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== In Process of Updating... Check back 11/23/06 == | |
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Emily Kirkman is working on this project. == Class Docstrings == {{{ A collection of constructors of common graphs. USES: A list of all graphs and graph structures in this database is available via tab completion. Type "graphs." and then hit tab to see which graphs are available. The docstrings include educational information about each named graph with the hopes that this database can be used as a reference. PLOTTING: All graphs (i.e., networks) have an associated SAGE graphics object, which you can display: sage: G = WheelGraph(15) sage: p = G.plot() sage: is_Graphics(p) True When creating a graph in SAGE, the default positioning of nodes is determined using the spring-layout algorithm. Often, it is more efficient to pre-set the positions in a dictionary. Additionally, we can use this position dictionary to display the graph in an intuitive manner, whereas the spring-layout would fail if the graph is not very symmetric. For example, consider the Petersen graph with default node positioning vs. the Petersen graph constructed by this database: sage: petersen_spring = Graph({0:[1,4,5], 1:[0,2,6], 2:[1,3,7], 3:[2,4,8], 4:[0,3,9],\ 5:[0,7,8], 6:[1,8,9], 7:[2,5,9], 8:[3,5,6], 9:[4,6,7]}) sage.: petersen_spring.show() sage: petersen_database = graphs.PetersenGraph() sage.: petersen_database.show() For all the constructors in this database (except the random and empty graphs), the position dictionary is filled, instead of using the spring-layout algorithm. ORGANIZATION: The constructors available in this database are organized as follows: Basic Structures: - EmptyGraph - CycleGraph - StarGraph - WheelGraph Named Graphs: - PetersenGraph Families of Graphs: - CompleteGraph - CompleteBipartiteGraph - RandomGNP - RandomGNPFast AUTHORS: -- Robert Miller (2006-11-05): initial version - empty, random, petersen -- Emily Kirkman (2006-11-12): basic structures, node positioning for all constructors -- Emily Kirkman (2006-11-19): docstrings, examples TODO: [] more named graphs [] thorough docstrings and examples }}} |
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We've begun to implement some basic graph constructors with (hopefully) intuitive graphics. Please browse below and for more information on attachment:complete_array.png |
We've begun to implement some basic graph constructors with (hopefully) intuitive graphics. Please browse below and for more information on graph plotting, look at Rober Miller's [http://sage.math.washington.edu:9001/graph_plotting wiki]. === Empty Graphs === ==== Info ==== * Returns an empty graph (0 nodes and 0 edges). * This is useful for constructing graphs by adding edges and vertices individually or in a loop. ==== Plotting ==== * When plotting, this graph will use the default spring-layout algorithm, unless a position dictionary is specified. ==== Code ==== ==== Examples ==== {{{ # Add one vertex to an empty graph and then show: sage: empty1 = graphs.EmptyGraph() sage: empty1.add_vertex() sage.: empty1.show() }}} attachment:empty1.png {{{ # Use for loops to build a graph from an empty graph: sage: empty2 = graphs.EmptyGraph() sage: for i in range(5): ... empty2.add_vertex() # add 5 nodes, labeled 0-4 ... sage: for i in range(3): ... empty2.add_edge(i,i+1) # add edges {[0:1],[1:2],[2:3]} ... sage: for i in range(4)[1:]: ... empty2.add_edge(4,i) # add edges {[1:4],[2:4],[3:4]} ... sage.: empty2.show() }}} === Cycle Graphs === ==== Info ==== * Returns a cycle graph with n nodes. * A cycle graph is a basic structure which is also typically called an n-gon. * This constructor is dependant on vertices numbered 0 through n-1 in NetworkX cycle_graph() ==== Plotting ==== * Upon construction, the position dictionary is filled to override the spring-layout algorithm. By convention, each cycle graph will be displayed with the first (0) node at the top, with the rest following in a counterclockwise manner. * The cycle graph is a good opportunity to compare efficiency of filling a position dictionary vs. using the spring-layout algorithm for plotting. Because the cycle graph is very symmetric, the resulting plots should be similar (in cases of small n). * Filling the position dictionary in advance adds O(n) to the constructor. Feel free to race the constructors below in the examples section. The much larger difference is the time added by the spring-layout algorithm when plotting. (Also shown in the example below). The spring model is typically described as O(n^3), as appears to be the case in the NetworkX source code. ==== Code ==== ==== Examples ==== {{{ # The following examples require NetworkX (to use default) sage: import networkx as NX # Compare the constructors (results will vary) sage.: time n = NX.cycle_graph(3989); spring3989 = Graph(n) # CPU time: 0.05 s, Wall time: 0.07 s sage.: time posdict3989 = graphs.CycleGraph(3989) # CPU time: 5.18 s, Wall time: 6.17 s # Compare the plotting speeds (results will vary) sage: n = NX.cycle_graph(23) sage: spring23 = Graph(n) sage: posdict23 = graphs.CycleGraph(23) sage.: time spring23.show() # CPU time: 2.04 s, Wall time: 2.72 s sage.: time posdict23.show() # CPU time: 0.57 s, Wall time: 0.71 s # View many cycle graphs as a SAGE Graphics Array # With this constructor (i.e., the position dictionary filled) sage: g = [] sage: j = [] sage: for i in range(16): ... k = graphs.CycleGraph(i+3) ... g.append(k) ... sage: for i in range(4): ... n = [] ... for m in range(4): ... n.append(g[4*i + m].plot(node_size=50, with_labels=False)) ... j.append(n) ... sage: G = sage.plot.plot.GraphicsArray(j) sage.: G.show() # Compared to plotting with the spring-layout algorithm sage: g = [] sage: j = [] sage: for i in range(16): ... spr = NX.cycle_graph(i+3) ... k = Graph(spr) ... g.append(k) ... sage: for i in range(4): ... n = [] ... for m in range(4): ... n.append(g[4*i + m].plot(node_size=50, with_labels=False)) ... j.append(n) ... sage: G = sage.plot.plot.GraphicsArray(j) sage.: G.show() }}} === Star Graphs === ==== Info ==== ==== Plotting ==== ==== Code ==== ==== Examples ==== === Wheel Graphs === ==== Info ==== ==== Plotting ==== ==== Code ==== ==== Examples ==== |
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=== Petersen === ==== Info ==== ==== Plotting ==== ==== Properties ==== ==== Code ==== ==== Examples ==== * Here is the Petersen Graph as constructed in the database attachment:petersen_pos.png * And compare with the Petersen Graph plotted using the spring layout algorithm attachment:petersen_spring.png == Graph Families == === Complete Graphs === ==== Info ==== ==== Plotting ==== ==== Code ==== ==== Examples ==== === Complete Bipartite Graphs === ==== Info ==== ==== Plotting ==== ==== Code ==== ==== Examples ==== == Graphs I Plan to Add == |
In Process of Updating... Check back 11/23/06
Introduction
The SAGE Graph Theory Project aims to implement Graph objects and algorithms in ["SAGE"].
The goal of the Graph Database is to implement constructors for many common graphs, as well as thorough docstrings that can be used for educational purposes. Please check below for updates and note the section set aside for suggestions at the bottom of the page.
Emily Kirkman is working on this project.
Class Docstrings
A collection of constructors of common graphs. USES: A list of all graphs and graph structures in this database is available via tab completion. Type "graphs." and then hit tab to see which graphs are available. The docstrings include educational information about each named graph with the hopes that this database can be used as a reference. PLOTTING: All graphs (i.e., networks) have an associated SAGE graphics object, which you can display: sage: G = WheelGraph(15) sage: p = G.plot() sage: is_Graphics(p) True When creating a graph in SAGE, the default positioning of nodes is determined using the spring-layout algorithm. Often, it is more efficient to pre-set the positions in a dictionary. Additionally, we can use this position dictionary to display the graph in an intuitive manner, whereas the spring-layout would fail if the graph is not very symmetric. For example, consider the Petersen graph with default node positioning vs. the Petersen graph constructed by this database: sage: petersen_spring = Graph({0:[1,4,5], 1:[0,2,6], 2:[1,3,7], 3:[2,4,8], 4:[0,3,9],\ 5:[0,7,8], 6:[1,8,9], 7:[2,5,9], 8:[3,5,6], 9:[4,6,7]}) sage.: petersen_spring.show() sage: petersen_database = graphs.PetersenGraph() sage.: petersen_database.show() For all the constructors in this database (except the random and empty graphs), the position dictionary is filled, instead of using the spring-layout algorithm. ORGANIZATION: The constructors available in this database are organized as follows: Basic Structures: - EmptyGraph - CycleGraph - StarGraph - WheelGraph Named Graphs: - PetersenGraph Families of Graphs: - CompleteGraph - CompleteBipartiteGraph - RandomGNP - RandomGNPFast AUTHORS: -- Robert Miller (2006-11-05): initial version - empty, random, petersen -- Emily Kirkman (2006-11-12): basic structures, node positioning for all constructors -- Emily Kirkman (2006-11-19): docstrings, examples TODO: [] more named graphs [] thorough docstrings and examples
Basic Structures
We've begun to implement some basic graph constructors with (hopefully) intuitive graphics. Please browse below and for more information on graph plotting, look at Rober Miller's [http://sage.math.washington.edu:9001/graph_plotting wiki].
Empty Graphs
Info
- Returns an empty graph (0 nodes and 0 edges).
- This is useful for constructing graphs by adding edges and vertices individually or in a loop.
Plotting
- When plotting, this graph will use the default spring-layout algorithm, unless a position dictionary is specified.
Code
Examples
# Add one vertex to an empty graph and then show: sage: empty1 = graphs.EmptyGraph() sage: empty1.add_vertex() sage.: empty1.show()
attachment:empty1.png
# Use for loops to build a graph from an empty graph: sage: empty2 = graphs.EmptyGraph() sage: for i in range(5): ... empty2.add_vertex() # add 5 nodes, labeled 0-4 ... sage: for i in range(3): ... empty2.add_edge(i,i+1) # add edges {[0:1],[1:2],[2:3]} ... sage: for i in range(4)[1:]: ... empty2.add_edge(4,i) # add edges {[1:4],[2:4],[3:4]} ... sage.: empty2.show()
Cycle Graphs
Info
- Returns a cycle graph with n nodes.
- A cycle graph is a basic structure which is also typically called an n-gon.
- This constructor is dependant on vertices numbered 0 through n-1 in NetworkX cycle_graph()
Plotting
- Upon construction, the position dictionary is filled to override the spring-layout algorithm. By convention, each cycle graph will be displayed with the first (0) node at the top, with the rest following in a counterclockwise manner.
- The cycle graph is a good opportunity to compare efficiency of filling a position dictionary vs. using the spring-layout algorithm for plotting. Because the cycle graph is very symmetric, the resulting plots should be similar (in cases of small n).
- Filling the position dictionary in advance adds O(n) to the constructor. Feel free to race the constructors below in the examples section. The much larger difference is the time added by the spring-layout algorithm when plotting. (Also shown in the example below). The spring model is typically described as O(n^3), as appears to be the case in the NetworkX source code.
Code
Examples
# The following examples require NetworkX (to use default) sage: import networkx as NX # Compare the constructors (results will vary) sage.: time n = NX.cycle_graph(3989); spring3989 = Graph(n) # CPU time: 0.05 s, Wall time: 0.07 s sage.: time posdict3989 = graphs.CycleGraph(3989) # CPU time: 5.18 s, Wall time: 6.17 s # Compare the plotting speeds (results will vary) sage: n = NX.cycle_graph(23) sage: spring23 = Graph(n) sage: posdict23 = graphs.CycleGraph(23) sage.: time spring23.show() # CPU time: 2.04 s, Wall time: 2.72 s sage.: time posdict23.show() # CPU time: 0.57 s, Wall time: 0.71 s # View many cycle graphs as a SAGE Graphics Array # With this constructor (i.e., the position dictionary filled) sage: g = [] sage: j = [] sage: for i in range(16): ... k = graphs.CycleGraph(i+3) ... g.append(k) ... sage: for i in range(4): ... n = [] ... for m in range(4): ... n.append(g[4*i + m].plot(node_size=50, with_labels=False)) ... j.append(n) ... sage: G = sage.plot.plot.GraphicsArray(j) sage.: G.show() # Compared to plotting with the spring-layout algorithm sage: g = [] sage: j = [] sage: for i in range(16): ... spr = NX.cycle_graph(i+3) ... k = Graph(spr) ... g.append(k) ... sage: for i in range(4): ... n = [] ... for m in range(4): ... n.append(g[4*i + m].plot(node_size=50, with_labels=False)) ... j.append(n) ... sage: G = sage.plot.plot.GraphicsArray(j) sage.: G.show()
Star Graphs
Info
Plotting
Code
Examples
Wheel Graphs
Info
Plotting
Code
Examples
Named Graphs
Petersen
Info
Plotting
Properties
Code
Examples
- Here is the Petersen Graph as constructed in the database
attachment:petersen_pos.png
- And compare with the Petersen Graph plotted using the spring layout algorithm
attachment:petersen_spring.png
Graph Families
Complete Graphs
Info
Plotting
Code
Examples
Complete Bipartite Graphs
Info
Plotting
Code
Examples
Graphs I Plan to Add
Suggestions
- ???