From 54d57bd2cccf2afb5b7ebc9bd8f3669e3cb2e7bc Mon Sep 17 00:00:00 2001
From: Carl Philipp Klemm <philipp@uvos.xyz>
Date: Tue, 21 Feb 2023 13:59:33 +0100
Subject: [PATCH] Model: add function to find the most interesting indecies
---
eisgenerator/model.h | 1 +
model.cpp | 68 ++++++++++++++++++++++++++++++++++++++++++++
2 files changed, 69 insertions(+)
diff --git a/eisgenerator/model.h b/eisgenerator/model.h
index f110d33..8db355a 100644
--- a/eisgenerator/model.h
+++ b/eisgenerator/model.h
@@ -48,6 +48,7 @@ public:
void resolveSteps(int64_t index);
size_t getRequiredStepsForSweeps();
bool isParamSweep();
+ std::vector<size_t> getRecommendedParamIndices(eis::Range omegaRange, double distance, bool threaded = false);
};
}
diff --git a/model.cpp b/model.cpp
index 900d018..5a8f420 100644
--- a/model.cpp
+++ b/model.cpp
@@ -6,6 +6,8 @@
#include <array>
#include <thread>
#include <fstream>
+#include <algorithm>
+#include <execution>
#include "strops.h"
#include "cap.h"
@@ -16,6 +18,8 @@
#include "warburg.h"
#include "paralellseriel.h"
#include "log.h"
+#include "normalize.h"
+#include "basicmath.h"
using namespace eis;
@@ -451,3 +455,67 @@ bool Model::isParamSweep()
{
return getRequiredStepsForSweeps() > 1;
}
+
+std::vector<size_t> Model::getRecommendedParamIndices(eis::Range omegaRange, double distance, bool threaded)
+{
+ std::vector<std::vector<eis::DataPoint>> sweeps;
+ size_t count = getRequiredStepsForSweeps();
+ eis::Log(eis::Log::INFO)<<"Executeing "<<count<<" steps";
+ std::vector<std::vector<eis::DataPoint>> allSweeps;
+ std::vector<size_t> indices;
+
+ if(threaded)
+ allSweeps = executeAllSweeps(omegaRange);
+
+ for(size_t i = 0; i < count; ++i)
+ {
+ std::vector<eis::DataPoint> data;
+ if(threaded)
+ data = allSweeps[i];
+ else
+ data = executeSweep(omegaRange, i);
+ normalize(data);
+
+ fvalue maxJump = maximumNyquistJump(data);
+ if(maxJump > 0.30)
+ {
+ eis::Log(eis::Log::DEBUG)<<"skipping output for step "<<i
+ <<" is not well centered: "<<maxJump;
+ continue;
+ }
+
+ fvalue correlation = std::abs(pearsonCorrelation(data));
+ if(correlation > 0.8)
+ {
+ eis::Log(eis::Log::DEBUG)<<"skipping output for step "<<i
+ <<" as data is too linear: "<<correlation;
+ continue;
+ }
+
+ std::vector<std::vector<eis::DataPoint>>::iterator search;
+ if(threaded)
+ {
+ search = std::find_if(std::execution::par, sweeps.begin(), sweeps.end(),
+ [distance, &data](std::vector<eis::DataPoint>& a){return distance > eisDistance(data, a);});
+ }
+ else
+ {
+ search = std::find_if(std::execution::seq, sweeps.begin(), sweeps.end(),
+ [distance, &data](std::vector<eis::DataPoint>& a){return distance > eisDistance(data, a);});
+ }
+ if(search == sweeps.end())
+ {
+ indices.push_back(i);
+ sweeps.push_back(data);
+ if(threaded)
+ resolveSteps(i);
+ }
+ if(i % 200 == 0)
+ {
+ eis::Log(eis::Log::INFO, false)<<'.';
+ std::cout<<std::flush;
+ }
+ }
+ eis::Log(eis::Log::INFO, false)<<'\n';
+ return indices;
+}
--
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