:py:mod:`src.tools`
===================

.. py:module:: src.tools


Submodules
----------
.. toctree::
   :titlesonly:
   :maxdepth: 1

   bnorm/index.rst


Package Contents
----------------


Functions
~~~~~~~~~

.. autoapisummary::

   src.tools.get_tensor_distance
   src.tools.phi_coeff_from_nb
   src.tools.get_matrix_dPhi
   src.tools.compute_j
   src.tools.compute_dpsi_full
   src.tools.get_rot_tensor
   src.tools.compute_Qj
   src.tools.compute_dQjdtheta
   src.tools.compute_LS_old
   src.tools.compute_LS
   src.tools.compute_dLS



Attributes
~~~~~~~~~~

.. autoapisummary::

   src.tools.eijk


.. py:data:: eijk
   

   

.. py:function:: get_tensor_distance(S1, S2, rot_tensor)

   S1 has a grid lu1 x lv1 and S2 lu2 x lv2x3 with the same Np
   return the tensor Npxlu1xlv1xlu2xlv2 x 3 of the vector between
   such that T[i,j,k,l,m,n] is the nth coordinates bwn the rotation of
   2pi i/Np psi1_j,k and psi2_l,m


.. py:function:: phi_coeff_from_nb(k, phisize)

   the coefficents of Phi are store as 1d array,
   this function make the conversion with a 2d matrix


.. py:function:: get_matrix_dPhi(phisize, grids)

   generate the tensor (2+lc) xluxlvx2 of divergence free vector fields
   lc is the number of fourier component given by phisize


.. py:function:: compute_j(boldpsi, matrixd_phi, Np)


.. py:function:: compute_dpsi_full(dpsi, Np)


.. py:function:: get_rot_tensor(Np)


.. py:function:: compute_Qj(matrixd_phi, dpsi, dS)

   take only the segment whitout rotation of j


.. py:function:: compute_dQjdtheta(matrixd_phi, dpsi, dS, dtheta, dSdtheta)

   take only the segment whitout rotation of j


.. py:function:: compute_LS_old(T, j, dS, normalp)

   T is the distance tensor Npxlu1xlv1xlu2xlv2 x 3
   and j the current tensor (lc+2) x Np x lu1 x lv1 x 3
   dS lu1 x lv1
   normalp 3 x lu2 x lv2


.. py:function:: compute_LS(T, matrixd_phi, dpsi, rot_tensor, normalp)

   T is the distance tensor Npxlu1xlv1xlu2xlv2 x 3
   and j the current tensor (lc+2) x Np x lu1 x lv1 x 3
   dS lu1 x lv1
   normalp 3 x lu2 x lv2


.. py:function:: compute_dLS(T, matrixd_phi, dpsi, rot_tensor, normalp, theta, dtildetheta)

   T is the distance tensor Npxlu1xlv1xlu2xlv2 x 3
   and j the current tensor (lc+2) x Np x lu1 x lv1 x 3
   dS lu1 x lv1
   normalp 3 x lu2 x lv2