Final MPI Calculations here
This commit is contained in:
Silas Oettinghaus
@@ -11,14 +11,22 @@ classdef FFE_DCTracking < FFE_plain
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dc_tracking_persistence_gain
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dc_tracking_persistence_gain
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dc_tracking_power_exponent
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dc_tracking_power_exponent
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dc_tracking_buffer_len
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dc_tracking_buffer_len
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dc_tracking_mu_eff_max
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e_dc
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e_dc
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optimize_dc_tracking_params = 0
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dc_tracking_optimization
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dc_tracking_optimization_iter = 0
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dc_tracking_optimization_len
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dc_tracking_optimization_max_evals
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dc_tracking_optimization_delay_weight
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dc_tracking_optimization_smoothing_len
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end
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end
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properties (Access = private)
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properties (Access = private)
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dc_tracking_mu_min = 1e-6
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dc_tracking_mu_min = 1e-6
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dc_tracking_mu_max = 3e-1
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dc_tracking_mu_max = 3e-1
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dc_tracking_mu_eff_min = 0
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dc_tracking_mu_eff_min = 0
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dc_tracking_mu_eff_max = inf
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end
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end
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methods
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methods
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@@ -42,6 +50,7 @@ classdef FFE_DCTracking < FFE_plain
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options.dc_tracking_persistence_gain = 0
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options.dc_tracking_persistence_gain = 0
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options.dc_tracking_power_exponent = 2
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options.dc_tracking_power_exponent = 2
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options.dc_tracking_buffer_len = 1
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options.dc_tracking_buffer_len = 1
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options.dc_tracking_mu_eff_max = inf
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options.decide = false
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options.decide = false
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@@ -50,6 +59,11 @@ classdef FFE_DCTracking < FFE_plain
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options.mu_optimization_len = 2^15
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options.mu_optimization_len = 2^15
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options.plot_mu_optimization = 0
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options.plot_mu_optimization = 0
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options.mu_optimization_fignum = 3010
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options.mu_optimization_fignum = 3010
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options.optimize_dc_tracking_params = 0
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options.dc_tracking_optimization_len = 2^15
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options.dc_tracking_optimization_max_evals = 20
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options.dc_tracking_optimization_delay_weight = 1e-3
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options.dc_tracking_optimization_smoothing_len = 501
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end
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end
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obj@FFE_plain( ...
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obj@FFE_plain( ...
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@@ -75,8 +89,18 @@ classdef FFE_DCTracking < FFE_plain
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obj.dc_tracking_persistence_gain = options.dc_tracking_persistence_gain;
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obj.dc_tracking_persistence_gain = options.dc_tracking_persistence_gain;
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obj.dc_tracking_power_exponent = options.dc_tracking_power_exponent;
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obj.dc_tracking_power_exponent = options.dc_tracking_power_exponent;
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obj.dc_tracking_buffer_len = floor(options.dc_tracking_buffer_len);
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obj.dc_tracking_buffer_len = floor(options.dc_tracking_buffer_len);
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obj.dc_tracking_mu_eff_max = options.dc_tracking_mu_eff_max;
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obj.e_dc = 0;
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obj.e_dc = 0;
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obj.optimize_dc_tracking_params = options.optimize_dc_tracking_params;
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obj.dc_tracking_optimization_len = options.dc_tracking_optimization_len;
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obj.dc_tracking_optimization_max_evals = max(1, ...
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floor(options.dc_tracking_optimization_max_evals));
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obj.dc_tracking_optimization_delay_weight = ...
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max(0,options.dc_tracking_optimization_delay_weight);
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obj.dc_tracking_optimization_smoothing_len = max(1, ...
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floor(options.dc_tracking_optimization_smoothing_len));
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assert(obj.dc_tracking_buffer_len >= 0);
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assert(obj.dc_tracking_buffer_len >= 0);
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end
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end
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@@ -90,6 +114,11 @@ classdef FFE_DCTracking < FFE_plain
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obj.resetTrackingState();
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obj.resetTrackingState();
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end
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end
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if obj.optimize_dc_tracking_params
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obj.optimizeDcTrackingParams(X.signal,D.signal);
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obj.resetTrackingState();
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end
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training = true;
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training = true;
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showviz = false;
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showviz = false;
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obj.equalize(X.signal,D.signal,obj.mu_tr,obj.epochs_tr,obj.len_tr,training,showviz);
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obj.equalize(X.signal,D.signal,obj.mu_tr,obj.epochs_tr,obj.len_tr,training,showviz);
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@@ -134,7 +163,8 @@ classdef FFE_DCTracking < FFE_plain
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if obj.dd_mode
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if obj.dd_mode
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vars = [vars, optimizableVariable("mu_dd",mu_range,"Transform","log")];
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vars = [vars, optimizableVariable("mu_dd",mu_range,"Transform","log")];
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end
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end
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optimize_dc_tracking_mu = obj.dc_tracking_mu ~= 0;
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optimize_dc_tracking_mu = obj.dc_tracking_mu ~= 0 && ...
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~obj.optimize_dc_tracking_params;
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if optimize_dc_tracking_mu
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if optimize_dc_tracking_mu
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vars = [vars, optimizableVariable("dc_tracking_mu",[1e-5,1e-1],"Transform","log")];
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vars = [vars, optimizableVariable("dc_tracking_mu",[1e-5,1e-1],"Transform","log")];
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end
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end
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@@ -175,6 +205,61 @@ classdef FFE_DCTracking < FFE_plain
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end
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end
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end
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end
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function optimizeDcTrackingParams(obj,x,d)
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[x_opt,d_opt,N_opt] = obj.optimizationSignals( ...
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x,d,obj.dc_tracking_optimization_len);
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vars = optimizableVariable( ...
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"dc_tracking_mu",[1e-5,1e-1],"Transform","log");
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initial_values = min(max(obj.dc_tracking_mu,1e-5),1e-1);
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initial_names = "dc_tracking_mu";
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if obj.dc_tracking_adaptive_enabled
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vars = [vars, ...
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optimizableVariable("dc_tracking_persistence_gain",[0,2]), ...
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optimizableVariable("dc_tracking_mu_eff_max",[1e-3,3e-1], ...
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"Transform","log")];
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initial_values = [initial_values, ...
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min(max(obj.dc_tracking_persistence_gain,0),2), ...
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min(max(obj.dc_tracking_mu_eff_max,1e-3),3e-1)];
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initial_names = [initial_names, ...
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"dc_tracking_persistence_gain", "dc_tracking_mu_eff_max"];
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end
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initial_x = array2table(initial_values, ...
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"VariableNames",cellstr(initial_names));
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obj.dc_tracking_optimization_iter = 0;
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fprintf("FFE_DCTracking DC opt uses fixed mu_tr=%9.3e, mu_dd=%9.3e on %d samples / %d symbols\n", ...
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obj.mu_tr,obj.mu_dd,N_opt,numel(d_opt));
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old_rng = rng;
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cleanup_rng = onCleanup(@()rng(old_rng));
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rng(42,"twister");
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obj.dc_tracking_optimization = bayesopt( ...
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@(p)obj.dcTrackingObjective(p,x_opt,d_opt),vars, ...
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"MaxObjectiveEvaluations",obj.dc_tracking_optimization_max_evals, ...
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"InitialX",initial_x, ...
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"AcquisitionFunctionName","expected-improvement-plus", ...
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"IsObjectiveDeterministic",true, ...
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"Verbose",0, ...
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"PlotFcn",[]);
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clear cleanup_rng
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best = obj.dc_tracking_optimization.XAtMinObjective;
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obj.dc_tracking_mu = best.dc_tracking_mu;
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if obj.dc_tracking_adaptive_enabled
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obj.dc_tracking_persistence_gain = ...
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best.dc_tracking_persistence_gain;
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obj.dc_tracking_mu_eff_max = best.dc_tracking_mu_eff_max;
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fprintf("\nFFE_DCTracking DC opt done: dc_tracking_mu=%9.3e, persistence_gain=%6.3f, mu_eff_max=%9.3e, objective=%9.3e\n", ...
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obj.dc_tracking_mu,obj.dc_tracking_persistence_gain, ...
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obj.dc_tracking_mu_eff_max, ...
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obj.dc_tracking_optimization.MinObjective);
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else
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fprintf("\nFFE_DCTracking DC opt done: dc_tracking_mu=%9.3e, objective=%9.3e\n", ...
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obj.dc_tracking_mu,obj.dc_tracking_optimization.MinObjective);
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end
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end
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function objective = muObjective(obj,params,x,d)
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function objective = muObjective(obj,params,x,d)
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old_state = obj.captureTrackingObjectiveState();
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old_state = obj.captureTrackingObjectiveState();
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cleanup = onCleanup(@()obj.restoreTrackingObjectiveState(old_state));
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cleanup = onCleanup(@()obj.restoreTrackingObjectiveState(old_state));
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@@ -218,6 +303,49 @@ classdef FFE_DCTracking < FFE_plain
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clear cleanup
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clear cleanup
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end
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end
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function objective = dcTrackingObjective(obj,params,x,d)
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old_state = obj.captureTrackingObjectiveState();
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cleanup = onCleanup(@()obj.restoreTrackingObjectiveState(old_state));
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obj.applyDcTrackingObjectiveParams(params);
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obj.save_debug = 1;
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obj.resetTrackingState();
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N_tr = min(obj.len_tr,numel(x));
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obj.equalize(x,d,obj.mu_tr,obj.epochs_tr,N_tr,true,false);
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if obj.dd_mode
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[signal,~] = obj.equalize( ...
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x,d,obj.mu_dd,obj.epochs_dd,numel(x),false,false);
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else
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[signal,~] = obj.equalize(x,d,0,1,numel(x),false,false);
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end
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[ber,errors] = obj.berObjective(signal,d);
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[delay_symbols,delay_corr] = obj.dcTrackingDelayObjective(signal,d);
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delay_penalty = obj.dc_tracking_optimization_delay_weight * ...
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abs(delay_symbols) / max(numel(d),1);
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objective = ber + delay_penalty;
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if ~isfinite(objective)
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objective = inf;
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end
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obj.dc_tracking_optimization_iter = ...
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obj.dc_tracking_optimization_iter + 1;
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if obj.dc_tracking_adaptive_enabled
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fprintf("\rFFE_DCTracking DC opt %02d: dc_tracking_mu=%9.3e, persistence_gain=%6.3f, mu_eff_max=%9.3e, BER=%9.3e, delay=%7.0f, corr=%6.3f, obj=%9.3e, errors=%d", ...
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obj.dc_tracking_optimization_iter,params.dc_tracking_mu, ...
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params.dc_tracking_persistence_gain, ...
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params.dc_tracking_mu_eff_max,ber,delay_symbols,delay_corr, ...
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objective,errors);
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else
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fprintf("\rFFE_DCTracking DC opt %02d: dc_tracking_mu=%9.3e, BER=%9.3e, delay=%7.0f, corr=%6.3f, obj=%9.3e, errors=%d", ...
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obj.dc_tracking_optimization_iter,params.dc_tracking_mu, ...
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ber,delay_symbols,delay_corr,objective,errors);
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end
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clear cleanup
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end
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function [y,d_hat] = equalize(obj,x,d,mu,epochs,N,training,showviz)
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function [y,d_hat] = equalize(obj,x,d,mu,epochs,N,training,showviz)
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arguments
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arguments
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obj
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obj
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@@ -392,6 +520,9 @@ classdef FFE_DCTracking < FFE_plain
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state.save_debug = obj.save_debug;
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state.save_debug = obj.save_debug;
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state.debug_struct = obj.debug_struct;
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state.debug_struct = obj.debug_struct;
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state.dc_tracking_mu = obj.dc_tracking_mu;
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state.dc_tracking_mu = obj.dc_tracking_mu;
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state.dc_tracking_persistence_gain = ...
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obj.dc_tracking_persistence_gain;
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state.dc_tracking_mu_eff_max = obj.dc_tracking_mu_eff_max;
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end
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end
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function restoreTrackingObjectiveState(obj,state)
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function restoreTrackingObjectiveState(obj,state)
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@@ -403,6 +534,106 @@ classdef FFE_DCTracking < FFE_plain
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obj.save_debug = state.save_debug;
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obj.save_debug = state.save_debug;
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obj.debug_struct = state.debug_struct;
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obj.debug_struct = state.debug_struct;
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obj.dc_tracking_mu = state.dc_tracking_mu;
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obj.dc_tracking_mu = state.dc_tracking_mu;
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obj.dc_tracking_persistence_gain = ...
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state.dc_tracking_persistence_gain;
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obj.dc_tracking_mu_eff_max = state.dc_tracking_mu_eff_max;
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end
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function applyDcTrackingObjectiveParams(obj,params)
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var_names = string(params.Properties.VariableNames);
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if any(var_names == "dc_tracking_mu")
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obj.dc_tracking_mu = params.dc_tracking_mu;
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end
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if any(var_names == "dc_tracking_persistence_gain")
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obj.dc_tracking_persistence_gain = ...
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params.dc_tracking_persistence_gain;
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end
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if any(var_names == "dc_tracking_mu_eff_max")
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obj.dc_tracking_mu_eff_max = params.dc_tracking_mu_eff_max;
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end
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end
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function [delay_symbols,delay_corr] = ...
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dcTrackingDelayObjective(obj,signal,d)
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delay_symbols = 0;
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delay_corr = 0;
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if ~isfield(obj.debug_struct,"dc_tracking_est") || ...
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isempty(obj.debug_struct.dc_tracking_est)
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return
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end
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smooth_len = obj.dc_tracking_optimization_smoothing_len;
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dc_tracking_est_s = movmean( ...
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obj.debug_struct.dc_tracking_est(:),smooth_len,"omitnan");
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avg_lvl_dc = obj.averageLevelTrace(signal,d,smooth_len);
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xcorr_len = min(numel(dc_tracking_est_s),numel(avg_lvl_dc));
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if xcorr_len < 2
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return
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end
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inv_dc_xcorr = -dc_tracking_est_s(1:xcorr_len);
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avg_lvl_xcorr = avg_lvl_dc(1:xcorr_len);
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inv_dc_xcorr = fillmissing( ...
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inv_dc_xcorr,"linear","EndValues","nearest");
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avg_lvl_xcorr = fillmissing( ...
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avg_lvl_xcorr,"linear","EndValues","nearest");
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inv_dc_xcorr = inv_dc_xcorr - mean(inv_dc_xcorr,"omitnan");
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avg_lvl_xcorr = avg_lvl_xcorr - mean(avg_lvl_xcorr,"omitnan");
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if rms(inv_dc_xcorr) <= eps || rms(avg_lvl_xcorr) <= eps
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return
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end
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[dc_level_xcorr,dc_level_lags] = xcorr( ...
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inv_dc_xcorr,avg_lvl_xcorr,"coeff");
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[delay_corr,delay_idx] = max(dc_level_xcorr);
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delay_symbols = dc_level_lags(delay_idx);
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if ~isfinite(delay_corr)
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delay_corr = 0;
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delay_symbols = 0;
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end
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end
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function avg_lvl_dc = averageLevelTrace(obj,signal,d,smooth_len)
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signal = signal(:);
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d = d(:);
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n_symbols = min(numel(signal),numel(d));
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signal = signal(1:n_symbols);
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d = d(1:n_symbols);
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levels = unique(d);
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avg_for_lvl = NaN(numel(levels),n_symbols);
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for level_idx = 1:numel(levels)
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level_mask = d == levels(level_idx);
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level_samples = signal(level_mask);
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if isempty(level_samples)
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continue
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end
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smooth_window = min(smooth_len,numel(level_samples));
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avg_for_lvl(level_idx,level_mask) = movmean( ...
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level_samples,smooth_window,"omitnan","Endpoints","shrink");
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avg_for_lvl(level_idx,:) = obj.interpolateMissingAverage( ...
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avg_for_lvl(level_idx,:));
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end
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avg_lvl_dc = mean(avg_for_lvl,1,"omitnan").';
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end
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function level_average = interpolateMissingAverage(~,level_average)
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valid_samples = isfinite(level_average);
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if nnz(valid_samples) == 0
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return
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elseif nnz(valid_samples) == 1
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level_average(:) = level_average(valid_samples);
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return
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end
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||||||
|
t = 1:numel(level_average);
|
||||||
|
level_average(~valid_samples) = interp1( ...
|
||||||
|
t(valid_samples),level_average(valid_samples), ...
|
||||||
|
t(~valid_samples),"linear","extrap");
|
||||||
end
|
end
|
||||||
|
|
||||||
function N = validSampleLength(obj,N,x,d)
|
function N = validSampleLength(obj,N,x,d)
|
||||||
|
|||||||
@@ -66,9 +66,12 @@ if run_conventional_ffe
|
|||||||
"plot_mu_optimization", options.debug_plots, ...
|
"plot_mu_optimization", options.debug_plots, ...
|
||||||
"save_debug", eq_save_debug);
|
"save_debug", eq_save_debug);
|
||||||
|
|
||||||
|
storageName = "conventional_ffe";
|
||||||
[ffe_results,equalized_signal] = runFfe(eq_ffe, "Conventional FFE", ...
|
[ffe_results,equalized_signal] = runFfe(eq_ffe, "Conventional FFE", ...
|
||||||
Scpe_sig, Symbols, Tx_bits, options);
|
Scpe_sig, Symbols, Tx_bits, options);
|
||||||
output.conventional_ffe = ffe_results;
|
ffe_results = attachMpiReductionConfig(ffe_results, eq_ffe, storageName, ...
|
||||||
|
"plain_ffe", "baseline", block_update);
|
||||||
|
output.(char(storageName)) = ffe_results;
|
||||||
|
|
||||||
if plot_output_signals
|
if plot_output_signals
|
||||||
plotEqSignals(equalized_signal,Symbols,options,400,-1);
|
plotEqSignals(equalized_signal,Symbols,options,400,-1);
|
||||||
@@ -85,7 +88,7 @@ if run_a2_tracked_levels
|
|||||||
"len_tr", eq_len_tr, ...
|
"len_tr", eq_len_tr, ...
|
||||||
"epochs_tr", eq_epochs_tr, ...
|
"epochs_tr", eq_epochs_tr, ...
|
||||||
"mu_tr", eq_mu_tr, ...
|
"mu_tr", eq_mu_tr, ...
|
||||||
"dd_mode", false, ...
|
"dd_mode", true, ...
|
||||||
"epochs_dd", eq_epochs_dd, ...
|
"epochs_dd", eq_epochs_dd, ...
|
||||||
"mu_dd", 0.012, ...
|
"mu_dd", 0.012, ...
|
||||||
"dc_smoothing_a2", 1, ...
|
"dc_smoothing_a2", 1, ...
|
||||||
@@ -94,9 +97,12 @@ if run_a2_tracked_levels
|
|||||||
"dc_level_weights_a2", [1], ...
|
"dc_level_weights_a2", [1], ...
|
||||||
"save_debug", eq_save_debug);
|
"save_debug", eq_save_debug);
|
||||||
|
|
||||||
|
storageName = "a2_adaptive_levels";
|
||||||
[ffe_results,equalized_signal] = runFfe(eq_ffe, "A2 tracked levels", ...
|
[ffe_results,equalized_signal] = runFfe(eq_ffe, "A2 tracked levels", ...
|
||||||
Scpe_sig, Symbols, Tx_bits, options);
|
Scpe_sig, Symbols, Tx_bits, options);
|
||||||
output.a2_adaptive_levels = ffe_results;
|
ffe_results = attachMpiReductionConfig(ffe_results, eq_ffe, storageName, ...
|
||||||
|
"a2_tracked_levels", "tracked_levels", block_update);
|
||||||
|
output.(char(storageName)) = ffe_results;
|
||||||
|
|
||||||
if plot_output_signals
|
if plot_output_signals
|
||||||
plotEqSignals(equalized_signal,Symbols,options,410,-1);
|
plotEqSignals(equalized_signal,Symbols,options,410,-1);
|
||||||
@@ -122,9 +128,12 @@ if run_a2_residual
|
|||||||
"dc_level_weights_a2", [0.6], ...
|
"dc_level_weights_a2", [0.6], ...
|
||||||
"save_debug", eq_save_debug, "optmize_mus",0);
|
"save_debug", eq_save_debug, "optmize_mus",0);
|
||||||
|
|
||||||
|
storageName = "a2_residual";
|
||||||
[ffe_results,equalized_signal] = runFfe(eq_ffe, "A2 residual", ...
|
[ffe_results,equalized_signal] = runFfe(eq_ffe, "A2 residual", ...
|
||||||
Scpe_sig, Symbols, Tx_bits, options);
|
Scpe_sig, Symbols, Tx_bits, options);
|
||||||
output.a2_residual = ffe_results;
|
ffe_results = attachMpiReductionConfig(ffe_results, eq_ffe, storageName, ...
|
||||||
|
"a2_residual", "residual_correction", block_update);
|
||||||
|
output.(char(storageName)) = ffe_results;
|
||||||
|
|
||||||
if plot_output_signals
|
if plot_output_signals
|
||||||
plotEqSignals(equalized_signal,Symbols,options,420,-1);
|
plotEqSignals(equalized_signal,Symbols,options,420,-1);
|
||||||
@@ -149,9 +158,12 @@ if run_a1
|
|||||||
"dc_avg_update_blocklength_a1", block_update, ...
|
"dc_avg_update_blocklength_a1", block_update, ...
|
||||||
"save_debug", eq_save_debug);
|
"save_debug", eq_save_debug);
|
||||||
|
|
||||||
|
storageName = "a1_ff_dc_avg";
|
||||||
[ffe_results,equalized_signal] = runFfe(eq_ffe, "A1", ...
|
[ffe_results,equalized_signal] = runFfe(eq_ffe, "A1", ...
|
||||||
Scpe_sig, Symbols, Tx_bits, options);
|
Scpe_sig, Symbols, Tx_bits, options);
|
||||||
output.a1_ff_dc_avg = ffe_results;
|
ffe_results = attachMpiReductionConfig(ffe_results, eq_ffe, storageName, ...
|
||||||
|
"a1_moving_average", "ff_dc_avg", block_update);
|
||||||
|
output.(char(storageName)) = ffe_results;
|
||||||
|
|
||||||
if plot_output_signals
|
if plot_output_signals
|
||||||
plotEqSignals(equalized_signal,Symbols,options,430,-1);
|
plotEqSignals(equalized_signal,Symbols,options,430,-1);
|
||||||
@@ -176,12 +188,18 @@ if run_tracking_adaptive
|
|||||||
"dc_tracking_persistence_gain", 0, ...
|
"dc_tracking_persistence_gain", 0, ...
|
||||||
"dc_tracking_buffer_len", block_update, ...
|
"dc_tracking_buffer_len", block_update, ...
|
||||||
"optmize_mus", false, ...
|
"optmize_mus", false, ...
|
||||||
|
"optimize_dc_tracking_params", true, ...
|
||||||
|
"dc_tracking_optimization_len", 2^15, ...
|
||||||
|
"dc_tracking_optimization_max_evals", 20, ...
|
||||||
"plot_mu_optimization", options.debug_plots, ...
|
"plot_mu_optimization", options.debug_plots, ...
|
||||||
"save_debug", eq_save_debug);
|
"save_debug", eq_save_debug);
|
||||||
|
|
||||||
|
storageName = "dc_tracking";
|
||||||
[ffe_results,equalized_signal] = runFfe(eq_ffe, "DC tracking adaptive", ...
|
[ffe_results,equalized_signal] = runFfe(eq_ffe, "DC tracking adaptive", ...
|
||||||
Scpe_sig, Symbols, Tx_bits, options);
|
Scpe_sig, Symbols, Tx_bits, options);
|
||||||
output.dc_tracking = ffe_results;
|
ffe_results = attachMpiReductionConfig(ffe_results, eq_ffe, storageName, ...
|
||||||
|
"dc_tracking", "adaptive", block_update);
|
||||||
|
output.(char(storageName)) = ffe_results;
|
||||||
|
|
||||||
if plot_output_signals
|
if plot_output_signals
|
||||||
plotEqSignals(equalized_signal,Symbols,options,450,-1);
|
plotEqSignals(equalized_signal,Symbols,options,450,-1);
|
||||||
@@ -200,6 +218,60 @@ function [ffe_results,equalized_signal] = runFfe(eq_ffe,description,Scpe_sig,Sym
|
|||||||
ffe_results.metrics.print("description",resultDescription(description,options));
|
ffe_results.metrics.print("description",resultDescription(description,options));
|
||||||
end
|
end
|
||||||
|
|
||||||
|
function ffe_results = attachMpiReductionConfig(ffe_results, eq_ffe, storageName, ...
|
||||||
|
algorithm, algorithmVariant, block_update)
|
||||||
|
ffe_results.mpi_reduction_config = struct( ...
|
||||||
|
"storage_name", char(storageName), ...
|
||||||
|
"algorithm", char(algorithm), ...
|
||||||
|
"algorithm_variant", char(algorithmVariant), ...
|
||||||
|
"eq_class", class(eq_ffe), ...
|
||||||
|
"params", collectMpiReductionParams(eq_ffe, block_update));
|
||||||
|
end
|
||||||
|
|
||||||
|
function params = collectMpiReductionParams(eq_ffe, block_update)
|
||||||
|
params = struct();
|
||||||
|
params.block_update = block_update;
|
||||||
|
|
||||||
|
whitelistedProps = [ ...
|
||||||
|
"sps", ...
|
||||||
|
"order", ...
|
||||||
|
"decide", ...
|
||||||
|
"adaption_technique", ...
|
||||||
|
"len_tr", ...
|
||||||
|
"epochs_tr", ...
|
||||||
|
"mu_tr", ...
|
||||||
|
"dd_mode", ...
|
||||||
|
"epochs_dd", ...
|
||||||
|
"mu_dd", ...
|
||||||
|
"optmize_mus", ...
|
||||||
|
"plot_mu_optimization", ...
|
||||||
|
"save_debug", ...
|
||||||
|
"dc_smoothing_a1", ...
|
||||||
|
"dc_avg_bufferlength_a1", ...
|
||||||
|
"dc_avg_update_blocklength_a1", ...
|
||||||
|
"dc_smoothing_a2", ...
|
||||||
|
"dc_level_avg_bufferlength_a2", ...
|
||||||
|
"dc_level_update_blocklength_a2", ...
|
||||||
|
"dc_level_weights_a2", ...
|
||||||
|
"dc_tracking_mu", ...
|
||||||
|
"dc_tracking_adaptive_enabled", ...
|
||||||
|
"dc_tracking_persistence_gain", ...
|
||||||
|
"dc_tracking_buffer_len", ...
|
||||||
|
"dc_tracking_mu_eff_max", ...
|
||||||
|
"optimize_dc_tracking_params", ...
|
||||||
|
"dc_tracking_optimization_len", ...
|
||||||
|
"dc_tracking_optimization_max_evals", ...
|
||||||
|
"dc_tracking_optimization_delay_weight", ...
|
||||||
|
"dc_tracking_optimization_smoothing_len"];
|
||||||
|
|
||||||
|
for propIdx = 1:numel(whitelistedProps)
|
||||||
|
propName = char(whitelistedProps(propIdx));
|
||||||
|
if isprop(eq_ffe, propName)
|
||||||
|
params.(propName) = eq_ffe.(propName);
|
||||||
|
end
|
||||||
|
end
|
||||||
|
end
|
||||||
|
|
||||||
function description = resultDescription(prefix,options)
|
function description = resultDescription(prefix,options)
|
||||||
sir = options.dataTable.sir;
|
sir = options.dataTable.sir;
|
||||||
if numel(sir) > 1
|
if numel(sir) > 1
|
||||||
|
|||||||
@@ -3,6 +3,9 @@ function output = dsp_runid(run_id, options)
|
|||||||
arguments
|
arguments
|
||||||
run_id
|
run_id
|
||||||
options.append_to_db = 0;
|
options.append_to_db = 0;
|
||||||
|
options.append_mpi_reduction_db (1,1) logical = false;
|
||||||
|
options.mpi_reduction_study_name string = "mpi_reduction_v1";
|
||||||
|
options.mpi_reduction_writer_path string = "";
|
||||||
options.max_occurences = 4;
|
options.max_occurences = 4;
|
||||||
options.start_occurence = 1;
|
options.start_occurence = 1;
|
||||||
options.userParameters = struct();
|
options.userParameters = struct();
|
||||||
@@ -24,7 +27,11 @@ try
|
|||||||
database = [];
|
database = [];
|
||||||
inputSource = normalizeDspInputSource(options.mode);
|
inputSource = normalizeDspInputSource(options.mode);
|
||||||
|
|
||||||
if inputSource == "run_id" || options.append_to_db
|
if options.append_mpi_reduction_db && strlength(options.mpi_reduction_writer_path) > 0
|
||||||
|
addpath(options.mpi_reduction_writer_path);
|
||||||
|
end
|
||||||
|
|
||||||
|
if inputSource == "run_id" || options.append_to_db || options.append_mpi_reduction_db
|
||||||
database = DBHandler("dataBase", [options.dataBase], "type", options.database_type, ...
|
database = DBHandler("dataBase", [options.dataBase], "type", options.database_type, ...
|
||||||
"user", options.user, "password", options.password, ...
|
"user", options.user, "password", options.password, ...
|
||||||
"server", options.server, "port", options.port);
|
"server", options.server, "port", options.port);
|
||||||
@@ -60,6 +67,12 @@ try
|
|||||||
if options.append_to_db
|
if options.append_to_db
|
||||||
appendDspOutputToDatabase(database, run_id, dspOutput);
|
appendDspOutputToDatabase(database, run_id, dspOutput);
|
||||||
end
|
end
|
||||||
|
if options.append_mpi_reduction_db
|
||||||
|
occurrence_idx = options.start_occurence + r - 1;
|
||||||
|
appendMpiReductionDspOutput(database, run_id, occurrence_idx, dspOutput, options, ...
|
||||||
|
"study_name", options.mpi_reduction_study_name, ...
|
||||||
|
"verbose", false);
|
||||||
|
end
|
||||||
end
|
end
|
||||||
|
|
||||||
catch ME
|
catch ME
|
||||||
|
|||||||
@@ -0,0 +1,254 @@
|
|||||||
|
%% BER over SIR from MpiReductionResults
|
||||||
|
% 1) gather data from the database
|
||||||
|
% 2) clean data and remove per-curve outliers
|
||||||
|
% 3) plot BER over SIR grouped by algorithm
|
||||||
|
|
||||||
|
clear; clc;
|
||||||
|
|
||||||
|
%% 1) Gather data
|
||||||
|
|
||||||
|
studyName = "pam4_112_greater_3153";
|
||||||
|
pathLengthToPlot = 0;
|
||||||
|
selectedBlockUpdate = 1; % set [] to pool all block_update values
|
||||||
|
selectedPamLevels = []; % set [] to use all PAM levels in the query result
|
||||||
|
selectedAlgorithms = []; % set [] to use all algorithms in the query result
|
||||||
|
|
||||||
|
useBoundedLines = true;
|
||||||
|
usePolyfit = true;
|
||||||
|
polyfitOrderMax = 4;
|
||||||
|
maxBerForPlot = 0.1;
|
||||||
|
|
||||||
|
db = DBHandler( ...
|
||||||
|
"dataBase", "labor", ...
|
||||||
|
"type", "mysql", ...
|
||||||
|
"server", "192.168.178.192", ...
|
||||||
|
"user", "silas", ...
|
||||||
|
"password", "silas");
|
||||||
|
db.refresh();
|
||||||
|
|
||||||
|
fp = QueryFilter();
|
||||||
|
fp.where('Runs', 'interference_path_length', 'EQUALS', pathLengthToPlot);
|
||||||
|
fp.where('Runs', 'fiber_length', 'EQUALS', 0);
|
||||||
|
fp.where('Runs', 'db_mode', 'EQUALS', '"no_db"');
|
||||||
|
fp.where('MpiReductionResults', 'study_name', 'EQUALS', char(studyName));
|
||||||
|
if ~isempty(selectedBlockUpdate)
|
||||||
|
fp.where('MpiReductionResults', 'block_update', 'EQUALS', selectedBlockUpdate);
|
||||||
|
end
|
||||||
|
|
||||||
|
selectedFields = { ...
|
||||||
|
'Runs.run_id', ...
|
||||||
|
'Runs.sir', ...
|
||||||
|
'Runs.pam_level', ...
|
||||||
|
'Runs.symbolrate', ...
|
||||||
|
'Runs.interference_path_length', ...
|
||||||
|
'Runs.power_mpi_interference', ...
|
||||||
|
'MpiReductionResults.occurrence_idx', ...
|
||||||
|
'MpiReductionResults.storage_name', ...
|
||||||
|
'MpiReductionResults.algorithm', ...
|
||||||
|
'MpiReductionResults.algorithm_variant', ...
|
||||||
|
'MpiReductionResults.eq_class', ...
|
||||||
|
'MpiReductionResults.block_update', ...
|
||||||
|
'MpiReductionResults.BER', ...
|
||||||
|
'MpiReductionResults.BER_precoded', ...
|
||||||
|
'MpiReductionResults.SNR', ...
|
||||||
|
'MpiReductionResults.GMI', ...
|
||||||
|
'MpiReductionResults.AIR'};
|
||||||
|
selectedFields = selectedFields(:);
|
||||||
|
|
||||||
|
[rawData, query] = db.queryDB(fp, selectedFields);
|
||||||
|
disp(query);
|
||||||
|
fprintf("Fetched %d MPI reduction rows.\n", height(rawData));
|
||||||
|
|
||||||
|
%% 2) Clean data
|
||||||
|
|
||||||
|
data = rawData;
|
||||||
|
numericFields = ["run_id", "sir", "pam_level", "symbolrate", ...
|
||||||
|
"interference_path_length", "occurrence_idx", "block_update", ...
|
||||||
|
"power_mpi_interference", "BER", "BER_precoded", "SNR", "GMI", "AIR"];
|
||||||
|
for fieldIdx = 1:numel(numericFields)
|
||||||
|
fieldName = numericFields(fieldIdx);
|
||||||
|
if ismember(fieldName, string(data.Properties.VariableNames))
|
||||||
|
data.(char(fieldName)) = numericColumn(data.(char(fieldName)));
|
||||||
|
end
|
||||||
|
end
|
||||||
|
|
||||||
|
stringFields = ["storage_name", "algorithm", "algorithm_variant", "eq_class"];
|
||||||
|
for fieldIdx = 1:numel(stringFields)
|
||||||
|
fieldName = stringFields(fieldIdx);
|
||||||
|
if ismember(fieldName, string(data.Properties.VariableNames))
|
||||||
|
data.(char(fieldName)) = stringColumn(data.(char(fieldName)));
|
||||||
|
end
|
||||||
|
end
|
||||||
|
|
||||||
|
data = data(isfinite(data.BER) & data.BER > 0 & data.BER < maxBerForPlot, :);
|
||||||
|
data.sir_exact = -7 - data.power_mpi_interference;
|
||||||
|
if isempty(data)
|
||||||
|
warning("PLOT_mpi_reduction_db_ber_vs_sir:NoRows", ...
|
||||||
|
"No rows remain after initial BER/path/study/block filtering.");
|
||||||
|
return
|
||||||
|
end
|
||||||
|
|
||||||
|
if isempty(selectedPamLevels)
|
||||||
|
selectedPamLevels = unique(data.pam_level(isfinite(data.pam_level))).';
|
||||||
|
else
|
||||||
|
data = data(ismember(data.pam_level, selectedPamLevels), :);
|
||||||
|
end
|
||||||
|
|
||||||
|
if isempty(selectedAlgorithms)
|
||||||
|
selectedAlgorithms = unique(data.algorithm, "stable").';
|
||||||
|
else
|
||||||
|
selectedAlgorithms = string(selectedAlgorithms);
|
||||||
|
data = data(ismember(data.algorithm, selectedAlgorithms), :);
|
||||||
|
end
|
||||||
|
|
||||||
|
if isempty(data)
|
||||||
|
warning("PLOT_mpi_reduction_db_ber_vs_sir:NoSelectedRows", ...
|
||||||
|
"No rows remain after selectedPamLevels/selectedAlgorithms filtering.");
|
||||||
|
return
|
||||||
|
end
|
||||||
|
|
||||||
|
data.clean_keep = true(height(data), 1);
|
||||||
|
[groupId, groupPam, groupAlgorithm, groupSir] = findgroups(data.pam_level, data.algorithm, data.sir);
|
||||||
|
for groupIdx = 1:max(groupId)
|
||||||
|
rowMask = groupId == groupIdx;
|
||||||
|
berValues = data.BER(rowMask);
|
||||||
|
if nnz(rowMask) > 3
|
||||||
|
data.clean_keep(rowMask) = ~isoutlier(berValues);
|
||||||
|
end
|
||||||
|
end
|
||||||
|
cleanData = data(data.clean_keep, :);
|
||||||
|
|
||||||
|
summaryTable = groupsummary(cleanData, ["pam_level", "algorithm", "sir"], ...
|
||||||
|
{"mean", "min", "max"}, "BER");
|
||||||
|
sirExactTable = groupsummary(cleanData, ["pam_level", "algorithm", "sir"], ...
|
||||||
|
"median", "sir_exact");
|
||||||
|
summaryTable.sir_exact = sirExactTable.median_sir_exact;
|
||||||
|
summaryTable = sortrows(summaryTable, ["pam_level", "algorithm", "sir"]);
|
||||||
|
|
||||||
|
fprintf("Cleaned to %d rows across %d PAM/algorithm/SIR groups.\n", ...
|
||||||
|
height(cleanData), height(summaryTable));
|
||||||
|
disp(groupcounts(cleanData, ["pam_level", "algorithm"]));
|
||||||
|
|
||||||
|
%% 3) Plot data
|
||||||
|
|
||||||
|
if exist("linspecer", "file")
|
||||||
|
algColors = linspecer(numel(selectedAlgorithms));
|
||||||
|
else
|
||||||
|
algColors = lines(numel(selectedAlgorithms));
|
||||||
|
end
|
||||||
|
|
||||||
|
figure(); clf;
|
||||||
|
tiledlayout(numel(selectedPamLevels), 1, "TileSpacing", "compact");
|
||||||
|
|
||||||
|
for pamIdx = 1:numel(selectedPamLevels)
|
||||||
|
pamLevel = selectedPamLevels(pamIdx);
|
||||||
|
nexttile; hold on;
|
||||||
|
|
||||||
|
for algIdx = 1:numel(selectedAlgorithms)
|
||||||
|
algorithmName = selectedAlgorithms(algIdx);
|
||||||
|
algColor = algColors(algIdx, :);
|
||||||
|
rawMask = cleanData.pam_level == pamLevel & cleanData.algorithm == algorithmName;
|
||||||
|
curveMask = summaryTable.pam_level == pamLevel & summaryTable.algorithm == algorithmName;
|
||||||
|
|
||||||
|
if ~any(curveMask)
|
||||||
|
continue
|
||||||
|
end
|
||||||
|
scatter(cleanData.sir_exact(rawMask), cleanData.BER(rawMask), ...
|
||||||
|
30, ...
|
||||||
|
"Marker", ".", ...
|
||||||
|
"MarkerEdgeColor", algColor, ...
|
||||||
|
"HandleVisibility", "off");
|
||||||
|
|
||||||
|
sirValues = summaryTable.sir_exact(curveMask).';
|
||||||
|
meanBer = summaryTable.mean_BER(curveMask).';
|
||||||
|
minBer = summaryTable.min_BER(curveMask).';
|
||||||
|
maxBer = summaryTable.max_BER(curveMask).';
|
||||||
|
valid = isfinite(sirValues) & isfinite(meanBer) & meanBer > 0;
|
||||||
|
|
||||||
|
if useBoundedLines && exist("boundedline", "file") && any(valid)
|
||||||
|
yLower = max(meanBer - minBer, 0);
|
||||||
|
yUpper = max(maxBer - meanBer, 0);
|
||||||
|
yBounds = [yLower(:), yUpper(:)];
|
||||||
|
|
||||||
|
[hl, hp] = boundedline(sirValues(valid).', meanBer(valid).', yBounds(valid, :), ...
|
||||||
|
'alpha', 'transparency', 0.08, ...
|
||||||
|
'cmap', algColor, ...
|
||||||
|
'nan', 'fill', ...
|
||||||
|
'orientation', 'vert');
|
||||||
|
set(hl, "LineStyle", "none", "Marker", "none", "HandleVisibility", "off");
|
||||||
|
set(hp, "LineStyle", "none", "HandleVisibility", "off");
|
||||||
|
end
|
||||||
|
|
||||||
|
plot(sirValues(valid), meanBer(valid), ...
|
||||||
|
"LineStyle", "none", ...
|
||||||
|
"Marker", "o", ...
|
||||||
|
"MarkerSize", 5, ...
|
||||||
|
"LineWidth", 1.2, ...
|
||||||
|
"Color", algColor, ...
|
||||||
|
"MarkerFaceColor", algColor, ...
|
||||||
|
"DisplayName", char(algorithmName));
|
||||||
|
|
||||||
|
if usePolyfit
|
||||||
|
fitMask = valid & meanBer > 0;
|
||||||
|
if nnz(fitMask) >= 2
|
||||||
|
fitOrder = min(polyfitOrderMax, nnz(fitMask) - 1);
|
||||||
|
fitCoeff = polyfit(sirValues(fitMask), log10(meanBer(fitMask)), fitOrder);
|
||||||
|
xFit = linspace(min(sirValues(fitMask)), max(sirValues(fitMask)), 300);
|
||||||
|
yFit = 10 .^ polyval(fitCoeff, xFit);
|
||||||
|
|
||||||
|
plot(xFit, yFit, ...
|
||||||
|
"LineStyle", "--", ...
|
||||||
|
"LineWidth", 1.1, ...
|
||||||
|
"Color", algColor, ...
|
||||||
|
"HandleVisibility", "off");
|
||||||
|
end
|
||||||
|
end
|
||||||
|
end
|
||||||
|
|
||||||
|
yline(2.2e-4, "LineWidth", 1, "LineStyle", "--", "HandleVisibility", "off");
|
||||||
|
yline(3.8e-3, "LineWidth", 1, "LineStyle", "--", "HandleVisibility", "off");
|
||||||
|
yline(2e-2, "LineWidth", 1, "LineStyle", "--", "HandleVisibility", "off");
|
||||||
|
|
||||||
|
title(sprintf("PAM %.0f, path %.0f m, block update %s", ...
|
||||||
|
pamLevel, pathLengthToPlot, blockUpdateLabel(selectedBlockUpdate)));
|
||||||
|
xlabel("SIR (dB)");
|
||||||
|
ylabel("BER");
|
||||||
|
set(gca, "YScale", "log");
|
||||||
|
ylim([9e-5, maxBerForPlot]);
|
||||||
|
grid on;
|
||||||
|
box on;
|
||||||
|
legend("Location", "best", "Interpreter", "none");
|
||||||
|
end
|
||||||
|
|
||||||
|
if exist("beautifyBERplot", "file")
|
||||||
|
beautifyBERplot("logscale", true, "setcolors", false, "setmarkers", false);
|
||||||
|
end
|
||||||
|
|
||||||
|
%% Local helpers
|
||||||
|
|
||||||
|
function values = numericColumn(values)
|
||||||
|
if iscell(values)
|
||||||
|
values = string(values);
|
||||||
|
end
|
||||||
|
if isstring(values) || ischar(values)
|
||||||
|
values = str2double(values);
|
||||||
|
end
|
||||||
|
values = double(values);
|
||||||
|
end
|
||||||
|
|
||||||
|
function values = stringColumn(values)
|
||||||
|
if iscell(values)
|
||||||
|
values = string(values);
|
||||||
|
elseif ischar(values)
|
||||||
|
values = string(values);
|
||||||
|
end
|
||||||
|
values = strip(string(values));
|
||||||
|
end
|
||||||
|
|
||||||
|
function label = blockUpdateLabel(selectedBlockUpdate)
|
||||||
|
if isempty(selectedBlockUpdate)
|
||||||
|
label = "pooled";
|
||||||
|
else
|
||||||
|
label = string(selectedBlockUpdate);
|
||||||
|
end
|
||||||
|
end
|
||||||
99
projects/Diss/MPI_revisit/db/appendMpiReductionDspOutput.m
Normal file
99
projects/Diss/MPI_revisit/db/appendMpiReductionDspOutput.m
Normal file
@@ -0,0 +1,99 @@
|
|||||||
|
function [summary, rows] = appendMpiReductionDspOutput(db, run_id, occurrence_idx, dspOutput, dsp_options, options)
|
||||||
|
%appendMpiReductionDspOutput Store one DSP occurrence in MpiReductionResults.
|
||||||
|
|
||||||
|
arguments
|
||||||
|
db
|
||||||
|
run_id
|
||||||
|
occurrence_idx
|
||||||
|
dspOutput struct
|
||||||
|
dsp_options struct = struct()
|
||||||
|
options.study_name string = "mpi_reduction_v1"
|
||||||
|
options.dry_run (1,1) logical = false
|
||||||
|
options.verbose (1,1) logical = false
|
||||||
|
end
|
||||||
|
|
||||||
|
summary = emptySummary();
|
||||||
|
rows = {};
|
||||||
|
|
||||||
|
packageNames = fieldnames(dspOutput);
|
||||||
|
if isempty(packageNames)
|
||||||
|
return
|
||||||
|
end
|
||||||
|
|
||||||
|
block_update = resolveBlockUpdate(dspOutput, dsp_options);
|
||||||
|
wh = DataStorage(struct( ...
|
||||||
|
"run_id", double(run_id), ...
|
||||||
|
"block_update", double(block_update)));
|
||||||
|
|
||||||
|
hasPackages = false;
|
||||||
|
for packageIdx = 1:numel(packageNames)
|
||||||
|
packageName = packageNames{packageIdx};
|
||||||
|
package = dspOutput.(packageName);
|
||||||
|
if isempty(package)
|
||||||
|
continue
|
||||||
|
end
|
||||||
|
|
||||||
|
if iscell(package)
|
||||||
|
packageCell = package;
|
||||||
|
else
|
||||||
|
packageCell = {package};
|
||||||
|
end
|
||||||
|
|
||||||
|
wh.addStorage(packageName);
|
||||||
|
wh.addValueToStorageByLinIdx(packageCell, packageName, 1);
|
||||||
|
hasPackages = true;
|
||||||
|
end
|
||||||
|
|
||||||
|
if ~hasPackages
|
||||||
|
return
|
||||||
|
end
|
||||||
|
|
||||||
|
dsp_options_local = dsp_options;
|
||||||
|
dsp_options_local.start_occurence = occurrence_idx;
|
||||||
|
dsp_options_local.userParameters.block_update = block_update;
|
||||||
|
|
||||||
|
[summary, rows] = appendMpiReductionWarehouse(db, wh, run_id, dsp_options_local, ...
|
||||||
|
"study_name", options.study_name, ...
|
||||||
|
"dry_run", options.dry_run, ...
|
||||||
|
"verbose", options.verbose);
|
||||||
|
|
||||||
|
end
|
||||||
|
|
||||||
|
function summary = emptySummary()
|
||||||
|
summary = struct( ...
|
||||||
|
"rows_considered", 0, ...
|
||||||
|
"rows_inserted", 0, ...
|
||||||
|
"rows_skipped_duplicate", 0, ...
|
||||||
|
"rows_skipped_existing_key", 0, ...
|
||||||
|
"rows_skipped_empty", 0);
|
||||||
|
end
|
||||||
|
|
||||||
|
function block_update = resolveBlockUpdate(dspOutput, dsp_options)
|
||||||
|
if isfield(dsp_options, "userParameters") && ...
|
||||||
|
isfield(dsp_options.userParameters, "block_update") && ...
|
||||||
|
isscalar(dsp_options.userParameters.block_update)
|
||||||
|
block_update = dsp_options.userParameters.block_update;
|
||||||
|
return
|
||||||
|
end
|
||||||
|
|
||||||
|
packageNames = fieldnames(dspOutput);
|
||||||
|
for packageIdx = 1:numel(packageNames)
|
||||||
|
package = dspOutput.(packageNames{packageIdx});
|
||||||
|
if isempty(package)
|
||||||
|
continue
|
||||||
|
end
|
||||||
|
if iscell(package)
|
||||||
|
package = package{1};
|
||||||
|
end
|
||||||
|
if isstruct(package) && ...
|
||||||
|
isfield(package, "mpi_reduction_config") && ...
|
||||||
|
isfield(package.mpi_reduction_config, "params") && ...
|
||||||
|
isfield(package.mpi_reduction_config.params, "block_update")
|
||||||
|
block_update = package.mpi_reduction_config.params.block_update;
|
||||||
|
return
|
||||||
|
end
|
||||||
|
end
|
||||||
|
|
||||||
|
error("appendMpiReductionDspOutput:MissingBlockUpdate", ...
|
||||||
|
"Could not resolve scalar block_update from dsp_options or package metadata.");
|
||||||
|
end
|
||||||
307
projects/Diss/MPI_revisit/db/appendMpiReductionWarehouse.m
Normal file
307
projects/Diss/MPI_revisit/db/appendMpiReductionWarehouse.m
Normal file
@@ -0,0 +1,307 @@
|
|||||||
|
function [summary, rows] = appendMpiReductionWarehouse(db, wh, run_ids, dsp_options, options)
|
||||||
|
%appendMpiReductionWarehouse Store MPI reduction warehouse entries in MySQL.
|
||||||
|
|
||||||
|
arguments
|
||||||
|
db
|
||||||
|
wh
|
||||||
|
run_ids
|
||||||
|
dsp_options struct
|
||||||
|
options.study_name string = "mpi_reduction_v1"
|
||||||
|
options.dry_run (1,1) logical = false
|
||||||
|
options.verbose (1,1) logical = true
|
||||||
|
end
|
||||||
|
|
||||||
|
ensureTableVisible(db);
|
||||||
|
|
||||||
|
storageNames = fieldnames(wh.sto);
|
||||||
|
summary = struct( ...
|
||||||
|
"rows_considered", 0, ...
|
||||||
|
"rows_inserted", 0, ...
|
||||||
|
"rows_skipped_duplicate", 0, ...
|
||||||
|
"rows_skipped_existing_key", 0, ...
|
||||||
|
"rows_skipped_empty", 0);
|
||||||
|
rows = {};
|
||||||
|
|
||||||
|
for storageIdx = 1:numel(storageNames)
|
||||||
|
storageName = storageNames{storageIdx};
|
||||||
|
storageArray = wh.sto.(storageName);
|
||||||
|
|
||||||
|
for linIdx = 1:numel(storageArray)
|
||||||
|
packageCell = storageArray{linIdx};
|
||||||
|
if isempty(packageCell)
|
||||||
|
summary.rows_skipped_empty = summary.rows_skipped_empty + 1;
|
||||||
|
continue
|
||||||
|
end
|
||||||
|
|
||||||
|
phys = physicalCoordinates(wh, linIdx);
|
||||||
|
run_id = resolveRunId(phys, run_ids);
|
||||||
|
block_update = resolveBlockUpdate(phys, dsp_options);
|
||||||
|
packageCell = normalizePackageCell(packageCell);
|
||||||
|
|
||||||
|
for packageIdx = 1:numel(packageCell)
|
||||||
|
package = packageCell{packageIdx};
|
||||||
|
if isempty(package) || ~isstruct(package) || ~isfield(package, "metrics")
|
||||||
|
summary.rows_skipped_empty = summary.rows_skipped_empty + 1;
|
||||||
|
continue
|
||||||
|
end
|
||||||
|
|
||||||
|
occurrence_idx = startOccurrence(dsp_options) + packageIdx - 1;
|
||||||
|
row = buildRow(db, package, storageName, run_id, occurrence_idx, ...
|
||||||
|
block_update, options.study_name);
|
||||||
|
summary.rows_considered = summary.rows_considered + 1;
|
||||||
|
rows{end+1,1} = row; %#ok<AGROW>
|
||||||
|
|
||||||
|
if options.dry_run
|
||||||
|
continue
|
||||||
|
end
|
||||||
|
|
||||||
|
if resultHashExists(db, row.result_hash)
|
||||||
|
summary.rows_skipped_duplicate = summary.rows_skipped_duplicate + 1;
|
||||||
|
if options.verbose
|
||||||
|
fprintf("MPI reduction DB: skipped duplicate %s, run_id=%d, occurrence=%d, block_update=%d\n", ...
|
||||||
|
row.storage_name, row.run_id, row.occurrence_idx, row.block_update);
|
||||||
|
end
|
||||||
|
continue
|
||||||
|
end
|
||||||
|
|
||||||
|
if uniqueResultKeyExists(db, row)
|
||||||
|
summary.rows_skipped_existing_key = summary.rows_skipped_existing_key + 1;
|
||||||
|
if options.verbose
|
||||||
|
fprintf("MPI reduction DB: skipped existing key %s, run_id=%d, occurrence=%d, block_update=%d\n", ...
|
||||||
|
row.storage_name, row.run_id, row.occurrence_idx, row.block_update);
|
||||||
|
end
|
||||||
|
continue
|
||||||
|
end
|
||||||
|
|
||||||
|
db.appendToTable("MpiReductionResults", row);
|
||||||
|
summary.rows_inserted = summary.rows_inserted + 1;
|
||||||
|
end
|
||||||
|
end
|
||||||
|
end
|
||||||
|
|
||||||
|
if options.verbose
|
||||||
|
fprintf("MPI reduction DB: considered %d rows, inserted %d, duplicates %d, existing keys %d, empty %d\n", ...
|
||||||
|
summary.rows_considered, summary.rows_inserted, ...
|
||||||
|
summary.rows_skipped_duplicate, summary.rows_skipped_existing_key, ...
|
||||||
|
summary.rows_skipped_empty);
|
||||||
|
end
|
||||||
|
|
||||||
|
end
|
||||||
|
|
||||||
|
function ensureTableVisible(db)
|
||||||
|
if ~isfield(db.tables, "MpiReductionResults")
|
||||||
|
db.refresh();
|
||||||
|
end
|
||||||
|
|
||||||
|
if ~isfield(db.tables, "MpiReductionResults")
|
||||||
|
error("appendMpiReductionWarehouse:MissingTable", ...
|
||||||
|
"Table MpiReductionResults is not visible to DBHandler. Create the table and call db.refresh().");
|
||||||
|
end
|
||||||
|
end
|
||||||
|
|
||||||
|
function phys = physicalCoordinates(wh, linIdx)
|
||||||
|
phys = struct();
|
||||||
|
[physValues, physNames] = wh.getPhysIndicesByLinIndex(linIdx);
|
||||||
|
|
||||||
|
for physIdx = 1:numel(physNames)
|
||||||
|
name = char(physNames{physIdx});
|
||||||
|
phys.(name) = physValues{physIdx};
|
||||||
|
end
|
||||||
|
end
|
||||||
|
|
||||||
|
function run_id = resolveRunId(phys, run_ids)
|
||||||
|
if isfield(phys, "run_id")
|
||||||
|
run_id = phys.run_id;
|
||||||
|
return
|
||||||
|
end
|
||||||
|
|
||||||
|
if isscalar(run_ids)
|
||||||
|
run_id = run_ids;
|
||||||
|
return
|
||||||
|
end
|
||||||
|
|
||||||
|
error("appendMpiReductionWarehouse:MissingRunId", ...
|
||||||
|
"Warehouse has no run_id axis, but run_ids is not scalar.");
|
||||||
|
end
|
||||||
|
|
||||||
|
function block_update = resolveBlockUpdate(phys, dsp_options)
|
||||||
|
if isfield(phys, "block_update")
|
||||||
|
block_update = phys.block_update;
|
||||||
|
return
|
||||||
|
end
|
||||||
|
|
||||||
|
if isfield(dsp_options, "userParameters") && ...
|
||||||
|
isfield(dsp_options.userParameters, "block_update") && ...
|
||||||
|
isscalar(dsp_options.userParameters.block_update)
|
||||||
|
block_update = dsp_options.userParameters.block_update;
|
||||||
|
return
|
||||||
|
end
|
||||||
|
|
||||||
|
error("appendMpiReductionWarehouse:MissingBlockUpdate", ...
|
||||||
|
"Could not resolve block_update from warehouse coordinates or scalar userParameters.");
|
||||||
|
end
|
||||||
|
|
||||||
|
function packageCell = normalizePackageCell(packageCell)
|
||||||
|
if ~iscell(packageCell)
|
||||||
|
packageCell = {packageCell};
|
||||||
|
end
|
||||||
|
end
|
||||||
|
|
||||||
|
function occurrence = startOccurrence(dsp_options)
|
||||||
|
occurrence = 1;
|
||||||
|
if isfield(dsp_options, "start_occurence")
|
||||||
|
occurrence = dsp_options.start_occurence;
|
||||||
|
end
|
||||||
|
end
|
||||||
|
|
||||||
|
function row = buildRow(db, package, storageName, run_id, occurrence_idx, block_update, study_name)
|
||||||
|
config = fieldOr(package, "mpi_reduction_config", fallbackConfig(storageName, block_update));
|
||||||
|
params = fieldOr(config, "params", struct());
|
||||||
|
if isempty(params)
|
||||||
|
params = struct();
|
||||||
|
end
|
||||||
|
|
||||||
|
metrics = package.metrics;
|
||||||
|
if isobject(metrics) && ismethod(metrics, "toStruct")
|
||||||
|
metrics = metrics.toStruct();
|
||||||
|
end
|
||||||
|
|
||||||
|
param_json = jsonencode(params);
|
||||||
|
if strlength(string(param_json)) == 0
|
||||||
|
param_json = "{}";
|
||||||
|
end
|
||||||
|
|
||||||
|
row = struct();
|
||||||
|
row.run_id = double(run_id);
|
||||||
|
row.occurrence_idx = double(occurrence_idx);
|
||||||
|
row.study_name = char(study_name);
|
||||||
|
row.storage_name = char(fieldOr(config, "storage_name", storageName));
|
||||||
|
row.algorithm = char(fieldOr(config, "algorithm", "unknown"));
|
||||||
|
row.algorithm_variant = char(fieldOr(config, "algorithm_variant", ""));
|
||||||
|
row.eq_class = char(fieldOr(config, "eq_class", "unknown"));
|
||||||
|
row.block_update = double(block_update);
|
||||||
|
|
||||||
|
row.sps = scalarParam(params, "sps");
|
||||||
|
row.eq_order = scalarParam(params, "order");
|
||||||
|
row.len_tr = scalarParam(params, "len_tr");
|
||||||
|
row.epochs_tr = scalarParam(params, "epochs_tr");
|
||||||
|
row.mu_tr = scalarParam(params, "mu_tr");
|
||||||
|
row.dd_mode = logicalParam(params, "dd_mode");
|
||||||
|
row.epochs_dd = scalarParam(params, "epochs_dd");
|
||||||
|
row.mu_dd = scalarParam(params, "mu_dd");
|
||||||
|
|
||||||
|
row.numBits = metricScalar(metrics, "numBits", 0);
|
||||||
|
row.numBitErr = metricScalar(metrics, "numBitErr", 0);
|
||||||
|
row.BER = metricScalar(metrics, "BER", NaN);
|
||||||
|
row.numBitErr_precoded = metricScalar(metrics, "numBitErr_precoded", NaN);
|
||||||
|
row.BER_precoded = metricScalar(metrics, "BER_precoded", NaN);
|
||||||
|
row.SNR = metricScalar(metrics, "SNR", NaN);
|
||||||
|
row.SNR_level = metricJson(metrics, "SNR_level");
|
||||||
|
row.GMI = metricScalar(metrics, "GMI", NaN);
|
||||||
|
row.AIR = metricScalar(metrics, "AIR", NaN);
|
||||||
|
row.EVM = metricScalar(metrics, "EVM", NaN);
|
||||||
|
row.EVM_level = metricJson(metrics, "EVM_level");
|
||||||
|
row.STD = metricScalar(metrics, "STD", NaN);
|
||||||
|
row.STD_level = metricJson(metrics, "STD_level");
|
||||||
|
row.STDrx = metricScalar(metrics, "STDrx", NaN);
|
||||||
|
row.STDrx_level = metricJson(metrics, "STDrx_level");
|
||||||
|
row.Alpha = firstFiniteScalar(fieldOr(metrics, "Alpha", NaN));
|
||||||
|
|
||||||
|
row.param_json = char(param_json);
|
||||||
|
row.param_hash = db.calcHash(params);
|
||||||
|
row.result_hash = db.calcHash(row);
|
||||||
|
end
|
||||||
|
|
||||||
|
function config = fallbackConfig(storageName, block_update)
|
||||||
|
params = struct("block_update", block_update);
|
||||||
|
config = struct( ...
|
||||||
|
"storage_name", storageName, ...
|
||||||
|
"algorithm", "unknown", ...
|
||||||
|
"algorithm_variant", "", ...
|
||||||
|
"eq_class", "unknown", ...
|
||||||
|
"params", params);
|
||||||
|
end
|
||||||
|
|
||||||
|
function value = fieldOr(s, fieldName, defaultValue)
|
||||||
|
fieldName = char(fieldName);
|
||||||
|
if isstruct(s) && isfield(s, fieldName) && ~isempty(s.(fieldName))
|
||||||
|
value = s.(fieldName);
|
||||||
|
else
|
||||||
|
value = defaultValue;
|
||||||
|
end
|
||||||
|
end
|
||||||
|
|
||||||
|
function value = scalarParam(params, fieldName)
|
||||||
|
value = firstFiniteScalar(fieldOr(params, fieldName, NaN));
|
||||||
|
end
|
||||||
|
|
||||||
|
function value = logicalParam(params, fieldName)
|
||||||
|
value = firstFiniteScalar(fieldOr(params, fieldName, false));
|
||||||
|
if isnan(value)
|
||||||
|
value = false;
|
||||||
|
else
|
||||||
|
value = logical(value);
|
||||||
|
end
|
||||||
|
end
|
||||||
|
|
||||||
|
function value = metricScalar(metrics, fieldName, defaultValue)
|
||||||
|
value = firstFiniteScalar(fieldOr(metrics, fieldName, defaultValue));
|
||||||
|
end
|
||||||
|
|
||||||
|
function value = metricJson(metrics, fieldName)
|
||||||
|
metricValue = fieldOr(metrics, fieldName, []);
|
||||||
|
value = char(jsonencode(metricValue));
|
||||||
|
end
|
||||||
|
|
||||||
|
function value = firstFiniteScalar(valueIn)
|
||||||
|
if islogical(valueIn)
|
||||||
|
valueIn = double(valueIn);
|
||||||
|
end
|
||||||
|
|
||||||
|
if isempty(valueIn)
|
||||||
|
value = NaN;
|
||||||
|
return
|
||||||
|
end
|
||||||
|
|
||||||
|
if isnumeric(valueIn)
|
||||||
|
finiteValues = valueIn(isfinite(valueIn));
|
||||||
|
if isempty(finiteValues)
|
||||||
|
value = NaN;
|
||||||
|
else
|
||||||
|
value = double(finiteValues(1));
|
||||||
|
end
|
||||||
|
return
|
||||||
|
end
|
||||||
|
|
||||||
|
value = str2double(string(valueIn));
|
||||||
|
if isnan(value)
|
||||||
|
value = NaN;
|
||||||
|
end
|
||||||
|
end
|
||||||
|
|
||||||
|
function exists = resultHashExists(db, resultHash)
|
||||||
|
query = sprintf("SELECT mpi_result_id FROM MpiReductionResults WHERE result_hash = '%s' LIMIT 1", ...
|
||||||
|
char(resultHash));
|
||||||
|
existing = db.fetch(query);
|
||||||
|
exists = ~isempty(existing);
|
||||||
|
end
|
||||||
|
|
||||||
|
function exists = uniqueResultKeyExists(db, row)
|
||||||
|
query = sprintf( ...
|
||||||
|
"SELECT mpi_result_id FROM MpiReductionResults " + ...
|
||||||
|
"WHERE run_id = %d " + ...
|
||||||
|
"AND occurrence_idx = %d " + ...
|
||||||
|
"AND study_name = '%s' " + ...
|
||||||
|
"AND storage_name = '%s' " + ...
|
||||||
|
"AND block_update = %d " + ...
|
||||||
|
"AND param_hash = '%s' LIMIT 1", ...
|
||||||
|
row.run_id, row.occurrence_idx, ...
|
||||||
|
sqlString(row.study_name), sqlString(row.storage_name), ...
|
||||||
|
row.block_update, sqlString(row.param_hash));
|
||||||
|
existing = db.fetch(query);
|
||||||
|
exists = ~isempty(existing);
|
||||||
|
end
|
||||||
|
|
||||||
|
function value = sqlString(value)
|
||||||
|
value = strrep(char(value), '''', '''''');
|
||||||
|
end
|
||||||
@@ -7,6 +7,12 @@ dsp_options.start_occurence = 1;
|
|||||||
dsp_options.max_occurences = 15;
|
dsp_options.max_occurences = 15;
|
||||||
dsp_options.debug_plots = false;
|
dsp_options.debug_plots = false;
|
||||||
|
|
||||||
|
write_mpi_reduction_db = 1;
|
||||||
|
stream_mpi_reduction_db = 1;
|
||||||
|
mpi_reduction_study_name = "block_update_sweep";
|
||||||
|
mpi_reduction_writer_path = fullfile(fileparts(mfilename('fullpath')),"db");
|
||||||
|
addpath(mpi_reduction_writer_path);
|
||||||
|
|
||||||
dsp_options.database_type = "mysql";
|
dsp_options.database_type = "mysql";
|
||||||
|
|
||||||
dsp_options.dataBase = "labor";
|
dsp_options.dataBase = "labor";
|
||||||
@@ -16,6 +22,9 @@ dsp_options.server = "192.168.178.192";
|
|||||||
dsp_options.port = 3306;
|
dsp_options.port = 3306;
|
||||||
dsp_options.user = "silas";
|
dsp_options.user = "silas";
|
||||||
dsp_options.password = "silas";
|
dsp_options.password = "silas";
|
||||||
|
dsp_options.append_mpi_reduction_db = write_mpi_reduction_db && stream_mpi_reduction_db;
|
||||||
|
dsp_options.mpi_reduction_study_name = mpi_reduction_study_name;
|
||||||
|
dsp_options.mpi_reduction_writer_path = mpi_reduction_writer_path;
|
||||||
|
|
||||||
db = DBHandler("dataBase", [dsp_options.dataBase],...
|
db = DBHandler("dataBase", [dsp_options.dataBase],...
|
||||||
"type", dsp_options.database_type,...
|
"type", dsp_options.database_type,...
|
||||||
@@ -45,7 +54,6 @@ for i = 1
|
|||||||
|
|
||||||
[dataTable,~] = db.queryDB(fp, db.getTableFieldNames('Runs'));
|
[dataTable,~] = db.queryDB(fp, db.getTableFieldNames('Runs'));
|
||||||
|
|
||||||
|
|
||||||
[~, sortIdx] = sort(dataTable.sir, 'descend');
|
[~, sortIdx] = sort(dataTable.sir, 'descend');
|
||||||
dataTable = dataTable(sortIdx, :);
|
dataTable = dataTable(sortIdx, :);
|
||||||
|
|
||||||
@@ -55,11 +63,10 @@ for i = 1
|
|||||||
|
|
||||||
%% === Warehouse setup ===
|
%% === Warehouse setup ===
|
||||||
dsp_options.userParameters = struct();
|
dsp_options.userParameters = struct();
|
||||||
dsp_options.userParameters.block_update = 1;%[1,2,4,8,16,32,64,112,224,448,512,1024,2048,2048*2,2048*4];%%logspace(-3.8,-1,22);%[linspace(2,4096,22)];
|
dsp_options.userParameters.block_update = [1,2,4,8,16,32,64,112,224,448,448*2,1024,2048,4096,8192,16384];%%logspace(-3.8,-1,22);%[linspace(2,4096,22)];
|
||||||
% dsp_options.userParameters.block_update = linspace(1,224,22);
|
% dsp_options.userParameters.block_update = linspace(1,224,22);
|
||||||
wh = DataStorage(dsp_options.userParameters);
|
wh = DataStorage(dsp_options.userParameters);
|
||||||
|
|
||||||
|
|
||||||
%%
|
%%
|
||||||
n_realizations = (dsp_options.max_occurences - dsp_options.start_occurence + 1);
|
n_realizations = (dsp_options.max_occurences - dsp_options.start_occurence + 1);
|
||||||
n_userparams = prod(wh.dim);
|
n_userparams = prod(wh.dim);
|
||||||
@@ -76,6 +83,14 @@ for i = 1
|
|||||||
[results, wh] = submitJobs(run_ids, dsp_options, processingMode.parallel, ...
|
[results, wh] = submitJobs(run_ids, dsp_options, processingMode.parallel, ...
|
||||||
"wh", wh, ...
|
"wh", wh, ...
|
||||||
"waitbar", true);
|
"waitbar", true);
|
||||||
|
|
||||||
|
%%
|
||||||
|
|
||||||
|
if write_mpi_reduction_db && ~stream_mpi_reduction_db
|
||||||
|
db.refresh();
|
||||||
|
appendMpiReductionWarehouse(db, wh, run_ids, dsp_options, ...
|
||||||
|
"study_name", mpi_reduction_study_name);
|
||||||
|
end
|
||||||
|
|
||||||
% savepath = fullfile("C:","Users","Silas","Documents","MATLAB","imdd_simulation","projects","Diss","MPI_revisit","algorithms",sprintf("pam_%d_results.mat",M));
|
% savepath = fullfile("C:","Users","Silas","Documents","MATLAB","imdd_simulation","projects","Diss","MPI_revisit","algorithms",sprintf("pam_%d_results.mat",M));
|
||||||
% save(wh,savepath)
|
% save(wh,savepath)
|
||||||
|
|||||||
BIN
workerError.mat
BIN
workerError.mat
Binary file not shown.
Reference in New Issue
Block a user