json ---> svg (editable) ---> svg (extra features)

With this module one can take the json-file with the metabolic network layout info and make a pretty svg. See folder 'metabolic_maps' for examples. The svg can, if needed, be edited in an svg-editor (e.g. Inkscape). The (edited) svg can then be turned into an svg-file with data on hover when viewed in a browser.

json ---> graphml (editable) ---> svg (editable) ---> svg (extra features)

If the graph in the json-file is not to your satisfaction to start with, one can also first turn the layout info from the json-file to a graphml-file, edit the graph (e.g. with Gephi), and turn the graphml-file into an svg.

json_to_svg.py: create an svg-file from the json output from Nicholas' module. This file is editable in an svg-editor such as Inkscape. Use json_to_svg.py --help for information on available flags.

layout_final.py: create an svg-file from the output svg-file of json_to_svg.py and/or graph_to_svg.py with annotations on hover that can be used with visualize.py. Use layout_final.py --help for information on available flags.

json_to_graphml.py: create a graph-file (graphml) from the json output from Nicholas' module. This graph can be edited in a graph editor such as Gephi.

graph_to_svg.py: create an svg from a graph file. This file is editable in an svg-editor such as Inkscape.

snap_to_grid.py: change coordinates of nodes in graph file such that they are on a grid.

readers.py contains functions for reading the json, xml and graphml files.

svg_paths.py contains functions to make svg-paths (used in json_to_svg.py).

svg_assembly.py contains functions to assemble an svg-file (used in json_to_svg.py).

visualize.py contains classes for mapping FBA results from cbmpy to an svg graphical map of the metabolic network (as created by json_to_svg.py).

Make an svg from "yeast_5_01_model_xml_nucleotide reactions.json"

1. To create the svg-file with metabolic map, use the command:

python modules\json_to_svg.py "json_files\yeast_5_01_model_xml_nucleotide reactions.json" --svg_name "editable_svg_files\Y5_nucleotides.svg" --scale 20 15 --normalize --add_cofactors_from_sbml "models\Y5.xml"

A file with the metabolic map called 'Y5_nucleotides.svg' should now be saved in the editable_svg_files directory. This file can be edited in e.g. inkscape.

2. To create a file with annotations, clickable labels and other information on hover that can be used with the visualize.py module, use the command:

python modules\layout_final.py "editable_svg_files\Y5_nucleotides.svg" "models\Y7.xml" r_ s_ --svg_name "Y5_nucleotides.svg"

A file called 'Y5_nucleotides.svg' should now be saved in the metabolic_maps folder and opened in a new tab in your browser.

A good svg editor is Inkscape: https://inkscape.org/en/download/

NOTES/ISSUES:

1. when copy/pasting svg-elements in Inkscape, make sure the ids are unique and still compatible. The formats are:

paths: 'path_ReactionIDSpeciesID'

reaction nodes: 'ReactionID' or 'ReactionID_copy_1'

species labels: 'SpeciesID' or 'SpeciesID_copy_1'

cofactor labels: 'SpeciesIDReactionID'

reaction value placeholders: 'rval_ReactionID'

2. when copy/pasting svg-paths in Inkscape, the name of the marker will be changed (e.g. from 'substrate' to 'substrate-2'). This needs to be changed back to the original marker name, otherwise markers won't be visible when converting the svg to the svg with extra features.

A good graph editor is Gephi: https://gephi.org/

NOTES/ISSUES:

The graphml format is recommended. Make sure the nodes have the 'label', 'node_type' and 'pathway' attribute. Converting to svg works best if the nodes are on a grid, use the 'snap_to_grid.py' module for this.