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Commit e8c5e8e9 authored by Carl Philipp Klemm's avatar Carl Philipp Klemm
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main: refactor mode options, add ability to export witch parametrs are interesting in a range

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main.cpp
+ 145
− 35
View file @ e8c5e8e9
......@@ -16,7 +16,7 @@
#define M_PI 3.14159265358979323846
#endif
static constexpr double DIST_THRESH = 0.01;
static constexpr double STEP_THRESH = 0.30;
static constexpr char PARA_SWEEP_OUTPUT_DIR[] = "./sweep";
static void printComponants(eis::Model& model)
......@@ -52,7 +52,8 @@ static void runSweep(const Config& config, eis::Model& model)
if(config.reduce)
{
eis::Log(eis::Log::INFO)<<"reduced normalized results:";
results = eis::reduceRegion(results);
results = eis::reduceRegion(results, 0.01, false);
results = eis::reduceRegion(results, 0.01, true);
}
else if(config.normalize)
{
......@@ -67,7 +68,7 @@ static void runSweep(const Config& config, eis::Model& model)
if(config.noise > 0)
eis::noise(results, config.noise, false);
std::cout<<(config.hertz ? "freqency" : "omega")<<",real,im\n";
eis::Log(eis::Log::INFO)<<(config.hertz ? "freqency" : "omega")<<",real,im";
for(const eis::DataPoint& res : results)
std::cout<<(config.hertz ? res.omega/(2*M_PI) : res.omega)<<','<<
......@@ -97,9 +98,32 @@ static void runParamSweep(const Config& config, eis::Model& model)
data = allSweeps[i];
else
data = model.executeSweep(config.omegaRange, i);
size_t outputSize = data.size();
if(config.normalize)
eis::normalize(data);
if(config.reduce)
{
size_t initalDataSize = data.size();
data = eis::reduceRegion(data);
data = eis::rescale(data, outputSize);
if(data.size() < initalDataSize/8)
{
eis::Log(eis::Log::INFO)<<"\nskipping output for step "<<i
<<" as data has no interesting region";
continue;
}
//data = eis::rescale(data, initalDataSize);
}
if(config.skipLinear && i > 0)
{
fvalue correlation = std::abs(pearsonCorrelation(data));
if(correlation > 0.5)
{
eis::Log(eis::Log::INFO)<<"skipping output for step "<<i
<<" as data is too linear: "<<correlation;
continue;
}
}
eis::saveToDisk(data, std::string(PARA_SWEEP_OUTPUT_DIR)+std::string("/")+std::to_string(i)+".csv", model.getModelStrWithParam(i));
eis::Log(eis::Log::INFO, false)<<'.';
}
......@@ -110,25 +134,18 @@ static void runParamSweep(const Config& config, eis::Model& model)
eis::Log(eis::Log::INFO)<<"time taken: "<<duration.count()<<" ms";
}
void findRanges(const Config& config, eis::Model& model)
static std::vector<std::vector<fvalue>> getRangeValuesForModel(const Config& config, eis::Model& model, std::vector<size_t>* indices = nullptr)
{
std::vector<std::vector<fvalue>> values;
std::vector<std::vector<eis::DataPoint>> sweeps;
size_t count = model.getRequiredStepsForSweeps();
eis::Log(eis::Log::INFO)<<"Executeing "<<count<<" steps";
std::vector<eis::Componant*> componants = model.getFlatComponants();
std::vector<std::vector<eis::DataPoint>> allSweeps;
if(config.threaded)
allSweeps = model.executeAllSweeps(config.omegaRange);
std::vector<char> componantChars;
for(eis::Componant* componant : componants)
{
std::vector<eis::Range>& ranges = componant->getParamRanges();
for(size_t i = 0; i < ranges.size(); ++i)
componantChars.push_back(componant->getComponantChar());
}
for(size_t i = 0; i < count; ++i)
{
std::vector<eis::DataPoint> data;
......@@ -136,14 +153,29 @@ void findRanges(const Config& config, eis::Model& model)
data = allSweeps[i];
else
data = model.executeSweep(config.omegaRange, i);
size_t outputSize = data.size();
data = eis::reduceRegion(data);
data = eis::rescale(data, outputSize);
normalize(data);
fvalue maxJump = maximumNyquistJump(data);
if(maxJump > STEP_THRESH)
{
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;
}
bool found = false;
for(ssize_t i = static_cast<ssize_t>(sweeps.size())-1; i >= 0; --i)
for(ssize_t j = static_cast<ssize_t>(sweeps.size())-1; j >= 0; --j)
{
if(eisDistance(data, sweeps[i]) < DIST_THRESH)
fvalue dist = eisDistance(data, sweeps[j]);
if(dist < config.rangeDistance)
{
found = true;
break;
......@@ -151,6 +183,8 @@ void findRanges(const Config& config, eis::Model& model)
}
if(!found)
{
if(indices)
indices->push_back(i);
sweeps.push_back(data);
values.push_back(std::vector<fvalue>());
if(config.threaded)
......@@ -170,6 +204,20 @@ void findRanges(const Config& config, eis::Model& model)
}
eis::Log(eis::Log::INFO, false)<<'\n';
return values;
}
static void findRanges(const Config& config, eis::Model& model)
{
std::vector<std::vector<fvalue>> values = getRangeValuesForModel(config, model);
std::vector<eis::Componant*> componants = model.getFlatComponants();
if(values.empty())
{
eis::Log(eis::Log::INFO)<<"Cant recommend a range";
return;
}
std::vector<fvalue> maxValues(values[0].size(), std::numeric_limits<fvalue>::min());
std::vector<fvalue> minValues(values[0].size(), std::numeric_limits<fvalue>::max());
for(size_t i = 0; i < values.size(); ++i)
......@@ -183,11 +231,45 @@ void findRanges(const Config& config, eis::Model& model)
}
}
eis::Log(eis::Log::INFO)<<"Recommended ranges:";
for(size_t i = 0; i < maxValues.size(); ++i)
size_t i = 0;
for(eis::Componant* componant : componants)
{
std::vector<eis::Range>& ranges = componant->getParamRanges();
for(eis::Range& range : ranges)
{
fvalue mean = (maxValues[i]+minValues[i])/2;
fvalue var = std::pow(maxValues[i]-minValues[i], 2)/std::pow(mean, 2);
if(var < 0.1)
{
range.start = mean;
range.end = mean;
range.count = 1;
}
else
{
range.start = minValues[i];
range.end = maxValues[i];
}
++i;
}
}
eis::Log(eis::Log::INFO)<<"Recommended ranges:\n"<<model.getModelStrWithParam();
}
static void outputRanges(const Config& config, eis::Model& model)
{
std::vector<size_t> indices;
getRangeValuesForModel(config, model, &indices);
if(indices.empty())
{
eis::Log(eis::Log::INFO)<<componantChars[i]<<": "<<minValues[i]<<'-'<<maxValues[i];
eis::Log(eis::Log::INFO)<<"Cant recommend a range";
return;
}
for(size_t index : indices)
std::cout<<model.getModelStrWithParam(index)<<'\n';
}
int main(int argc, char** argv)
......@@ -212,23 +294,51 @@ int main(int argc, char** argv)
else if(config.inputType == INPUT_TYPE_UNKOWN)
eis::Log(eis::Log::WARN)<<"Invalid input type specified, assumeing eis";
eis::Log(eis::Log::INFO)<<"Using model string: "<<config.modelStr;
if(config.inputType != INPUT_TYPE_EIS)
eis::Log(eis::Log::INFO)<<"Using translated model string: "<<config.modelStr;
try
{
eis::Model model(config.modelStr, config.paramSteps);
eis::Log(eis::Log::INFO)<<"Using parsed model string: "<<model.getModelStrWithParam();
printComponants(model);
if(config.findRange && !model.isParamSweep())
if(config.mode == MODE_INVALID)
{
eis::Log(eis::Log::ERROR)<<"Invalid mode selected";
return 1;
}
if(config.mode == MODE_FIND_RANGE && !model.isParamSweep())
{
eis::Log(eis::Log::ERROR)<<"Cant find range on a non-sweep model";
return 1;
}
if(model.isParamSweep() && config.findRange)
if(config.mode == MODE_FIND_RANGE)
{
findRanges(config, model);
else if(model.isParamSweep())
}
if(config.mode == MODE_OUTPUT_RANGE_DATAPOINTS)
{
outputRanges(config, model);
}
else
{
if(model.isParamSweep())
runParamSweep(config, model);
else
runSweep(config, model);
}
}
catch(const std::invalid_argument& ia)
{
eis::Log(eis::Log::ERROR)<<"Unable to parse model string, "<<ia.what();
return 1;
}
return 0;
}
options.h
+ 32
− 3
View file @ e8c5e8e9
......@@ -26,8 +26,10 @@ static struct argp_option options[] =
{"invert", 'i', 0, 0, "inverts the imaginary axis"},
{"noise", 'x', "[AMPLITUDE]", 0, "add noise to output"},
{"input-type", 't', "[STRING]", 0, "set input string type, possible values: eis, boukamp, relaxis"},
{"find-range", 'f', 0, 0, "find sensible part of parameter range"},
{"find-range", 'f', "[STRING]", 0, "mode, possible values: export, find-range, export-ranges"},
{"range-distance", 'd', "[DISTANCE]", 0, "distance from a previous point where a range is considered \"new\""},
{"parallel", 'p', 0, 0, "run on multiple threads"},
{"skip-linear", 'e', 0, 0, "dont output param sweeps that create linear nyquist plots"},
{ 0 }
};
......@@ -39,19 +41,29 @@ enum
INPUT_TYPE_UNKOWN
};
enum
{
MODE_NORMAL,
MODE_FIND_RANGE,
MODE_OUTPUT_RANGE_DATAPOINTS,
MODE_INVALID,
};
struct Config
{
std::string modelStr = "c{1e-6}r{1e3}-r{1e3}";
int inputType = INPUT_TYPE_EIS;
int mode = MODE_NORMAL;
size_t paramSteps = 10;
eis::Range omegaRange;
bool normalize = false;
bool reduce = false;
bool hertz = false;
bool invert = false;
bool findRange = false;
bool threaded = false;
bool skipLinear = false;
double noise = 0;
double rangeDistance = 0.35;
Config(): omegaRange(1, 1e6, 50, true)
{}
......@@ -68,6 +80,17 @@ static int parseInputType(const std::string& str)
return INPUT_TYPE_UNKOWN;
}
static int parseMode(const std::string& str)
{
if(str == "export")
return INPUT_TYPE_EIS;
else if(str == "find-range")
return MODE_FIND_RANGE;
else if(str == "export-ranges")
return MODE_OUTPUT_RANGE_DATAPOINTS;
return MODE_INVALID;
}
static error_t
parse_opt (int key, char *arg, struct argp_state *state)
{
......@@ -148,11 +171,17 @@ parse_opt (int key, char *arg, struct argp_state *state)
config->inputType = parseInputType(std::string(arg));
break;
case 'f':
config->findRange = true;
config->mode = parseMode(std::string(arg));
break;
case 'p':
config->threaded = true;
break;
case 'e':
config->skipLinear = true;
break;
case 'd':
config->rangeDistance = std::stod(std::string(arg));
break;
default:
return ARGP_ERR_UNKNOWN;
}
......
strops.cpp
+ 10
− 0
View file @ e8c5e8e9
......@@ -104,6 +104,16 @@ size_t eisRemoveUnneededBrackets(std::string& in, long int bracketStart)
{
bool bracketNeeded = false;
size_t paramBracketCount = 0;
if(bracketStart == -1 && in.size() > 2)
{
if(in[0] == '(' && in.back() == ')')
{
in.erase(in.begin());
in.pop_back();
}
}
for(size_t i = (bracketStart >= 0 ? bracketStart+1 : 0); i < in.size(); ++i)
{
if(paramBracketCount == 0)
......
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