calc = Calculator(Param.GFN2xTB, mol.get_atomic_numbers(), mol.get_scaled_positions(), charge=1)
res = calc.singlepoint()
print('energy', res.get_energy())

mol2 = read('qca_seed10.xyz') 
mol2.set_calculator(XTB(method="GFN2-xTB", charge=1))
print('pe', mol2.get_potential_energy())

direct calc energy 71.23435304058115
direct calc energy 71.54337595108338
energy before conversion -63.89323100198211
ase/xtb pe -1738.623373139004
energy before conversion -63.89323100198211
ase/xtb pe -1738.623373139004

---------------------------------------------------------------------------
ModuleNotFoundError                       Traceback (most recent call last)
File ~/DD_tools/xtb-python/xtb/libxtb.py:32
     31 try:
---> 32     from ._libxtb import ffi, lib
     33 except ImportError:

ModuleNotFoundError: No module named 'xtb._libxtb'

During handling of the above exception, another exception occurred:

ImportError                               Traceback (most recent call last)
Cell In [2], line 1
----> 1 from xtb.interface import Calculator
      2 from xtb.utils import get_method
      3 import numpy as np

File ~/DD_tools/xtb-python/xtb/interface.py:25
     21 from enum import Enum, auto
     22 import numpy as np
---> 25 from .libxtb import (
     26     ffi as _ffi,
     27     lib as _lib,
     28     new_environment,
     29     new_molecule,
     30     new_calculator,
     31     new_results,
     32     copy_results,
     33     VERBOSITY_FULL,
     34     VERBOSITY_MINIMAL,
     35     VERBOSITY_MUTED
     36 )
     38 _verbosity_flags = {
     39     "full": VERBOSITY_FULL,
     40     "minimal": VERBOSITY_MINIMAL,
     41     "muted": VERBOSITY_MUTED
     42 }
     45 class XTBException(Exception):

File ~/DD_tools/xtb-python/xtb/libxtb.py:34
     32     from ._libxtb import ffi, lib
     33 except ImportError:
---> 34     raise ImportError("xtb C extension unimportable, cannot use C-API")
     37 VERBOSITY_FULL = 2
     38 VERBOSITY_MINIMAL = 1

ImportError: xtb C extension unimportable, cannot use C-API`

import sys
import numpy as np
from scipy import constants
import xtb
from xtb.interface import Calculator, XTBException
from xtb.libxtb import VERBOSITY_MUTED
from xtb.utils import get_method
ANGSTROM_IN_BOHR = constants.physical_constants['Bohr radius'][0] * 1.0e10


def run_xtb(atomic_numbers, xyz, net_charge, n_unpaired_electrons, max_iter=250, conv=1.0, method="GFN2-xTB"):
    '''
    Run a single xtb job and return the result.
    Throws XTBException for errors or unrealistic results.

    Arguments:
        atomic_numbers (np.array): integer element labels for all atoms
        xyz (np.array): Nx3 array of coordinates for all atoms, in Angstroms
        n_unpaired_electrons (int): number of unpaired electrons in the system
        max_iter (int): max number of SCF iterations before giving up
        conv (float): SCF cutoffs, smaller means tighter convergence
    Returns:
        E_xtb: total system energy in Hartree
        gradient_xtb: dE/dxyz for each atom, in Hartree/Angstrom
        dipole_xtb: system dipole in electron-Angstrom (not available with PBC)
        qs_xtb: Mulliken atomic charges, in elementary charge units
    '''
    calc = Calculator(get_method(method), atomic_numbers, xyz / ANGSTROM_IN_BOHR,
                      charge=net_charge, uhf=n_unpaired_electrons)
    calc.set_verbosity(VERBOSITY_MUTED)
    calc.set_accuracy(conv)  # default = 1.0, smaller = tighter convergence
    calc.set_max_iterations(max_iter)  # default = 250
    result = calc.singlepoint()
    if result.check() != 0:
        raise XTBException(result.get_error())
    E_xtb = result.get_energy()
    if np.isnan(E_xtb):  # yet another convergence issue
        raise XTBException('Energy is NaN')
    qs_xtb = result.get_charges()
    if abs(net_charge - np.sum(qs_xtb)) > 1e-5:
        raise XTBException('Bad net charge: %d vs %f' % (net_charge, np.sum(qs_xtb)))
    if np.max(np.abs(qs_xtb)) > 4.0:
        raise XTBException('Very implausible partial charge: %f' % np.max(np.abs(qs_xtb)))
    dipole_xtb = result.get_dipole() * ANGSTROM_IN_BOHR  # from electron-Bohr to electron-Angstrom
    gradient_xtb = result.get_gradient() / ANGSTROM_IN_BOHR  # from Hartree/Bohr to Hartree/Angstrom
    # units: Hartree, Hartree/Angstrom, electron-Angstrom, electrons
    return E_xtb, gradient_xtb, dipole_xtb, qs_xtb

def test_metal_cubes(atomic_number, default_scale=3.0, cube_size=3):
    print('Cube of atomic number', atomic_number, 'with', cube_size**3, 'atoms, default interatomic r =', default_scale)
    for scale in np.arange(0.2, 1.2, 0.01):
        scale *= default_scale
        xyz = []
        for i in range(cube_size):
            for j in range(cube_size):
                for k in range(cube_size):
                    xyz.append((i, j, k))
        xyz = np.array(xyz, dtype=np.float64) * scale
        atomic_numbers = np.array([atomic_number] * len(xyz))
        q = np.sum(atomic_numbers) % 2  # if odd n electrons, remove 1
        try:
            E_xtb, gradient_xtb, dipole_xtb, qs_xtb = run_xtb(atomic_numbers, xyz, q, 0)
            # print('r = %.2f' % scale, 'E_xtb =', E_xtb)
        except XTBException as ex:
            print('r = %.2f' % scale, 'Failed,', ex)

print('xTB version', xtb.__version__)
atomic_number, default_scale = int(sys.argv[1]), float(sys.argv[2])
test_metal_cubes(atomic_number, default_scale)

xTB version 20.1
Cube of atomic number 3 with 27 atoms, default interatomic r = 2.7
r = 0.92 Failed, Very implausible partial charge: 209.337257
r = 0.95 Failed, Very implausible partial charge: 96.060772
r = 0.97 Failed, Very implausible partial charge: 66.404307
r = 1.00 Failed, Very implausible partial charge: 163.766930
r = 1.05 Failed, Very implausible partial charge: 145.753860
r = 1.08 Failed, Bad net charge: 1 vs 1.000011
r = 1.13 Failed, Very implausible partial charge: 29.071110
r = 1.19 Failed, Very implausible partial charge: 257.358086
r = 1.22 Failed, Very implausible partial charge: 273.118857
r = 1.24 Failed, Bad net charge: 1 vs 0.412483
r = 1.27 Failed, Very implausible partial charge: 115.909595
r = 1.30 Failed, Very implausible partial charge: 19332.830109
r = 1.35 Failed, Very implausible partial charge: 5.019581
r = 1.38 Failed, Very implausible partial charge: 33.592007
r = 1.40 Failed, Very implausible partial charge: 33.003970
r = 1.43 Failed, Very implausible partial charge: 66.802335
r = 1.46 Failed, Bad net charge: 1 vs 1.000011
r = 1.49 Failed, Very implausible partial charge: 91.379054
r = 1.51 Failed, Bad net charge: 1 vs 1471240208384.000000
r = 1.76 Failed, Energy is NaN
r = 2.11 Failed, Energy is NaN

(base) ➜  xtb-python git:(main) conda config --add channels conda-forge
Warning: 'conda-forge' already in 'channels' list, moving to the top
(base) ➜  xtb-python git:(main) conda create --name xtb-tmp xyb-python  
Collecting package metadata (current_repodata.json): done
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed

PackagesNotFoundError: The following packages are not available from current channels:

  - xyb-python

Current channels:

  - https://conda.anaconda.org/conda-forge/osx-arm64
  - https://conda.anaconda.org/conda-forge/noarch
  - https://repo.anaconda.com/pkgs/main/osx-arm64
  - https://repo.anaconda.com/pkgs/main/noarch
  - https://repo.anaconda.com/pkgs/r/osx-arm64
  - https://repo.anaconda.com/pkgs/r/noarch

To search for alternate channels that may provide the conda package you're
looking for, navigate to

    https://anaconda.org

and use the search bar at the top of the page.

(base) ➜  xtb-python git:(main) conda search xtb-python --channel conda-forge
Loading channels: done
No match found for: xtb-python. Search: *xtb-python*
# Name                       Version           Build  Channel             
scine-xtb-python               1.0.2    pyhd8ed1ab_0  conda-forge  

xtb/interface.py:290: error: Incompatible types in assignment (expression has type "None", variable has type "ndarray")
xtb/interface.py:297: error: Incompatible types in assignment (expression has type "None", variable has type "ndarray")
xtb/interface.py:346: error: Incompatible types in assignment (expression has type "None", variable has type "ndarray")
xtb/interface.py:670: error: Argument 2 to "__init__" of "Molecule" has incompatible type "List[int]"; expected "ndarray"
xtb/interface.py:670: error: Argument 3 to "__init__" of "Molecule" has incompatible type "List[float]"; expected "ndarray"
xtb/interface.py:670: error: Argument 6 to "__init__" of "Molecule" has incompatible type "Optional[List[float]]"; expected "Optional[ndarray]"
xtb/interface.py:670: error: Argument 7 to "__init__" of "Molecule" has incompatible type "Optional[List[bool]]"; expected "Optional[ndarray]"

from ase.io import read, write
from xtb.ase.calculator import XTB

# Read structure data
atoms = read('test1.traj') # test2.traj works fine

# Create the calculator for GFN0-xTB under periodic boundary conditions
calc = XTB(method='GFN0-xTB')
atoms.calc = calc

# Get the single point energy and forces
e = atoms.get_potential_energy()
f = atoms.get_forces()
print(e)
print(f)

-4523.6795731769935
[[-inf  inf -inf]
 [-inf  inf -inf]
 [-inf -inf -inf]
 [ inf -inf -inf]
 [ inf  inf -inf]
 [ inf  inf -inf]
 [-inf  inf -inf]
 [-inf  inf -inf]
 [-inf -inf -inf]
 [ inf -inf -inf]
 [ inf  inf -inf]
 [-inf  inf -inf]
 [ inf  inf  inf]
 [ inf  inf  inf]
 [ inf -inf  inf]
 [-inf -inf  inf]
 [-inf  inf  inf]
 [-inf -inf  inf]
 [  0.   0.   0.]
 [  0.   0.   0.]
 [  0.   0.   0.]
 [  0.   0.   0.]
 [  0.   0.   0.]
 [  0.   0.   0.]
 [  0.   0.   0.]
 [  0.   0.   0.]
 [  0.   0.   0.]
 [  0.   0.   0.]
 [  0.   0.   0.]
 [  0.   0.   0.]
 [  0.   0.   0.]
 [  0.   0.   0.]
 [  0.   0.   0.]
 [  0.   0.   0.]
 [  0.   0.   0.]
 [  0.   0.   0.]
 [-inf -inf -inf]]

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
/tmp/ipykernel_3220/591948702.py in <module>
      5 atoms.calc = XTB(method="GFN2-xTB")
      6 atoms.get_potential_energy()
----> 7 deepcopy(atoms)

~/anaconda3/envs/xtb/lib/python3.8/copy.py in deepcopy(x, memo, _nil)
    170                     y = x
    171                 else:
--> 172                     y = _reconstruct(x, memo, *rv)
    173 
    174     # If is its own copy, don't memoize.

~/anaconda3/envs/xtb/lib/python3.8/copy.py in _reconstruct(x, memo, func, args, state, listiter, dictiter, deepcopy)
    268     if state is not None:
    269         if deep:
--> 270             state = deepcopy(state, memo)
    271         if hasattr(y, '__setstate__'):
    272             y.__setstate__(state)

~/anaconda3/envs/xtb/lib/python3.8/copy.py in deepcopy(x, memo, _nil)
    144     copier = _deepcopy_dispatch.get(cls)
    145     if copier is not None:
--> 146         y = copier(x, memo)
    147     else:
    148         if issubclass(cls, type):

~/anaconda3/envs/xtb/lib/python3.8/copy.py in _deepcopy_dict(x, memo, deepcopy)
    228     memo[id(x)] = y
    229     for key, value in x.items():
--> 230         y[deepcopy(key, memo)] = deepcopy(value, memo)
    231     return y
    232 d[dict] = _deepcopy_dict

~/anaconda3/envs/xtb/lib/python3.8/copy.py in deepcopy(x, memo, _nil)
    170                     y = x
    171                 else:
--> 172                     y = _reconstruct(x, memo, *rv)
    173 
    174     # If is its own copy, don't memoize.

~/anaconda3/envs/xtb/lib/python3.8/copy.py in _reconstruct(x, memo, func, args, state, listiter, dictiter, deepcopy)
    268     if state is not None:
    269         if deep:
--> 270             state = deepcopy(state, memo)
    271         if hasattr(y, '__setstate__'):
    272             y.__setstate__(state)

~/anaconda3/envs/xtb/lib/python3.8/copy.py in deepcopy(x, memo, _nil)
    144     copier = _deepcopy_dispatch.get(cls)
    145     if copier is not None:
--> 146         y = copier(x, memo)
    147     else:
    148         if issubclass(cls, type):

~/anaconda3/envs/xtb/lib/python3.8/copy.py in _deepcopy_dict(x, memo, deepcopy)
    228     memo[id(x)] = y
    229     for key, value in x.items():
--> 230         y[deepcopy(key, memo)] = deepcopy(value, memo)
    231     return y
    232 d[dict] = _deepcopy_dict

~/anaconda3/envs/xtb/lib/python3.8/copy.py in deepcopy(x, memo, _nil)
    170                     y = x
    171                 else:
--> 172                     y = _reconstruct(x, memo, *rv)
    173 
    174     # If is its own copy, don't memoize.

~/anaconda3/envs/xtb/lib/python3.8/copy.py in _reconstruct(x, memo, func, args, state, listiter, dictiter, deepcopy)
    268     if state is not None:
    269         if deep:
--> 270             state = deepcopy(state, memo)
    271         if hasattr(y, '__setstate__'):
    272             y.__setstate__(state)

~/anaconda3/envs/xtb/lib/python3.8/copy.py in deepcopy(x, memo, _nil)
    144     copier = _deepcopy_dispatch.get(cls)
    145     if copier is not None:
--> 146         y = copier(x, memo)
    147     else:
    148         if issubclass(cls, type):

~/anaconda3/envs/xtb/lib/python3.8/copy.py in _deepcopy_dict(x, memo, deepcopy)
    228     memo[id(x)] = y
    229     for key, value in x.items():
--> 230         y[deepcopy(key, memo)] = deepcopy(value, memo)
    231     return y
    232 d[dict] = _deepcopy_dict

~/anaconda3/envs/xtb/lib/python3.8/copy.py in deepcopy(x, memo, _nil)
    159                     reductor = getattr(x, "__reduce_ex__", None)
    160                     if reductor is not None:
--> 161                         rv = reductor(4)
    162                     else:
    163                         reductor = getattr(x, "__reduce__", None)

TypeError: cannot pickle '_cffi_backend.__CDataGCP' object

coordinates.flags
  C_CONTIGUOUS : False
  F_CONTIGUOUS : True
  OWNDATA : True
  WRITEABLE : True
  ALIGNED : True
  WRITEBACKIFCOPY : False
  UPDATEIFCOPY : False

5.134599834832412

  C_CONTIGUOUS : True
  F_CONTIGUOUS : False
  OWNDATA : True
  WRITEABLE : True
  ALIGNED : True
  WRITEBACKIFCOPY : False
  UPDATEIFCOPY : False

-4.0651143277974615

conda install -n xtb-python xtb-python 'libblas=*=*mkl*'

          ...................................................
          :                      SETUP                      :
          :.................................................:
          :  # basis functions                   6          :
          :  # atomic orbitals                   6          :
          :  # shells                            4          :
          :  # electrons                         8          :
          :  max. iterations                   250          :
          :  Hamiltonian                  GFN2-xTB          :
          :  restarted?                       true          :
          :  GBSA solvation                  false          :
          :  PC potential                    false          :
          :  electronic temp.          300.0000000     K    :
          :  accuracy                    1.0000000          :
          :  -> integral cutoff          0.2500000E+02      :
          :  -> integral neglect         0.1000000E-07      :
          :  -> SCF convergence          0.1000000E-05 Eh   :
          :  -> wf. convergence          0.1000000E-03 e    :
          :  Broyden damping             0.4000000          :
          ...................................................

ase version: 3.22.0
xtb version: 20.1
reference: -40.48059 Ha
'psi4': -40.19151 Ha
'nwchem': -39.86620 Ha
'xtb': -4.15454 Ha

>>> from xtb.libxtb import VERBOSITY_MINIMAL
>>> from xtb.interface import Calculator, Param
>>> import numpy as np
>>> numbers = np.array([8, 1, 1])
>>> positions = np.array([
... [ 0.00000000000000, 0.00000000000000,-0.73578586109551],
... [ 1.44183152868459, 0.00000000000000, 0.36789293054775],
... [-1.44183152868459, 0.00000000000000, 0.36789293054775]])
...
>>> calc = Calculator(Param.GFN2xTB, numbers, positions)

3                                                                                
                                                                                 
O 0.000000 -0.000000 -0.066467                                                   
H 0.000000 0.758588 0.527436                                                     
H 0.000000 -0.798588 0.527436                                                    

import numpy as np                                                               
from scipy import constants                                                      
from xtb.interface import Calculator, Param                                      
from xtb.libxtb import VERBOSITY_MINIMAL   , VERBOSITY_FULL                      
from xtb.utils import Solvent                                                    
                                                                                 
ANGSTROM_IN_BOHR = constants.physical_constants['Bohr radius'][0] * 1.0e10       

def run_xtb_python(atomic_numbers, positions, net_charge, solvent=None):         
    """                                                                          
    Run xTB with the provided python API                                         
    There is no error check                                                      
    """                                                                          
                                                                                 
    calc = Calculator(                                                           
        Param.GFN2xTB, atomic_numbers, positions / ANGSTROM_IN_BOHR, net_charge  
    )                                                                            
    calc.set_verbosity(VERBOSITY_FULL)                                           
    if solvent is not None:                                                      
        calc.set_solvent(solvent)                                                
                                                                                 
    res = calc.singlepoint()                                                     
                                                                                                                             
    energy = res.get_energy()                                                    
    # serialize and store a list object                                          
    gradient = (res.get_gradient() / ANGSTROM_IN_BOHR).tolist()                  
    charges = res.get_charges().tolist()                                         
                                                                                 
    print("eigenvalues", res.get_orbital_eigenvalues())                          
    print("total charge", sum(charges))                                          
    print("dipole", res.get_dipole())                                            
                                                                                 
    return {                                                                     
        "energy": energy,                                                        
        "charges": charges,                                                      
        "gradient": gradient                                                     
    }                                                                            

if __name__ == "__main__":
    PERIODIC_TABLE = {"H": 1, "O": 8}                                            
    atomic_numbers, positions = [], []                                           
    net_charge = 0                                                               
    with open("water.xyz") as fin:                                               
        token = next(fin)                                                        
        natoms = int(token)                                                      
        _ = next(fin)                                                            
        for i in range(natoms):                                                  
            elmnt, x, y, z = next(fin).split()                                   
            atomic_numbers.append(PERIODIC_TABLE[elmnt])                         
            positions.append([float(x), float(y), float(z)])                     
                                                                                 
    solvent = Solvent.h2o                         
                                                                                 
    output_data = run_xtb_python(                                                
        np.array(atomic_numbers),                                                
        np.array(positions),                                                     
        net_charge,                                                              
        solvent                                                                  
    )                                                                            

         :::::::::::::::::::::::::::::::::::::::::::::::::::::                                                                                                                                                                                
         ::                     SUMMARY                     ::                                                                                                                                                                                
         :::::::::::::::::::::::::::::::::::::::::::::::::::::                                                                                                                                                                                
         :: total energy              -5.086650340935 Eh    ::                                                                                                                                                                                
         :: total w/o Gsasa/hb        -5.072450640868 Eh    ::                                                                                                                                                                                
         :: gradient norm              0.034523773934 Eh/a0 ::                                                                                                                                                                                
         :: HOMO-LUMO gap             14.203449851402 eV    ::                                                                                                                                                                                
         ::.................................................::                                                                                                                                                                                
         :: SCC energy                -5.115460341784 Eh    ::                                                                                                                                                                                
         :: -> isotropic ES            0.055279536996 Eh    ::                                                                                                                                                                                
         :: -> anisotropic ES         -0.001553606638 Eh    ::                                                                                                                                                                                
         :: -> anisotropic XC          0.000001590124 Eh    ::                                                                                                                                                                                
         :: -> dispersion             -0.000124241951 Eh    ::                                                                                                                                                                                
         :: -> Gsolv                  -0.024975539514 Eh    ::                                                                                                                                                                                
         ::    -> Gborn               -0.010775839447 Eh    ::                                                                                                                                                                                
         ::    -> Gsasa                0.004887985565 Eh    ::                                                                                                                                                                                
         ::    -> Ghb                 -0.019499345345 Eh    ::                                                                                                                                                                                
         ::    -> Gshift               0.000411659713 Eh    ::                                                                                                                                                                                
         :: repulsion energy           0.028810000815 Eh    ::                                                                                                                                                                                
         :: add. restraining           0.000000000000 Eh    ::                                                                                                                                                                                
         :: total charge               0.000000000000 e     ::                                                                                                                                                                                
         :::::::::::::::::::::::::::::::::::::::::::::::::::::                                                                                                                                                                                

         :::::::::::::::::::::::::::::::::::::::::::::::::::::
         ::                     SUMMARY                     ::
         :::::::::::::::::::::::::::::::::::::::::::::::::::::
         :: total energy              -5.079191678312 Eh    ::
         :: total w/o Gsasa/hb        -5.071742364786 Eh    ::
         :: gradient norm              0.037702233171 Eh/a0 ::
         :: HOMO-LUMO gap             13.870116488842 eV    ::
         ::.................................................::
         :: SCC energy                -5.108001654563 Eh    ::
         :: -> isotropic ES            0.043341913075 Eh    ::
         :: -> anisotropic ES         -0.000309776201 Eh    ::
         :: -> anisotropic XC         -0.000217021538 Eh    ::
         :: -> dispersion             -0.000131539071 Eh    ::
         :: -> Gsolv                  -0.011920230479 Eh    ::
         ::    -> Gborn               -0.004470916953 Eh    ::
         ::    -> Gsasa                0.000215386523 Eh    ::
         ::    -> Ghb                 -0.009522143176 Eh    ::
         ::    -> Gshift               0.001857443127 Eh    ::
         :: repulsion energy           0.028809976217 Eh    ::
         :: add. restraining           0.000000000000 Eh    ::
         :: total charge              -0.000000000000 e     ::
         :::::::::::::::::::::::::::::::::::::::::::::::::::::

(py-3.6.10) [tang@grendel-s-s81n11:xtb-python-20200604]$ meson setup build --prefix=$PWD --libdir=xtb --default-library=shared
The Meson build system
Version: 0.53.0
Source dir: /home/tang/opt/xtb/xtb-python-20200604
Build dir: /home/tang/opt/xtb/xtb-python-20200604/build
Build type: native build
Project name: xtb-python
Project version: undefined
C compiler for the host machine: cc (gcc 4.8.5 "cc (GCC) 4.8.5 20150623 (Red Hat 4.8.5-4)")
C linker for the host machine: cc GNU ld.bfd 2.23.52.0.1-55
Host machine cpu family: x86_64
Host machine cpu: x86_64
Found pkg-config: /usr/bin/pkg-config (0.27.1)
Run-time dependency xtb found: YES 6.3.0
Program python3 (cffi) found: YES (/home/tang/python-virtualenv/py-3.6.10/bin/python3) modules: cffi
Dependency python found: YES (pkgconfig)
Configuring _libxtb.h with command
Configuring _libxtb.c with command
Build targets in project: 2
 
Option default_library is: shared [default: static]
Found ninja-1.9.0.git.kitware.dyndep-1.jobserver-1 at /home/tang/python-virtualenv/py-3.6.10/bin/ninja
(py-3.6.10) [tang@grendel-s-s81n11:xtb-python-20200604]$ ninja -C build install
ninja: Entering directory `build'
[3/4] Linking target _libxtb.cpython-36m-x86_64-linux-gnu.so.
FAILED: _libxtb.cpython-36m-x86_64-linux-gnu.so
cc  -o _libxtb.cpython-36m-x86_64-linux-gnu.so  -Wl,--as-needed -Wl,--allow-shlib-undefined -shared -fPIC -Wl,--start-group -Wl,-soname,_libxtb.cpython-36m-x86_64-linux-gnu.so -Wl,--whole-archive lib_libxtb.a -Wl,--no-whole-archive /home/tang/opt/xtb/xtb-python-20200604/subprojects/xtb/install/lib64/libxtb.so /comm/swstack/core/python/3.6.10/lib/libpython3.6m.a -Wl,--end-group '-Wl,-rpath,$ORIGIN/../subprojects/xtb/install/lib64' -Wl,-rpath-link,/home/tang/opt/xtb/xtb-python-20200604/build/../subprojects/xtb/install/lib64
/usr/bin/ld: /comm/swstack/core/python/3.6.10/lib/libpython3.6m.a(abstract.o): relocation R_X86_64_32S against `_Py_NotImplementedStruct' can not be used when making a shared object; recompile with -fPIC
/comm/swstack/core/python/3.6.10/lib/libpython3.6m.a: could not read symbols: Bad value
collect2: error: ld returned 1 exit status
ninja: build stopped: subcommand failed.

#!/bin/bash

# Get standalone package

wget https://github.com/grimme-lab/xtb/releases/download/v$1/xtb-$1-linux-x86_64.tar.xz
tar xf xtb-$1-linux-x86_64.tar.xz
cd xtb-$1

# Edit first line on lib/pkgconfig/xtb.pc:

sed -i 's|prefix=\/|prefix='$PWD'|g' lib/pkgconfig/xtb.pc

# Define environment variables:

export PKG_CONFIG_PATH=$PWD/lib/pkgconfig

# Get and compile xtb-python:

git clone https://github.com/grimme-lab/xtb-python python
cd python

meson setup build --prefix=$PWD --default-library=shared

ninja -C build install

# Install to site-packages:

python3.8 -m pip install -e .

from ase.io import read
from xtb.ase.calculator import XTB
atoms = read('H2CO.xyz')
atoms.calc = XTB(method="GFN2-xTB")
energy = atoms.get_potential_energy()
print(energy)

pytest --pyargs xtb

============================= test session starts ==============================
platform linux -- Python 3.9.6, pytest-6.2.4, py-1.10.0, pluggy-0.13.1
rootdir: /home/energy/stly/modules
collected 30 items

test_interface.py ..........                                             [ 33%]
test_libxtb.py .                                                         [ 36%]
test_utils.py ..                                                         [ 43%]
ase/test_calculator.py .....                                             [ 60%]
ase/test_optimize.py F.F                                                 [ 70%]
qcschema/test_qcschema.py F........                                      [100%]

=================================== FAILURES ===================================
______________________________ test_gfn1xtb_bfgs _______________________________

    def test_gfn1xtb_bfgs():
        """Perform geometry optimization with GFN1-xTB and BFGS"""
    
        thr = 1.0e-5
    
        atoms = Atoms(
            symbols = "NHCHC2H3OC2H3ONHCH3",
            positions = np.array([
                [ 1.40704587284727, -1.26605342016611, -1.93713466561923],
                [ 1.85007200612454, -0.46824072777417, -1.50918242392545],
                [-0.03362432532150, -1.39269245193812, -1.74003582081606],
                [-0.56857009928108, -1.01764444489068, -2.61263467107342],
                [-0.44096297340282, -2.84337808903410, -1.48899734014499],
                [-0.47991761226058, -0.55230954385212, -0.55520222968656],
                [-1.51566045903090, -2.89187354810876, -1.32273881320610],
                [-0.18116520746778, -3.45187805987944, -2.34920431470368],
                [ 0.06989722340461, -3.23298998903001, -0.60872832703814],
                [-1.56668253918793,  0.00552120970194, -0.52884675001441],
                [ 1.99245341064342, -1.73097165236442, -3.08869239114486],
                [ 3.42884244212567, -1.30660069291348, -3.28712665743189],
                [ 3.87721962540768, -0.88843123009431, -2.38921453037869],
                [ 3.46548545761151, -0.56495308290988, -4.08311788302584],
                [ 4.00253374168514, -2.16970938132208, -3.61210068365649],
                [ 1.40187968630565, -2.43826111827818, -3.89034127398078],
                [ 0.40869198386066, -0.49101709352090,  0.47992424955574],
                [ 1.15591901335007, -1.16524842262351,  0.48740266650199],
                [ 0.00723492494701,  0.11692276177442,  1.73426297572793],
                [ 0.88822128447468,  0.28499001838229,  2.34645658013686],
                [-0.47231557768357,  1.06737634000561,  1.52286682546986],
                [-0.70199987915174, -0.50485938116399,  2.28058247845421],
            ]),
        )
    
        atoms.calc = XTB(method="GFN1-xTB", accuracy=2.0, cache_api=False)
        opt = BFGS(atoms)
        opt.run(fmax=0.1)
    
        assert approx(atoms.get_potential_energy(), thr) == -951.9006674709672
>       assert approx(np.linalg.norm(atoms.get_forces(), ord=2), thr) == 0.2052117803208497
E       AssertionError: assert 0.2051907763726757 ± 2.1e-06 == 0.2052117803208497
E        +  where 0.2051907763726757 ± 2.1e-06 = approx(0.2051907763726757, 1e-05)
E        +    where 0.2051907763726757 = <function norm at 0x7f95f1cf0790>(array([[ 0.02237361,  0.02429641, -0.06093066],\n       [-0.00613627,  0.020313  ,  0.03872088],\n       [-0.02944359, -...0481288, -0.03749684],\n       [ 0.00898936, -0.03774712, -0.02156718],\n       [ 0.05122454, -0.01808473, -0.06098617]]), ord=2)
E        +      where <function norm at 0x7f95f1cf0790> = <module 'numpy.linalg' from '/home/modules/software/SciPy-bundle/2021.10-intel-2021b/lib/python3.9/site-packages/numpy/linalg/__init__.py'>.norm
E        +        where <module 'numpy.linalg' from '/home/modules/software/SciPy-bundle/2021.10-intel-2021b/lib/python3.9/site-packages/numpy/linalg/__init__.py'> = np.linalg
E        +      and   array([[ 0.02237361,  0.02429641, -0.06093066],\n       [-0.00613627,  0.020313  ,  0.03872088],\n       [-0.02944359, -...0481288, -0.03749684],\n       [ 0.00898936, -0.03774712, -0.02156718],\n       [ 0.05122454, -0.01808473, -0.06098617]]) = <bound method Atoms.get_forces of Atoms(symbols='NHCHC2H3OC2H3ONHCH3', pbc=False, calculator=XTB(...))>()
E        +        where <bound method Atoms.get_forces of Atoms(symbols='NHCHC2H3OC2H3ONHCH3', pbc=False, calculator=XTB(...))> = Atoms(symbols='NHCHC2H3OC2H3ONHCH3', pbc=False, calculator=XTB(...)).get_forces

/home/modules/energy/software/xtb-python/20.2-intel-2021b-Python-3.9.6/xtb-python-20.2/xtb/ase/test_optimize.py:67: AssertionError
----------------------------- Captured stdout call -----------------------------
      Step     Time          Energy          fmax
BFGS:    0 11:23:59     -951.875911   9.91156e-01
BFGS:    1 11:23:59     -951.883077   1.11168e+00
BFGS:    2 11:23:59     -951.896465   1.46586e-01
BFGS:    3 11:23:59     -951.898042   1.16038e-01
BFGS:    4 11:23:59     -951.900667   9.72160e-02
_________________________ test_gfn2xtb_velocityverlet __________________________

    def test_gfn2xtb_velocityverlet():
        """Perform molecular dynamics with GFN2-xTB and Velocity Verlet Integrator"""
    
        thr = 1.0e-5
    
        atoms = Atoms(
            symbols = "NHCHC2H3OC2H3ONHCH3",
            positions = np.array([
                [ 1.40704587284727, -1.26605342016611, -1.93713466561923],
                [ 1.85007200612454, -0.46824072777417, -1.50918242392545],
                [-0.03362432532150, -1.39269245193812, -1.74003582081606],
                [-0.56857009928108, -1.01764444489068, -2.61263467107342],
                [-0.44096297340282, -2.84337808903410, -1.48899734014499],
                [-0.47991761226058, -0.55230954385212, -0.55520222968656],
                [-1.51566045903090, -2.89187354810876, -1.32273881320610],
                [-0.18116520746778, -3.45187805987944, -2.34920431470368],
                [ 0.06989722340461, -3.23298998903001, -0.60872832703814],
                [-1.56668253918793,  0.00552120970194, -0.52884675001441],
                [ 1.99245341064342, -1.73097165236442, -3.08869239114486],
                [ 3.42884244212567, -1.30660069291348, -3.28712665743189],
                [ 3.87721962540768, -0.88843123009431, -2.38921453037869],
                [ 3.46548545761151, -0.56495308290988, -4.08311788302584],
                [ 4.00253374168514, -2.16970938132208, -3.61210068365649],
                [ 1.40187968630565, -2.43826111827818, -3.89034127398078],
                [ 0.40869198386066, -0.49101709352090,  0.47992424955574],
                [ 1.15591901335007, -1.16524842262351,  0.48740266650199],
                [ 0.00723492494701,  0.11692276177442,  1.73426297572793],
                [ 0.88822128447468,  0.28499001838229,  2.34645658013686],
                [-0.47231557768357,  1.06737634000561,  1.52286682546986],
                [-0.70199987915174, -0.50485938116399,  2.28058247845421],
            ]),
        )
    
        atoms.calc = XTB(method="GFN2-xTB", cache_api=False)
    
        dyn = VelocityVerlet(atoms, timestep=1.0*fs)
        dyn.run(20)
    
        assert approx(atoms.get_potential_energy(), thr) == -896.9772346260584
>       assert approx(atoms.get_kinetic_energy(), thr) == 0.022411127028842362
E       AssertionError: assert 0.022409341448333585 ± 2.2e-07 == 0.022411127028842362
E        +  where 0.022409341448333585 ± 2.2e-07 = approx(0.022409341448333585, 1e-05)
E        +    where 0.022409341448333585 = <bound method Atoms.get_kinetic_energy of Atoms(symbols='NHCHC2H3OC2H3ONHCH3', pbc=False, momenta=..., calculator=XTB(...))>()
E        +      where <bound method Atoms.get_kinetic_energy of Atoms(symbols='NHCHC2H3OC2H3ONHCH3', pbc=False, momenta=..., calculator=XTB(...))> = Atoms(symbols='NHCHC2H3OC2H3ONHCH3', pbc=False, momenta=..., calculator=XTB(...)).get_kinetic_energy

/home/modules/energy/software/xtb-python/20.2-intel-2021b-Python-3.9.6/xtb-python-20.2/xtb/ase/test_optimize.py:150: AssertionError
_____________________________ test_gfn2xtb_energy ______________________________

    def test_gfn2xtb_energy():
        """Use QCSchema to calculate the energy of a halogen bond compound"""
        thr = 1.0e-7
    
        atomic_input = qcel.models.AtomicInput(
            molecule = {
                "symbols": [
                    "C", "C", "C", "C", "C", "C", "I", "H", "H",
                    "H", "H", "H", "S", "H", "C", "H", "H", "H",
                ],
                "geometry": [
                    -1.42754169820131, -1.50508961850828, -1.93430551124333,
                     1.19860572924150, -1.66299114873979, -2.03189643761298,
                     2.65876001301880,  0.37736955363609, -1.23426391650599,
                     1.50963368042358,  2.57230374419743, -0.34128058818180,
                    -1.12092277855371,  2.71045691257517, -0.25246348639234,
                    -2.60071517756218,  0.67879949508239, -1.04550707592673,
                    -2.86169588073340,  5.99660765711210,  1.08394899986031,
                     2.09930989272956, -3.36144811062374, -2.72237695164263,
                     2.64405246349916,  4.15317840474646,  0.27856972788526,
                     4.69864865613751,  0.26922271535391, -1.30274048619151,
                    -4.63786461351839,  0.79856258572808, -0.96906659938432,
                    -2.57447518692275, -3.08132039046931, -2.54875517521577,
                    -5.88211879210329, 11.88491819358157,  2.31866455902233,
                    -8.18022701418703, 10.95619984550779,  1.83940856333092,
                    -5.08172874482867, 12.66714386256482, -0.92419491629867,
                    -3.18311711399702, 13.44626574330220, -0.86977613647871,
                    -5.07177399637298, 10.99164969235585, -2.10739192258756,
                    -6.35955320518616, 14.08073002965080, -1.68204314084441,
                ],
            },
            driver = "energy",
            model = {
                "method": "GFN2-xTB",
            },
            keywords = {
                "accuracy": 1.0,
                "electronic_temperature": 300.0,
                "max_iterations": 50,
                "solvent": "none",
            }
        )
        dipole_moment = np.array(
            [0.3345064021648074, -1.0700925215553294, -1.2299195418603437]
        )
    
        atomic_result = run_qcschema(atomic_input)
    
        assert atomic_result.success
        assert approx(atomic_result.return_result, abs=thr) == -26.60185037124828
>       assert approx(atomic_result.properties.scf_dipole_moment, abs=thr) == dipole_moment
E       AssertionError: assert approx([0.3345115197707841 ± 1.0e-07, -1.070101790561011 ± 1.0e-07, -1.229921234359982 ± 1.0e-07]) == array([ 0.3345064021648074, -1.0700925215553294, -1.2299195418603437])
E        +  where approx([0.3345115197707841 ± 1.0e-07, -1.070101790561011 ± 1.0e-07, -1.229921234359982 ± 1.0e-07]) = approx(array([ 0.3345115197707841, -1.070101790561011 , -1.229921234359982 ]), abs=1e-07)
E        +    where array([ 0.3345115197707841, -1.070101790561011 , -1.229921234359982 ]) = AtomicResultProperties(return_energy=-26.60185043351621, scf_dipole_moment=array([ 0.3345115197707841, -1.070101790561011 , -1.229921234359982 ])).scf_dipole_moment
E        +      where AtomicResultProperties(return_energy=-26.60185043351621, scf_dipole_moment=array([ 0.3345115197707841, -1.070101790561011 , -1.229921234359982 ])) = AtomicResult(driver='energy', model={'method': 'GFN2-xTB', 'basis': None}, molecule_hash='3b522fc').properties

/home/modules/energy/software/xtb-python/20.2-intel-2021b-Python-3.9.6/xtb-python-20.2/xtb/qcschema/test_qcschema.py:73: AssertionError
=========================== short test summary info ============================
FAILED ase/test_optimize.py::test_gfn1xtb_bfgs - AssertionError: assert 0.205...
FAILED ase/test_optimize.py::test_gfn2xtb_velocityverlet - AssertionError: as...
FAILED qcschema/test_qcschema.py::test_gfn2xtb_energy - AssertionError: asser...
========================= 3 failed, 27 passed in 4.82s =========================

meson --prefix /home/modules/energy/software/xtb-python/20.2-intel-2021b-Python-3.9.6 --default-library=shared -Dla_backend=mkl -Dfortran_link_args=-qopenmp  -Dlibdir=lib  /home/modules/energy/build/xtbpython/20.2/intel-2021b-Python-3.9.6/xtb-python-20.2/

No errors in build command with the following output.

#### Meson output:
 The Meson build system
 Version: 0.58.2
 Source dir: /home/modules/energy/build/xtbpython/20.2/intel-2021b-Python-3.9.6/xtb-python-20.2
 Build dir: /home/modules/energy/build/xtbpython/20.2/intel-2021b-Python-3.9.6/easybuild_obj
 Build type: native build
 Project name: xtb-python
 Project version: undefined
 C compiler for the host machine: icc (intel 2021.4.0 "icc (ICC) 2021.4.0 20210910")
 C linker for the host machine: icc ld.bfd 2.37
 Host machine cpu family: x86_64
 Host machine cpu: x86_64
 Found pkg-config: /usr/bin/pkg-config (0.27.1)
 Run-time dependency xtb found: YES 6.4.1
 Program python3 (cffi) found: YES (/home/modules/software/Python/3.9.6-GCCcore-11.2.0/bin/python3) modules: cffi
 Dependency python found: YES (pkgconfig)
 Configuring _libxtb.h with command
 Configuring _libxtb.c with command
 Build targets in project: 2
 
 Option libdir is: lib [default: xtb]
 Option default_library is: shared [default: static]
 Found ninja-1.10.2 at /home/modules/software/Ninja/1.10.2-GCCcore-11.2.0/bin/ninja

The Meson build system
Version: 0.63.2
Source dir: /disk-samsung/freebsd-ports/science/py-xtb/work/xtb-python-20.2-11-g3335421
Build dir: /disk-samsung/freebsd-ports/science/py-xtb/work/xtb-python-20.2-11-g3335421/_build
Build type: native build
Project name: xtb-python
Project version: undefined
C compiler for the host machine: cc (clang 14.0.5 "FreeBSD clang version 14.0.5 (https://github.com/llvm/llvm-project.git llvmorg-14.0.5-0-gc12386ae247c)")
C linker for the host machine: cc ld.lld 14.0.5
Host machine cpu family: x86_64
Host machine cpu: x86_64
Found pkg-config: /usr/local/bin/pkg-config (1.8.0)
Found CMake: /usr/local/bin/cmake (3.24.3)
Run-time dependency xtb found: NO (tried pkgconfig)
Looking for a fallback subproject for the dependency xtb

meson.build:33:2: ERROR: Subproject exists but has no meson.build file

from ._libxtb import ffi, lib
ModuleNotFoundError: No module named 'xtb._libxtb'

The Meson build system
Version: 0.63.3
Source dir: /Users/hannes/prog/xtb-python
Build dir: /Users/hannes/prog/xtb-python/build
Build type: native build
Project name: xtb-python
Project version: undefined
C compiler for the host machine: cc (clang 14.0.0 "Apple clang version 14.0.0 (clang-1400.0.29.202)")
C linker for the host machine: cc ld64 820.1
Host machine cpu family: aarch64
Host machine cpu: arm64
Found pkg-config: /opt/homebrew/bin/pkg-config (0.29.2)
Run-time dependency xtb found: YES 6.5.1
Program python3 (cffi) found: YES (/opt/homebrew/bin/python3) modules: cffi
Configuring _libxtb.h with command
Configuring _libxtb.c with command
Build targets in project: 2

xtb-python undefined

  User defined options
    default_library: shared
    prefix         : /Users/hannes/prog/xtb-python

Found ninja-1.11.1 at /opt/homebrew/bin/ninja

ninja: Entering directory `build'
[3/4] Linking target _libxtb.cpython-310-darwin.so
ld: warning: -undefined dynamic_lookup may not work with chained fixups
[3/4] Installing files.
Installing _libxtb.cpython-310-darwin.so to /Users/hannes/prog/xtb-python/opt/homebrew/lib/python3.10/site-packages/

  File "/home/modules/software/Python/3.7.4-GCCcore-8.3.0/lib/python3.7/json/encoder.py", line 199, in encode
    chunks = self.iterencode(o, _one_shot=True)
  File "/home/modules/software/Python/3.7.4-GCCcore-8.3.0/lib/python3.7/json/encoder.py", line 257, in iterencode
    return _iterencode(o, 0)
  File "/home/energy/shuha/newASE/ase/io/jsonio.py", line 37, in default
    return json.JSONEncoder.default(self, obj)
  File "/home/modules/software/Python/3.7.4-GCCcore-8.3.0/lib/python3.7/json/encoder.py", line 179, in default
    raise TypeError(f'Object of type {o.__class__.__name__} ' 
TypeError: Object of type Param is not JSON serializable

from ase.io import *
from ase.optimize.bfgs import BFGS
from xtb.ase.calculator import XTB
from xtb.utils import get_method
calc = XTB(method=get_method('GFN1-xTB'))
atoms = read('test.traj')
atoms.set_calculator(calc)
opt = BFGS(atoms, trajectory = 'relaxation_gfn1.traj', logfile='relaxation.log')
opt.run(fmax=0.1)
atoms.get_potential_energy()
atoms.get_forces()

FROM buildpack-deps:bullseye

[...]

RUN conda install -y -c anaconda python=3.8 \
    && conda config --add channels conda-forge \
    && conda install -y -c conda-forge xtb-python qcelemental ase

[...]

Python 3.8.15 (default, Nov 24 2022, 15:19:38) 
[GCC 11.2.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> from xtb.libxtb import VERBOSITY_FULL
Traceback (most recent call last):
  File "/opt/conda/lib/python3.8/site-packages/xtb/libxtb.py", line 32, in <module>
    from ._libxtb import ffi, lib
ImportError: /opt/conda/lib/python3.8/site-packages/_cffi_backend.cpython-38-x86_64-linux-gnu.so: undefined symbol: ffi_type_uint32, version LIBFFI_BASE_7.0

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/opt/conda/lib/python3.8/site-packages/xtb/libxtb.py", line 34, in <module>
    raise ImportError("xtb C extension unimportable, cannot use C-API")
ImportError: xtb C extension unimportable, cannot use C-API
>>>

from ase.io import read
import matplotlib.pyplot as plt
import os
from tqdm import tqdm
from xtb.ase.calculator import XTB


def calc_energy(structure):
    structure.calc = XTB(method="GFN2-xTB")
    eng_pot = structure.get_potential_energy()
    return eng_pot


if __name__ == "__main__":
    path = "/home/janssen/pyiron/projects/2023-02-19-xtb-high-throughput/dsgdb9nsd"
    structure_lst = [read(os.path.join(path, f), format="xyz") for f in os.listdir(path)]
    potential_energy_lst = [calc_energy(structure=structure) for structure in tqdm(structure_lst)]
    print("Done")

from ase.io import read
import matplotlib.pyplot as plt
import os
from tqdm import tqdm
from xtb.ase.calculator import XTB


def calc_energy(structure):
    structure.calc = XTB(method="GFN2-xTB")
    eng_pot = structure.get_potential_energy()
    return eng_pot


if __name__ == "__main__":
    path = "/home/janssen/pyiron/projects/2023-02-19-xtb-high-throughput/dsgdb9nsd"
    structure_lst = [read(os.path.join(path, f), format="xyz") for f in os.listdir(path)]
    potential_energy_lst = [calc_energy(structure=structure.copy()) for structure in tqdm(structure_lst)]
    print("Done")

< potential_energy_lst = [calc_energy(structure=structure) for structure in tqdm(structure_lst)]
> potential_energy_lst = [calc_energy(structure=structure.copy()) for structure in tqdm(structure_lst)]