Metadata-Version: 2.1
Name: leveldiagram
Version: 0.1.dev1
Summary: Energy level diagram plotting from graphs
Author: David Meyer
License: BSD-3-Clause
Keywords: physics,diagram,graph
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE.md
Requires-Dist: numpy
Requires-Dist: matplotlib
Requires-Dist: networkx
Provides-Extra: docs
Requires-Dist: Sphinx==7.2.6; extra == "docs"
Requires-Dist: sphinx-rtd-theme==2.0.0; extra == "docs"
Requires-Dist: nbconvert; extra == "docs"
Requires-Dist: pandoc; extra == "docs"
Provides-Extra: mypy
Requires-Dist: mypy; extra == "mypy"
Requires-Dist: numpy>=1.21; extra == "mypy"
Requires-Dist: lxml; extra == "mypy"
Provides-Extra: linter
Requires-Dist: ruff; extra == "linter"

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# leveldiagram

This module creates energy level diagrams common to atomic physics as matplotlib graphics.
The level structure is defined using networkx graphs.

## Quick Usage

This package takes networkx directional graphs,
which can be used to effectively define a system hamiltonian,
and creates an energy diagram representing the system.
The nodes of the graph represent the energy levels.
The edges of the graph represent the couplings between levels.

Passing a simple graph to the basic level diagram constructor will produce a passable output for simple visualization purposes.

```python
nodes = (0,1,2)
edges = ((0,1),(1,2))
graph = nx.DiGraph()
graph.add_nodes_from(nodes)
graph.add_edges_from(edges)
d = ld.LD(graph)
d.draw()
```
![Simple 3-level diagram with default options](https://raw.githubusercontent.com/dihm/leveldiagram/main/docs/source/img/basic_example.png)

Global settings for the three primitive objects used by leveldiagram can be set by passing keyword argument dictionaries to the `LD` constructor.
To control options for a single level or coupling,
save these keyword arguments to the respective node or edge of the supplied graph.
Generally, the levels and couplings take standard matplotlib 2D line configuration arguments.

```python
nodes = ((0,{'bottom_text':'ground'}),
         (1,{'right_text':'excited'}),
         (2,{'top_text':'rydberg'}))
edges = ((0,1, {'label':'$\\Omega_p$'}),
         (1,2, {'label':'$\\Omega_c$'}))
graph = nx.DiGraph()
graph.add_nodes_from(nodes)
graph.add_edges_from(edges)
d = ld.LD(graph, coupling_defaults = {'arrowsize':0.15,'lw':3})
d.draw()
```
![3-level diagram with some custom options](https://raw.githubusercontent.com/dihm/leveldiagram/main/docs/source/img/intermediate_example.png)

With some basic scripting to create the graph appropriately,
much more complicated level diagrams can be made with relative ease.

```python
hf_nodes =  [((f,i), {('top' if f==2 else 'bottom') + '_text':'$m_F='+f'{i:d}'+'$',
                      'energy':f-1,
                      'xpos':i,
                      'width':0.75,
                      'text_kw':{'fontsize':'large'}})
             for f in [1,2]
             for i in range(-f,f+1)]
lin_couples = [((1,i),(2,i),{'label':l,'color':'C0',
                            'label_kw':{'fontsize':'medium','color':'C0'}})
               for i,l in zip(range(-1,2), ['1/2','2/3','1/2'])]
sp_couples = [((1,i),(2,i+1),{'label':l,'color':'C1',
                              'label_offset':'right',
                             'label_kw':{'fontsize':'medium','color':'C1'}})
              for i,l in zip(range(-1,2), ['1/6','1/2','1'])]
sm_couples = [((1,i),(2,i-1),{'label':l, 'color':'C2',
                              'label_offset':'left',
                             'label_kw':{'fontsize':'medium','color':'C2'}})
              for i,l in zip(range(-1,2), ['1','1/2','1/6'])]
hf_edges = lin_couples + sp_couples + sm_couples
hf_graph = nx.DiGraph()
hf_graph.add_nodes_from(hf_nodes)
hf_graph.add_edges_from(hf_edges)
d = ld.LD(hf_graph, default_label = 'none')
d.ax.margins(y=0.2)
d.draw()
```
![Hyperfine states with Clebsh-Gordon Coefficients](https://raw.githubusercontent.com/dihm/leveldiagram/main/docs/source/img/hyperfine.png)


## Installation

Presently, installation must be done manually using a copy of the repository.

### Pure pip installation

To install in an editable way (which allows edits of the source code), run:
```shell
pip install -e .
```
from within the top level `leveldiagram` directory (i.e. where the `setup.cfg` file resides).
This command will use pip to install all necessary dependencies.

To install normally, run:
```shell
pip install .
```
from the same directory.


### Updating an existing installation

Upgrading an existing installation is simple.
Simply run the pip installation commands described above with the update flag.
```shell
pip install -U .
```
This command will also install any new dependencies that are required.

If using an editable install, simply replacing the files in the same directory is sufficient.
Though it is recommended to also run the appropriate pip update command as well.
```shell
pip install -U -e .
```

### Dependencies

Requires `matplotlib`, `networkx`, and `numpy`.

## Documentation

A PDF copy of the documentation is avaiable in the `docs/build/latex/` directory.

### Examples

Example jupyter notebooks that demonstrate leveldiagrams can be found in the `examples` subdirectory.
Printouts of these notebooks are available in the docs as well.
