From 0647530f690aaeda28deef85bc0fa11c7681cae4 Mon Sep 17 00:00:00 2001 From: "silas (home)" Date: Tue, 23 Dec 2025 08:32:03 +0100 Subject: [PATCH] file naming for WDM simulation --- projects/WDM/WDM_model.m | 251 +++++++++++------- .../{WDM_model_16x200.m => WDM_model_old.m} | 47 ++-- projects/WDM/WDM_settings.m | 57 ---- projects/WDM/getDispersionVector.m | 32 +++ 4 files changed, 210 insertions(+), 177 deletions(-) rename projects/WDM/{WDM_model_16x200.m => WDM_model_old.m} (88%) create mode 100644 projects/WDM/getDispersionVector.m diff --git a/projects/WDM/WDM_model.m b/projects/WDM/WDM_model.m index cdc8a74..37c0990 100644 --- a/projects/WDM/WDM_model.m +++ b/projects/WDM/WDM_model.m @@ -1,25 +1,96 @@ %%% Run parameters % TX -% --- FIRST LINE: evaluate settings located beside this script --- -run(fullfile(fileparts(mfilename('fullpath')),'WDM_settings.m')); -num_realiz = 50; -s.wavelengthplan = calcWavelengthPlan(16,400e9,1310); +function WDM_model(options) + +arguments + options.num_channels = 16; + options.channel_spacing = 400e9; + options.fiber_length_km = 0; + options.rand_key = 1; + options.num_realiz = 1; + options.fwm_mitigation_technique = "co"; +end + +%% + +% Add the imdd_simulation framework to the path +if ispc + addpath(genpath('C:\Users\Silas\Documents\MATLAB\imdd_simulation')); +else + % Linux path on the cluster + addpath(genpath('/work_beegfs/sutef391/imdd_simulation')); +end + +% Quiet the ambiguous CET warning (best is to set TZ in sbatch; see below) +warning('off','MATLAB:datetime:AmbiguousTimeZone'); + +% How many workers? +cpus = str2double(getenv('SLURM_CPUS_PER_TASK')); +if ~isfinite(cpus) || cpus < 1, cpus = max(1, feature('numcores')); end + +% Use a per-job, node-local JobStorageLocation to avoid stale locks on $HOME +% Prefer $TMPDIR if your cluster provides it, else tempdir(). +tmpbase = getenv('TMPDIR'); +if isempty(tmpbase), tmpbase = tempdir; end +jsl = fullfile(tmpbase, sprintf('matlab_jobstorage_%s_%s', ... + getenv('USER'), getenv('SLURM_JOB_ID'))); +if ~exist(jsl,'dir'); mkdir(jsl); end + +% Configure the local cluster explicitly and start the pool +c = parcluster('local'); +c.NumWorkers = cpus; +c.JobStorageLocation = jsl; + +p = gcp('nocreate'); +if isempty(p) || p.NumWorkers ~= cpus + if ~isempty(p), delete(p); end + p = parpool(c, cpus); % avoids the “queued” state +end +fprintf('parpool up with %d workers; JobStorage=%s\n', p.NumWorkers, c.JobStorageLocation); + +% result filename (timestamp + optional job id) +t = datetime('now','TimeZone','local','Format','yyyyMMdd_HHmmss'); +jobid = getenv('SLURM_JOB_ID'); if isempty(jobid), jobid = 'nojid'; end +host = getenv('HOSTNAME'); if isempty(host), host = 'localhost'; end + +% Output directory depends on platform +% create/ use folders foroptions.fiber_length_km, options.num_channels, options.channel_spacing.*1e-9, options.fwm_mitigation_technique +foldname = sprintf('%dkm_%dch_%dghz_%s', options.fiber_length_km, options.num_channels, options.channel_spacing.*1e-9, options.fwm_mitigation_technique); +if ispc + output_root = fullfile('C:\Users\Silas\Documents\MATLAB\Datensätze\FWM_2025\',foldname,'\'); +else + output_root = fullfile('/work_beegfs/sutef391/results_WDM',foldname,'\'); +end +if ~exist(output_root,'dir'), mkdir(output_root); end + +% Build filename +t = datetime('now','TimeZone','local','Format','yyyyMMdd_HHmmss'); +jobid = getenv('SLURM_JOB_ID'); if isempty(jobid), jobid = 'nojid'; end +host = getenv('HOSTNAME'); if isempty(host), host = 'localhost'; end + +fname = sprintf('WDM_%s_%s_%s_%dkm_%dch_%dghz_%s.mat', char(t), host, jobid, options.fiber_length_km, options.num_channels, options.channel_spacing.*1e-9, options.fwm_mitigation_technique); + + +%% +s.num_realiz = options.num_realiz; +% s.wavelengthplan = calcWavelengthPlan(16,400e9,1310); +s.wavelengthplan = calcWavelengthPlan(options.num_channels,options.channel_spacing,1310); % wavelengthplan = [1295,1305,1315,1325]; -link_length = 10; -pmd = 0.1; -gamma = 0.0023; +link_length = options.fiber_length_km; +s.pmd = 0.1; +s.gamma = 0.0023; -M = 4; -m = floor(log2(M)*10)/10; +s.M = 4; +m = floor(log2(s.M)*10)/10; fsym = 112e9; fdac = 2*fsym; -fadc = 2*fsym; -s.random_key = 100; +fadc = 120000000000; +s.random_key = options.rand_key; % Laser / s.Modulator vbias_rel = 0.5; -u_pi = 3.2; +u_pi = 4.6; vbias = -vbias_rel*u_pi; laser_linewidth = 0e6; @@ -38,7 +109,7 @@ mu_dc = 0.005; mu_ffe = [mu_ffe1 mu_ffe3 mu_ffe3]; mu_dfe = 0.0004; -%DB Stuff +%DB Stuff db_precode = 0; db_encode = 0; duob_mode = db_mode.no_db; @@ -52,7 +123,7 @@ f_plan = physconst('lightspeed')./(s.wavelengthplan.*1e-9); margin = 25e12; % some THz left and right f_span = (max(f_plan)+margin)-(min(f_plan)-margin); f_nyq = f_span/2; -kover = 8; +kover = 4; upsample_required = f_nyq./(fdac*kover/2); upsample_pow = 2^nextpow2(upsample_required); upsample_ceil = ceil(upsample_required); @@ -64,18 +135,34 @@ signal_cell = {}; Symbols = {}; Tx_bits = {}; -s.rop = -6:0.75:-0.75; +s.rop = -12:0.75:-0.75; output_ffe = cell(length(s.wavelengthplan),length(s.rop),s.num_realiz); output_vnle = cell(length(s.wavelengthplan),length(s.rop),s.num_realiz); output_mlse = cell(length(s.wavelengthplan),length(s.rop),s.num_realiz); output_dbt = cell(length(s.wavelengthplan),length(s.rop),s.num_realiz); +s.p = options.fwm_mitigation_technique; +switch s.p + case "co" + pol_rot = 100.*ones(1,length(s.wavelengthplan)); + d_local = 0; + case "pair" + pol_rot = repmat([100,100,0,0],1,length(s.wavelengthplan)/4); + d_local = 0; + case "alt" + pol_rot = repmat([100,0,100,0],1,length(s.wavelengthplan)/4); + d_local = 0; + case "seg" + pol_rot = 100.*ones(1,length(s.wavelengthplan)); + d_local = 3; +end + for realiz = 1:s.num_realiz - + parfor l = 1:N - + [Digi_sig,Symbols{l},Tx_bits{l}] = PAMsource(... "fsym",fsym,"M",s.M,"order",18,"useprbs",0,... "fs_out",fdac,... @@ -84,93 +171,92 @@ for realiz = 1:s.num_realiz "randkey",s.random_key+l+realiz,... "db_precode",db_precode,"db_encode",db_encode,... "mrds_code",0,"mrds_blocklength",512,"duobinary_mode",duob_mode).process(); - + % Digi_sig.spectrum("fignum",101,"displayname",'bla','normalizeTo0dB',0,'lambda0_nm',1310,'useWavelengthAxis',0); - Lp_awg = Filter('filtdegree',3,"f_cutoff",100e9,"fs",fdac*kover,"filterType",filtertypes.gaussian,"active",true); - El_sig = AWG("fdac",fdac,"f_cutoff",fsym,"lpf_active",1,"kover",kover,"bit_resolution",12,"upsampling_method","samplehold","precomp_sinc_rolloff",0,"H_lpf",Lp_awg,"dac_max",0.6,"dac_min",-0.6).process(Digi_sig); + Lp_awg = Filter('filtdegree',3,"f_cutoff",56e9,"fs",fdac*kover,"filterType",filtertypes.gaussian,"active",true); + El_sig = AWG("fdac",fdac,"f_cutoff",fsym,"lpf_active",1,"kover",kover,"bit_resolution",6,"upsampling_method","samplehold","precomp_sinc_rolloff",0,"H_lpf",Lp_awg,"dac_max",0.6,"dac_min",-0.6).process(Digi_sig); % El_sig = s.M8199B("kover",kover).process(Digi_sig); % El_sig.spectrum("fignum",101,"displayname",'bla','normalizeTo0dB',0,'lambda0_nm',1310,'useWavelengthAxis',0); - + %%%%% Electrical Driver Amplifier %%%%%% El_sig = El_sig.normalize("mode","oneone"); + El_sig = El_sig .* u_pi .* 0.5; % El_sig = El_sig.setPower(1,"dBm"); % figure;histogram(El_sig.signal); - + %%%%% s.MODULATE E/O CONVERSION %%%%% Eml_out = EML("mode",eml_mode.im_cosinus,"power",3,"fsimu",El_sig.fs,"lambda",s.wavelengthplan(l),"bias",vbias,"u_pi",u_pi,"linewidth",laser_linewidth,"randomkey",s.random_key+l+realiz).process(El_sig); - - signal_cell{l} = Polarization_Controller("mode","rot_power","desired_power",100).process(Eml_out); + + signal_cell{l} = Polarization_Controller("mode","rot_power","desired_power",pol_rot(l)).process(Eml_out); end - + Opt_sig_wdm = Optical_Multiplex("fs_in",fdac*kover,"fs_out",upsample_pow*fdac*kover,... - "lambda_center",1310,"random_key",0,"filtype",1,"B",200e9).process(signal_cell); - + "lambda_center",1310,"random_key",0,"filtype",1,"B",120e9).process(signal_cell); + Opt_sig_wdm = Amplifier("amp_mode","ideal_no_noise","gain_mode","output_power","amplification_db",3+10*log10(N)).process(Opt_sig_wdm); - + % Opt_sig_wdm.spectrum("fignum",101,"displayname",'bla','normalizeTo0dB',0,'lambda0_nm',1310,'useWavelengthAxis',0); - + % Opt_sig_wdm.spectrum("fignum",101,"displayname",'bla','normalizeTo0dB',1,'max_num_lines',2); - + %%%%%% Fiber %%%%%% Opt_sig_wdm_fib=Opt_sig_wdm; - + segment_length = 1; % km nSegments = link_length/segment_length; zdw = 1310; - D_local = 0; %if ~=0, simulation uses "segmented fiber with d+,d-) + d_local = d_local; %if ~=0, simulation uses "segmented fiber with d+,d-) randomize_D = true; - Dvec = getDispersionVector(nSegments, D_local, zdw, randomize_D, s.random_key+realiz); + Dvec = getDispersionVector(nSegments, d_local, zdw, randomize_D, s.random_key+realiz); for seg = 1:nSegments - - Opt_sig_wdm_fib = DP_Fiber("L",segment_length,"D",Dvec(s),"Dpmd",pmd,"Ds",0.07,... - "beat_len",10,"corr_len",100,"dz",1,"manakov",0,... - "gamma",s.gamma,"lambda",zdw,"n_waveplates",10,"SS_dphimax",0.01,... - "SS_dzmax",50,"SS_dzmin",10,"X_alpha",0.3,"X_beta",0,"rng",1).process(Opt_sig_wdm_fib); - + + Opt_sig_wdm_fib = DP_Fiber("L",segment_length,"D",Dvec(seg),"Dpmd",s.pmd,"Ds",0.07,... + "beat_len",10,"corr_len",100,"dz",1,"manakov",0,... + "gamma",s.gamma,"lambda",zdw,"n_waveplates",10,"SS_dphimax",0.01,... + "SS_dzmax",50,"SS_dzmin",10,"X_alpha",0.3,"X_beta",0,"rng",1).process(Opt_sig_wdm_fib); + end - - Opt_sig_wdm_fib.spectrum("fignum",realiz,"displayname",'bla','lambda0_nm',1310,'useWavelengthAxis',0); - + + % Opt_sig_wdm_fib.spectrum("fignum",realiz,"displayname",'bla','lambda0_nm',1310,'useWavelengthAxis',0); + % Opt_sig_wdm_fib.move_it_spectrum("fignum",100212,"displayname",'bla'); - + % Opt_sig = Fiber("fsimu",Opt_sig.fs,"fiber_length",s.link_length/1000,"alpha",0.3,"D",0,"lambda0",1310,"s.gamma",0,"Dslope",0.07).process(Opt_sig) - + Opt_sig_wdm_demux = Optical_Demultiplex("attenuation",0,"B",200e9,"filtype",1,"fs_out",fdac*kover,"fs_in",fdac*kover*upsample_pow,"lambda_center",1310).process(Opt_sig_wdm_fib); + for ri = 1:length(s.rop) - - %%%%%% ROP %%%%%% - Opt_sig_wdm_rx = Amplifier("amp_mode","ideal_no_noise","gain_mode","output_power","amplification_db",s.rop(ri)+10*log10(N)).process(Opt_sig_wdm_fib); - - Opt_sig_wdm_demux = Optical_Demultiplex("attenuation",0,"B",200e9,"filtype",1,"fs_out",Opt_sig_wdm_rx.fs/upsample_pow,"fs_in",Opt_sig_wdm_rx.fs,"lambda_center",1310).process(Opt_sig_wdm_rx); - - PD_cell = {}; - for l = 1:N - + + parfor l = 1:N + + %%%%%% ROP %%%%%% + Opt_sig_wdm_rx = Amplifier("amp_mode","ideal_no_noise","gain_mode","output_power","amplification_db",s.rop(ri)).process(Opt_sig_wdm_demux{l}); % rop+10*log10(N) + %%%%%% PD Square Law %%%%%% - assert(fdac*kover==Opt_sig_wdm_demux{l}.fs,'Sampling Frequencies do not match! Check previous steps'); - PD_sig = Photodiode("fsimu",fdac*kover,"dark_current",2e-08,"responsivity",1,"temperature",20,"nep",1.8e-11,"randomkey",s.random_key+l+realiz).process(Opt_sig_wdm_demux{l}); - + assert(fdac*kover==Opt_sig_wdm_rx.fs,'Sampling Frequencies do not match! Check previous steps'); + PD_sig = Photodiode("fsimu",fdac*kover,"dark_current",2e-08,"responsivity",1,"temperature",20,"nep",1.8e-11,"randomkey",s.random_key+l+realiz).process(Opt_sig_wdm_rx); + % PD_sig.spectrum("fignum",222,"displayname",'bla','normalizeTo0dB',1); - + %%%%%% Low-pass RX (PD, El. Connectors and Scope %%%%%% rx_bwl = 100e9; PD_sig = Filter('filtdegree',4,"f_cutoff",rx_bwl,"fs",fdac*kover,"filterType",filtertypes.butterworth,"active",true).process(PD_sig); - + % %%%%%% Low-pass Scope %%%%%% - Lp_scpe = Filter('filtdegree',4,"f_cutoff",110e9,"fs",fadc,"filterType",filtertypes.butterworth,"active",true); - + Lp_scpe = Filter('filtdegree',4,"f_cutoff",80e9,"fs",fadc,"filterType",filtertypes.butterworth,"active",true); + %%%%%% Scope %%%%%% Scpe_sig = Scope("fsimu",fdac*kover,"fadc",fadc,... "delay",0,"fixed_delay",0,"filtertype",filtertypes.butterworth,... "samplingdelay",0,"rand_samplingdelay",0,"freq_offset",0,"samp_jitter",0,... - "adcresolution",8,"quantbuffer",0.1,'block_dc',1,'lpf_active',1,'H_lpf',Lp_scpe).process(PD_sig); - + "adcresolution",8,"quantbuffer",0.1,'block_dc',1,'lpf_active',0,'H_lpf',Lp_scpe).process(PD_sig); + Scpe_sig_2sps = Scpe_sig.resample("fs_out",2*fsym); % Scpe_sig.spectrum("fignum",222,"displayname",'bla','normalizeTo0dB',1); - + [~, Scpe_cell, ~, found_sync] = Scpe_sig_2sps.tsynch("reference", Symbols{l}, "fs_ref", fsym, "debug_plots", 1); Rx_sig = Scpe_cell{1}; Rx_sig = Rx_sig.normalize("mode","rms"); - + % FFE @@ -227,7 +313,7 @@ for realiz = 1:s.num_realiz output_dbt{l,ri,realiz} = dbt_results; end - + end res = struct(); @@ -244,36 +330,7 @@ for realiz = 1:s.num_realiz end - -function dispersion_vector = getDispersionVector(N, D, ref_zdw, randomize_ZDW, randomkey) -% s.MATLAB version of the Python generator shown above. -% Returns an N×1 vector (ps/(nm·km)). -% -% D is the nominal dispersion magnitude. For D>0 the link is segmented with -% alternating sign (+D, -D, +D, …). For D==0 it is flat (0) except for -% ZDW randomization. The ZDW detuning is ~N(0, 2 nm) around 1310 nm and is -% converted to dispersion via 0.09 ps/(nm·km) per nm. - - % constants (matching the Python code) - meanLambda_nm = 1310; % center wavelength - sigma_nm = 2; % ZDW sigma - Dslope = 0.07; % ps/(nm·km) per nm detuning - - % random ZDW-induced dispersion offset - if randomize_ZDW - rng(randomkey, 'twister'); - rand_zdws_nm = meanLambda_nm + sigma_nm .* randn(N,1); - rand_D = (rand_zdws_nm - ref_zdw) .* Dslope; % ps/(nm·km) - else - rand_D = zeros(N,1); - end - - % nominal segmented pattern (match Python intent; keep length N) - if D > 0 - base = (-1) .^ ((0:N-1).'); % +1,-1,+1,-1,... - else % D == 0 (or anything else) - base = ones(N,1); - end - - dispersion_vector = base .* D + rand_D; % ps/(nm·km) end + + + diff --git a/projects/WDM/WDM_model_16x200.m b/projects/WDM/WDM_model_old.m similarity index 88% rename from projects/WDM/WDM_model_16x200.m rename to projects/WDM/WDM_model_old.m index 7000966..cdc8a74 100644 --- a/projects/WDM/WDM_model_16x200.m +++ b/projects/WDM/WDM_model_old.m @@ -3,23 +3,23 @@ % --- FIRST LINE: evaluate settings located beside this script --- run(fullfile(fileparts(mfilename('fullpath')),'WDM_settings.m')); -s.num_realiz = 2; +num_realiz = 50; s.wavelengthplan = calcWavelengthPlan(16,400e9,1310); % wavelengthplan = [1295,1305,1315,1325]; -link_length = 0; +link_length = 10; pmd = 0.1; gamma = 0.0023; -s.M = 4; -m = floor(log2(s.M)*10)/10; +M = 4; +m = floor(log2(M)*10)/10; fsym = 112e9; fdac = 2*fsym; -fadc = 120000000000; +fadc = 2*fsym; s.random_key = 100; % Laser / s.Modulator vbias_rel = 0.5; -u_pi = 4.6; +u_pi = 3.2; vbias = -vbias_rel*u_pi; laser_linewidth = 0e6; @@ -86,14 +86,13 @@ for realiz = 1:s.num_realiz "mrds_code",0,"mrds_blocklength",512,"duobinary_mode",duob_mode).process(); % Digi_sig.spectrum("fignum",101,"displayname",'bla','normalizeTo0dB',0,'lambda0_nm',1310,'useWavelengthAxis',0); - Lp_awg = Filter('filtdegree',3,"f_cutoff",56e9,"fs",fdac*kover,"filterType",filtertypes.gaussian,"active",true); - El_sig = AWG("fdac",fdac,"f_cutoff",fsym,"lpf_active",1,"kover",kover,"bit_resolution",6,"upsampling_method","samplehold","precomp_sinc_rolloff",0,"H_lpf",Lp_awg,"dac_max",0.6,"dac_min",-0.6).process(Digi_sig); + Lp_awg = Filter('filtdegree',3,"f_cutoff",100e9,"fs",fdac*kover,"filterType",filtertypes.gaussian,"active",true); + El_sig = AWG("fdac",fdac,"f_cutoff",fsym,"lpf_active",1,"kover",kover,"bit_resolution",12,"upsampling_method","samplehold","precomp_sinc_rolloff",0,"H_lpf",Lp_awg,"dac_max",0.6,"dac_min",-0.6).process(Digi_sig); % El_sig = s.M8199B("kover",kover).process(Digi_sig); % El_sig.spectrum("fignum",101,"displayname",'bla','normalizeTo0dB',0,'lambda0_nm',1310,'useWavelengthAxis',0); %%%%% Electrical Driver Amplifier %%%%%% El_sig = El_sig.normalize("mode","oneone"); - El_sig = El_sig .* u_pi .* 0.5; % El_sig = El_sig.setPower(1,"dBm"); % figure;histogram(El_sig.signal); @@ -104,7 +103,7 @@ for realiz = 1:s.num_realiz end Opt_sig_wdm = Optical_Multiplex("fs_in",fdac*kover,"fs_out",upsample_pow*fdac*kover,... - "lambda_center",1310,"random_key",0,"filtype",1,"B",120e9).process(signal_cell); + "lambda_center",1310,"random_key",0,"filtype",1,"B",200e9).process(signal_cell); Opt_sig_wdm = Amplifier("amp_mode","ideal_no_noise","gain_mode","output_power","amplification_db",3+10*log10(N)).process(Opt_sig_wdm); @@ -135,19 +134,21 @@ for realiz = 1:s.num_realiz % Opt_sig_wdm_fib.move_it_spectrum("fignum",100212,"displayname",'bla'); % Opt_sig = Fiber("fsimu",Opt_sig.fs,"fiber_length",s.link_length/1000,"alpha",0.3,"D",0,"lambda0",1310,"s.gamma",0,"Dslope",0.07).process(Opt_sig) - Opt_sig_wdm_demux = Optical_Demultiplex("attenuation",0,"B",200e9,"filtype",1,"fs_out",Opt_sig_wdm_rx.fs/upsample_pow,"fs_in",Opt_sig_wdm_rx.fs,"lambda_center",1310).process(Opt_sig_wdm_fib); - + for ri = 1:length(s.rop) - parfor l = 1:N - - %%%%%% ROP %%%%%% - Opt_sig_wdm_rx = Amplifier("amp_mode","ideal_no_noise","gain_mode","output_power","amplification_db",s.rop(ri)).process(Opt_sig_wdm_demux{l}); % rop+10*log10(N) - + %%%%%% ROP %%%%%% + Opt_sig_wdm_rx = Amplifier("amp_mode","ideal_no_noise","gain_mode","output_power","amplification_db",s.rop(ri)+10*log10(N)).process(Opt_sig_wdm_fib); + + Opt_sig_wdm_demux = Optical_Demultiplex("attenuation",0,"B",200e9,"filtype",1,"fs_out",Opt_sig_wdm_rx.fs/upsample_pow,"fs_in",Opt_sig_wdm_rx.fs,"lambda_center",1310).process(Opt_sig_wdm_rx); + + PD_cell = {}; + for l = 1:N + %%%%%% PD Square Law %%%%%% - assert(fdac*kover==Opt_sig_wdm_rx.fs,'Sampling Frequencies do not match! Check previous steps'); - PD_sig = Photodiode("fsimu",fdac*kover,"dark_current",2e-08,"responsivity",1,"temperature",20,"nep",1.8e-11,"randomkey",s.random_key+l+realiz).process(Opt_sig_wdm_rx); - + assert(fdac*kover==Opt_sig_wdm_demux{l}.fs,'Sampling Frequencies do not match! Check previous steps'); + PD_sig = Photodiode("fsimu",fdac*kover,"dark_current",2e-08,"responsivity",1,"temperature",20,"nep",1.8e-11,"randomkey",s.random_key+l+realiz).process(Opt_sig_wdm_demux{l}); + % PD_sig.spectrum("fignum",222,"displayname",'bla','normalizeTo0dB',1); %%%%%% Low-pass RX (PD, El. Connectors and Scope %%%%%% @@ -155,13 +156,13 @@ for realiz = 1:s.num_realiz PD_sig = Filter('filtdegree',4,"f_cutoff",rx_bwl,"fs",fdac*kover,"filterType",filtertypes.butterworth,"active",true).process(PD_sig); % %%%%%% Low-pass Scope %%%%%% - Lp_scpe = Filter('filtdegree',4,"f_cutoff",80e9,"fs",fadc,"filterType",filtertypes.butterworth,"active",true); - + Lp_scpe = Filter('filtdegree',4,"f_cutoff",110e9,"fs",fadc,"filterType",filtertypes.butterworth,"active",true); + %%%%%% Scope %%%%%% Scpe_sig = Scope("fsimu",fdac*kover,"fadc",fadc,... "delay",0,"fixed_delay",0,"filtertype",filtertypes.butterworth,... "samplingdelay",0,"rand_samplingdelay",0,"freq_offset",0,"samp_jitter",0,... - "adcresolution",8,"quantbuffer",0.1,'block_dc',1,'lpf_active',0,'H_lpf',Lp_scpe).process(PD_sig); + "adcresolution",8,"quantbuffer",0.1,'block_dc',1,'lpf_active',1,'H_lpf',Lp_scpe).process(PD_sig); Scpe_sig_2sps = Scpe_sig.resample("fs_out",2*fsym); % Scpe_sig.spectrum("fignum",222,"displayname",'bla','normalizeTo0dB',1); diff --git a/projects/WDM/WDM_settings.m b/projects/WDM/WDM_settings.m index c64071f..fd40910 100644 --- a/projects/WDM/WDM_settings.m +++ b/projects/WDM/WDM_settings.m @@ -2,60 +2,3 @@ -% Add the imdd_simulation framework to the path -if ispc - addpath(genpath('C:\Users\Silas\Documents\MATLAB\imdd_simulation')); -else - % Linux path on the cluster - addpath(genpath('/work_beegfs/sutef391/imdd_simulation')); -end - -% Quiet the ambiguous CET warning (best is to set TZ in sbatch; see below) -warning('off','MATLAB:datetime:AmbiguousTimeZone'); - -% How many workers? -cpus = str2double(getenv('SLURM_CPUS_PER_TASK')); -if ~isfinite(cpus) || cpus < 1, cpus = max(1, feature('numcores')); end - -% Use a per-job, node-local JobStorageLocation to avoid stale locks on $HOME -% Prefer $TMPDIR if your cluster provides it, else tempdir(). -tmpbase = getenv('TMPDIR'); -if isempty(tmpbase), tmpbase = tempdir; end -jsl = fullfile(tmpbase, sprintf('matlab_jobstorage_%s_%s', ... - getenv('USER'), getenv('SLURM_JOB_ID'))); -if ~exist(jsl,'dir'); mkdir(jsl); end - -% Configure the local cluster explicitly and start the pool -c = parcluster('local'); -c.NumWorkers = cpus; -c.JobStorageLocation = jsl; - -p = gcp('nocreate'); -if isempty(p) || p.NumWorkers ~= cpus - if ~isempty(p), delete(p); end - p = parpool(c, cpus); % avoids the “queued” state -end -fprintf('parpool up with %d workers; JobStorage=%s\n', p.NumWorkers, c.JobStorageLocation); - - - - -% result filename (timestamp + optional job id) -t = datetime('now','TimeZone','local','Format','yyyyMMdd_HHmmss'); -jobid = getenv('SLURM_JOB_ID'); if isempty(jobid), jobid = 'nojid'; end -host = getenv('HOSTNAME'); if isempty(host), host = 'localhost'; end - -% Output directory depends on platform -if ispc - output_root = fullfile('C:\Users\Silas\Documents\MATLAB\Datensätze\FWM_2025\'); -else - output_root = '/work_beegfs/sutef391/results_WDM'; -end -if ~exist(output_root,'dir'), mkdir(output_root); end - -% Build filename -t = datetime('now','TimeZone','local','Format','yyyyMMdd_HHmmss'); -jobid = getenv('SLURM_JOB_ID'); if isempty(jobid), jobid = 'nojid'; end -host = getenv('HOSTNAME'); if isempty(host), host = 'localhost'; end - -fname = sprintf('WDM_%s_%s_%s.mat', char(t), host, jobid); \ No newline at end of file diff --git a/projects/WDM/getDispersionVector.m b/projects/WDM/getDispersionVector.m new file mode 100644 index 0000000..cabd584 --- /dev/null +++ b/projects/WDM/getDispersionVector.m @@ -0,0 +1,32 @@ +function dispersion_vector = getDispersionVector(N, D, ref_zdw, randomize_ZDW, randomkey) +% s.MATLAB version of the Python generator shown above. +% Returns an N×1 vector (ps/(nm·km)). +% +% D is the nominal dispersion magnitude. For D>0 the link is segmented with +% alternating sign (+D, -D, +D, …). For D==0 it is flat (0) except for +% ZDW randomization. The ZDW detuning is ~N(0, 2 nm) around 1310 nm and is +% converted to dispersion via 0.09 ps/(nm·km) per nm. + + % constants (matching the Python code) + meanLambda_nm = 1310; % center wavelength + sigma_nm = 2; % ZDW sigma + Dslope = 0.07; % ps/(nm·km) per nm detuning + + % random ZDW-induced dispersion offset + if randomize_ZDW + rng(randomkey, 'twister'); + rand_zdws_nm = meanLambda_nm + sigma_nm .* randn(N,1); + rand_D = (rand_zdws_nm - ref_zdw) .* Dslope; % ps/(nm·km) + else + rand_D = zeros(N,1); + end + + % nominal segmented pattern (match Python intent; keep length N) + if D > 0 + base = (-1) .^ ((0:N-1).'); % +1,-1,+1,-1,... + else % D == 0 (or anything else) + base = ones(N,1); + end + + dispersion_vector = base .* D + rand_D; % ps/(nm·km) +end \ No newline at end of file