Reading a Tensor from parameter file

[Paras Kumar]

Dear deal.II community,

I am trying to read a second order tensor from a .prm file using the ParameterHandler functionalities. The tensor (for dim=3) is set in .prm file as

  set macro def grad = 1.2|0.0|0.0|0.0|1.1|0.0|0.0|0.0|1.4

and is currently read as a string using

parameterHandler.declare_entry(
          "macro def grad",
          "1.0|1.0|1.0|1.0",
          dealii::Patterns::Anything(),
          "Macroscopic deformation gradient for homogenization");

auto temp = parameterHandler.get("macro def grad");
std::vector<std::string> defGradComps;
boost::algorithm::split(defGradComps,
                        temp,
                       boost::algorithm::is_any_of("|"));
Assert(defGradComps.size() == dim * dim,
       dealii::ExcDimensionMismatch(defGradComps.size(),
                                                dim * dim));
           for (mncfrac::utilities::UnsignedIntType i = 0; i < dim; ++i)
              for (mncfrac::utilities::UnsignedIntType j = 0; j < dim; ++j)
                this->problemSpecificParameters_.macroDefGrad_[i][j] =
                  std::stod(defGradComps[i * dim + j]);

I am curious to know, if there is a smarter way (avoiding this manual copying by looping over the tensor entries) to do so using some other type of dealii::Patterns object or some other way.

Thanks in advance and best regards,

Paras Kumar

[Ahmad Shahba]

I don't know if it is the optimal way but I would use the following approach

1. Read tensor components as Patterns::List
2. Use  get  method of ParameterHandler to read all tensor  components as one string into a string variable
3. Use  split_string_list   in the Utilities namespace to split the string into individual components (still all components are strings)
4. Convert  string-type components into doubles using  string_to_double in the Utilities namespace
5. Use  Tensor (const Tensor< rank_, dim, OtherNumber > &initializer) to construct the tensor

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[Paras Kumar]

Ahmad,

On Tuesday, April 14, 2020 at 5:39:06 PM UTC+2, Ahmad Shahba wrote:

I don't know if it is the optimal way but I would use the following approach

1. Read tensor components as Patterns::List
   
2. Use  get  method of ParameterHandler to read all tensor  components as one string into a string variable
3. Use  split_string_list   in the Utilities namespace to split the string into individual components (still all components are strings)
4. Convert  string-type components into doubles using  string_to_double in the Utilities namespace
5. Use  Tensor (const Tensor< rank_, dim, OtherNumber > &initializer) to construct the tensor

Could you please elaborate on pointa 1 and 5, or share a code snippet which explains the process.

Best,

Paras

[Ahmad Shahba]

Here is the code that does what I explained. I just switched up step 5 with a much simpler approach. Note that you can simply make this into a function/class template so that you could read general tensors, not just 3x3 tensors. I leave that to you :-)

#include <deal.II/base/tensor.h>
#include <deal.II/base/parameter_handler.h>
#include <deal.II/base/utilities.h>
#include <string>
#include <iostream>
#include <sstream>

using namespace dealii;

int main() {


    // Let's read this tensor from an istringstream. You may read it from istream in your
    // application
    std::istringstream is("set Tensor3x3 = 11, 12, 13, 21, 22, 23, 31, 32, 33");


    // Now let's set up the ParameterHandler object. Since you are reading 3x3 tensor, you are
    // dealing with 9 components and the default value should also have 9 components (here 9 
    // zeros) in it
    ParameterHandler prm;

    using Patterns::List;
    using Patterns::Double;
    prm.declare_entry("Tensor3x3",
                      "0,0,0,0,0,0,0,0,0",
                      List(Double(), 9, 9),
                      "Tensor components");


    // Let's read it in now
    prm.parse_input(is);
    const std::string tensorString = prm.get("Tensor3x3");

    // Now let's split the string into individual components
    const std::vector<std::string> tensorComponentsString =
            Utilities::split_string_list(tensorString);

    // Now go over each component, convert it into double and put it in the tensor
    Tensor<2, 3> tensor;
    unsigned int counter = 0;
    for (unsigned ii = 0; ii < tensor.dimension; ++ii) {
        for (unsigned jj = 0; jj < tensor.dimension; ++jj) {
            tensor[ii][jj] = Utilities::string_to_double(tensorComponentsString[counter++]);
        }
    }


    // Let's check if we read the tensor correctly
    for (unsigned ii = 0; ii < tensor.dimension; ++ii) {
        for (unsigned jj = 0; jj < tensor.dimension; ++jj) {
            std::cout << "component [" << ii << ", " << jj << " ] = "
                      << tensor[ii][jj] << std::endl;
        }
    }


}

[Ahmad Shahba]

Ooops! The background was too dark :-)

Enter code here...

[Luca Heltai]

Currently, this is also the simplest way:

Tensor<rank, dim> tens;

prm.add_parameter("Tensor", tens);

Take a look at the documentation of the add parameter method.

Patterns::Tools::to_string(tens);

And 

Patterns::Tools::to_value 

Are also available to simplify what you want to achieve. 

Alternatively: Patterns::Tools::Convert offers ways to construct default Patterns for many types, including Tensors. 

Best,

Luca

Il giorno 15 apr 2020, alle ore 14:57, Ahmad Shahba <ah.s...@gmail.com> ha scritto:



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[Paras Kumar]

Hi,

Could you please provide an MWE to describe how the Patterns::Convert::to_value() function would work in this case.

Is it must to use prm.add_parameter()  to be able to do so? I usually use prm.declare_entry() and prm.get().

Best regards,

Paras

[luca.heltai]

> Could you please provide an MWE to describe how the Patterns::Convert::to_value() function would work in this case.

In the dealii/tests/parameter_handler/patterns_05.cc

there are many examples that show how to use these.

> Is it must to use prm.add_parameter() to be able to do so?
> I usually use prm.declare_entry() and prm.get().

No. It is more convenient, but not necessary:

Tensor<rank, dim> tensor;

using C = Patterns::Tools::Convert<Tensor<rank, dim>>;

prm.declare_entry(“My tensor”, C::to_string(tensor), *C::to_pattern(), “Documentation”);

...

tensor = C::to_value(prm.get(“My tensor”));


Best,
Luca.

[Paras Kumar]

Dear Luca,

Thank you. This really shortens the code. Is it also possible to set the delimiter to a user desired value, say "|" instead of ",". Also, where exactly is the procedure for conversion from string to deali::Tensor or some other type say std::vector<double> defined? I could not find it in the source code.

Best regards,

Paras

[Luca Heltai]

Thank you. This really shortens the code. Is it also possible to set the delimiter to a user desired value, say "|" instead of ",".

All functions of the Convert class take a unique pointer to a pattern. You can specify your own pattern, and use that in the conversion. The code is all in

deal.II/base/patterns_tools.h

After the Class declarations, you’ll find the implementations for the basic classes of deal.II, including vector, map, pairs and tuples of them. 

Best,

Luca 

Also, where exactly is the procedure for conversion from string to deali::Tensor or some other type say std::vector<double> defined? I could not find it in the source code.

Best regards,

Paras

On Tuesday, August 4, 2020 at 6:15:47 PM UTC+2, Paras Kumar wrote:

Hi,

Could you please provide an MWE to describe how the Patterns::Convert::to_value() function would work in this case.

Is it must to use prm.add_parameter()  to be able to do so? I usually use prm.declare_entry() and prm.get().

Best regards,

Paras

On Wednesday, April 15, 2020 at 6:01:53 PM UTC+2, Luca Heltai wrote:

Currently, this is also the simplest way:

Tensor<rank, dim> tens;

prm.add_parameter("Tensor", tens);

Take a look at the documentation of the add parameter method.

Patterns::Tools::to_string(tens);

And 

Patterns::Tools::to_value 

Are also available to simplify what you want to achieve. 

Alternatively: Patterns::Tools::Convert offers ways to construct default Patterns for many types, including Tensors. 

Best,

Luca

 

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