# Network CalculationΒΆ

**parallel workers**: number of workers used for parallel computing.**filetype**: files in the filetype will be searched in input directories.**data dir**: directory where all**.txt*correlation matrix results are stored.**matrix type**:**raw value**: use raw value to construct binary matrix.**absolute value**: use absolute value to construct binary matrix.

**intensity threshold**: vector of thresholds for matrix intensity. e.g. correlation coefficient**thresholds of sparsity**: a vector of sparsity threshold, for each element, threshold the input matrix using the fraction of the matrix’s largest number of connection n*(n+1)/2;**minimum spanning tree**: a process to avoid unconnected network. To label the backbone of the network’s nodes.**matrix type**: binarized and weighted network. The binarized networks comes from thresholded input matrics, while the weighted network comes from a dot product operation of binarized network and the original network.**Network properies**: a panel to select network properties. In the option panel, (*) means the calculation of the property is slow.**out dir**: output directory for saving results.**zero value in clustering coefficient**: if the network is connected in a way (e.g. Hamilton path) that neighbour nodes are not connected; or the current node has only one neighbour node.**Inf in small worldness**: The small-worldness is calculated as real-network / random-network, and in real and random case, small-worldness is calculated as clustering coefficient/shortest-path length. If the mean clustering coefficient of the random-network is zero, then the small-worldness of random-network is zero, and it will cause the real-network / random-network to be Inf(any non-zero divided by 0). The solution is set smaller thresholds that avaliable for all subjects.

**Buttons**:**S**: Save parameters of the current panel to a**.mat*file. The**.mat*can be further loaded for the panel or be used in a script processing.**L**: Load parameters from**.mat*for the current panel.**?**: Help information.