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file naming for WDM simulation

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This commit is contained in:
silas (home)
2025-12-23 08:32:03 +01:00
parent 3d01eaaa50
commit 0647530f69
4 changed files with 210 additions and 177 deletions
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251
projects/WDM/WDM_model.m
View File

@@ -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

47
projects/WDM/WDM_model_16x200.m → projects/WDM/WDM_model_old.m
View File

@@ -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);

57
projects/WDM/WDM_settings.m
View File

@@ -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);

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projects/WDM/getDispersionVector.m Normal file
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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