Connectivity Analysis Toolkit License Version history Getting Started Overview of Methods Three Methods for Connectivity Analysis Subset Centrality: Mapping Linkages All-pairs Centrality: Mapping Landscape Connectivity Network Flow Analysis of Time Series Input files Output files Running the Toolkit from the GUI Hexmap Tab Graphs Tab Connectivity Tab Output Tab Running the Toolkit from the Command Prompt Flowchart of analysis process Examples Example 1: Shortest-path betweenness centrality (BC) Example 2: Shortest-path betweenness subset centrality Example 3: Comparison of subset and all-pairs current flow BC Example 4: Comparison of shortest-path and current flow BC Tutorial Exercise 1 - Mapping linkages with min-cost-max-flow subset centrality Exercise 2 - Mapping linkages with shortest-path subset centrality Exercise 3 - Mapping landscape connectivity with all-pairs centrality Exercise 4 - Mapping connectivity under climate change: analysis of time series Troubleshooting Related Resources System requirements Contacts & Credits
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# System requirements Minimal System Requirements For the 32-bit version: Microsoft Windows XP/Vista/7/8, 1.6 GHz processor, 2 GB RAM For the 64-bit version: Microsoft Windows XP/Vista/7/8 64-bit, 1.6 GHz processor, 3 GB RAM Additionally, the source code for the functions based on NetworkX and LEMON are available from www.connectivitytools.org. The Python script which is the basis for the betweenness, current flow, and PageRank functions will run within Python on other platforms such as Linux or Mac OSX. Source code for the LEMON-based functions is also available, and we hope to port this to Linux at a future date. The various functions differ in requirements for computational time and memory (RAM). The exact current flow BC subset function is RAM-intensive. All other functions, including approximate current flow BC, can be run on most desktop systems (i.e., with <4GB RAM). Time requirements scale rapidly from several minutes for graphs of several thousand nodes to hours for graphs with tens of thousands of nodes. If analyses are taking too long to complete, several options are available to reduce computational time: 1) use a coarser resolution for hxn and graph generation (set more hectares per hexagon), 2) decrease the proportion of nodes sampled (shortest-path BC), or 3) increase the error tolerance (current-flow BC).
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