make using torch execution easier for sweeps by adding a method of easily...

make using torch execution easier for sweeps by adding a method of easily creating the tensors taken by the torch model function

README.md

@@ -45,3 +45,5 @@ TorchScript exectution is performed differently than on the C++ and two extra fu
 		1. a 1d, (n) sized tensor containing the model parameters
 		2. a 1d, (n) sized tensor with omega values to calculate the impance at
 	* a 1d complex tensor is returned with the impedance values
+* `eisgenerator.getModelParameters`
+	* returns the model paramters at the given index as a torch.Tensor

example/exampleTorch.py

@@ -16,9 +16,8 @@ eis.compileModel(model)
 
 modelFn = eis.getModelFunction(model)
 
-parameters = torch.empty((2))
-parameters[0] = 1e-6
-parameters[1] = 100
+parameters = eis.getModelParameters(model, 0)
 omegas = torch.logspace(0, 5, 10)
+print(f'Parameters:\n{parameters}\nOmegas:\n{omegas}\n')
 
 print(modelFn(parameters, omegas))

src/eisgenerator/__init__.py

 from ._core import __doc__, __version__, Model, DataPoint, Range, Log, ParseError, FileError, eisDistance, EisSpectra, eisNyquistDistance, ostream_redirect
-from .execute import compileModel, getModelFunction
+from .execute import compileModel, getModelFunction, getModelParameters

src/eisgenerator/execute.py

@@ -35,3 +35,15 @@ def getModelFunction(model: Model):
 	return models[fn_name]
 
 
+def getModelParameters(model: Model, index: int):
+	try:
+		import torch
+	except  ModuleNotFoundError:
+		Log.print("Could not import torch, torch must be availble create torch paramter tensors.", Log.level.ERROR)
+		return False
+
+	model.resolveSteps(index)
+	eisparameters = model.getFlatParameters()
+
+	parameters = torch.Tensor(eisparameters)
+	return parameters

src/main.cpp

@@ -54,6 +54,7 @@ PYBIND11_MODULE(_core, m)
 		.def("getCppCode", &Model::getCode)
 		.def("getTorchScript", &Model::getTorchScript)
 		.def("getCompiledFunctionName", &Model::getCompiledFunctionName)
+		.def("getFlatParameters", &Model::getFlatParameters)
 		.def("__repr__", &Model::getModelStr);
 	py::class_<DataPoint>(m, "DataPoint")
 		.def(py::init<std::complex<fvalue>, fvalue>(), py::arg("im") = std::complex<fvalue>(0, 0), py::arg("omega") = 100)