From 56f91c0e224961d095972ea45a30028fc39e7b6c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Marie=20Joss=C3=A9?= <84919248+Marie59@users.noreply.github.com> Date: Mon, 15 Jul 2024 11:52:36 +0200 Subject: [PATCH 01/55] add batch tool diva --- tools/ocean/divandfull.jl | 260 +++++++++++++++++++++++++++++++++++++ tools/ocean/divandfull.xml | 109 ++++++++++++++++ 2 files changed, 369 insertions(+) create mode 100644 tools/ocean/divandfull.jl create mode 100644 tools/ocean/divandfull.xml diff --git a/tools/ocean/divandfull.jl b/tools/ocean/divandfull.jl new file mode 100644 index 000000000..a2aaeb421 --- /dev/null +++ b/tools/ocean/divandfull.jl @@ -0,0 +1,260 @@ +#Julia script + +############################### +## DIVAndrun analsysis ## +############################### +import Pkg; +#Pkg.add("julia") +using Pkg +Pkg.status() + +### Import packages +# using NCDatasets +# using PhysOcean +# using DataStructures +using DIVAnd +using Dates +# using Statistics +# using Random + +using Printf +# Pkg.add("PyCall") +# using PyCall +# PyCall.pyimport("matplotlib.pyplot") +### Import data +# Récupération des arguments de la ligne de commande +args = ARGS + +# Importation des données +if length(args) < 4 + error("This tool needs at least 4 arguments") +else + netcdf_data = args[1] + longmin = parse(Float64, args[2]) + longmax = parse(Float64, args[3]) + latmin = parse(Float64, args[4]) + latmax = parse(Float64, args[5]) + startdate = args[6] # yyyy,mm,dd + enddate = args[7] + varname = args[8] + selmin = parse(Int, args[9]) + selmax = parse(Int, args[10]) +end + +## This script will create a climatology: +# 1. ODV data reading. +# 2. Extraction of bathymetry and creation of mask +# 3. Data download from other sources and duplicate removal. +# 4. Quality control. +# 5. Parameter optimisation. +# 6. Spatio-temporal interpolation with DIVAnd. + + +### Configuration +# Define the horizontal, vertical (depth levels) and temporal resolutions. +# Select the variable of interest + +dx, dy = 0.125, 0.125 +lonr = longmin:dx:longmax +latr = latmin:dy:latmax + +# Extracting year, month, and day +startyear = startdate[1:4] # extract first four characters (year) +startmonth = startdate[5:6] # extract characters 5 and 6 (month) +startday = startdate[7:8] # extract last two characters (day) +# Converting to integers +startyear = parse(Int, startyear) +startmonth = parse(Int, startmonth) +startday = parse(Int, startday) + +endyear = enddate[1:4] # extract first four characters (year) +endmonth = enddate[5:6] # extract characters 5 and 6 (month) +endday = enddate[7:8] # extract last two characters (day) +endyear = parse(Int, endyear) +endmonth = parse(Int, endmonth) +endday = parse(Int, endday) + +timerange = [Date(startyear, startmonth, startday),Date(endyear, endmonth, endday)]; + +depthr = [0.,5., 10., 15., 20., 25., 30., 40., 50., 66, + 75, 85, 100, 112, 125, 135, 150, 175, 200, 225, 250, + 275, 300, 350, 400, 450, 500, 550, 600, 650, 700, 750, + 800, 850, 900, 950, 1000, 1050, 1100, 1150, 1200, 1250, + 1300, 1350, 1400, 1450, 1500, 1600, 1750, 1850, 2000]; +depthr = [0.,10.,20.]; + +varname = varname +yearlist = [1900:2023]; +monthlist = [[1,2,3],[4,5,6],[7,8,9],[10,11,12]]; + +# We create here the variable TS (for "tDataset(netcdf_data,"r")ime selector"), which allows us to work with the observations corresponding to each period of interest. + +TS = DIVAnd.TimeSelectorYearListMonthList(yearlist,monthlist); +@show TS; + +figdir = "outputs/" +if ~(isdir(figdir)) + mkdir(figdir) +else + @info("Figure directory already exists") +end +### 1. Read your ODV file +# Adapt the datadir and datafile values. +# The example is based on a sub-setting of the Mediterranean Sea aggregated dataset. +# The dataset has been extracted around the Adriatic Sea and exported to a netCDF using Ocean Data +datadir = "../data" + +datafile = netcdf_data + +# Then you can read the full file: +@time obsval,obslon,obslat,obsdepth,obstime,obsid = NCODV.load(Float64, datafile, + "Water body $(varname)"); + +#figure("Data") +#ax = subplot(1,1,1) +#plot(obslon, obslat, "ko", markersize=.1, markerfacecolor="k") +#aspectratio = 1/cos(mean(latr) * pi/180) +#ax.tick_params("both",labelsize=6) +#gca().set_aspect(aspectratio) +#figname = "Data.png" +#plt.savefig(joinpath(figdir, figname), dpi=600, bbox_inches="tight"); +#plt.close_figs() + +# Check the extremal values of the observations +checkobs((obslon,obslat,obsdepth,obstime),obsval,obsid) + +### 2. Extract the bathymetry + +# It is used to delimit the domain where the interpolation is performed. +## 2.1 Choice of bathymetry + +# Modify bathname according to the resolution required. + +download("https://dox.ulg.ac.be/index.php/s/U0pqyXhcQrXjEUX/download", "gebco_30sec_8.nc") +bathname="gebco_30sec_8.nc" + +@time bx,by,b = load_bath(bathname,true,lonr,latr); + +#figure("Data-Bathymetry") +#ax = subplot(1,1,1) +#pcolor(bx, by, permutedims(b, [2,1])); +#colorbar(orientation="vertical", shrink=0.8).ax.tick_params(labelsize=8) +#contour(bx, by, permutedims(b, [2,1]), [0, 0.1], colors="k", linewidths=.5) +#gca().set_aspect(aspectratio) +#ax.tick_params("both",labelsize=6) +#figname = "Bathymetry.png" +#plt.savefig(joinpath(figdir, figname), dpi=600, bbox_inches="tight"); +#plt.close_figs() + +## 2.2 Create mask +# False for sea +# True for land + +mask = falses(size(b,1),size(b,2),length(depthr)) +for k = 1:length(depthr) + for j = 1:size(b,2) + for i = 1:size(b,1) + mask[i,j,k] = b[i,j] >= depthr[k] + end + end +end +@show size(mask) + + +#figure("Data-Mask") +#ax = subplot(1,1,1) +#gca().set_aspect(aspectratio) +#ax.tick_params("both",labelsize=6) +#ax.pcolor(bx, by, transpose(mask[:,:,1]), cmap=plt.cm.binary_r) +#ax.set_title("Land-sea mask") +#figname = "Mask.png" +#plt.savefig(joinpath(figdir, figname), dpi=600, bbox_inches="tight"); +#plt.close_figs() + +### 3. Quality control +# We check the salinity value. +# Adapt the criteria to your region and variable. + +sel = (obsval .<= selmax) .& (obsval .>= selmin); + +obsval = obsval[sel] +obslon = obslon[sel] +obslat = obslat[sel] +obsdepth = obsdepth[sel] +obstime = obstime[sel] +obsid = obsid[sel]; + + +### 4. Analysis parameters +# Correlation lengths and noise-to-signal ratio + +# We will use the function diva3D for the calculations. +# With this function, the correlation length has to be defined in meters, not in degrees. + +sz = (length(lonr),length(latr),length(depthr)); +lenx = fill(100_000.,sz) # 100 km +leny = fill(100_000.,sz) # 100 km +lenz = fill(25.,sz); # 25 m +len = (lenx, leny, lenz); +epsilon2 = 0.1; +#epsilon2 = epsilon2 * rdiag; + +### Output file name +outputdir = "outputs_netcdf/" +if !isdir(outputdir) + mkpath(outputdir) +end +filename = joinpath(outputdir, "Water_body_$(replace(varname," "=>"_")).nc") + +### 7. Analysis +# Remove the result file before running the analysis, otherwise you'll get the message +if isfile(filename) + rm(filename) # delete the previous analysis + @info "Removing file $filename" +end + +## 7.1 Plotting function +# Define a plotting function that will be applied for each time index and depth level. +# All the figures will be saved in a selected directory. + +function plotres(timeindex,sel,fit,erri) + tmp = copy(fit) + nx,ny,nz = size(tmp) + for i in 1:nz + figure("Additional-Data") + ax = subplot(1,1,1) + ax.tick_params("both",labelsize=6) + ylim(39.0, 46.0); + xlim(11.5, 20.0); + title("Depth: (timeindex)", fontsize=6) + pcolor(lonr.-dx/2.,latr.-dy/2, permutedims(tmp[:,:,i], [2,1]); + vmin = 33, vmax = 40) + colorbar(extend="both", orientation="vertical", shrink=0.8).ax.tick_params(labelsize=8) + + contourf(bx,by,permutedims(b,[2,1]), levels = [-1e5,0],colors = [[.5,.5,.5]]) + aspectratio = 1/cos(mean(latr) * pi/180) + gca().set_aspect(aspectratio) + + figname = varname * @sprintf("_%02d",i) * @sprintf("_%03d.png",timeindex) + plt.savefig(joinpath(figdir, figname), dpi=600, bbox_inches="tight"); + plt.close_figs() + end +end + +## 7.2 Create the gridded fields using diva3d +# Here only the noise-to-signal ratio is estimated. +# Set fitcorrlen to true to also optimise the correlation length. + +@time dbinfo = diva3d((lonr,latr,depthr,TS), + (obslon,obslat,obsdepth,obstime), obsval, + len, epsilon2, + filename,varname, + bathname=bathname, + fitcorrlen = false, + niter_e = 2, + surfextend = true + ); + +# Save the observation metadata in the NetCDF file. + +DIVAnd.saveobs(filename,(obslon,obslat,obsdepth,obstime),obsid); \ No newline at end of file diff --git a/tools/ocean/divandfull.xml b/tools/ocean/divandfull.xml new file mode 100644 index 000000000..f2b800def --- /dev/null +++ b/tools/ocean/divandfull.xml @@ -0,0 +1,109 @@ + + Data-Interpolating Variational Analysis in n dimensions + + 0.1.0 + 0 + + + julia + julia-divand + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + [0-9a-zA-Z_]+ + + + + + + + + + + + + + + + + + + + + + + + `_ but not further developed anymore). + +The method bears some similarities and equivalences with Optimal Interpolation or Krigging in that it allows to create a smooth and continous field from a collection of observations, observations which can be affected by errors. The analysis method is however different in practise, allowing to take into account topological features, physical constraints etc in a natural way. The method was initially developped with ocean data in mind, but it can be applied to any field where localized observations have to be used to produce gridded fields which are "smooth". + +DIVAndrun is the core analysis function in n dimensions. It does not know anything about the physical parameters or units you work with. Coordinates can also be very general. The only constraint is that the metrics (pm,pn,po,...) when multiplied by the corresponding length scales len lead to non-dimensional parameters. Furthermore the coordinates of the output grid (xi,yi,zi,...) need to have the same units as the observation coordinates (x,y,z,...). + +DIVAndfun is a version with a minimal set of parameters (the coordinates and values of observations, i.e. (x,f), the remaining parameters being optional) and provides an interpolation function rather than an already gridded field. + +diva3D is a higher-level function specifically designed for climatological analysis of data on Earth, using longitude/latitude/depth/time coordinates and correlations length in meters. It makes the necessary preparation of metrics, parameter optimizations etc you normally would program yourself before calling the analysis function DIVAndrun. + +DIVAnd_heatmap can be used for additive data and produces Kernel Density Estimations. + +DIVAndgo is only needed for very large problems when a call to DIVAndrun leads to memory or CPU time problems. This function tries to decide which solver (direct or iterative) to use and how to make an automatic domain decomposition. Not all options from DIVAndrun are available. + +If you want to try out multivariate approaches, you can look at DIVAnd_multivarEOF and DIVAnd_multivarJAC + +If you want more informations about the functions and parameters see also the `documentations here `_. + + ]]> + + doi:10.5194/gmd-7-225-2014 + + \ No newline at end of file From f10ecd40effd34c9a853f8d3d8636edb4502d923 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Marie=20Joss=C3=A9?= <84919248+Marie59@users.noreply.github.com> Date: Mon, 15 Jul 2024 12:13:12 +0200 Subject: [PATCH 02/55] add test files --- .../test-data/DIVAnd_netcdf_output.netcdf | Bin 0 -> 297051 bytes ...hication_Med_profiles_2022_unrestricted.nc | Bin 0 -> 1333669 bytes 2 files changed, 0 insertions(+), 0 deletions(-) create mode 100644 tools/ocean/test-data/DIVAnd_netcdf_output.netcdf create mode 100644 tools/ocean/test-data/data_from_Eutrophication_Med_profiles_2022_unrestricted.nc diff --git a/tools/ocean/test-data/DIVAnd_netcdf_output.netcdf b/tools/ocean/test-data/DIVAnd_netcdf_output.netcdf new file mode 100644 index 0000000000000000000000000000000000000000..06cbf8da377279163996c7ad2fd2194f7e5ebe77 GIT binary patch literal 297051 zcmeFa2|Scv`#(NNcG``sCE3EDvJ*mfX;ER2LCU_5Eg~ut*@+PCiAq_=5;ce{sgS*~ zM#h$X`QP`zw;K*IBM}&Rv%e9n@rD+|Ec% zPY)x9H7J-~T1QMmKpACcB|jJ*I%rJI;zvcjlbA@e5y~^?AUzNu+`6320cO#_7)d;~_6{}{PF9X2 zzTFU?v!{oPr-!?RlZ}Tp%2vX}%EQLZ;#z%wWh;lUMoI6J727K%hY*vLw6PVFmX+Kmc3RG6pDaoSA#JsHKeHGN zcv~76ElCmzkpIJbNFk*5iXmjgB=;Sal$75mC%;#Ys0yG6FxaV^@ROPWMn$y+OrfTt zqB;pa0D+7&TR_EcqZhfBTHgG@`IG;hxKzo zDa@ijSeUw=>X9SFmH~~IWMTRm21m3F4J?kRtLkaMn0dhTZ!Kw{s;@z$2j38+cW`!s zfkHvMVFi=|q?46$(B2U+ogdTz)d}nrpm{)c?&)OjLFx|7kW`e7otuq~yM>LFy9e_g zph1b!iJijT!^#O|<%ash$Qk~qik-cOC(4Fd2<%wjx&%-~yMID`FGKhGpN<swx@( zbz@7QBZ-WKB$FHTKWc2CWs&T{g_czA_J3wamW44N5W#lJMOpNZ3)(oX-`%Af%NuvJp{SFDU4oFrg0)YJyY zAz=W3)gT)hGb~J+l!Jh5L6ngchuK5;-ve<~Jt?4-e5)~!0jXfHvw<}REtU>;P=S>C zfCMlY^j_rXzY|0D)(ZVlrEy?d1p_$QfK_5ng#lA64U7$j00(|!4NVPW4Fh!z3q9>4 zM`8N`y8uT}V4|~fxAB0%*daEQy`znjJ22hD=)wH&=LOO;ISmG5Beownl9Iy9tt2GJ z55s?q<9L6J+f^O5Blb!-)M2USsbKV=!NS^w73WCAfByZmQT|-9e~VEDB1uJq!oN34 zRv4Cvlw$x6{y^}6@W0t8**9AG5{Etpu#DqLQyewWP|X zf*mC)Ir%xg^`DhV%mSp45mM$3-fywY=? zgX0%yJCB&&=_c!KsZAJ;wTGF_tan$E#6lNA)xTeeD4$`AOb|-aWnzFhei_a0b97Nb#*jKA0z%0L%tpSA4K*RTyRh zJiq`80@Gg(B`CsZ!6#sb1E-1_9|>dF1>gY&j5(ksTSNq3f!zcX02Xk7vSC(^h1G)z za*z`3)1JWYfikj5y=mLbmlD`EkU|ywfx)cbG>z=t#nn!VQGWj&8X&em!w+iyp=Ez) z#2*^)$Hx1<@qe(UA1vtyEBc|aPi*

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z*Ci&Ll_&`JpEwY(i>g@b;gbiCht%VNw^Bz>V-g&vPCcv7+(z{v73nt>4%yJtlFJHe zxS~Z+WD3>kMwPoAuMNR$FgPcq!AB{AivN)8!f73+vhkEUY3KRZe z^Z~3&Zag$&;~it^qV-n*@3J|=2?P2Ye}sa8UsBm`cHo*JfrZu$KEC~g6td2s?FcfY zT4H_is@1|!x_03TLyU*(#K;SMVP>)_Hyp%*JdKd=ipJq$re9za?8c_v;=&Rf5s857 zsSRlCr#joZL@6`}vFNT^_!Xh~0jkBZP0(;A8I?m8%h{qX%Rq;Z4SKjF9aRbL_1u;w z;B7s!iS-z2Sr`SA7*h@qX1wi93D7fzxwT`g z`~}U_jO&A7p7PYWgv`RlQ6@0Lb5}Qakvjb*fuLE_@o2p^T!sSn#maHzc0Mwbi`{JFl1~&5PN>gI%e^H2pLn2dR~1?#wh1YUYv&A-nQ&NcwZ ze7Q6HMgejMgsJ(IXljodDucE=%7K?ercK$gvo))sJ`@6b`W9ZDd!PWm!Z`BFHickb zi8rAeQuy1jrWjd+gkH(1qaBlG(-Q;RwJOb^M59l&ev}@B+V53=|5!!;ZJk1}u0ih= z$UqG?!THTPti3g^wV1lpF592gfrM^eJ4=`WLui&K9ZFiO-oI5SaMOsTo%+RXWRK`l zxM}ziTp6BiXZ{Eti(_V-Umh@@P#&PPoD&VX Date: Tue, 23 Jul 2024 22:32:17 +0200 Subject: [PATCH 03/55] Set JULIA_DEPOT_PATH to get a writable Julia HOME --- tools/ocean/divandfull.xml | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/tools/ocean/divandfull.xml b/tools/ocean/divandfull.xml index f2b800def..9100dc3e9 100644 --- a/tools/ocean/divandfull.xml +++ b/tools/ocean/divandfull.xml @@ -14,6 +14,8 @@ --> doi:10.5194/gmd-7-225-2014 - \ No newline at end of file + From 8924551ce073be128437c341fb477074a19e0483 Mon Sep 17 00:00:00 2001 From: Bjoern Gruening Date: Tue, 23 Jul 2024 22:42:25 +0200 Subject: [PATCH 04/55] fix some test settings more needed --- tools/ocean/divandfull.xml | 73 +++++++++++++++++++++++--------------- 1 file changed, 44 insertions(+), 29 deletions(-) diff --git a/tools/ocean/divandfull.xml b/tools/ocean/divandfull.xml index 9100dc3e9..1a1b51b6e 100644 --- a/tools/ocean/divandfull.xml +++ b/tools/ocean/divandfull.xml @@ -16,18 +16,18 @@ @@ -37,22 +37,22 @@ - - + + - - + + - - + + - + [0-9a-zA-Z_]+ @@ -64,7 +64,7 @@ + --> @@ -73,32 +73,47 @@ - + + + - + - `_ but not further developed anymore). +DIVAnd (Data-Interpolating Variational Analysis in n dimensions) performs an n-dimensional variational analysis/gridding of +arbitrarily located observations. Observations will be interpolated/analyzed on a curvilinear grid in 1, 2, 3 or more dimensions. +In this sense it is a generalization of the original two-dimensional DIVA version (still available `here `_ but +not further developed anymore). -The method bears some similarities and equivalences with Optimal Interpolation or Krigging in that it allows to create a smooth and continous field from a collection of observations, observations which can be affected by errors. The analysis method is however different in practise, allowing to take into account topological features, physical constraints etc in a natural way. The method was initially developped with ocean data in mind, but it can be applied to any field where localized observations have to be used to produce gridded fields which are "smooth". +The method bears some similarities and equivalences with Optimal Interpolation or Krigging in that it allows to create a smooth +and continous field from a collection of observations, observations which can be affected by errors. The analysis method is however +different in practise, allowing to take into account topological features, physical constraints etc in a natural way. +The method was initially developped with ocean data in mind, but it can be applied to any field where localized observations have +to be used to produce gridded fields which are "smooth". -DIVAndrun is the core analysis function in n dimensions. It does not know anything about the physical parameters or units you work with. Coordinates can also be very general. The only constraint is that the metrics (pm,pn,po,...) when multiplied by the corresponding length scales len lead to non-dimensional parameters. Furthermore the coordinates of the output grid (xi,yi,zi,...) need to have the same units as the observation coordinates (x,y,z,...). +DIVAndrun is the core analysis function in n dimensions. It does not know anything about the physical parameters or units you work with. +Coordinates can also be very general. The only constraint is that the metrics (pm,pn,po,...) when multiplied by the corresponding length +scales len lead to non-dimensional parameters. Furthermore the coordinates of the output grid (xi,yi,zi,...) need to have the same units +as the observation coordinates (x,y,z,...). -DIVAndfun is a version with a minimal set of parameters (the coordinates and values of observations, i.e. (x,f), the remaining parameters being optional) and provides an interpolation function rather than an already gridded field. +DIVAndfun is a version with a minimal set of parameters (the coordinates and values of observations, i.e. (x,f), the remaining parameters +being optional) and provides an interpolation function rather than an already gridded field. -diva3D is a higher-level function specifically designed for climatological analysis of data on Earth, using longitude/latitude/depth/time coordinates and correlations length in meters. It makes the necessary preparation of metrics, parameter optimizations etc you normally would program yourself before calling the analysis function DIVAndrun. +diva3D is a higher-level function specifically designed for climatological analysis of data on Earth, using longitude/latitude/depth/time +coordinates and correlations length in meters. It makes the necessary preparation of metrics, parameter optimizations etc you normally would +program yourself before calling the analysis function DIVAndrun. DIVAnd_heatmap can be used for additive data and produces Kernel Density Estimations. -DIVAndgo is only needed for very large problems when a call to DIVAndrun leads to memory or CPU time problems. This function tries to decide which solver (direct or iterative) to use and how to make an automatic domain decomposition. Not all options from DIVAndrun are available. +DIVAndgo is only needed for very large problems when a call to DIVAndrun leads to memory or CPU time problems. This function tries to decide +which solver (direct or iterative) to use and how to make an automatic domain decomposition. Not all options from DIVAndrun are available. If you want to try out multivariate approaches, you can look at DIVAnd_multivarEOF and DIVAnd_multivarJAC From 0caabeb53938edf86dcf329428ef27968f9de9df Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Marie=20Joss=C3=A9?= <84919248+Marie59@users.noreply.github.com> Date: Wed, 24 Jul 2024 11:43:54 +0200 Subject: [PATCH 05/55] fix dates --- tools/ocean/divandfull.jl | 34 +++++++++++++++++----------------- tools/ocean/divandfull.xml | 8 ++++---- 2 files changed, 21 insertions(+), 21 deletions(-) diff --git a/tools/ocean/divandfull.jl b/tools/ocean/divandfull.jl index a2aaeb421..5d6df02c1 100644 --- a/tools/ocean/divandfull.jl +++ b/tools/ocean/divandfull.jl @@ -37,8 +37,8 @@ else startdate = args[6] # yyyy,mm,dd enddate = args[7] varname = args[8] - selmin = parse(Int, args[9]) - selmax = parse(Int, args[10]) + selmin = parse(Float64, args[9]) + selmax = parse(Float64, args[10]) end ## This script will create a climatology: @@ -58,21 +58,21 @@ dx, dy = 0.125, 0.125 lonr = longmin:dx:longmax latr = latmin:dy:latmax -# Extracting year, month, and day -startyear = startdate[1:4] # extract first four characters (year) -startmonth = startdate[5:6] # extract characters 5 and 6 (month) -startday = startdate[7:8] # extract last two characters (day) -# Converting to integers -startyear = parse(Int, startyear) -startmonth = parse(Int, startmonth) -startday = parse(Int, startday) - -endyear = enddate[1:4] # extract first four characters (year) -endmonth = enddate[5:6] # extract characters 5 and 6 (month) -endday = enddate[7:8] # extract last two characters (day) -endyear = parse(Int, endyear) -endmonth = parse(Int, endmonth) -endday = parse(Int, endday) +# Convert string in date +startdate = Date(startdate, "yyyy-mm-dd") + +# extract year month day +startyear = year(startdate) +startmonth = month(startdate) +startday = day(startdate) + +# Convert string in date +enddate = Date(enddate, "yyyy-mm-dd") + +# extract year month day +endyear = year(enddate) +endmonth = month(enddate) +endday = day(enddate) timerange = [Date(startyear, startmonth, startday),Date(endyear, endmonth, endday)]; diff --git a/tools/ocean/divandfull.xml b/tools/ocean/divandfull.xml index 1a1b51b6e..796e056ae 100644 --- a/tools/ocean/divandfull.xml +++ b/tools/ocean/divandfull.xml @@ -74,10 +74,10 @@ - - + + - + @@ -123,4 +123,4 @@ If you want more informations about the functions and parameters see also the `d doi:10.5194/gmd-7-225-2014 - + \ No newline at end of file From 877ae314621015df517966134426d4899fc3f296 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Marie=20Joss=C3=A9?= <84919248+Marie59@users.noreply.github.com> Date: Wed, 31 Jul 2024 15:31:01 +0200 Subject: [PATCH 06/55] add test files --- .../test-data/DIVAnd_netcdf_output.netcdf | Bin 297051 -> 297051 bytes tools/ocean/test-data/gebco_30sec_8.nc | Bin 0 -> 14634552 bytes 2 files changed, 0 insertions(+), 0 deletions(-) create mode 100644 tools/ocean/test-data/gebco_30sec_8.nc diff --git a/tools/ocean/test-data/DIVAnd_netcdf_output.netcdf b/tools/ocean/test-data/DIVAnd_netcdf_output.netcdf index 06cbf8da377279163996c7ad2fd2194f7e5ebe77..cf392d1fe07501115a093ab7950521dc08f112ff 100644 GIT binary patch delta 99 zcmcaTLFo1bp$!3yDybIcrsgJQiMl3f#zwk^hN)?~M#gD|x)$c@pwWzpHM7Mr0&OdBP?PV|@o*ww0y9lP=wfN@<=tIzlFFXIT zB@J+}x$z&KW(udC8#E&yhdInij}eS_J#JqY|JahxU3A{Ui)t?n?f=o4wK(F^dKWtK z(#vWus;|AIK7S03mmBlpr5Bxl*`*ka&GC<{Z#eIghK5TQUi7(3E?XRgBYh*0lSSP= z$HE>4u4}r-?{u)o^RbzDj5!#__V$>9TtegWAJ-AN$JJ1Ksr!TCF_rnS*rHYV=dilq z?;Padg75XXKH0FOp&5UM&t2rz)_tzI!Mn7f)thRo>sO z?}ZJQHC&>9%nwI)ZchiJBIyTg#Wh9PjIFrpL2Mgs#ie82W-BhZ6Wd+3qHZ|05w@aw z4YswmqGTYpqin_WmDpC<3UP<(V=GR*9NQJPBEA>fK3j28Ben)xF?5I9Y{fC<*vf3h z5!>8mD-L(uB3u4f<(B`+VaM9?SCm`+TjiF&pxpAOlw1Coa?7o9%kNii`Q6GbzfHO2 zwTgrS( zgM7bgOPOye^DSk*r9r;nGT+i;$Ys8z%y$m+ofG6c&dy=JbC~ZO<~xV^&I$7Us-44p z=P=(n%y$m+ox^k|5uKwuJeX1o=j63G*#sz9r1JB*=HC zEn&VT%(sO3mIV2N%X~|iZwd1)VZJ3nzTh(766RaNd`p;b3G*#sz9r1Jg!z^P`5K#I zzA5ILV!kQnn+o#1$)=cZiutCPZz{<5a+?bB-D^|KH^qEYLB16>#e7pizTh(76!T3n z-xTvr1^I%@d{fLf#e7pizTgJ=g3EkU%r_O}3oi3bG2e6layhmu?YX~i#J1R;`)oP3 zN_*}jMc9lz_s3(gjkD)|cevZ^x!)Yh zco5qrd+y11Vq0g={p1>KYwfuoU5V{$b~d@Q$(>E^Y;tFlJDc3u2=Omb(EJCod*J%`+L$UTSLbI3i1+;hmCLGBE4XOKIC+!^G~Aa@42GsvAm?hJBgkUN9i8RX6& zcLupEuo)cRIP#1MUfSI=R!yolfp_a;K9!o!sf8nkL~c>QEwV-A7Li*N za0l9=fcqg^L~aqeMdTKdTSRUVxkcnoC3h;hQ^}o5?o@K82HfFxD!Eh1ol5Rha;K6z zmE5W1P9=9LxrG7u3R_5SA-RR*76#n0wvgPyfP0iJB)5>rA$JP7Q^=h{?i6yTkUNFkDdY;dLaqed3M=GFz#V6W zTp?G;6>^1KAy>#1awXv2WQE+xd)?M)CvS7xc02h_x2?02SGsMLo!scQ#ddO$+luYv z;cgpgCr8}Y$DXyrZCQKPgKm4sp0&npH`}u=ciR>Atny&9XN`5+ID6JWw+*tB$el#) zByuN_JBi#$kJD%L}obU57}|#jw5#*x#P$kNA5Us z$B{dh&+k}r$C5ji+_B`2C3kGV9bw0kJBHjb-9YgLIaz~Rpn%vRkjwW|B zxuXNFv7^ZyO>UChB)Lg)lL7Zin+&*>Hc4)h+(fWn)+U1SH`@dsUn1xqWaGi(>9BD= zj(ET?w()@5$HoHQLpDZEEI9rI8|CvC4f43#MuW$HfsF=_d!#*u+*8Osh1^rfJ(=8- z$vv6elga%Ixt}5TGvtm6xPP*v$Q?!QC~`kd?x)H9G`XK9_at&pBKIV6Pa^k3a!(}p zL~=)xJCfXye7;7KJA&L19UgG6wZq9BPVNchoEzk z7jRFs!-D;OYKH~mC)(qKaqaf_p#Rf$Xz+Oc-3|>N$0zJ@0slICT)_RX9TM=C+fN0Y zH|?i_<1ewF4Dxx|elp0T#vU6y{$JQ*gU3C?4kmXnxt}2S6XYI4?lI&ZP43a;4kGs` za*rZ+Ah`p{Eg-jm+yTLUD{TK@{3Z6tV4QD{2>NH+j|Y$EEZZ-598vqRfPb9*Xu$1f z`v$ys?1ux+ZhLre{O9dqK|YV#K0zKou^$Q^|E)F>JnnCA{=3_6-{G787L4Du`JG^# z-TYrc|IM5K96X-SZ+7RM?hLp`Z+=XB9nvtcC=2`<9u|o9yc{vIjxiT{ljg~ zPu9nA#AJP3$;tXSQ^Up86u`1WMY>w(EZo_n7c&HHN6zr%H+f0vBt-|0u9f47H4 z|Blay{#|#;M*{AjMgQ)7MW2UbMW2^ZqR-RmqR-n5(dTiV=<~Wn^m(2v`n>;K^mULD zeOK8LLiBa`ZPC}|P|?@v_eEc~anaZDPefnW zlSNigeo6Fm+7tcUt{43rZxj7o-y`}tpAh}rzfAOd-~ste z!2O%(_k@UkZ?uShk8BbBUO7_qduER4_s(}jzlVM$`n}|deoxhles8sjeviE(`n{GA z{hqr_^n33CiIJ<{iz50xd5!4z=3}DYqeqH8vN^8iouyr59@JfU9nyrD((JfcnXyke{9dB$s^=N$#2 z=OJT6&r8Zg&r_O3&s$cDp2utuJ+FC5#*nM$J)Y=!P@(8~QN8GSQj6$$Q=8~{)K<~+ zsy(9TSp}l!U1LPg!^%X@%bG>c(^iX~w`~wTk9$eRk*nu!LlP*GU6Jubak*UPqORURNy@z0O)K zdfl}_^g8S%Ig?zyPV+>s+X_Xmsmyw^V&qO`?iW+2ksHQE*v0woj6AHy0KLB zI`T5n>&n%l*O?ncuRC9ov&hx!Qcv_cwNUiBwO;f(wng;1woUXpcdO`i?;g?X;FY4+ z#cS}v6MXTDUN>(Ly^h`{dR@Ik^g4U5$QJ^z=yiC3=ymxCqSxtTL>_S`3R6X|l;L`^P5Gl`&Ww21KcD!FL0;mJi&va^9I{Q=Mi>@&MWMdDdg(BLxJc##0jGF5@ST? zDW;0fTa<~;V>F1)Yb+I==U6E^?{SmpJjk7*^CAz5&Xa5xoj2JbI*+nf3dz-ZmIBdv zmlH(iVaABg%S;uWrzw-d-@6m02GMz(rK0mXEu!;0t3~I1+C=ApHi*s(Z4;d*+95h` zv`=&%DI%O#63#P;&O412&O?dLOO=VvQ#FXrTQ!T$W3`CRYpoWY=V}w3_u3#j54Kfw zUTlZxJlQ@eN(U!)!g(~&d9~r9^K4^<^KPQ^aAl(Nat)&Mbj_mkb}gdwc&kO{_1Z+| z`8J5o`)w7S2ize#FSt)QPbfNXI8byRak%Kb;#kpn#;Kz7j%A|rkPV{qlFg#?lr5t3 zma9eQG22AvH8+UPb8Z!#_uL^m54ul^nXk^14wT~W1}C_p^QdD*=T)bQ&a;+@&bu~< z&cil~&daul&eN_IowschoyXlEI`pJRdgP`OmtqoL3EzIS#;jLMRXp1wdlNjo9I0K2GM!@t)lbzJ4EO8_sZGi z>b(Cz;e7zn`vPM{?-LY>-Zv-{y^qi!dS9Vg^gct2=zWLPqW2-%MDI&%5WP>aRrJ2a z4w-S0yRg|SGsxBZ90P^-Jw)$=j1|2vQY3nxq)ha_NrUKplxETUDlMY-SyqeQcWD#7 z53@n^zRXt9`!qX*_if}Ha`nE>K;eBJ(fdAQMehR@iQX3~6TMH=AbQ`ZS!RCJU4XTS z-d9>JdY`FH^uE&u(fd$aMej@P5Z< zEPCIpMf5(}YSH^@ZKC(tHi+JL+bVh=Zin!`oXjGZ_w9uD@kHge{`?4Oh$T;QOde^uFQ-(ff>BMejTA5Z;HB+2ry*rSQI`=zYwwqW3k6 zMDKH!iQe~Y5WNrDEP7wGMf5)DYSH_qZKC&4H;CR>-70#Yb%*f2tDH+N@5>7B(~91= z9V>btw@CE9ZkgzP-UiY8zRjZdfv1Yz7v3g%pSVo)zVQyx`^XK#`^v)m%#xa{-@kev zdZp-n=>p+>YSH`F!$t37-zj=ud#vbv?gvHhdxLwe`+NZR26urD?k&NUx9ELyaPQXl z5AUl>YBRZyxz{DQPq_=0ci&>*^QV6W&pf@UdUzPip}rEuMW=sJX(MAsz@7hR`tmy}!@OhAaPW7sIVt^r); 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