Merge remote-tracking branch 'origin/main' into main

README.md

 # kirchhoff
 
 ##  Introduction
-
+This module 'kirchhoff' is part of a series of pyton packages encompassing a set of class and method implementations for a kirchhoff network datatype, which includes a visualization routine based on plotly. The concept is to build kirchhoff networks from networkx graphs, by providing a container for the graphs as well as separate containers for network attributes meant for fast(er) computation in the follow-up modules 'hailhydro' and 'goflow' 
 ##  Installation
 pip install kirchhoff
 
 ##  Usage
+Generally, just take a weighted networkx graph and read it in as shown. You can plot the network interactivly, with full display of edge and node attributes if desired. Default attributes are 'source'/'potential' for nodes and 'conductivity'/'flow_rate' for edges. 
+
+```
+import kirchhoff.circuit_init as ki
+n=3
+G=nx.grid_graph(( n,n,1))
+K = ki.initialize_circuit_from_networkx(G)
+
+import kirchhoff.circuit_dual as kid
+kid.initialize_dual_flux_circuit_from_minsurf('simple',3)
+
+```
+
+Single and dual networks are supported at the moment, and can be constructed from networkx generator or custom pre-defined types of spatially embedded graphs such as  
+- crystals/periodic, initialize_circuit_from_crystal(crystal_type='default',periods=1): 'default': simple cubic lattice 3D, 'chain': 1D chain, 'bcc': bcc lattice 3D,  'fcc': fcc lattice 3D,'diamond': diamond lattice 3D,'laves': laves lattice 3D,'trigonal_stack': trigonal lattice stacked and interconnected 3D, 'square': simple cubic lattice 2D, 'hexagonal': hexagonal lattice 2D,'trigonal_planar': trigonal lattice 2D
+-  random voronoi tesselation, initialize_circuit_from_random(random_type='default',periods=10,sidelength=1):  'default': planar voronoi tesselation with periodic boundaries,  'voronoi_volume': 3D voronoi tesselation with periodic boundaries
+-   intertwined systems, initialize_dual_circuit_from_minsurf(dual_type='simple',num_periods=2): supporting most of the above in 3D
+      
+Further one can define 'flow' and 'flux' circuits for hydrodynamic simulations which are based on Hagen-Poiseuille flow and transport of solutes via advection-diffusion. Doing so will enable more specifically tailored methods for source/solute influx topology control:
+```
+import kirchhoff.circuit_flow as kfc
+kfc.initialize_circuit_from_networkx(G)
+kfc.initialize_flow_circuit_from_crystal('simple',3)
+kfc.initialize_flow_circuit_from_random(random_type='voronoi_volume')
+
+import kirchhoff.circuit_flux as kfx
+kfx.initialize_circuit_from_networkx(G)
+kfx.initialize_flux_circuit_from_crystal('simple',3)
+kfx.initialize_flux_circuit_from_random(random_type='voronoi_volume')
+```
+
+To set node and edge attributes ('source','potential' ,'conductivity','flow_rate') use the set_source_landscape(), set_plexus_landscape() methods of the kirchhof class and use the class method plot_circuit for plotly output:
+```
+import kirchhoff.circuit_flow as kfc
+
+K=kfc.initialize_flow_circuit_from_crystal('hexagonal',3)
+K.set_source_landscape()
+K.set_plexus_landscape()
+
+fig=K.plot_circuit()
+fig.show()
+```
+![hex](./gallery/hexagonal.png)
 ./notebook contains examples to play with in the form of jupyter notebooks
 ##  Requirements
-``` pandas ```,``` networkx ```, ``` numpy ```
-##  Gallery
-
+``` pandas ```,``` networkx ```, ``` numpy ```,```plotly```
+## Gallery
+![simple](./gallery/simplecubic3d.png)
+![dual](./gallery/duallaves.png)
+![voronoi](./gallery/voronoi3d.png)
 ## Acknowledgement
 ```kirchhoff``` written by Felix Kramer