Merge pull request #48 from mcocdawc/small_cosmetic_changes

Removal of trailing whitespaces & Python Requires Cleanup
troyvvgroup · Oct 30, 2024 · b5cf74a · b5cf74a
2 parents 7596d10 + 7361cc7
commit b5cf74a
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diff --git a/README.md b/README.md
@@ -34,7 +34,7 @@ processors.
 
 <sub><sup>##</sup>The modified version of [libDMET](https://github.com/gkclab/libdmet_preview) available
 at [here](https://github.com/oimeitei/libdmet_preview) is
-recommended to run periodic BE using QuEmb.  
+recommended to run periodic BE using QuEmb.
 <sup>&&</sup>Wannier90 code is interfaced via [libDMET](https://github.com/gkclab/libdmet_preview) in QuEmb</sub>
 
 ### Steps
@@ -43,16 +43,16 @@ recommended to run periodic BE using QuEmb.
    ```bash
    git clone https://github.com/oimeitei/quemb.git
    cd quemb
-   
+
 2. Install QuEmb using one of the following approaches:
     ```bash
-    pip install .  
+    pip install .
     ```
     or simply add `path/to/quemd` to `PYTHONPATH`
     ```bash
     export PYTHONPATH=/path/to/quemb:$PYTHONPATH
     ```
-    
+
     For conda (or virtual environment) installations, after creating your environment, specify the path to mol-be source as a path file, as in:
     ```bash
     echo path/to/quemb > $(python -c "from distutils.sysconfig import get_python_lib; print(get_python_lib())")/quemb.pth
@@ -94,6 +94,6 @@ Alternatively, you can view the latest documentation online [here](https://quemb
 ## References
 
 The methods implemented in this code are described in details in the following papers:
-- OR Meitei, T Van Voorhis, Periodic bootstrap embedding, [JCTC 19 3123 2023](https://doi.org/10.1021/acs.jctc.3c00069)  
-- OR Meitei, T Van Voorhis, Electron correlation in 2D periodic systems, [arXiv:2308.06185](https://arxiv.org/abs/2308.06185)  
+- OR Meitei, T Van Voorhis, Periodic bootstrap embedding, [JCTC 19 3123 2023](https://doi.org/10.1021/acs.jctc.3c00069)
+- OR Meitei, T Van Voorhis, Electron correlation in 2D periodic systems, [arXiv:2308.06185](https://arxiv.org/abs/2308.06185)
 - HZ Ye, HK Tran, T Van Voorhis, Bootstrap embedding for large molecular systems, [JCTC 16 5035 2020](https://doi.org/10.1021/acs.jctc.0c00438)
diff --git a/docs/source/index.rst b/docs/source/index.rst
@@ -24,7 +24,7 @@ References
 2. OR Meitei, T Van Voorhis, Electron correlation in 2D periodic systems, `arXiv:2308.06185 <https://arxiv.org/abs/2308.06185>`_
 3. HZ Ye, HK Tran, T Van Voorhis, Bootstrap embedding for large molecular systems, `JCTC 16 5035 2020 <https://doi.org/10.1021/acs.jctc.0c00438>`_
 
-   
+
 .. toctree::
    :maxdepth: 1
 
@@ -37,4 +37,4 @@ References
    solvers
    misc
 
-	   
+
diff --git a/docs/source/install.rst b/docs/source/install.rst
@@ -25,18 +25,18 @@ pip install
 -----------
 
 ::
-   
+
   pip install .
 
 Add to ``PYTHONPATH``
 ---------------------
 Simply add ``path/to/quemb`` to ``PYTHONPATH``
 ::
-   
+
    export PYTHONPATH=/path/to/quemb:$PYTHONPATH
 
 Conda or virtual environment
 ----------------------------
 For conda (or virtual environment) installations, after creating your environment, specify the path to mol-be source as a path file, as in::
-  
+
   echo path/to/quemb > $(python -c "from distutils.sysconfig import get_python_lib; print(get_python_lib())")/quemb.pth
diff --git a/docs/source/kernel.rst b/docs/source/kernel.rst
@@ -31,5 +31,5 @@ Serial BE Solver
 .. toctree::
    :maxdepth: 4
 .. autofunction:: molbe.solver.be_func
-   
+
 
diff --git a/docs/source/optimize.rst b/docs/source/optimize.rst
@@ -7,7 +7,7 @@ Main BE optimization
 .. toctree::
    :maxdepth: 4
 .. autoclass:: molbe._opt.BEOPT
-   :members:	       
+   :members:
 
 Quasi-Newton optimization
 =========================

diff --git a/docs/source/pfrag.rst b/docs/source/pfrag.rst
@@ -17,4 +17,4 @@ Periodic fragments
    :maxdepth: 4
 .. automodule:: kbe.pfrag
    :members:
-     
+
diff --git a/docs/source/solvers.rst b/docs/source/solvers.rst
@@ -14,7 +14,7 @@ Crystalline orbital localization
 --------------------------------
 
 .. autofunction:: kbe.lo.localize
-		  
+
 Density Matching Error
 ======================
 
@@ -24,9 +24,9 @@ Interface to Quantum Chemistry Methods
 ======================================
 
 .. autofunction:: molbe.solver.solve_mp2
-		  
+
 .. autofunction:: molbe.solver.solve_ccsd
-		  
+
 .. autofunction:: molbe.helper.get_scfObj
 
 Schmidt Decomposition
@@ -44,15 +44,15 @@ Periodic Schmidt decomposition
 
 Handling Hamiltonian
 ====================
-		  
+
 .. autofunction:: molbe.helper.get_eri
-		  
+
 .. autofunction:: molbe.helper.get_core
 
 
 Build molecular HF potential
 ----------------------------
-		  
+
 .. autofunction:: molbe.helper.get_veff
 
 Build perioidic HF potential
@@ -63,9 +63,9 @@ Build perioidic HF potential
 
 Handling Energies
 =================
-		  
+
 .. autofunction:: molbe.helper.get_frag_energy
-		  
+
 .. autofunction:: molbe.rdm.compute_energy_full
 
 Handling Densities

diff --git a/docs/source/usage.rst b/docs/source/usage.rst
@@ -15,9 +15,9 @@ Simple example of BE calculation on molecular system::
 
   # Perform pyscf calculations to get mol, mf objects
   # See quemb/example/molbe_h8_density_matching.py
-  # get mol: pyscf.gto.M 
-  # get mf: pyscf.scf.RHF 
-  
+  # get mol: pyscf.gto.M
+  # get mf: pyscf.scf.RHF
+
   # Define fragments
   myFrag = fragpart(be_type='be2', mol=mol)
 
@@ -26,7 +26,7 @@ Simple example of BE calculation on molecular system::
 
   # Perform density matching in BE
   mybe.optimize(solver='CCSD')
-  
+
 
 Simple example of periodic BE calculation on 1D periodic system::
 
@@ -47,4 +47,4 @@ Simple example of periodic BE calculation on 1D periodic system::
 
   # Perform density matching in BE
   mybe.optimize(solver='CCSD')
-  
+
diff --git a/example/data/hexene.xyz b/example/data/hexene.xyz
@@ -1,20 +1,20 @@
 18
 
-C       -5.6502267899      0.7485927383     -0.0074809907                 
-C       -4.5584842828      1.7726977952     -0.0418619714                 
-H       -5.5515181382      0.0602177800     -0.8733001951                 
-H       -6.6384111226      1.2516490350     -0.0591711493                 
-H       -5.5928112720      0.1649656434      0.9355613930                 
-C       -3.2701647911      1.4104028701      0.0085107804                 
-C       -2.1789947571      2.4456245961     -0.0265301736                 
-C       -0.7941361337      1.7933691827      0.0427863465                 
-H       -2.3064879754      3.1340763205      0.8376047229                 
-H       -2.2652945230      3.0294980525     -0.9691823088                 
-C        0.3121144607      2.8438276122      0.0072105803                 
-H       -0.6626010212      1.1042272672     -0.8201573062                 
-H       -0.7037327970      1.2086599200      0.9845037688                 
-H        0.2581952957      3.4296615741     -0.9351274363                 
-H        1.3021608456      2.3437050700      0.0587054221                 
-H        0.2170130582      3.5342406229      0.8723087816                 
-H       -4.8264911382      2.8238751191     -0.1088423637                 
-H       -3.0132059318      0.3554469837      0.0754505007                 
+C       -5.6502267899      0.7485927383     -0.0074809907
+C       -4.5584842828      1.7726977952     -0.0418619714
+H       -5.5515181382      0.0602177800     -0.8733001951
+H       -6.6384111226      1.2516490350     -0.0591711493
+H       -5.5928112720      0.1649656434      0.9355613930
+C       -3.2701647911      1.4104028701      0.0085107804
+C       -2.1789947571      2.4456245961     -0.0265301736
+C       -0.7941361337      1.7933691827      0.0427863465
+H       -2.3064879754      3.1340763205      0.8376047229
+H       -2.2652945230      3.0294980525     -0.9691823088
+C        0.3121144607      2.8438276122      0.0072105803
+H       -0.6626010212      1.1042272672     -0.8201573062
+H       -0.7037327970      1.2086599200      0.9845037688
+H        0.2581952957      3.4296615741     -0.9351274363
+H        1.3021608456      2.3437050700      0.0587054221
+H        0.2170130582      3.5342406229      0.8723087816
+H       -4.8264911382      2.8238751191     -0.1088423637
+H       -3.0132059318      0.3554469837      0.0754505007
diff --git a/example/kbe_polyacetylene.py b/example/kbe_polyacetylene.py
@@ -21,14 +21,14 @@
 cell.a = lat
 
 cell.atom='''
-H      1.4285621630072645    0.0    -0.586173422487319    
-C      0.3415633681566205    0.0    -0.5879921146011252    
-H     -1.4285621630072645    0.0     0.586173422487319    
-C     -0.3415633681566205    0.0     0.5879921146011252    
-H      1.4285621630072645    0.0     1.868826577512681    
-C      0.3415633681566205    0.0     1.867007885398875    
-H     -1.4285621630072645    0.0     3.041173422487319    
-C     -0.3415633681566205    0.0     3.0429921146011254    
+H      1.4285621630072645    0.0    -0.586173422487319
+C      0.3415633681566205    0.0    -0.5879921146011252
+H     -1.4285621630072645    0.0     0.586173422487319
+C     -0.3415633681566205    0.0     0.5879921146011252
+H      1.4285621630072645    0.0     1.868826577512681
+C      0.3415633681566205    0.0     1.867007885398875
+H     -1.4285621630072645    0.0     3.041173422487319
+C     -0.3415633681566205    0.0     3.0429921146011254
 '''
 
 cell.unit='Angstrom'

diff --git a/example/molbe_dmrg_block2.py b/example/molbe_dmrg_block2.py
@@ -1,5 +1,5 @@
 # A run through the `QuEmb` interface with `block2` for performing BE-DMRG.
-# `block2` is a DMRG and sparse tensor network library developed by the 
+# `block2` is a DMRG and sparse tensor network library developed by the
 # Garnet-Chan group at Caltech: https://block2.readthedocs.io/en/latest/index.html
 
 import os, numpy, sys
@@ -13,7 +13,7 @@
 fci_ecorr, ccsd_ecorr, ccsdt_ecorr, bedmrg_ecorr = [], [], [], []
 
 # Specify a scratch directory for fragment DMRG files:
-scratch = os.getcwd() 
+scratch = os.getcwd()
 
 for a in seps:
     # Hartree-Fock serves as the starting point for all BE calculations:
@@ -31,42 +31,42 @@
     # Exact diagonalization (FCI) will provide the reference:
     mc = fci.FCI(mf)
     fci_ecorr.append(mc.kernel()[0] - mf.e_tot)
-    
+
     # CCSD and CCSD(T) are good additional points of comparison:
     mycc = cc.CCSD(mf).run()
     et_correction = mycc.ccsd_t()
     ccsd_ecorr.append(mycc.e_tot - mf.e_tot)
     ccsdt_ecorr.append(mycc.e_tot + et_correction - mf.e_tot)
 
-    # Define BE1 fragments. Prior to DMRG the localization of MOs 
-    # is usually necessary. While there doesn't appear to be 
+    # Define BE1 fragments. Prior to DMRG the localization of MOs
+    # is usually necessary. While there doesn't appear to be
     # any clear advantage to using any one scheme over another,
     # the Pipek-Mezey scheme continues to be the most popular. With
     # BE-DMRG, localization takes place prior to fragmentation:
     fobj = fragpart(be_type='be1', mol=mol)
     mybe = BE(
-        mf, 
-        fobj, 
+        mf,
+        fobj,
         lo_method='pipek-mezey',                        # or 'lowdin', 'iao', 'boys'
         pop_method='lowdin'                             # or 'meta-lowdin', 'mulliken', 'iao', 'becke'
         )
-    
+
     # Next, run BE-DMRG with default parameters and maxM=100.
     mybe.oneshot(
         solver='block2',                                # or 'DMRG', 'DMRGSCF', 'DMRGCI'
         scratch=scratch,                                # Scratch dir for fragment DMRG
         maxM=100,                                       # Max fragment bond dimension
         force_cleanup=True,                             # Remove all fragment DMRG tmpfiles
-        ) 
+        )
 
     bedmrg_ecorr.append(mybe.ebe_tot - mf.e_tot)
-    # Setting `force_cleanup=True` will clean the scratch directory after each 
+    # Setting `force_cleanup=True` will clean the scratch directory after each
     # fragment DMRG calculation finishes. DMRG tempfiles can be quite large, so
     # be sure to keep an eye on them if `force_cleanup=False` (default).
-    
+
     # NOTE: This does *not* delete the log files `dmrg.conf` and `dmrg.out`for each frag,
     # which can still be found in `/scratch/`.
-    
+
 # Finally, plot the resulting potential energy curves:
 fig, ax = plt.subplots()
 
@@ -81,7 +81,7 @@
 # (See ../quemb/example/figures/BEDMRG_H8_PES20.png for an example.)
 
 # For larger fragments, you'll want greater control over the fragment
-# DMRG calculations. Using the same setup as above for a single geometry: 
+# DMRG calculations. Using the same setup as above for a single geometry:
 mol = gto.M()
 mol.atom = [['H', (0.,0.,i*1.2)] for i in range(8)]
 mol.basis = 'sto-3g'
@@ -90,15 +90,15 @@
 mol.build()
 fobj = fragpart(be_type='be2', mol=mol)
 mybe = BE(
-    mf, 
-    fobj, 
+    mf,
+    fobj,
     lo_method='pipek-mezey',
     pop_method='lowdin'
     )
 
 # We automatically construct the fragment DMRG schedules based on user keywords. The following
 # input, for example, yields a 60 sweep schedule which uses the two-dot algorithm from sweeps 0-49,
-# and the one-dot algo from 50-60. The fragment orbitals are also reordered according the Fiedler 
+# and the one-dot algo from 50-60. The fragment orbitals are also reordered according the Fiedler
 # vector procedure, along with a few other tweaks:
 
 mybe.optimize(
@@ -114,7 +114,7 @@
     block_extra_keyword=['fiedler'],                # Specify orbital reordering algorithm
     force_cleanup=True,                             # Remove all fragment DMRG tmpfiles
     only_chem=True,
-) 
+)
 
 # Or, alternatively, we can construct a full schedule by hand:
 schedule={
@@ -127,16 +127,16 @@
 # and pass it to the fragment solver through `schedule_kwargs`:
 mybe.optimize(
     solver='block2',
-    scratch=scratch, 
+    scratch=scratch,
     schedule_kwargs=schedule,
     block_extra_keyword=['fiedler'],
     force_cleanup=True,
     only_chem=True,
 )
 
-# To make sure the calculation is proceeding as expected, make sure to check `[scratch]/dmrg.conf` 
+# To make sure the calculation is proceeding as expected, make sure to check `[scratch]/dmrg.conf`
 # and `[scratch]/dmrg.out`, which are the fragment DMRG inputs and outputs, respectively, used
-# by `block2`. 
+# by `block2`.
 
 #NOTE: Parameters in `schedule_kwargs` will overwrite any other DMRG kwargs.
 #NOTE: The DMRG schedule kwargs and related syntax follows the standard notation used in block2.
Original file line number	Diff line number	Diff line change
Expand Up		@@ -31,5 +31,5 @@ Serial BE Solver
		.. toctree::
		:maxdepth: 4
		.. autofunction:: molbe.solver.be_func
Original file line number	Diff line number	Diff line change
Expand Up		@@ -17,4 +17,4 @@ Periodic fragments
		:maxdepth: 4
		.. automodule:: kbe.pfrag
		:members: