Improve bond guess (#50)

* add `rdkit_determine_bonds` function

* bump version

* more test and edge cases

* start refactoring

* some refactoring

* mostly done with refactoring

* fixed so far

* something is working

* update tests

* format

* something works

* remove print statements

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* split into sub method

* fix pre-commit errors

* small tests

* more tests

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* remove comments

* more tests

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* comments

* update docstrings

* docstrings

* docstrings

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* rerun notebooks

* `codespell` ignore `ipynb`

* remove unnecessary line

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Author: PythonFZ

docs/source/ase_tools.ipynb

@@ -82,7 +82,7 @@
      "data": {
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",
       "text/plain": [
-       "<rdkit.Chem.rdchem.Mol at 0x12731d620>"
+       "<rdkit.Chem.rdchem.Mol at 0x12454d310>"
       ]
      },
      "execution_count": 5,
@@ -111,7 +111,7 @@
     {
      "data": {
       "text/plain": [
-       "Atoms(symbols='OH2OH2OH2OH2OH2C2OH6C2OH6C2OH6C2OH6C2OH6', pbc=False, initial_charges=...)"
+       "Atoms(symbols='OH2OH2OH2OH2OH2C2OH6C2OH6C2OH6C2OH6C2OH6', pbc=True, cell=[8.728901107040366, 8.728901107040366, 8.728901107040366], initial_charges=...)"
       ]
      },
      "execution_count": 6,
@@ -120,7 +120,7 @@
     }
    ],
    "source": [
-    "rdkit2ase.networkx2atoms(graph)"
+    "rdkit2ase.networkx2ase(graph)"
    ]
   }
  ],

docs/source/networkx_tools.ipynb

@@ -18,7 +18,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 1,
    "id": "5b2423ed",
    "metadata": {},
    "outputs": [],
@@ -30,7 +30,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "id": "a0f43110",
    "metadata": {},
    "outputs": [],
@@ -44,7 +44,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 3,
    "id": "f6b6bb66",
    "metadata": {},
    "outputs": [
@@ -70,7 +70,7 @@
        " Atoms(symbols='C2H3OH3', pbc=True, cell=[8.728901107040366, 8.728901107040366, 8.728901107040366])]"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -90,7 +90,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 4,
    "id": "6cf8c2cb",
    "metadata": {},
    "outputs": [