Generation and use of an orbital-based grid

[1]:

import pymolpro
p = pymolpro.Project("orbital")
p.write_input("symmetry,nosym;geometry={o;h,o,r;h,o,r,h,theta};r=1 angstrom, theta=104 degree; rhf;locali,pipek,thrpip=1e-10;put,xml")
p.run(wait=True)

[2]:

orbitals = p.orbitals(minocc=1.0)

[3]:

import pandas
for orbital in orbitals:
    points = orbital.grid(4)
    # values = p.evaluateOrbitals(points, ID=orbital.ID, values=True)
    # values = p.evaluateOrbitals(points, ID=orbital.ID)['values']
    values = orbital.evaluate(points, values=True)
    print(orbital.ID, orbital.centroid, orbital.second_moment_eigenvalues)
    print(pandas.DataFrame(points).transpose())
    print(pandas.DataFrame(values).transpose())

1.1 [4.36189315945102e-17, -5.65839184589554e-18, -0.129953086882215] [0.01772806 0.01772858 0.01772861]
         0         1         2         3         4         5         6   \
0 -0.079239 -0.023853  0.023853  0.079239 -0.079239 -0.023853  0.023853
1 -0.079238 -0.079238 -0.079238 -0.079238 -0.079238 -0.079238 -0.079238
2 -0.209192 -0.209192 -0.209192 -0.209192 -0.153806 -0.153806 -0.153806

         7         8         9   ...        54        55        56        57  \
0  0.079239 -0.079239 -0.023853  ...  0.023853  0.079239 -0.079239 -0.023853
1 -0.079238 -0.079238 -0.079238  ...  0.079238  0.079238  0.079238  0.079238
2 -0.153806 -0.106100 -0.106100  ... -0.153806 -0.153806 -0.106100 -0.106100

         58        59        60        61        62        63
0  0.023853  0.079239 -0.079239 -0.023853  0.023853  0.079239
1  0.079238  0.079238  0.079238  0.079238  0.079238  0.079238
2 -0.106100 -0.106100 -0.050714 -0.050714 -0.050714 -0.050714

[3 rows x 64 columns]
         0         1         2         3         4        5        6   \
0  4.148478  4.946147  4.946147  4.148478  4.942366  6.16284  6.16284

         7         8         9   ...       54        55        56        57  \
0  4.942366  4.939117  6.157132  ...  6.16284  4.942366  4.939117  6.157132

         58        59        60        61        62        63
0  6.157132  4.939117  4.141304  4.935353  4.935353  4.141304

[1 rows x 64 columns]
2.1 [-2.23133341860535e-12, -0.78317178943009, 0.524537657987677] [0.44530382 0.45564982 0.9098715 ]
         0         1         2         3         4         5         6   \
0 -0.397127 -0.397127 -0.397127 -0.397127 -0.397127 -0.397127 -0.397127
1 -0.543217 -0.870101 -1.151653 -1.478537 -0.384056 -0.710940 -0.992493
2 -0.128179  0.096732  0.290453  0.515364  0.103144  0.328055  0.521776

         7         8         9   ...        54        55        56        57  \
0 -0.397127 -0.397127 -0.397127  ...  0.397127  0.397127  0.397127  0.397127
1 -1.319376 -0.246967 -0.573851  ... -0.992493 -1.319376 -0.246967 -0.573851
2  0.746687  0.302388  0.527299  ...  0.521776  0.746687  0.302388  0.527299

         58        59        60        61        62        63
0  0.397127  0.397127  0.397127  0.397127  0.397127  0.397127
1 -0.855404 -1.182288 -0.087806 -0.414690 -0.696243 -1.023127
2  0.721020  0.945931  0.533711  0.758622  0.952343  1.177254

[3 rows x 64 columns]
         0        1         2         3         4         5         6   \
0  0.399322  0.38697  0.338028  0.291293  0.478133  0.440586  0.378372

        7       8         9   ...        54       55      56        57  \
0  0.33094  0.4647  0.433285  ...  0.378372  0.33094  0.4647  0.433285

         58        59        60       61        62        63
0  0.376373  0.332005  0.371588  0.37075  0.332924  0.293541

[1 rows x 64 columns]
3.1 [8.26672974408137e-13, 9.77485020009494e-13, -0.732716827889661] [0.46977397 0.49098249 0.50177496]
         0         1         2         3         4         5         6   \
0 -0.416999 -0.416999 -0.416999 -0.416999 -0.125526 -0.125526 -0.125526
1  0.421557  0.126898 -0.126898 -0.421557  0.421557  0.126898 -0.126898
2 -1.140610 -1.140610 -1.140610 -1.140610 -1.140610 -1.140610 -1.140610

         7         8         9   ...        54        55        56        57  \
0 -0.125526  0.125526  0.125526  ... -0.125526 -0.125526  0.125526  0.125526
1 -0.421557  0.421557  0.126898  ... -0.126898 -0.421557  0.421557  0.126898
2 -1.140610 -1.140610 -1.140610  ... -0.324824 -0.324824 -0.324824 -0.324824

         58        59        60        61        62        63
0  0.125526  0.125526  0.416999  0.416999  0.416999  0.416999
1 -0.126898 -0.421557  0.421557  0.126898 -0.126898 -0.421557
2 -0.324824 -0.324824 -0.324824 -0.324824 -0.324824 -0.324824

[3 rows x 64 columns]
        0         1         2        3         4         5         6   \
0  0.33011  0.372633  0.372633  0.33011  0.371277  0.422702  0.422702

         7         8         9   ...        54        55        56        57  \
0  0.371277  0.371277  0.422702  ...  0.272424  0.439186  0.439186  0.272424

         58        59        60        61        62        63
0  0.272424  0.439186  0.413244  0.439966  0.439966  0.413244

[1 rows x 64 columns]
4.1 [1.64073810474965e-12, -5.72458747072346e-17, -0.0876418809415855] [0.43603925 0.45045416 1.25108042]
         0         1         2         3         4         5         6   \
0  0.665647  0.200375 -0.200375 -0.665647  0.665647  0.200375 -0.200375
1 -0.399417 -0.399417 -0.399417 -0.399417 -0.120234 -0.120234 -0.120234
2  0.305333  0.305333  0.305333  0.305333  0.305333  0.305333  0.305333

         7         8         9   ...        54        55        56        57  \
0 -0.665647  0.665647  0.200375  ... -0.200375 -0.665647  0.665647  0.200375
1 -0.120234  0.120234  0.120234  ... -0.120234 -0.120234  0.120234  0.120234
2  0.305333  0.305333  0.305333  ... -0.480616 -0.480616 -0.480616 -0.480616

         58        59        60        61        62        63
0 -0.200375 -0.665647  0.665647  0.200375 -0.200375 -0.665647
1  0.120234  0.120234  0.399417  0.399417  0.399417  0.399417
2 -0.480616 -0.480616 -0.480616 -0.480616 -0.480616 -0.480616

[3 rows x 64 columns]
         0         1         2         3         4         5         6   \
0  0.344496  0.198343 -0.198343 -0.344496  0.420137  0.274622 -0.274622

         7         8         9   ...        54        55        56        57  \
0 -0.420137  0.420137  0.274622  ... -0.323382 -0.445447  0.445447  0.323382

         58        59        60        61        62        63
0 -0.323382 -0.445447  0.358141  0.219639 -0.219639 -0.358141

[1 rows x 64 columns]
5.1 [-2.37023848286065e-13, 0.783171789429109, 0.524537657987883] [0.44530382 0.45564982 0.9098715 ]
         0         1         2         3         4         5         6   \
0 -0.397127 -0.397127 -0.397127 -0.397127 -0.397127 -0.397127 -0.397127
1  0.087806  0.414690  0.696243  1.023127  0.246967  0.573851  0.855404
2  0.533711  0.758622  0.952343  1.177254  0.302388  0.527299  0.721020

         7         8         9   ...        54        55        56        57  \
0 -0.397127 -0.397127 -0.397127  ...  0.397127  0.397127  0.397127  0.397127
1  1.182288  0.384056  0.710940  ...  0.855404  1.182288  0.384056  0.710940
2  0.945931  0.103144  0.328055  ...  0.721020  0.945931  0.103144  0.328055

         58        59        60        61        62        63
0  0.397127  0.397127  0.397127  0.397127  0.397127  0.397127
1  0.992493  1.319376  0.543217  0.870101  1.151653  1.478537
2  0.521776  0.746687 -0.128179  0.096732  0.290453  0.515364

[3 rows x 64 columns]
         0        1         2         3       4         5         6   \
0  0.371588  0.37075  0.332924  0.293541  0.4647  0.433285  0.376373

         7         8         9   ...        54        55        56        57  \
0  0.332005  0.478133  0.440586  ...  0.376373  0.332005  0.478133  0.440586

         58       59        60       61        62        63
0  0.378372  0.33094  0.399322  0.38697  0.338028  0.291293

[1 rows x 64 columns]