trexio/trex.org

#+TITLE: TREX Configuration file
#+STARTUP: latexpreview
#+SETUPFILE: docs/theme.setup

This page contains information about the general structure of the
TREXIO library. The source code of the library can be automatically
generated based on the contents of the ~trex.json~ configuration file,
which itself is generated from different sections (groups) presented
below.

All quantities are saved in TREXIO files in atomic units. The
dimensions of the arrays in the tables below are given in column-major
order (as in Fortran), and the ordering of the dimensions is reversed
in the produced ~trex.json~ configuration file as the library is
written in C.

TREXIO currently supports ~int~, ~float~ and ~str~ types for both
single attributes and arrays.  Note, that some attributes might have
~dim~ type (e.g. ~num~ of the ~nucleus~ group).  This type is treated
exactly in the same way as ~int~ with the only difference that ~dim~
variables cannot be negative. This additional constraint is required
because ~dim~ attributes are used internally to allocate memory and to
check array boundaries in the memory-safe API. Most of the times, the
~dim~ variables contain the ~num~ suffix.
You may also encounter some ~dim readonly~ variables.
It means that the value is automatically computed and written by the
TREXIO library, thus it is read-only and cannot be (over)written by the
user.

In Fortran, arrays are 1-based and in most other languages the
arrays are 0-based. Hence, we introduce the ~index~ type which is a
1-based ~int~ in the Fortran interface and 0-based otherwise.

For sparse data structures such as electron replusion integrals,
the data can be too large to fit in memory and the data needs to be
fetched using multiple function calls to perform I/O on buffers.
For more information on how to read/write sparse data structures, see
the [[./examples.html][examples]]. The ~sparse~ data representation implies the
[[https://en.wikipedia.org/wiki/Sparse_matrix#Coordinate_list_(COO)][coordinate list]] representation, namely the user has to write a list
of indices and values.

For the Configuration Interfaction (CI) and Configuration State Function (CSF)
groups, the ~buffered~ data type is introduced, which allows similar incremental
I/O as for ~sparse~ data but without the need to write indices of the sparse values.

For determinant lists (integer bit fields), the ~special~ attribute is present in the type.
This means that the source code is not produced by the generator, but hand-written.

  #+begin_src python :tangle trex.json :exports none
{
  #+end_src

* Metadata (metadata group)

  As we expect our files to be archived in open-data repositories, we
  need to give the possibility to the users to store some metadata
  inside the files. We propose to store the list of names of the codes
  which have participated to the creation of the file, a list of
  authors of the file, and a textual description.

  #+NAME: metadata
  | Variable          | Type  | Dimensions (for arrays) | Description                              |
  |-------------------+-------+-------------------------+------------------------------------------|
  | ~code_num~        | ~dim~ |                         | Number of codes used to produce the file |
  | ~code~            | ~str~ | ~(metadata.code_num)~   | Names of the codes used                  |
  | ~author_num~      | ~dim~ |                         | Number of authors of the file            |
  | ~author~          | ~str~ | ~(metadata.author_num)~ | Names of the authors of the file         |
  | ~package_version~ | ~str~ |                         | TREXIO version used to produce the file  |
  | ~description~     | ~str~ |                         | Text describing the content of file      |
  | ~unsafe~          | ~int~ |                         | ~1~: true, ~0~: false                    |

  **Note:** ~unsafe~ attribute of the ~metadata~ group indicates whether the file has been previously opened with ~'u'~ mode.
  It is automatically written in the file upon the first unsafe opening.
  If the user has checked that the TREXIO file is valid (e.g. using ~trexio-tools~) after unsafe operations,
  then the ~unsafe~ attribute value can be manually overwritten (in unsafe mode) from ~1~ to ~0~.

  #+CALL: json(data=metadata, title="metadata")
  #+RESULTS:
  :results:
  #+begin_src python :tangle trex.json
      "metadata": {
                 "code_num" : [ "dim", []                        ]
        ,            "code" : [ "str", [ "metadata.code_num" ]   ]
        ,      "author_num" : [ "dim", []                        ]
        ,          "author" : [ "str", [ "metadata.author_num" ] ]
        , "package_version" : [ "str", []                        ]
        ,     "description" : [ "str", []                        ]
        ,          "unsafe" : [ "int", []                        ]
      } ,
  #+end_src
  :end:

* Electron (electron group)

   We consider wave functions expressed in the spin-free formalism, where
   the number of \uparrow and \downarrow electrons is fixed.

  #+NAME:electron
  | Variable | Type  | Dimensions | Description                         |
  |----------+-------+------------+-------------------------------------|
  | ~num~    | ~dim~ |            | Number of electrons                 |
  | ~up_num~ | ~int~ |            | Number of \uparrow-spin electrons   |
  | ~dn_num~ | ~int~ |            | Number of \downarrow-spin electrons |

  #+CALL: json(data=electron, title="electron")
  #+RESULTS:
  :results:
  #+begin_src python :tangle trex.json
      "electron": {
             "num" : [ "dim", []  ]
        , "up_num" : [ "int", []  ]
        , "dn_num" : [ "int", []  ]
      } ,
  #+end_src
  :end:

* Nucleus (nucleus group)

  The nuclei are considered as fixed point charges. Coordinates are
  given in Cartesian $(x,y,z)$ format.

  #+NAME: nucleus
  | Variable      | Type    | Dimensions        | Description              |
  |---------------+---------+-------------------+--------------------------|
  | ~num~         | ~dim~   |                   | Number of nuclei         |
  | ~charge~      | ~float~ | ~(nucleus.num)~   | Charges of the nuclei    |
  | ~coord~       | ~float~ | ~(3,nucleus.num)~ | Coordinates of the atoms |
  | ~label~       | ~str~   | ~(nucleus.num)~   | Atom labels              |
  | ~point_group~ | ~str~   |                   | Symmetry point group     |
  | ~repulsion~   | ~float~ |                   | Nuclear repulsion energy |

  #+CALL: json(data=nucleus, title="nucleus")
  #+RESULTS:
  :results:
  #+begin_src python :tangle trex.json
      "nucleus": {
                  "num" : [ "dim"  , []                     ]
        ,      "charge" : [ "float", [ "nucleus.num" ]      ]
        ,       "coord" : [ "float", [ "nucleus.num", "3" ] ]
        ,       "label" : [ "str"  , [ "nucleus.num" ]      ]
        , "point_group" : [ "str"  , []                     ]
        ,   "repulsion" : [ "float", []                     ]
      } ,
  #+end_src
  :end:

* Effective core potentials (ecp group)

  An effective core potential (ECP) $V_A^{\text{ECP}}$ replacing the
  core electrons of atom $A$ can be expressed as
  \[
  V_A^{\text{ECP}} =
  V_{A \ell_{\max}+1} +
  \sum_{\ell=0}^{\ell_{\max}}
  \sum_{m=-\ell}^{\ell} | Y_{\ell m} \rangle \left[
  V_{A \ell} - V_{A \ell_{\max}+1} \right] \langle Y_{\ell m} |
  \]

  The first term in the equation above is sometimes attributed to the local channel,
  while the remaining terms correspond to the non-local channel projections.

  The functions $V_{A\ell}$ are parameterized as:
  \[
  V_{A \ell}(\mathbf{r}) =
  \sum_{q=1}^{N_{q \ell}}
  \beta_{A q \ell}\, |\mathbf{r}-\mathbf{R}_{A}|^{n_{A q \ell}}\,
  e^{-\alpha_{A q \ell} |\mathbf{r}-\mathbf{R}_{A}|^2 }
  \]

  See http://dx.doi.org/10.1063/1.4984046 or https://doi.org/10.1063/1.5121006 for more info.

  #+NAME: ecp
  | Variable             | Type    | Dimensions      | Description                                                                            |
  |----------------------+---------+-----------------+----------------------------------------------------------------------------------------|
  | ~max_ang_mom_plus_1~ | ~int~   | ~(nucleus.num)~ | $\ell_{\max}+1$, one higher than the max angular momentum in the removed core orbitals |
  | ~z_core~             | ~int~   | ~(nucleus.num)~ | Number of core electrons to remove per atom                                            |
  | ~num~                | ~dim~   |                 | Total number of ECP functions for all atoms and all values of $\ell$                   |
  | ~ang_mom~            | ~int~   | ~(ecp.num)~     | One-to-one correspondence between ECP items and the angular momentum $\ell$            |
  | ~nucleus_index~      | ~index~ | ~(ecp.num)~     | One-to-one correspondence between ECP items and the atom index                         |
  | ~exponent~           | ~float~ | ~(ecp.num)~     | $\alpha_{A q \ell}$ all ECP exponents                                                  |
  | ~coefficient~        | ~float~ | ~(ecp.num)~     | $\beta_{A q \ell}$ all ECP coefficients                                                |
  | ~power~              | ~int~   | ~(ecp.num)~     | $n_{A q \ell}$ all ECP powers                                                          |


There might be some confusion in the meaning of the $\ell_{\max}$.
It can be attributed to the maximum angular momentum occupied
in the core orbitals, which are removed by the ECP.
On the other hand, it can be attributed to the maximum angular momentum of the
ECP that replaces the core electrons.
*Note*, that the latter $\ell_{\max}$ is always higher by 1 than the former.


*Note for developers*: avoid having variables with similar prefix in their name.
HDF5 back end might cause issues due to the way ~find_dataset~ function works.
For example, in the ECP group we use ~max_ang_mom~ and not ~ang_mom_max~.
The latter causes issues when written before the ~ang_mom~ array in the TREXIO file.
*Update*: in fact, the aforementioned issue has only been observed when using HDF5 version 1.10.4
installed via ~apt-get~. Installing the same version from the ~conda-forge~ channel and running it in
an isolated ~conda~ environment works just fine. Thus, it seems to be a bug in the ~apt~-provided package.
If you encounter the aforementioned issue, please report it to our [[https://github.com/TREX-CoE/trexio/issues][issue tracker on GitHub]].


  #+CALL: json(data=ecp, title="ecp")

  #+RESULTS:
  :results:
  #+begin_src python :tangle trex.json
      "ecp": {
          "max_ang_mom_plus_1" : [ "int"  , [ "nucleus.num" ] ]
        ,             "z_core" : [ "int"  , [ "nucleus.num" ] ]
        ,                "num" : [ "dim"  , []                ]
        ,            "ang_mom" : [ "int"  , [ "ecp.num" ]     ]
        ,      "nucleus_index" : [ "index", [ "ecp.num" ]     ]
        ,           "exponent" : [ "float", [ "ecp.num" ]     ]
        ,        "coefficient" : [ "float", [ "ecp.num" ]     ]
        ,              "power" : [ "int"  , [ "ecp.num" ]     ]
      } ,
  #+end_src
  :end:

** Example

  For example, consider H_2 molecule with the following
  [[https://pseudopotentiallibrary.org/recipes/H/ccECP/H.ccECP.gamess][effective core potential]]
  (in GAMESS input format for the H atom):

   #+BEGIN_EXAMPLE
H-ccECP GEN 0 1
3
1.00000000000000    1 21.24359508259891
21.24359508259891   3 21.24359508259891
-10.85192405303825  2 21.77696655044365
1
0.00000000000000    2 1.000000000000000
   #+END_EXAMPLE

   In TREXIO representation this would be:

   #+BEGIN_EXAMPLE
num = 8

# lmax+1 per atom
max_ang_mom_plus_1 = [ 1, 1 ]

# number of core electrons to remove per atom
zcore = [ 0, 0 ]

# first 4 ECP elements correspond to the first H atom ; the remaining 4 elements are for the second H atom
nucleus_index = [
  0, 0, 0, 0,
  1, 1, 1, 1
  ]

# 3 first ECP elements correspond to potential of the P orbital (l=1), then 1 element for the S orbital (l=0) ; similar for the second H atom
ang_mom = [
  1, 1, 1, 0,
  1, 1, 1, 0
  ]

# ECP quantities that can be attributed to atoms and/or angular momenta based on the aforementioned ecp_nucleus and ecp_ang_mom arrays
coefficient = [
  1.00000000000000, 21.24359508259891, -10.85192405303825, 0.00000000000000,
  1.00000000000000, 21.24359508259891, -10.85192405303825, 0.00000000000000
  ]

exponent = [
  21.24359508259891, 21.24359508259891, 21.77696655044365, 1.000000000000000,
  21.24359508259891, 21.24359508259891, 21.77696655044365, 1.000000000000000
  ]

power = [
  -1, 1, 0, 0,
  -1, 1, 0, 0
  ]
   #+END_EXAMPLE

* Basis set (basis group)

  We consider here basis functions centered on nuclei. Hence, we enable
  the possibility to define /dummy atoms/ to place basis functions in
  random positions.

  The atomic basis set is defined as a list of shells. Each shell $s$ is
  centered on a center $A$, possesses a given angular momentum $l$ and a
  radial function $R_s$. The radial function is a linear combination of
  $N_{\text{prim}}$ /primitive/ functions that can be of type
  Slater ($p=1$) or Gaussian ($p=2$),
  parameterized by exponents $\gamma_{ks}$ and coefficients $a_{ks}$:
  \[
  R_s(\mathbf{r}) = \mathcal{N}_s \vert\mathbf{r}-\mathbf{R}_A\vert^{n_s}
  \sum_{k=1}^{N_{\text{prim}}} a_{ks}\, f_{ks}(\gamma_{ks},p)\,
  \exp \left( - \gamma_{ks}
  \vert \mathbf{r}-\mathbf{R}_A \vert ^p \right).
  \]

  In the case of Gaussian functions, $n_s$ is always zero.

  Different codes normalize functions at different levels. Computing
  normalization factors requires the ability to compute overlap
  integrals, so the normalization factors should be written in the
  file to ensure that the file is self-contained and does not need the
  client program to have the ability to compute such integrals.

  Some codes assume that the contraction coefficients are for a linear
  combination of /normalized/ primitives. This implies that a normalization
  constant for the primitive $ks$ needs to be computed and stored. If
  this normalization factor is not required, $f_{ks}=1$.

  Some codes assume that the basis function are normalized. This
  implies the computation of an extra normalization factor, $\mathcal{N}_s$.
  If the the basis function is not considered normalized, $\mathcal{N}_s=1$.


  All the basis set parameters are stored in one-dimensional arrays:

  #+NAME: basis
  | Variable        | Type    | Dimensions          | Description                                                  |
  |-----------------+---------+---------------------+--------------------------------------------------------------|
  | ~type~          | ~str~   |                     | Type of basis set: "Gaussian" or "Slater"                    |
  | ~prim_num~      | ~dim~   |                     | Total number of primitives                                   |
  | ~shell_num~     | ~dim~   |                     | Total number of shells                                       |
  | ~nucleus_index~ | ~index~ | ~(basis.shell_num)~ | One-to-one correspondence between shells and atomic indices  |
  | ~shell_ang_mom~ | ~int~   | ~(basis.shell_num)~ | One-to-one correspondence between shells and angular momenta |
  | ~shell_factor~  | ~float~ | ~(basis.shell_num)~ | Normalization factor of each shell ($\mathcal{N}_s$)         |
  | ~shell_index~   | ~index~ | ~(basis.prim_num)~  | One-to-one correspondence between primitives and shell index |
  | ~exponent~      | ~float~ | ~(basis.prim_num)~  | Exponents of the primitives ($\gamma_{ks}$)                  |
  | ~coefficient~   | ~float~ | ~(basis.prim_num)~  | Coefficients of the primitives ($a_{ks}$)                    |
  | ~prim_factor~   | ~float~ | ~(basis.prim_num)~  | Normalization coefficients for the primitives ($f_{ks}$)     |

  #+CALL: json(data=basis, title="basis")

  #+RESULTS:
  :results:
  #+begin_src python :tangle trex.json
      "basis": {
                   "type" : [ "str"  , []                    ]
        ,      "prim_num" : [ "dim"  , []                    ]
        ,     "shell_num" : [ "dim"  , []                    ]
        , "nucleus_index" : [ "index", [ "basis.shell_num" ] ]
        , "shell_ang_mom" : [ "int"  , [ "basis.shell_num" ] ]
        ,  "shell_factor" : [ "float", [ "basis.shell_num" ] ]
        ,   "shell_index" : [ "index", [ "basis.prim_num" ]  ]
        ,      "exponent" : [ "float", [ "basis.prim_num" ]  ]
        ,   "coefficient" : [ "float", [ "basis.prim_num" ]  ]
        ,   "prim_factor" : [ "float", [ "basis.prim_num" ]  ]
      } ,
  #+end_src
  :end:

** Example

  For example, consider H_2 with the following basis set (in GAMESS
  format), where both the AOs and primitives are considered normalized:

   #+BEGIN_EXAMPLE
HYDROGEN
S   5
1         3.387000E+01           6.068000E-03
2         5.095000E+00           4.530800E-02
3         1.159000E+00           2.028220E-01
4         3.258000E-01           5.039030E-01
5         1.027000E-01           3.834210E-01
S   1
1         3.258000E-01           1.000000E+00
S   1
1         1.027000E-01           1.000000E+00
P   1
1         1.407000E+00           1.000000E+00
P   1
1         3.880000E-01           1.000000E+00
D   1
1         1.057000E+00           1.000000E+00
   #+END_EXAMPLE

   In TREXIO representaion we have:

   #+BEGIN_EXAMPLE
type  = "Gaussian"
prim_num   = 20
shell_num   = 12

# 6 shells per H atom
nucleus_index =
[ 0, 0, 0, 0, 0, 0,
  1, 1, 1, 1, 1, 1 ]

# 3 shells in S (l=0), 2 in P (l=1), 1 in D (l=2)
shell_ang_mom =
[ 0, 0, 0, 1, 1, 2,
  0, 0, 0, 1, 1, 2 ]

# no need to renormalize shells
shell_factor =
[ 1., 1., 1., 1., 1., 1.,
  1., 1., 1., 1., 1., 1. ]

# 5 primitives for the first S shell and then 1 primitive per remaining shells in each H atom
shell_index =
[ 0, 0, 0, 0, 0, 1, 2, 3, 4, 5,
  6, 6, 6, 6, 6, 7, 8, 9, 10, 11 ]

# parameters of the primitives (10 per H atom)
exponent =
[ 33.87, 5.095, 1.159, 0.3258, 0.1027, 0.3258, 0.1027, 1.407, 0.388, 1.057,
  33.87, 5.095, 1.159, 0.3258, 0.1027, 0.3258, 0.1027, 1.407, 0.388, 1.057 ]

coefficient =
[ 0.006068, 0.045308, 0.202822, 0.503903, 0.383421, 1.0, 1.0, 1.0, 1.0, 1.0,
  0.006068, 0.045308, 0.202822, 0.503903, 0.383421, 1.0, 1.0, 1.0, 1.0, 1.0 ]
`
prim_factor =
[ 1.0006253235944540e+01, 2.4169531573445120e+00, 7.9610924849766440e-01
  3.0734305383061117e-01, 1.2929684417481876e-01, 3.0734305383061117e-01,
  1.2929684417481876e-01, 2.1842769845268308e+00, 4.3649547399719840e-01,
  1.8135965626177861e+00, 1.0006253235944540e+01, 2.4169531573445120e+00,
  7.9610924849766440e-01, 3.0734305383061117e-01, 1.2929684417481876e-01,
  3.0734305383061117e-01, 1.2929684417481876e-01, 2.1842769845268308e+00,
  4.3649547399719840e-01, 1.8135965626177861e+00 ]
   #+END_EXAMPLE

* Atomic orbitals (ao group)

  Going from the atomic basis set to AOs implies a systematic
  construction of all the angular functions of each shell.  We
  consider two cases for the angular functions: the real-valued
  spherical harmonics, and the polynomials in Cartesian coordinates.
  In the case of real spherical harmonics, the AOs are ordered as
  $0, +1, -1, +2, -2, \dots, +m, -m$ (see [[https://en.wikipedia.org/wiki/Table_of_spherical_harmonics#Real_spherical_harmonics][Wikipedia]]).
  In the case of polynomials we
  impose the canonical (or alphabetical) ordering), i.e

  \begin{eqnarray}
  p & : & p_x, p_y, p_z \nonumber \\
  d & : & d_{xx}, d_{xy}, d_{xz}, d_{yy}, d_{yz}, d_{zz} \nonumber \\
  f & : & f_{xxx}, f_{xxy}, f_{xxz}, f_{xyy}, f_{xyz}, f_{xzz}, f_{yyy}, f_{yyz}, f_{yzz},      …f_{zzz} \nonumber \\
  {\rm etc.} \nonumber
  \end{eqnarray}

  Note that there is no exception for $p$ orbitals in spherical
  coordinates: the ordering is $0,+1,-1$ which corresponds $p_z, p_x, p_y$.

  AOs are defined as

  \[
  \chi_i (\mathbf{r}) = \mathcal{N}_i\, P_{\eta(i)}(\mathbf{r})\, R_{\theta(i)} (\mathbf{r})
  \]

  where $i$ is the atomic orbital index,
  $P$ encodes for either the
  polynomials or the spherical harmonics, $\theta(i)$ returns the
  shell on which the AO is expanded, and $\eta(i)$ denotes which
  angular function is chosen.
  $\mathcal{N}_i$ is a normalization factor that enables the
  possibility to have different normalization coefficients within a
  shell, as in the GAMESS convention where
  $\mathcal{N}_{x^2} \ne \mathcal{N}_{xy}$ because
  \[ \left[ \iiint \left(x-X_A \right)^2 R_{\theta(i)}
  (\mathbf{r}) dx\, dy\, dz \right]^{-1/2} \ne
   \left[ \iiint \left( x-X_A \right) \left( y-Y_A \right) R_{\theta(i)}
  (\mathbf{r}) dx\, dy\, dz \right]^{-1/2}.  \]

  In such a case, one should set the normalization of the shell (in
  the [[Basis set (basis group)][Basis set]] section) to $\mathcal{N}_{z^2}$, which is the
  normalization factor of the atomic orbitals in spherical coordinates.
  The normalization factor of the $xy$ function which should be
  introduced here should be $\frac{\mathcal{N}_{xy}}{\mathcal{N}_{z^2}}$.

  #+NAME: ao
  | Variable        | Type    | Dimensions | Description                     |
  |-----------------+---------+------------+---------------------------------|
  | ~cartesian~     | ~int~   |            | ~1~: true, ~0~: false           |
  | ~num~           | ~dim~   |            | Total number of atomic orbitals |
  | ~shell~         | ~index~ | ~(ao.num)~ | basis set shell for each AO     |
  | ~normalization~ | ~float~ | ~(ao.num)~ | Normalization factors           |

  #+CALL: json(data=ao, title="ao")

  #+RESULTS:
  :results:
  #+begin_src python :tangle trex.json
      "ao": {
              "cartesian" : [ "int"  , []           ]
        ,           "num" : [ "dim"  , []           ]
        ,         "shell" : [ "index", [ "ao.num" ] ]
        , "normalization" : [ "float", [ "ao.num" ] ]
      } ,
  #+end_src
  :end:

** One-electron integrals (~ao_1e_int~ group)
   :PROPERTIES:
   :CUSTOM_ID: ao_one_e
   :END:

   - \[ \hat{V}_{\text{ne}} = \sum_{A=1}^{N_\text{nucl}}
     \sum_{i=1}^{N_\text{elec}} \frac{-Z_A }{\vert \mathbf{R}_A -
     \mathbf{r}_i \vert} \] : electron-nucleus attractive potential,
   - \[ \hat{T}_{\text{e}} =
     \sum_{i=1}^{N_\text{elec}} -\frac{1}{2}\hat{\Delta}_i \] : electronic kinetic energy
   - $\hat{h} = \hat{T}_\text{e} + \hat{V}_\text{ne} + \hat{V}_\text{ECP}$ : core electronic Hamiltonian

   The one-electron integrals for a one-electron operator $\hat{O}$ are
   \[ \langle p \vert \hat{O} \vert q \rangle \], returned as a matrix
   over atomic orbitals.

   #+NAME: ao_1e_int
  | Variable              | Type    | Dimensions         | Description                                                                       |
  |-----------------------+---------+--------------------+-----------------------------------------------------------------------------------|
  | ~overlap~             | ~float~ | ~(ao.num, ao.num)~ | $\langle p \vert q \rangle$  (real part, general case)                            |
  | ~kinetic~             | ~float~ | ~(ao.num, ao.num)~ | $\langle p \vert \hat{T}_e \vert q \rangle$  (real part, general case)            |
  | ~potential_n_e~       | ~float~ | ~(ao.num, ao.num)~ | $\langle p \vert \hat{V}_{\text{ne}} \vert q \rangle$  (real part, general case)  |
  | ~ecp~                 | ~float~ | ~(ao.num, ao.num)~ | $\langle p \vert \hat{V}_{\text{ecp}} \vert q \rangle$  (real part, general case) |
  | ~core_hamiltonian~    | ~float~ | ~(ao.num, ao.num)~ | $\langle p \vert \hat{h} \vert q \rangle$  (real part, general case)              |
  | ~overlap_im~          | ~float~ | ~(ao.num, ao.num)~ | $\langle p \vert q \rangle$ (imaginary part)  (imaginary part)                    |
  | ~kinetic_im~          | ~float~ | ~(ao.num, ao.num)~ | $\langle p \vert \hat{T}_e \vert q \rangle$   (imaginary part)                    |
  | ~potential_n_e_im~    | ~float~ | ~(ao.num, ao.num)~ | $\langle p \vert \hat{V}_{\text{ne}} \vert q \rangle$  (imaginary part)           |
  | ~ecp_im~              | ~float~ | ~(ao.num, ao.num)~ | $\langle p \vert \hat{V}_{\text{ECP}} \vert q \rangle$  (imaginary part)          |
  | ~core_hamiltonian_im~ | ~float~ | ~(ao.num, ao.num)~ | $\langle p \vert \hat{h} \vert q \rangle$ (imaginary part)                        |

   #+CALL: json(data=ao_1e_int, title="ao_1e_int")

   #+RESULTS:
   :results:
   #+begin_src python :tangle trex.json
       "ao_1e_int": {
                       "overlap" : [ "float", [ "ao.num", "ao.num" ] ]
         ,             "kinetic" : [ "float", [ "ao.num", "ao.num" ] ]
         ,       "potential_n_e" : [ "float", [ "ao.num", "ao.num" ] ]
         ,                 "ecp" : [ "float", [ "ao.num", "ao.num" ] ]
         ,    "core_hamiltonian" : [ "float", [ "ao.num", "ao.num" ] ]
         ,          "overlap_im" : [ "float", [ "ao.num", "ao.num" ] ]
         ,          "kinetic_im" : [ "float", [ "ao.num", "ao.num" ] ]
         ,    "potential_n_e_im" : [ "float", [ "ao.num", "ao.num" ] ]
         ,              "ecp_im" : [ "float", [ "ao.num", "ao.num" ] ]
         , "core_hamiltonian_im" : [ "float", [ "ao.num", "ao.num" ] ]
       } ,
   #+end_src
   :end:

** Two-electron integrals (~ao_2e_int~ group)
   :PROPERTIES:
   :CUSTOM_ID: ao_two_e
   :END:

   The two-electron integrals for a two-electron operator $\hat{O}$ are
   \[ \langle p q \vert \hat{O} \vert r s \rangle \] in physicists
   notation or \[ ( pr \vert \hat{O} \vert qs ) \] in chemists
   notation, where $p,q,r,s$ are indices over atomic orbitals.

   Functions are provided to get the indices in physicists or chemists
   notation.

   # TODO: Physicist / Chemist functions

   - \[ \hat{W}_{\text{ee}} = \sum_{i=2}^{N_\text{elec}} \sum_{j=1}^{i-1} \frac{1}{\vert \mathbf{r}_i - \mathbf{r}_j \vert} \] : electron-electron repulsive potential operator.
   - \[ \hat{W}^{lr}_{\text{ee}} = \sum_{i=2}^{N_\text{elec}}
     \sum_{j=1}^{i-1} \frac{\text{erf}(\vert \mathbf{r}_i -
     \mathbf{r}_j \vert)}{\vert \mathbf{r}_i - \mathbf{r}_j \vert} \] : electron-electron long range potential

   #+NAME: ao_2e_int
  | Variable | Type           | Dimensions                         | Description                             |
  |----------+----------------+------------------------------------+-----------------------------------------|
  | ~eri~    | ~float sparse~ | ~(ao.num, ao.num, ao.num, ao.num)~ | Electron repulsion integrals            |
  | ~eri_lr~ | ~float sparse~ | ~(ao.num, ao.num, ao.num, ao.num)~ | Long-range Electron repulsion integrals |

   #+CALL: json(data=ao_2e_int, title="ao_2e_int")

   #+RESULTS:
   :results:
   #+begin_src python :tangle trex.json
       "ao_2e_int": {
              "eri" : [ "float sparse", [ "ao.num", "ao.num", "ao.num", "ao.num" ] ]
         , "eri_lr" : [ "float sparse", [ "ao.num", "ao.num", "ao.num", "ao.num" ] ]
       } ,
   #+end_src
   :end:

* Molecular orbitals (mo group)

  #+NAME: mo
  | Variable         | Type    | Dimensions         | Description                                                              |
  |------------------+---------+--------------------+--------------------------------------------------------------------------|
  | ~type~           | ~str~   |                    | Free text to identify the set of MOs (HF, Natural, Local, CASSCF, /etc/) |
  | ~num~            | ~dim~   |                    | Number of MOs                                                            |
  | ~coefficient~    | ~float~ | ~(ao.num, mo.num)~ | MO coefficients (real part, general case)                                |
  | ~coefficient_im~ | ~float~ | ~(ao.num, mo.num)~ | MO coefficients (imaginary part, for periodic calculations)              |
  | ~class~          | ~str~   | ~(mo.num)~         | Choose among: Core, Inactive, Active, Virtual, Deleted                   |
  | ~symmetry~       | ~str~   | ~(mo.num)~         | Symmetry in the point group                                              |
  | ~occupation~     | ~float~ | ~(mo.num)~         | Occupation number                                                        |
  | ~energy~         | ~float~ | ~(mo.num)~         | For canonical MOs, corresponding eigenvalue                              |
  | ~spin~           | ~int~   | ~(mo.num)~         | For UHF wave functions, 0 is $\alpha$ and 1 is $\beta$                   |

  #+CALL: json(data=mo, title="mo")

  #+RESULTS:
  :results:
  #+begin_src python :tangle trex.json
      "mo": {
                    "type" : [ "str"  , []                     ]
        ,            "num" : [ "dim"  , []                     ]
        ,    "coefficient" : [ "float", [ "mo.num", "ao.num" ] ]
        , "coefficient_im" : [ "float", [ "mo.num", "ao.num" ] ]
        ,          "class" : [ "str"  , [ "mo.num" ]           ]
        ,       "symmetry" : [ "str"  , [ "mo.num" ]           ]
        ,     "occupation" : [ "float", [ "mo.num" ]           ]
        ,         "energy" : [ "float", [ "mo.num" ]           ]
        ,           "spin" : [ "int"  , [ "mo.num" ]           ]
      } ,
  #+end_src
  :end:

** One-electron integrals (~mo_1e_int~ group)

   The operators as the same as those defined in the
   [[#ao_one_e][AO one-electron integrals section]]. Here, the integrals are given in
   the basis of molecular orbitals.

   #+NAME: mo_1e_int
  | Variable              | Type    | Dimensions         | Description                                                                       |
  |-----------------------+---------+--------------------+-----------------------------------------------------------------------------------|
  | ~overlap~             | ~float~ | ~(mo.num, mo.num)~ | $\langle i \vert j \rangle$  (real part, general case)                            |
  | ~kinetic~             | ~float~ | ~(mo.num, mo.num)~ | $\langle i \vert \hat{T}_e \vert j \rangle$ (real part, general case)             |
  | ~potential_n_e~       | ~float~ | ~(mo.num, mo.num)~ | $\langle i \vert \hat{V}_{\text{ne}} \vert j \rangle$  (real part, general case)  |
  | ~ecp~                 | ~float~ | ~(mo.num, mo.num)~ | $\langle i \vert \hat{V}_{\text{ECP}} \vert j \rangle$  (real part, general case) |
  | ~core_hamiltonian~    | ~float~ | ~(mo.num, mo.num)~ | $\langle i \vert \hat{h} \vert j \rangle$  (real part, general case)              |
  | ~overlap_im~          | ~float~ | ~(mo.num, mo.num)~ | $\langle i \vert j \rangle$ (imaginary part)  (imaginary part)                    |
  | ~kinetic_im~          | ~float~ | ~(mo.num, mo.num)~ | $\langle i \vert \hat{T}_e \vert j \rangle$   (imaginary part)                    |
  | ~potential_n_e_im~    | ~float~ | ~(mo.num, mo.num)~ | $\langle i \vert \hat{V}_{\text{ne}} \vert j \rangle$  (imaginary part)           |
  | ~ecp_im~              | ~float~ | ~(mo.num, mo.num)~ | $\langle i \vert \hat{V}_{\text{ECP}} \vert j \rangle$  (imaginary part)          |
  | ~core_hamiltonian_im~ | ~float~ | ~(mo.num, mo.num)~ | $\langle i \vert \hat{h} \vert j \rangle$ (imaginary part)                        |

   #+CALL: json(data=mo_1e_int, title="mo_1e_int")

   #+RESULTS:
   :results:
   #+begin_src python :tangle trex.json
       "mo_1e_int": {
                       "overlap" : [ "float", [ "mo.num", "mo.num" ] ]
         ,             "kinetic" : [ "float", [ "mo.num", "mo.num" ] ]
         ,       "potential_n_e" : [ "float", [ "mo.num", "mo.num" ] ]
         ,                 "ecp" : [ "float", [ "mo.num", "mo.num" ] ]
         ,    "core_hamiltonian" : [ "float", [ "mo.num", "mo.num" ] ]
         ,          "overlap_im" : [ "float", [ "mo.num", "mo.num" ] ]
         ,          "kinetic_im" : [ "float", [ "mo.num", "mo.num" ] ]
         ,    "potential_n_e_im" : [ "float", [ "mo.num", "mo.num" ] ]
         ,              "ecp_im" : [ "float", [ "mo.num", "mo.num" ] ]
         , "core_hamiltonian_im" : [ "float", [ "mo.num", "mo.num" ] ]
       } ,
   #+end_src
   :end:

** Two-electron integrals (~mo_2e_int~ group)

   The operators as the same as those defined in the
   [[#ao_two_e][AO two-electron integrals section]]. Here, the integrals are given in
   the basis of molecular orbitals.

   #+NAME: mo_2e_int
  | Variable | Type           | Dimensions                         | Description                             |
  |----------+----------------+------------------------------------+-----------------------------------------|
  | ~eri~    | ~float sparse~ | ~(mo.num, mo.num, mo.num, mo.num)~ | Electron repulsion integrals            |
  | ~eri_lr~ | ~float sparse~ | ~(mo.num, mo.num, mo.num, mo.num)~ | Long-range Electron repulsion integrals |

   #+CALL: json(data=mo_2e_int, title="mo_2e_int")

   #+RESULTS:
   :results:
   #+begin_src python :tangle trex.json
       "mo_2e_int": {
              "eri" : [ "float sparse", [ "mo.num", "mo.num", "mo.num", "mo.num" ] ]
         , "eri_lr" : [ "float sparse", [ "mo.num", "mo.num", "mo.num", "mo.num" ] ]
       } ,
   #+end_src
   :end:

* Slater determinants (determinant group)

  The configuration interaction (CI) wave function $\Psi$
  can be expanded in the basis of Slater determinants $D_I$ as follows

  \[
  \Psi = \sum_I C_I D_I
  \]

  For relatively small expansions, a given determinant can be represented as a list of occupied orbitals.
  However, this becomes unfeasible for larger expansions and requires more advanced data structures.
  The bit field representation is used here, namely a given determinant is represented as $N_{\text{int}}$
  64-bit integers where j-th bit is set to 1 if there is an electron in the j-th orbital and 0 otherwise.
  This gives access to larger determinant expansions by optimising the storage of the determinant lists
  in the memory.

  \[
  D_I = \alpha_1 \alpha_2 \ldots \alpha_{n_\uparrow} \beta_1 \beta_2 \ldots \beta_{n_\downarrow}
  \]

  where $\alpha$ and $\beta$ denote \uparrow-spin and \downarrow-spin electrons, respectively,
  $n_\uparrow$ and $n_\downarrow$ correspond to ~electron.up_num~ and ~electron.dn_num~, respectively.

  Note: the ~special~ attribute is present in the types, meaning that the source node is not
  produced by the code generator.

  An illustration on how to read determinants is presented in the [[./examples.html][examples]].

  #+NAME: determinant
  | Variable      | Type             | Dimensions          | Description                                            |
  |---------------+------------------+---------------------+--------------------------------------------------------|
  | ~num~         | ~dim readonly~   |                     | Number of determinants                                 |
  | ~list~        | ~int special~    | ~(determinant.num)~ | List of determinants as integer bit fields             |
  | ~coefficient~ | ~float buffered~ | ~(determinant.num)~ | Coefficients of the determinants from the CI expansion |

  #+CALL: json(data=determinant, title="determinant")

  #+RESULTS:
  :results:
  #+begin_src python :tangle trex.json
      "determinant": {
		  "num" : [ "dim readonly"  , []                    ]
	,        "list" : [ "int special"   , [ "determinant.num" ] ]
	, "coefficient" : [ "float buffered", [ "determinant.num" ] ]
      } ,
  #+end_src
  :end:

* Configuration state functions (csf group)

  The configuration interaction (CI) wave function $\Psi$ can be
  expanded in the basis of [[https://en.wikipedia.org/wiki/Configuration_state_function][configuration state functions]] (CSFs)
  $\Psi_I$ as follows

  \[
  \Psi = \sum_I C_I \psi_I.
  \]

  Each CSF is a linear combination of Slater determinants. Slater
  determinants are stored in the =determinant= section. In this group
  we store the CI coefficients in the basis of CSFs, and the
  matrix $\langle D_I | \psi_J \rangle$ needed to project the CSFs in
  the basis of Slater determinants.

  #+NAME: csf
  | Variable          | Type             | Dimensions                  | Description                                    |
  |-------------------+------------------+-----------------------------+------------------------------------------------|
  | ~num~             | ~dim readonly~   |                             | Number of CSFs                                 |
  | ~coefficient~     | ~float buffered~ | ~(csf.num)~                 | Coefficients of the CSFs from the CI expansion |
  | ~det_coefficient~ | ~float sparse~   | ~(determinant.num,csf.num)~ | Projection on the determinant basis            |

  #+CALL: json(data=csf, title="csf")

  #+RESULTS:
  :results:
  #+begin_src python :tangle trex.json
      "csf": {
		      "num" : [ "dim readonly"  , []                               ]
	,     "coefficient" : [ "float buffered", [ "csf.num" ]                    ]
	, "det_coefficient" : [ "float sparse"  , [ "csf.num", "determinant.num" ] ]
      } ,
  #+end_src
  :end:

* Excited states (state group)

  This group contains information about excited state. Since TREXIO version 2.3.0
  the state-specific data (e.g. CI/CSF coeffcients, RDMs) is written in a separate
  file in order to avoid over-complicated internal logics and global state switches.

  The ~file_name~ and ~label~ arrays have to be written only for the master file,
  e.g. the one containing the ground state wave function.
  The ~id~ and ~current_label~ attributes have to be specified for each file
  (containing both ground and excited state data).

  #+NAME: state
  | Variable        | Type  | Dimensions    | Description                                                                                   |
  |-----------------+-------+---------------+-----------------------------------------------------------------------------------------------|
  | ~num~           | ~dim~ |               | Number of states (including the ground state)                                                 |
  | ~id~            | ~int~ |               | Index of a current state (0 is ground state)                                                  |
  | ~label~         | ~str~ | ~(state.num)~ | Labels of all states related to this file (e.g. 'S' for singlets)                             |
  | ~current_label~ | ~str~ |               | Labels of the current state that is in a file                                                 |
  | ~file_name~     | ~str~ | ~(state.num)~ | Names of the TREXIO files linked to the current one (i.e. containing data for excited states) |

  #+CALL: json(data=state, title="state")

  #+RESULTS:
  :results:
  #+begin_src python :tangle trex.json
      "state": {
		    "num" : [ "dim", []              ]
	,            "id" : [ "int", []              ]
	,         "label" : [ "str", [ "state.num" ] ]
	, "current_label" : [ "str", []              ]
	,     "file_name" : [ "str", [ "state.num" ] ]
      } ,
  #+end_src
  :end:

* Reduced density matrices (rdm group)

  The reduced density matrices are defined in the basis of molecular
  orbitals.

  The \uparrow-spin and \downarrow-spin components of the one-body
  density matrix are given by
  \begin{eqnarray*}
    \gamma_{ij}^{\uparrow}   &=& \langle \Psi | \hat{a}^{\dagger}_{j\alpha}\, \hat{a}_{i\alpha} | \Psi \rangle \\
    \gamma_{ij}^{\downarrow} &=& \langle \Psi | \hat{a}^{\dagger}_{j\beta} \, \hat{a}_{i\beta}  | \Psi \rangle
  \end{eqnarray*}
  and the spin-summed one-body density matrix is
  \[
  \gamma_{ij} = \gamma^{\uparrow}_{ij} + \gamma^{\downarrow}_{ij}
  \]

  The $\uparrow \uparrow$,  $\downarrow \downarrow$, $\uparrow \downarrow$, $\downarrow \uparrow$
  components of the two-body density matrix are given by
  \begin{eqnarray*}
    \Gamma_{ijkl}^{\uparrow \uparrow} &=&
       \langle \Psi | \hat{a}^{\dagger}_{k\alpha}\, \hat{a}^{\dagger}_{l\alpha} \hat{a}_{j\alpha}\, \hat{a}_{i\alpha} | \Psi \rangle \\
    \Gamma_{ijkl}^{\downarrow \downarrow} &=&
       \langle \Psi | \hat{a}^{\dagger}_{k\beta}\, \hat{a}^{\dagger}_{l\beta} \hat{a}_{j\beta}\, \hat{a}_{i\beta} | \Psi \rangle \\
    \Gamma_{ijkl}^{\uparrow \downarrow} &=&
       \langle \Psi | \hat{a}^{\dagger}_{k\alpha}\, \hat{a}^{\dagger}_{l\beta} \hat{a}_{j\beta}\, \hat{a}_{i\alpha} | \Psi \rangle \\
    \Gamma_{ijkl}^{\downarrow \uparrow} &=&
       \langle \Psi | \hat{a}^{\dagger}_{k\beta}\, \hat{a}^{\dagger}_{l\alpha} \hat{a}_{j\alpha}\, \hat{a}_{i\beta} | \Psi \rangle \\
  \end{eqnarray*}
  and the spin-summed one-body density matrix is
  \[
  \Gamma_{ijkl} = \Gamma_{ijkl}^{\uparrow \uparrow} +
    \Gamma_{ijkl}^{\downarrow \downarrow} + \Gamma_{ijkl}^{\uparrow \downarrow} +
    \Gamma_{ijkl}^{\downarrow \uparrow}
  \]

  The total energy can be computed as:
  \[
  E = E_{\text{NN}} + \sum_{ij} \gamma_{ij} \langle j|h|i \rangle +
      \frac{1}{2} \sum_{ijlk} \Gamma_{ijkl} \langle k l | i j \rangle
  \]


  To compress the storage, the Cholesky decomposition of the RDMs can
  also be stored.
  
  #+NAME: rdm
  | Variable      | Type           | Dimensions                         | Description                                                           |
  |---------------+----------------+------------------------------------+-----------------------------------------------------------------------|
  | ~1e~          | ~float~        | ~(mo.num, mo.num)~                 | One body density matrix                                               |
  | ~1e_up~       | ~float~        | ~(mo.num, mo.num)~                 | \uparrow-spin component of the one body density matrix                |
  | ~1e_dn~       | ~float~        | ~(mo.num, mo.num)~                 | \downarrow-spin component of the one body density matrix              |
  | ~2e~          | ~float sparse~ | ~(mo.num, mo.num, mo.num, mo.num)~ | Two-body reduced density matrix (spin trace)                          |
  | ~2e_upup~     | ~float sparse~ | ~(mo.num, mo.num, mo.num, mo.num)~ | \uparrow\uparrow component of the two-body reduced density matrix     |
  | ~2e_dndn~     | ~float sparse~ | ~(mo.num, mo.num, mo.num, mo.num)~ | \downarrow\downarrow component of the two-body reduced density matrix |
  | ~2e_updn~     | ~float sparse~ | ~(mo.num, mo.num, mo.num, mo.num)~ | \uparrow\downarrow component of the two-body reduced density matrix   |
  | ~2e_dnup~     | ~float sparse~ | ~(mo.num, mo.num, mo.num, mo.num)~ | \downarrow\uparrow component of the two-body reduced density matrix   |
  | ~chol_num~    | ~dim~          |                                    | Number of cholesky vector                                             |
  | ~2e_cholesky~ | ~float sparse~ | ~(mo.num, mo.num, rdm.chol_num)~   | Two-body RDM (spin trace) in the basis of Cholesky vectors            |

  #+CALL: json(data=rdm, title="rdm")

  #+RESULTS:
  :results:
  #+begin_src python :tangle trex.json
      "rdm": {
                   "1e" : [ "float"       , [ "mo.num", "mo.num" ]                     ]
        ,       "1e_up" : [ "float"       , [ "mo.num", "mo.num" ]                     ]
        ,       "1e_dn" : [ "float"       , [ "mo.num", "mo.num" ]                     ]
        ,          "2e" : [ "float sparse", [ "mo.num", "mo.num", "mo.num", "mo.num" ] ]
        ,     "2e_upup" : [ "float sparse", [ "mo.num", "mo.num", "mo.num", "mo.num" ] ]
        ,     "2e_dndn" : [ "float sparse", [ "mo.num", "mo.num", "mo.num", "mo.num" ] ]
        ,     "2e_updn" : [ "float sparse", [ "mo.num", "mo.num", "mo.num", "mo.num" ] ]
        ,     "2e_dnup" : [ "float sparse", [ "mo.num", "mo.num", "mo.num", "mo.num" ] ]
        ,    "chol_num" : [ "dim"         , []                                         ]
        , "2e_cholesky" : [ "float sparse", [ "rdm.chol_num", "mo.num", "mo.num" ]     ]
      } ,
  #+end_src
  :end:

* Cell (cell group)

  #+NAME: cell
  | Variable | Type    | Dimensions | Description             |
  |----------+---------+------------+-------------------------|
  | ~a~      | ~float~ | ~(3)~      | First unit cell vector  |
  | ~b~      | ~float~ | ~(3)~      | Second unit cell vector |
  | ~c~      | ~float~ | ~(3)~      | Third unit cell vector  |

  #+CALL: json(data=cell, title="cell")

  #+RESULTS:
  :results:
  #+begin_src python :tangle trex.json
      "cell": {
          "a" : [ "float", [ "3" ] ]
        , "b" : [ "float", [ "3" ] ]
        , "c" : [ "float", [ "3" ] ]
      } ,
  #+end_src
  :end:

* Periodic boundary calculations (pbc group)

  #+NAME: pbc
  | Variable   | Type    | Dimensions | Description             |
  |------------+---------+------------+-------------------------|
  | ~periodic~ | ~int~   |            | ~1~: true or ~0~: false |
  | ~k_point~  | ~float~ | ~(3)~      | k-point sampling        |

  #+CALL: json(data=pbc, title="pbc")

  #+RESULTS:
  :results:
  #+begin_src python :tangle trex.json
      "pbc": {
          "periodic" : [ "int"  , []      ]
        ,  "k_point" : [ "float", [ "3" ] ]
      } ,
  #+end_src
  :end:

* Quantum Monte Carlo data (qmc group)

   In quantum Monte Carlo calculations, the wave function is evaluated
   at points of the 3N-dimensional space. Some algorithms require multiple
   independent /walkers/, so it is possible to store multiple coordinates,
   as well as some quantities evaluated at those points.

   By convention, the electron coordinates contain first all the electrons
   of $\uparrow$-spin and then all the $\downarrow$-spin.

   #+name: qmc
  | Variable | Type    | Dimensions                   | Description                           |
  |----------+---------+------------------------------+---------------------------------------|
  | ~num~    | ~dim~   |                              | Number of 3N-dimensional points       |
  | ~point~  | ~float~ | ~(3, electron.num, qmc.num)~ | 3N-dimensional points                 |
  | ~psi~    | ~float~ | ~(qmc.num)~                  | Wave function evaluated at the points |
  | ~e_loc~  | ~float~ | ~(qmc.num)~                  | Local energy evaluated at the points  |

   #+CALL: json(data=qmc, title="qmc", last=1)

   #+RESULTS:
   :results:
   #+begin_src python :tangle trex.json
       "qmc": {
             "num" : [ "dim"  , []                                 ]
         , "point" : [ "float", [ "qmc.num", "electron.num", "3" ] ]
         ,   "psi" : [ "float", [ "qmc.num" ]                      ]
         , "e_loc" : [ "float", [ "qmc.num" ]                      ]
       }
   #+end_src
   :end:

* Appendix    :noexport:
** Python script from table to json

 #+NAME: json
 #+begin_src python :var data=nucleus title="nucleus" last=0 :results output drawer
print("""#+begin_src python :tangle trex.json""")
print("""    "%s": {"""%(title))
indent = "        "
f1 = 0 ; f2 = 0 ; f3 = 0
for line in data:
    line = [ x.replace("~","") for x in line ]
    name = '"'+line[0]+'"'
    typ  = '"'+line[1]+'"'
    dims = line[2]
    if '(' in dims:
        dims = dims.strip()[1:-1]
        dims = [ '"'+x.strip()+'"' for x in dims.split(',') ]
        dims = "[ " + ", ".join(dims) + " ]"
    else:
        dims = "[ ]"
    f1 = max(f1, len(name))
    f2 = max(f2, len(typ))
    f3 = max(f3, len(dims))

fmt = "%%s%%%ds : [ %%%ds, %%%ds ]" % (f1, f2, f3)
for line in data:
    line = [ x.replace("~","") for x in line ]
    name = '"'+line[0]+'"'
    typ  = '"'+line[1]+'"'
    dims = line[2]
    if '(' in dims:
        dims = dims.strip()[1:-1]
        dims = [ '"'+x.strip()+'"' for x in dims.split(',') ]
        dims.reverse()
        dims = "[ " + ", ".join(dims) + " ]"
    else:
        if dims.strip() != "":
            dims = "ERROR"
        else:
            dims = "[]"
    buffer = fmt % (indent, name, typ.ljust(f2), dims.ljust(f3))
    indent = "      , "
    print(buffer)

if last == 0:
    print("    } ,")
else:
    print("    }")
print("""#+end_src""")

 #+end_src


  #+begin_src python :tangle trex.json :results output drawer :exports none
}
  #+end_src