                        self.lon_value = tmp[key]
+                    if key == 'lat_value':
+                        self.lat_value = tmp[key]
+                    if key == 'lon_name':
+                        self.lon_name = tmp[key]
+                    if key == 'lat_name':
+                        self.lat_name = tmp[key]
+                    if key == 'time_name':
+                        self.time_name = tmp[key]
+                    if key == 'title':
+                        self.title = tmp[key]
+                    if key == 'xlabel':
+                        self.xlabel = tmp[key]
+                    if key == 'ylabel':
+                        self.ylabel = tmp[key]
+                    if key == 'format_date':
+                        self.format_date = tmp[key]
+                        self.format_date = self.format_date.replace('X', '%')
+
+        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("varname: ", self.varname)
+            if self.time_start_value:
+                print("time_start_value: ", self.time_start_value)
+            if self.time_end_value:
+                print("time_end_value: ", self.time_end_value)
+            print("output: ", self.output)
+            if self.lon_value:
+                print(self.lon_name, self.lon_value)
+            if self.lat_value:
+                print(self.lat_name, self.lat_value)
+
+    def plot(self):
+        if self.lon_value:
+            lon_c = float(self.lon_value)
+        if self.lat_value:
+            lat_c = float(self.lat_value)
+        if self.lat_value and self.lon_value:
+            self.df = self.dset.sel({self.lat_name: lat_c,
+                                     self.lon_name: lon_c},
+                                    method='nearest')
+        else:
+            self.df = self.dset
+        if self.time_start_value or self.time_end_value:
+            self.df = self.df.sel({self.time_name: slice(self.time_start_value,
+                                                         self.time_end_value)})
+        # Saving the time series into a tabular
+        self.df = self.df[self.varname].squeeze().to_dataframe()
+        self.df.dropna().to_csv(self.save, sep='\t')
+        # Plot the time series into png image
+        fig = plt.figure(figsize=(15, 5))
+        ax = plt.subplot(111)
+        self.df[self.varname].plot(ax=ax)
+        if self.title:
+            plt.title(self.title)
+        if self.xlabel:
+            plt.xlabel(self.xlabel)
+        if self.ylabel:
+            plt.ylabel(self.ylabel)
+        if self.format_date:
+            ax.xaxis.set_major_formatter(DateFormatter(self.format_date))
+        fig.tight_layout()
+        fig.savefig(self.output)
+
+
+if __name__ == '__main__':
+    warnings.filterwarnings("ignore")
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        'input',
+        help='input filename with geographical coordinates (netCDF format)'
+    )
+    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(
+        '--save',
+        help='save resulting tabular file (tabular format) into filename'
+    )
+    parser.add_argument(
+        '--config',
+        help='pass timeseries parameters via a config file'
+    )
+    parser.add_argument(
+        "-v", "--verbose",
+        help="switch on verbose mode",
+        action="store_true")
+    args = parser.parse_args()
+
+    dset = TimeSeries(input=args.input, varname=args.varname,
+                      output=args.output, save=args.save, verbose=args.verbose,
+                      config_file=args.config)
+    dset.plot()
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/timeseries_plot.xml	Sun Jul 31 21:23:21 2022 +0000
@@ -0,0 +1,120 @@
+<tool id="timeseries_extraction" name="NetCDF timeseries Extractor" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" python_template_version="3.5" profile="@PROFILE@">
+    <description>Extract and plot time series</description>
+    <macros>
+        <import>macros.xml</import>
+        <import>macros_timeseries.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="1.6.0">netcdf4</requirement>
+        <requirement type="package" version="3.5.2">matplotlib</requirement>
+        <requirement type="package" version="2022.7.0">dask</requirement>
+        <requirement type="package" version="1.4.3">pandas</requirement>
+        <requirement type="package" version="1.6.1">cftime</requirement>
+    </requirements>
+    <command detect_errors="exit_code"><![CDATA[
+    mkdir output_dir &&
+    mkdir -p `pwd`/mlp_tmpdir &&
+    MPLCONFIGDIR=`pwd`/mlp_tmpdir &&
+    python '$__tool_directory__/timeseries.py' '$input' '$var'
+    --config '$series_customization' 
+         --output timeseries.png
+	 --save $timeseries_tabular
+         --verbose &&
+    mv timeseries.png $timeseries_plot
+    ]]></command>
+    <expand macro="config_series"/>
+    <inputs>
+        <param type="data" name="input" label="Input netcdf file" format="netcdf"  help="Select the input netCDF file."/>
+        <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 plot">
+            <options from_dataset="var_tab">
+                <column name="name" index="0"/>
+                <column name="value" index="0"/>
+            </options>
+        </param>
+        <conditional name="condi_datetime">
+            <param name="datetime" type="select" label="Datetime selection" help="Use this option to set the start and end values for plotting.">
+                <option value="no">No</option>
+                <option value="yes">Yes</option>
+            </param>
+            <when value="no"></when>
+            <when value="yes">
+                <param name="time_name" type="select" label="Choose the name for date and time values">
+                    <options from_dataset="var_tab">
+                        <column name="name" index="0"/>
+                        <column name="value" index="0"/>
+                    </options>
+                </param>
+		<param name="time_start_value" type="text" value="" label="Choose the beginning date/time to plot (YYY-MM-DD)"/>
+		<param name="time_end_value" type="text" value="" label="Choose the ending date/time to plot (YYYY-MM-DD)"/>
+            </when>
+        </conditional>
+        <param name="lat_value" type="float" optional="true" label="latitude value for limited geographical area" />
+        <param name="lat_name" type="select" label="Choose the name for latitudes" optional="true">
+            <options from_dataset="var_tab">
+                <column name="name" index="0"/>
+                <column name="value" index="0"/>
+            </options>
+        </param>
+        <param name="lon_value" type="float" optional="true" label="longitude value for limited geographical area " />
+        <param name="lon_name" type="select" label="Choose the name for longitudes" optional="true">
+            <options from_dataset="var_tab">
+                <column name="name" index="0"/>
+                <column name="value" index="0"/>
+            </options>
+        </param>
+        <section name="adv" title="Advanced Plotting Options" expanded="false">
+            <param name="plot_title" type="text" value="" label="Plot title" />
+            <param name="xlabel" type="text" value="" label="Label for x-axis" />
+            <param name="ylabel" type="text" value="" label="Label for y-axis" />
+            <param name="format_date" type="text" value="" label="format date/time for plotting" />
+        </section>
+    </inputs>
+    <outputs>
+        <data name="timeseries_tabular" format="tabular" label="Timeseries table"/>
+        <data name="timeseries_plot" format="png" label="Timeseries plot"/>
+    </outputs>
+    <tests>
+        <test>
+            <param name="input" value="dataset-ibi-reanalysis-bio-005-003-monthly-regulargrid_1510914389133.nc"/>
+            <param name="var" value="chl"/>
+            <param name="var_tab" value="var_tab_dataset-ibi"/>
+            <param name="lon_value" value="-5.0"/>
+            <param name="lat_value" value="43.50"/>
+            <param name="lon_name" value="longitude"/>
+            <param name="lat_name" value="latitude"/>
+            <conditional name="condi_datetime">
+                <param name="datetime" value="no"/>
+            </conditional>                    
+            <section name="adv">
+                <param name="plot_title" value="Timeseries of Chlorophyll concentration"/>
+                <param name="format_date" value="%Y"/>
+                <param name="xlabel" value="Year"/>
+                <param name="ylabel" value="Chl"/>
+            </section>
+            <output name="timeseries_tabular" ftype="tabular" file="time_series_customized.tabular"/>
+            <output name="timeseries_plot" ftype="png" file="time_series_customized.png"/>
+        </test>
+        <test>
+            <param name="input" value="dataset-ibi-reanalysis-bio-005-003-monthly-regulargrid_1510914389133.nc"/>
+            <param name="var" value="chl"/>
+            <param name="var_tab" value="var_tab_dataset-ibi"/>
+            <param name="lon_value" value="-7.0"/>
+            <param name="lat_value" value="44.75"/>
+            <param name="lon_name" value="longitude"/>
+            <param name="lat_name" value="latitude"/>
+            <conditional name="condi_datetime">
+                <param name="datetime" value="yes"/>
+                <param name="time_start_value" value="2010-12-15"/>
+                <param name="time_end_value" value="2013-12-31"/>
+            </conditional>                    
+            <output name="timeseries_tabular" ftype="tabular" file="time_series.tabular"/>
+            <output name="timeseries_plot" ftype="png" file="time_series.png"/>
+        </test>
+    </tests>
+    <help><![CDATA[ Extracts time series for a given variable in a .csv format file. This file can be used to plot the timeseries easily. ]]></help> 
+    <expand macro="citations"/>
+</tool> 
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/xarray_info.py	Sun Jul 31 21:23:21 2022 +0000
@@ -0,0 +1,107 @@
+# 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 xarray as xr
+
+
+class XarrayInfo ():
+    def __init__(self, infile, outfile_info="", outfile_summary="",
+                 verbose=False, coords_info=None):
+        self.infile = infile
+        self.outfile_info = outfile_info
+        self.outfile_summary = outfile_summary
+        self.coords_info = coords_info
+        self.verbose = verbose
+        # initialization
+        self.dset = None
+        self.gset = None
+        if self.verbose:
+            print("infile: ", self.infile)
+            print("outfile_info: ", self.outfile_info)
+            print("outfile_summary: ", self.outfile_summary)
+            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 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(
+        '--coords_info',
+        help='output-folder where for each coordinate, coordinate values '
+             ' are being printed in the corresponding outputfile'
+    )
+    parser.add_argument(
+        "-v", "--verbose",
+        help="switch on verbose mode",
+        action="store_true"
+    )
+    args = parser.parse_args()
+
+    p = XarrayInfo(args.infile, args.info, args.summary,
+                   args.verbose, args.coords_info)
+    if args.info:
+        p.info()
+    elif args.coords_info:
+        p.get_coords_info()
+    if args.summary:
+        p.summary()
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/xarray_mapplot.py	Sun Jul 31 21:23:21 2022 +0000
@@ -0,0 +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]
+#                               [--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
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/xarray_netcdf2netcdf.py	Sun Jul 31 21:23:21 2022 +0000
@@ -0,0 +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 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()
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/xarray_select.py	Sun Jul 31 21:23:21 2022 +0000
@@ -0,0 +1,294 @@
+# xarray tool for:
+# - getting metadata information
+# - select data and save results in csv file for further post-processing
+
+import argparse
+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 XarraySelect ():
+    def __init__(self, infile, select="", outfile="", outputdir="",
+                 latname="", latvalN="", latvalS="", lonname="",
+                 lonvalE="", lonvalW="", filter_list="", coords="",
+                 time="", verbose=False, no_missing=False,
+                 tolerance=None):
+        self.infile = infile
+        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
+        if self.verbose:
+            print("infile: ", self.infile)
+            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)
+
+    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()
+
+
+if __name__ == '__main__':
+    warnings.filterwarnings("ignore")
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument(
+        'infile',
+        help='netCDF input filename'
+    )
+    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(
+        '--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 = XarraySelect(args.infile, 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.tolerance)
+    if args.select:
+        p.selection()