Latest progress

.travis.yml

@@ -5,9 +5,9 @@ language: python
 matrix:
   include:
     # Extra includes for OSX since python language is not available by default on OSX
-    - os: osx
-      language: generic
-      env: PYTHON_VER=3.6
+ #  - os: osx
+ #    language: generic
+ #    env: PYTHON_VER=3.6
     - os: osx
       language: generic
       env: PYTHON_VER=3.7
@@ -45,7 +45,9 @@ install:
     # Activate the test environment
   - conda activate test
     # install pyscf
-  - pip install pyscf
+  - if [ "$TRAVIS_OS_NAME" = "osx" ]; then conda config --append channels pyscf ; fi
+  - if [ "$TRAVIS_OS_NAME" = "osx" ]; then conda install pyscf ; fi
+  - if [ "$TRAVIS_OS_NAME" = "linux" ]; then pip install pyscf ; fi
     # install QCElemental
   - pip install qcelemental
     # install pandas

README.md

@@ -1,8 +1,8 @@
 Taco
 ==============================
 [//]: # (Badges)
-[![Travis Build Status](https://travis-ci.com/maxscheurer/taco.svg?token=Xyntx2ELmeydq8pgqs8t&branch=master)](https://travis-ci.com/maxscheurer/taco)
-[![codecov](https://codecov.io/gh/maxscheurer/Taco/branch/master/graph/badge.svg)](https://codecov.io/gh/maxscheurer/Taco/branch/master)
+[![Travis Build Status](https://travis-ci.com/crisely09/taco.svg?branch=master)](https://travis-ci.com/crisely09/taco)
+[![codecov](https://codecov.io/gh/crisely09/taco/branch/master/graph/badge.svg)](https://codecov.io/gh/crisely09/taco)
 
 FDE wrapper library
 

codecov.yml

@@ -0,0 +1,2 @@
+codecov:
+    token: 40b8d2d2-b267-41c7-abd4-82cfe23a570b

devtools/travis-ci/before_install.sh

@@ -3,7 +3,6 @@ pushd .
 cd $HOME
 # Make sure some level of pip is installed
 python -m ensurepip
-
 # Install Miniconda
 if [ "$TRAVIS_OS_NAME" == "osx" ]; then
     # Make OSX md5 mimic md5sum from linux, alias does not work
@@ -12,11 +11,12 @@ if [ "$TRAVIS_OS_NAME" == "osx" ]; then
     }
     MINICONDA=Miniconda3-latest-MacOSX-x86_64.sh
 else
+    export CXX=g++-4.8 CC=gcc-4.8
     MINICONDA=Miniconda3-latest-Linux-x86_64.sh
 fi
 MINICONDA_HOME=$HOME/miniconda
-MINICONDA_MD5=$(curl -s https://repo.continuum.io/miniconda/ | grep -A3 $MINICONDA | sed -n '4p' | sed -n 's/ *<td>\(.*\)<\/td> */\1/p')
-wget -q https://repo.continuum.io/miniconda/$MINICONDA
+MINICONDA_MD5=$(wget -qO- https://repo.anaconda.com/miniconda/ | grep -A3 $MINICONDA | sed -n '4p' | sed -n 's/ *<td>\(.*\)<\/td> */\1/p')
+wget -q https://repo.anaconda.com/miniconda/$MINICONDA
 if [[ $MINICONDA_MD5 != $(md5sum $MINICONDA | cut -d ' ' -f 1) ]]; then
     echo "Miniconda MD5 mismatch"
     exit 1
@@ -29,13 +29,21 @@ export PIP_ARGS="-U"
 echo ". $MINICONDA_HOME/etc/profile.d/conda.sh" >> ~/.bashrc  # Source the profile.d file
 echo "conda activate" >> ~/.bashrc  # Activate conda
 source ~/.bashrc  # source file to get new commands
-#export PATH=$MINICONDA_HOME/bin:$PATH  # Old way, should not be needed anymore
-
-conda config --add channels conda-forge
-
 conda config --set always_yes yes
 conda install conda conda-build jinja2 anaconda-client
 conda update --quiet --all
-
+if [ "$TRAVIS_OS_NAME" == "osx" ]; then
+    HOMEBREW_NO_AUTO_UPDATE=1 brew upgrade pyenv
+    # Pyenv requires minor revision, get the latest
+    PYENV_VERSION=$(pyenv install --list |grep $PYTHON_VER | sed -n "s/^[ \t]*\(${PYTHON_VER}\.*[0-9]*\).*/\1/p" | tail -n 1)
+    # Install version
+    pyenv install -f $PYENV_VERSION
+    # Use version for this
+    pyenv global $PYENV_VERSION
+    # Setup up path shims
+    eval "$(pyenv init -)"
+fi
+pip install --upgrade pip setuptools
+{% endif %}
 # Restore original directory
 popd

examples/embedding/co_h2o_adcc.out

@@ -0,0 +1,23 @@
+converged SCF energy = -111.225169473797
+converged SCF energy = -74.9646931916275
+converged SCF energy = -111.408077919059
+Starting adc2 singlet Jacobi-Davidson ...
+Niter n_ss  max_residual  time  Ritz values
+  1     6      0.092177  821ms  [0.4008882  0.40092934 0.4494298 ]
+  2    12     0.0059539  976ms  [0.33879721 0.33883308 0.4095161 ]
+  3    18    0.00061796  695ms  [0.33503654 0.33510021 0.40951458]
+  4    24    2.1679e-06  710ms  [0.33407691 0.33411293 0.40951457]
+  5    30    5.3286e-09   1.6s  [0.33407553 0.33411179 0.40951457]
+=== Converged ===
+    Number of matrix applies:    30
+    Total solver time:             4s 860ms
++--------------------------------------------------------------+
+| adc2                                    singlet ,  converged |
++--------------------------------------------------------------+
+|  #        excitation energy     osc str    |v1|^2    |v2|^2  |
+|          (au)           (eV)                                 |
+|  0     0.3340755      9.090658   0.0282    0.9659   0.03412  |
+|  1     0.3341118      9.091645   0.0282    0.9659   0.03412  |
+|  2     0.4095146      11.14346   0.0000     0.974   0.02602  |
++--------------------------------------------------------------+
+

examples/embedding/pyscf_vemb_adc2.py

@@ -0,0 +1,32 @@
+"""Compute the embedding potential and export it."""
+from qcelemental.models import Molecule
+
+import adcc
+from taco.embedding.pyscf_wrap import PyScfWrap
+
+# Define Molecules with QCElemental
+co = Molecule.from_data("""C        -3.6180905689    1.3768035675   -0.0207958979
+                           O        -4.7356838533    1.5255563000    0.1150239130""")
+h2o = Molecule.from_data("""O  -7.9563726699    1.4854060709    0.1167920007
+                            H  -6.9923165534    1.4211335985    0.1774706091
+                            H  -8.1058463545    2.4422204631    0.1115993752""")
+# Define arguments
+with open("/home/users/g/gonzalcr/projects/tests/fdeta/2water/cc-pvdz-segopt.nwchem", 'r') as fb:
+    basis = fb.read()
+basis = 'sto-3g'
+method = 'hf'
+xc_code = 'LDA,VWN'
+args0 = {"mol": co, "basis": basis, "method": method}
+args1 = {"mol": h2o, "basis": basis, "method": method}
+embs = {"mol": co, "basis": basis, "method": 'hf',
+        "xc_code": xc_code, "t_code": 'LDA_K_TF,'}
+# Make a wrap
+wrap = PyScfWrap(args0, args1, embs)
+wrap.emb_method.scf_object.conv_tol = 1e-12
+wrap.run_embedding()
+# Get SCF object
+scfres = wrap.emb_method.scf_object
+
+# Call adcc
+state = adcc.adc2(scfres, n_singlets=3)
+print(state.describe())

examples/embedding/pyscf_vemb_grid.py

@@ -0,0 +1,67 @@
+"""Compute the embedding potential on a grid and export it."""
+import numpy as np
+from qcelemental.models import Molecule
+
+from pyscf import gto
+from pyscf.dft import gen_grid
+from pyscf.dft.numint import eval_ao, eval_rho
+from taco.methods.scf_pyscf import get_pyscf_molecule
+from taco.embedding.pyscf_wrap import PyScfWrap, get_charges_and_coords
+from taco.embedding.pyscf_wrap_single import get_density_from_dm, get_dft_grid_stuff
+from taco.embedding.cc_gridfns import coulomb_potential_grid, nuclear_attraction_energy
+
+# Define Molecules with QCElemental
+co = Molecule.from_data("""C        -3.6180905689    1.3768035675   -0.0207958979
+                           O        -4.7356838533    1.5255563000    0.1150239130""")
+h2o = Molecule.from_data("""O  -7.9563726699    1.4854060709    0.1167920007
+                            H  -6.9923165534    1.4211335985    0.1774706091
+                            H  -8.1058463545    2.4422204631    0.1115993752""")
+# Define arguments
+basis = 'cc-pvdz'
+method = 'dft'
+xc_code = 'LDA,VWN'
+args0 = {"mol": co, "basis": basis, "method": method, "xc_code": xc_code}
+args1 = {"mol": h2o, "basis": basis, "method": method, "xc_code": xc_code}
+embs = {"mol": co, "basis": basis, "method": 'dft',
+        "xc_code": xc_code, "t_code": 'XC_LDA_K_TF'}
+# Make a wrap
+wrap = PyScfWrap(args0, args1, embs)
+
+# Make molecule in pyscf
+co_mol = get_pyscf_molecule(co, basis)
+h2o_mol = get_pyscf_molecule(h2o, basis)
+dm0 = wrap.method0.get_density()
+dm1 = wrap.method1.get_density()
+# Create supersystem
+newatom = '\n'.join([co_mol.atom, h2o_mol.atom])
+system = gto.M(atom=newatom, basis=basis)
+# Construct grid for integration
+grids = gen_grid.Grids(system)
+grids.level = 4
+grids.build()
+# Grid for plot
+points = np.array([[0., 0., z] for z in np.arange(-10., 10., 0.1)])
+rho0 = get_density_from_dm(wrap.mol0, dm0, points)
+rho1 = get_density_from_dm(wrap.mol1, dm1, points)
+rho1_grid = get_density_from_dm(wrap.mol1, dm1, grids.coords)
+# Coulomb repulsion potential
+v_coul = coulomb_potential_grid(points, grids.coords, grids.weights, rho1_grid)
+# Nuclear-electron attraction potential
+mol1_charges, mol1_coords = get_charges_and_coords(h2o_mol)
+v1_nuc0 = np.zeros(rho0.shape)
+for i in range(len(mol1_charges)):
+    v1_nuc0 += - mol1_charges[i]*rho0/np.linalg.norm(points-mol1_coords[i]) 
+# DFT nad potential
+xc_code = embs["xc_code"]
+t_code = embs["t_code"]
+rho_both = rho0 + rho1
+excs, vxcs = get_dft_grid_stuff(xc_code, rho_both, rho0, rho1)
+ets, vts = get_dft_grid_stuff(t_code, rho_both, rho0, rho1)
+vxc_emb = vxcs[0][0] - vxcs[1][0]
+vt_emb = vts[0][0] - vts[1][0]
+
+vemb_tot = v_coul + v1_nuc0 + vxc_emb + vt_emb
+
+
+# Save it to use it later
+np.save('vemb_co_h2o.npy', vemb_tot)

setup.py

@@ -61,7 +61,7 @@ def __str__(self):
     license='LGPLv3',
 
     # External modules
-    ext_modules=ext_modules,
+    # ext_modules=ext_modules,
 
     # Which Python importable modules should be included when your package is installed
     # Handled automatically by setuptools. Use 'exclude' to prevent some specific

taco/__init__.py

@@ -3,9 +3,6 @@
 FDE wrapper library
 """
 
-# Add imports here
-from .taco import *
-
 # Handle versioneer
 from ._version import get_versions
 versions = get_versions()

taco/data/cache.py

@@ -0,0 +1,30 @@
+import os
+import glob
+
+from taco.testdata.cache import fullfile
+
+
+# TODO: will be refactored
+class DataCache():
+    @property
+    def files(self):
+        thisdir = os.path.dirname(__file__)
+        fnames = glob.glob(os.path.join(thisdir, "*.txt"))
+        ret = {}
+        for f in fnames:
+            bname = os.path.splitext(os.path.basename(f))[0]
+            ret[bname] = fullfile(f)
+        return ret
+
+    @property
+    def jfiles(self):
+        thisdir = os.path.dirname(__file__)
+        fnames = glob.glob(os.path.join(thisdir, "*.json"))
+        ret = {}
+        for f in fnames:
+            bname = os.path.splitext(os.path.basename(f))[0]
+            ret[bname] = fullfile(f)
+        return ret
+
+
+data = DataCache()

taco/data/translation.json

@@ -0,0 +1,44 @@
+{ "pyscf2molcas":
+    {"cc-pvdz":
+        {"first": [0, 1, 2, 3, 4],
+        "second": [0, 1, 2, 3, 6, 4, 7, 5, 8, 9, 10, 11, 12, 13]
+         }
+    },
+  "qchem2pyscf":
+    {"aug-cc-pvdz":
+        {"first":  [0, 1, 5, 2, 3, 4, 6, 7, 8],
+         "second": [0, 1, 2, 14, 3, 4, 5, 6, 7, 8, 15, 16, 17, 9, 10,
+                    11, 12, 13, 18, 19, 20, 21, 22],
+        },
+    "cc-pvdz":
+        {"first": [0, 1, 2, 3, 4],
+        "second": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13],
+        "third": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]
+        },
+    "cc-pvtz": 
+        {"first": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13],
+        "second": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,
+                   13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 
+                   23, 24, 25, 26, 27, 28, 29],
+        "third": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,
+                  17, 18, 19, 20, 21, 22, 23, 24, 25, 26,
+                  27, 28, 29, 30, 31, 32, 33]
+        }
+    },
+  "pyscf2qchem":
+    {"6-31g":
+        {"first": [0, 1],
+        "second": [0, 1, 2, 3, 6, 4, 7, 5, 8]
+        },
+    "aug-cc-pvdz": 
+        {"first": [],
+        "second": []
+        }
+    },
+  "molcas2pyscf":
+    {"cc-pvdz":
+        {"first": [0, 1, 2, 3, 4],
+        "second": [0, 1, 2, 3, 5, 7, 4, 6, 8, 9, 10, 11, 12, 13]
+         }
+    }
+}

taco/embedding/density.py

@@ -0,0 +1,56 @@
+"""Tools to handle densities."""
+
+import re
+import numpy as np
+from taco.translate.tools import parse_matrices
+
+
+def transform_density_matrix(dm, coeffs):
+    """Transform the Density Metrix into a different orbital representation.
+
+    Parameters
+    ----------
+    dm : np.ndarray
+        Density matrix to be transformed.
+    coeffs : np.ndarray
+        Set of orbital coefficients used for transformation, as follows:
+
+    .. math::
+        \gamma_{fin} = \sum_{ij} \chi_i \gamma_{ij} \chi^*_j
+
+    Returns
+    -------
+    dm_fin : np.ndarray
+        Transformed density matrix
+    """
+    dm_fin = np.einsum('ij,ki,lj->kl', dm, coeffs, coeffs)
+    return dm_fin
+
+
+def prepare_omolcas_density(fname, mo_repr=False):
+    """Prepare density to be read from OpenMolcas.
+
+    Parameters
+    ----------
+    fname : str
+        Name of file from where the density is taken.
+    mo_repr : bool
+        Whether the density matrix to be read is in MO basis.
+
+    Returns
+    -------
+    dm : np.ndarray
+        Density matrix in AO or MO representation.
+    """
+    if "RUNASCII" in fname:
+        if mo_repr:
+            hook = {'1dm': re.compile(r'\<(D1mo.)')}
+        else:
+            hook = {'1dm': re.compile(r'\<(D1ao.)')}
+        parsed = parse_matrices(fname, hook, software='molcas')
+        return parsed['1dm']
+    elif fname.endswith('.h5'):
+        pass
+    else:
+        raise ValueError("""Please specify correctly the name of file,"""
+                         """ either containing `RUNASCII` or use a `.h5`""")