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Merge pull request #65 from TREX-CoE/fix-basis-structure

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FIX: data format in the basis group consistent with ECP
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Anthony Scemama 2021-10-21 19:39:47 +02:00 committed by GitHub
commit 0967c5f4b8
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8 changed files with 90 additions and 62 deletions
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2
configure.ac
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@ -2,7 +2,7 @@
# Process this file with autoconf to produce a configure script.
AC_PREREQ([2.69])
AC_INIT([trexio], [1.1.0], [https://github.com/TREX-CoE/trexio/issues])
AC_INIT([trexio], [2.0.0], [https://github.com/TREX-CoE/trexio/issues])
AM_INIT_AUTOMAKE([subdir-objects color-tests parallel-tests silent-rules 1.11])
AM_MAINTAINER_MODE()
LT_PREREQ([2.2])

2
python/pytrexio/_version.py
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@ -1 +1 @@
__version__ = "0.1.0"
__version__ = "1.0.0"

18
python/test/test_api.py
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@ -71,11 +71,15 @@ charges_np = np.array(charges, dtype=np.int32)
# from the size of the list/array by SWIG using typemaps from numpy.i
trexio.write_nucleus_charge(test_file, charges_np)
basis_shell_num = 24
# initialize arrays of nuclear indices as a list and convert it to numpy array
indices = [i for i in range(nucleus_num)]
indices = [i for i in range(basis_shell_num)]
# type cast is important here because by default numpy transforms a list of integers into int64 array
indices_np = np.array(indices, dtype=np.int64)
# first write basis_shell_num because it is needed to check dimensions of basis_nucleus_index in TREXIO >= 2.0.0
trexio.write_basis_shell_num(test_file, basis_shell_num)
# function call below works with both lists and numpy arrays, dimension needed for memory-safety is derived
# from the size of the list/array by SWIG using typemacs from numpy.i
trexio.write_basis_nucleus_index(test_file, indices_np)
@ -160,20 +164,20 @@ except trexio.Error:
print("Unsafe call to safe API: checked")
# safe call to read array of int values (nuclear indices)
rindices_np_16 = trexio.read_basis_nucleus_index(test_file2, dim=nucleus_num, dtype=np.int16)
rindices_np_16 = trexio.read_basis_nucleus_index(test_file2, dim=basis_shell_num, dtype=np.int16)
assert rindices_np_16.dtype is np.dtype(np.int16)
for i in range(nucleus_num):
for i in range(basis_shell_num):
assert rindices_np_16[i]==indices_np[i]
rindices_np_32 = trexio.read_basis_nucleus_index(test_file2, dim=nucleus_num, dtype=np.int32)
rindices_np_32 = trexio.read_basis_nucleus_index(test_file2, dim=basis_shell_num, dtype=np.int32)
assert rindices_np_32.dtype is np.dtype(np.int32)
for i in range(nucleus_num):
for i in range(basis_shell_num):
assert rindices_np_32[i]==indices_np[i]
rindices_np_64 = trexio.read_basis_nucleus_index(test_file2)
assert rindices_np_64.dtype is np.dtype(np.int64)
assert rindices_np_64.size==nucleus_num
for i in range(nucleus_num):
assert rindices_np_64.size==basis_shell_num
for i in range(basis_shell_num):
assert rindices_np_64[i]==indices_np[i]
# read nuclear coordinates without providing optional argument dim

13
python/test/test_pytrexio.py
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@ -59,11 +59,16 @@ assert rc==0
# charges[i] = 1.
#rc = trexio_write_nucleus_charge(test_file, charges)
basis_num = 24
# initialize arrays of nuclear indices as a list and convert it to numpy array
indices = [i for i in range(nucleus_num)]
indices = [i for i in range(basis_num)]
# type cast is important here because by default numpy transforms a list of integers into int64 array
indices_np = np.array(indices, dtype=np.int32)
# first write basis_num because it is needed to check dimensions of basis_nucleus_index in TREXIO >= 2.0.0
rc = trexio_write_basis_shell_num(test_file, basis_num)
assert rc==0
# function call below works with both lists and numpy arrays, dimension needed for memory-safety is derived
# from the size of the list/array by SWIG using typemacs from numpy.i
rc = trexio_write_safe_basis_nucleus_index(test_file, indices_np)
@ -124,8 +129,12 @@ assert rc==23
#for i in range(nucleus_num):
# assert charges2[i]==charges[i]
result_basis = trexio_read_basis_shell_num(test_file2)
assert result[0]==0
assert result[1]==basis_num
# safe call to read_safe array of int values
rc, rindices_np = trexio_read_safe_basis_nucleus_index(test_file2, nucleus_num)
rc, rindices_np = trexio_read_safe_basis_nucleus_index(test_file2, basis_num)
assert rc==0
assert rindices_np.dtype is np.dtype(np.int32)
for i in range(nucleus_num):

4
tests/io_dset_int_hdf5.c
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@ -25,7 +25,7 @@ static int test_write_dset (const char* file_name, const back_end_t backend) {
assert (file != NULL);
// write numerical attribute in an empty file
rc = trexio_write_nucleus_num(file, num);
rc = trexio_write_basis_shell_num(file, num);
assert (rc == TREXIO_SUCCESS);
// write numerical (integer) dataset in a file
@ -91,7 +91,7 @@ static int test_read_dset (const char* file_name, const back_end_t backend) {
assert (file != NULL);
// read numerical attribute from the file
rc = trexio_read_nucleus_num(file, &num);
rc = trexio_read_basis_shell_num(file, &num);
assert (rc == TREXIO_SUCCESS);
assert (num == 12);

4
tests/io_dset_int_text.c
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@ -25,7 +25,7 @@ static int test_write_dset (const char* file_name, const back_end_t backend) {
assert (file != NULL);
// write numerical attribute in an empty file
rc = trexio_write_nucleus_num(file, num);
rc = trexio_write_basis_shell_num(file, num);
assert (rc == TREXIO_SUCCESS);
// write numerical (integer) dataset in a file
@ -91,7 +91,7 @@ static int test_read_dset (const char* file_name, const back_end_t backend) {
assert (file != NULL);
// read numerical attribute from the file
rc = trexio_read_nucleus_num(file, &num);
rc = trexio_read_basis_shell_num(file, &num);
assert (rc == TREXIO_SUCCESS);
assert (num == 12);

14
tests/test_f.f90
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@ -44,9 +44,9 @@ subroutine test_write(file_name, back_end)
integer :: rc = 1
integer :: num
integer :: num, basis_shell_num
integer :: basis_nucleus_index(12)
integer :: basis_nucleus_index(24)
double precision :: charge(12)
double precision :: coord(3,12)
@ -70,7 +70,8 @@ subroutine test_write(file_name, back_end)
0.00000000d0, 2.47304151d0 , 0.00000000d0 /), &
shape(coord) )
basis_nucleus_index = (/ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 /)
basis_shell_num = 24
basis_nucleus_index = (/ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24 /)
label = [character(len=8) :: 'C', 'Na','C', 'C 66', 'C','C', 'H 99', 'Ru', 'H', 'H', 'H', 'H' ]
@ -104,6 +105,8 @@ subroutine test_write(file_name, back_end)
deallocate(sym_str)
call trexio_assert(rc, TREXIO_SUCCESS, 'SUCCESS WRITE POINT GROUP')
rc = trexio_write_basis_shell_num(trex_file, basis_shell_num)
call trexio_assert(rc, TREXIO_SUCCESS, 'SUCCESS WRITE BASIS NUM')
rc = trexio_write_basis_nucleus_index(trex_file, basis_nucleus_index)
call trexio_assert(rc, TREXIO_SUCCESS, 'SUCCESS WRITE INDEX')
@ -137,9 +140,9 @@ subroutine test_read(file_name, back_end)
integer :: i, j, k, ind, offset, flag
integer :: rc = 1
integer :: num, num_read
integer :: num, num_read, basis_shell_num
integer :: basis_nucleus_index(12)
integer :: basis_nucleus_index(24)
double precision :: charge(12)
double precision :: coord(3,12)
@ -152,6 +155,7 @@ subroutine test_read(file_name, back_end)
character*(128) :: str
num = 12
basis_shell_num = 24
! ================= START OF TEST ===================== !

95
trex.org
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@ -215,20 +215,18 @@ arrays are 0-based. Hence, we introduce the ~index~ type which is an
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" |
| ~num~ | ~dim~ | | Total Number of shells |
| ~prim_num~ | ~dim~ | | Total number of primitives |
| ~nucleus_index~ | ~index~ | ~(nucleus.num)~ | Index of the first shell of each nucleus ($A$) |
| ~nucleus_shell_num~ | ~int~ | ~(nucleus.num)~ | Number of shells for each nucleus |
| ~shell_ang_mom~ | ~int~ | ~(basis.num)~ | Angular momentum ~0:S, 1:P, 2:D, ...~ |
| ~shell_prim_num~ | ~int~ | ~(basis.num)~ | Number of primitives in the shell ($N_{\text{prim}}$) |
| ~shell_factor~ | ~float~ | ~(basis.num)~ | Normalization factor of the shell ($\mathcal{N}_s$) |
| ~shell_prim_index~ | ~index~ | ~(basis.num)~ | Index of the first primitive in the complete list |
| ~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 ($f_{ks}$) |
| 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 |
| ~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")
@ -236,22 +234,22 @@ arrays are 0-based. Hence, we introduce the ~index~ type which is an
:RESULTS:
#+begin_src python :tangle trex.json
"basis": {
"type" : [ "str" , [] ]
, "num" : [ "dim" , [] ]
, "prim_num" : [ "dim" , [] ]
, "nucleus_index" : [ "index", [ "nucleus.num" ] ]
, "nucleus_shell_num" : [ "int" , [ "nucleus.num" ] ]
, "shell_ang_mom" : [ "int" , [ "basis.num" ] ]
, "shell_prim_num" : [ "int" , [ "basis.num" ] ]
, "shell_factor" : [ "float", [ "basis.num" ] ]
, "shell_prim_index" : [ "index", [ "basis.num" ] ]
, "exponent" : [ "float", [ "basis.prim_num" ] ]
, "coefficient" : [ "float", [ "basis.prim_num" ] ]
, "prim_factor" : [ "float", [ "basis.prim_num" ] ]
"type" : [ "str" , [] ]
, "prim_num" : [ "dim" , [] ]
, "shell_num" : [ "dim" , [] ]
, "nucleus_index" : [ "index", [ "basis.shell_num" ] ]
, "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:
@ -272,31 +270,44 @@ P 1
P 1
1 3.880000E-01 1.000000E+00
D 1
1 1.057000E+00 1.0000000
1 1.057000E+00 1.000000E+00
#+END_EXAMPLE
we have:
In TREXIO representaion we have:
#+BEGIN_EXAMPLE
type = "Gaussian"
num = 12
prim_num = 20
type = "Gaussian"
prim_num = 20
shell_num = 12
nucleus_index = [0 , 6]
shell_ang_mom = [0 , 0 , 0 , 1 , 1 , 2 , 0 , 0 , 0 , 1 , 1 , 2 ]
shell_prim_num = [5 , 1 , 1 , 1 , 1 , 1 , 5 , 1 , 1 , 1 , 1 , 1 ]
shell_prim_index = [0 , 5 , 6 , 7 , 8 , 9 , 10, 15, 16, 17, 18, 19]
shell_factor = [1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.]
# 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)
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]
[ 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]
[ 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