SF-py

Python scripts to compute Structure Function. These codes computes the structure function using the vectorization approach, as shown in https://joss.theoj.org/papers/10.21105/joss.02185. This code is compatible with both CPU and GPU.

All the relevant files are contained in the following directories:

• 2d/SF_2nd_order.py - contains the scripts to compute second order structure functions for two-dimensional input data

• 2d/SF_3rd_order.py - contains the scripts to compute third order structure functions for two-dimensional input data

• 3d/SF_2nd_order.py - contains the scripts to compute second order structure functions for three-dimensional input data

• 3d/SF_3rd_order.py - contains the scripts to compute third order structure functions for three-dimensional input data

Installing SF-py

SF relies on a few prerequisites which are Python, h5py, Numba, Cupy [For gpu].

Running SF-py

Please set the following things before you run the code.

• 
  #input field
  #change the names of the input file and datasets according to your convenience
  Vx = hdf5reader("U.V1r.h5", "U.V1r")
  Vz = hdf5reader("U.V3r.h5", "U.V3r")
  

Change the input file name and the names of the datasets. The above is the example of 2D input data. The similar thing is applicable for 3d also.

• ##input ##
  L = 2*np.pi #Length of the domain
  

Change the domain length according to your need.

• ##device ##
  device = "cpu" #by default code will run on cpu
  

Change the device to "gpu" if you need.

• ##device id ##
  device_id = 0 #by default code will run on gpu0
  

Change the device_id accordingly to use a particular gpu on which you want to run the code.

SF-py can be executed by the following way at the respective folders (2d/3d).

Example: for 2nd order structure function:

python SF_2nd_order.py

Output of the SF-py

SF-py outputs "str_function.h5" file, which contains the following datasets:

• For 2nd order - S: This dataset corresponds to $\langle(|\delta u|)^2\rangle$.
                                S_u_r: This dataset corresponds to $\langle(|\delta u{\parallel}|)^2\rangle$.
                                ``Sux``: This dataset corresponds to $\langle(|\delta u{x}|)^2\rangle$.
                                S_u_z: This dataset corresponds to $\langle(|\delta u{z}|)^2\rangle$.
                                ``Suy``: This dataset corresponds to $\langle(|\delta u{y}|)^2\rangle$. This is available in the output only for 3d data.

• For 3rd order - S: This dataset corresponds to $\langle(|\delta u|)^2\delta u{\parallel}\rangle$.
                                ``Sur``: This dataset corresponds to $\langle(|\delta u{\parallel}|)^3\rangle$.
                                S_u_x: This dataset corresponds to $\langle(|\delta u|)^2\delta u{x}\rangle$.
                                ``Suz``: This dataset corresponds to $\langle(|\delta u|)^2\delta u{z}\rangle$.
                                S_u_y: This dataset corresponds to $\langle(|\delta u|)^2\delta u_{y}\rangle$. This is available in the output only for 3d data.

License

SF-py is an open-source package made available under the New BSD License.

Contributions and bug reports

Contributions to this project are very welcome. If you wish to contribute, please create a branch with a pull request and the proposed changes can be discussed there.

If you find a bug, please open a new issue on the GitHub repository to report the bug. Please provide sufficient information for the bug to be reproduced.

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