CN107623594A - A kind of three-dimensional level network topology method for visualizing of geographical location information constraint - Google Patents
A kind of three-dimensional level network topology method for visualizing of geographical location information constraint Download PDFInfo
- Publication number
- CN107623594A CN107623594A CN201710778028.1A CN201710778028A CN107623594A CN 107623594 A CN107623594 A CN 107623594A CN 201710778028 A CN201710778028 A CN 201710778028A CN 107623594 A CN107623594 A CN 107623594A
- Authority
- CN
- China
- Prior art keywords
- node
- mrow
- msub
- information
- nodes
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Landscapes
- Processing Or Creating Images (AREA)
Abstract
The invention discloses a kind of three-dimensional level network topology method for visualizing of geographical location information constraint, comprise the following steps：S1, node data and relation data to input pre-process, and cluster out the node corporations associated with diverse geographic location restricted information node；S2：Network node is classified according to importance, and result is carried out to the mapping of third dimension information；S3：Three-dimensional layout is carried out to all-network node with reference to the three-dimensional information of mapping and the division of local geographic area；S4：Carry out the side binding of three dimensions；S5：Adjustment exports the three-dimensional information data of real complex network topologies position, realizes visualization.The present invention has the characteristics of logic placement and physical layout concurrently, the scope of specific geographic information node can be quickly found out, different range of nodes can be set according to different degree of restriction, so as to realize that the node location of more precision visualizes feature, the structural information of network is also more truly reflected while attractive in appearance.
Description
Technical field
The present invention relates to a kind of three-dimensional level network topology method for visualizing of geographical location information constraint.
Background technology
With the rise of internet, diversification is also increasingly goed deep into the research to network in recent years.From internet to traffic
Networking, from citation network to bio-networks, from brain network to various social relation networks, increasing subject and using quilt
Bring network this big field category into.But with the continuous progress of science and technology, information overload is also following, such as
In the epoch of modern this " big data ", substantial amounts of relation data network size is increasing, and traditional document representation method is not
Data research person must be made quickly and accurately to understand and analyze the structural information of a network, at this moment using computer graphics and
The visualization technique that image processing techniques becomes data topological diagram can but allow data research person to observe network at a glance
Overall condition and any minor structure details.
Visual concept is to be proposed by American science foundation (NSF) in a seminar in October, 1986 earliest
, the theory and method occurred at that time is uniformly classified as " scientific visualization ".Thereafter there is another data visualization again
Branch --- " information visualization ", after 21 century under the promotion of the fast development of computer graphics, generating again can
Depending on the wider range of concept such as analytics.Visualization technique relate to numerous fields, and such as computer graphics, data mining are led
It domain, can well help it is found that many key properties that data, information are included, and carry out more high-level points
Analysis.
Network visualization is a research branch in visualization field, is mainly converted into abstract network data intuitively
Image, wherein network topology visualization is an important behaviour mode in network visualization branch, and it is by network topology
It is combined with visualization and with computer graphics and the principle and method of other graphics, large scale text data is changed
Into the form of topological diagram picture, by network topology people can be allowed intuitively to obtain the structural information of current network.As network is believed
The scale of breath becomes big, and the concept of complex network is arisen at the historic moment.Complex network is corresponding to the live network being directed in real world
And come, narrowly see, the circuit of each operator is accessed in each area from the main frame of ordinary individual to the routing node of community
A sufficiently complex and unconspicuous complex network of rule is constituted simultaneously.From the point of view of more greatly, city and city, area
Contacted with regional or even interstate network abstraction, more constitute a world-class complex networks system.This
Bring one it is huge the problem of：Modern tool how is made full use of to go more clearly to show the magnanimity of such a multidimensional property
The complex networks system that data are formed, and the information fully in excavation system.
Traditional network visualization, the complexity of network is reduced using community detecting algorithm on data prediction, then
Carry out visual topological layout.The method of general main flow is visualized mainly for the logic placement of node.When to small rule
When lay wire network is visualized, this classic algorithm is directly guided using power.After network size complicates, current does
Method is typically all to carry out hierarchical clustering layout to large-scale complex network, and large complicated network reduction is compressed into several different layers
Secondary network area, carry out visualization further according to level and show.Its processing procedure is sufficiently complex, and great deal of nodes and side are easily made
Into blocking and overlapping situation.
The content of the invention
, will it is an object of the invention to overcome the deficiencies of the prior art and provide one kind on the basis of combining geographic information
Geography information half is weakened into range constraint, can move cloth to the node of geography information limitation in certain subrange
Office, so as to reach the adjustment characteristic attractive in appearance of logic placement from part, the scope of specific geographic information node can be quickly found out
A kind of three-dimensional level network topology method for visualizing of geographical location information constraint.
The purpose of the present invention is achieved through the following technical solutions：A kind of three-dimensional level of geographical location information constraint
Network topology method for visualizing, comprises the following steps：
S1, node data and relation data to input pre-process, and cluster out and diverse geographic location restricted information
The associated node corporations of node；
S2：Network node is classified according to importance, and result is carried out to the mapping of third dimension information；
S3：Three-dimensional layout is carried out to all-network node with reference to the three-dimensional information of mapping and the division of local geographic area；
S4：Carry out the side binding of three dimensions；
S5：Adjustment exports the three-dimensional information data of real complex network topologies position, realizes visualization.
Further, the step S1 includes following sub-step：
S11, real large-scale complex network topology text data is analyzed, designed needed for actual mechanical process
The data structure wanted, the relation in data is converted into the node being actually needed and side；Read in nodal information, side information, geography
Position limitation information and node level restricted information, network topology text data is converted into substantially first in computer graphical
Element；
S12, the node for finding out geographical position restricted information, searched out by RAK label clustering algorithms close with the node
The node set of cut even, marks off corporations；Detailed process is：
S121, it is that each has one label information of node distribution of geographical position restricted information, and inquires about its adjacent segments
The label information of point；If the number of nodes of each label is identical, random is currently to have geographical position restricted information
One label of node updates；If the node of label is incomplete same, the label for selecting nodes most has geographical position as this
Put the label of the node of restricted information；
S122, by the similarities and differences of label determine corporations；In obtained corporations, comprising it is one or more initial when have
The node of geographical position restricted information, these geographical position restricted informations are saved in the geography information of current affiliated corporations.
Further, the step S2 concrete methods of realizing is：
S21, the importance attribute for obtaining node：After primary data pre-processes, obtained using PageRank algorithms
The importance attribute of all nodes in network, different levels is divided into by PageRank value by node；
S22, the third dimension coordinate mapping for carrying out node：The three dimensions for treating layout is divided, and is divided into and node layer
Consistent z coordinate layer；Then the ratio of maximum is accounted for according to PageRank value, the z coordinate of the node is arranged to corresponding proportion
Z values, i.e., the z coordinate of node is determined by following formula：
Wherein, piFor the PageRank value of i-th of node, pmaxFor the PageRank value of maximum, ziFor the z of i-th of node
Coordinate value, zmaxFor the maximum z range of setting layout.
Further, the step S21 includes following sub-step：
S211, to each one identical PageRank value of node initializing, then according to following formula to each node i
PageRank value is updated：
In formula, PR (i) represents the PageRank value of node i；α represents damping factor, and the meaning of script is according to hyperlink
The probability browsed, use for reference here, as the selected probability of node, be taken as 0.85；N (j) represents node j and linked
Nodes；B (i) original ideas represent all combinations for having chain to i, change here with coming to represent to be connected with node i or indirect phase
Node even.The meaning that this formula is set up is that the PageRank value of each node is calculated by other interdependent nodes and obtained, and can be demonstrate,proved
Bright, with not stopping iteration, final PR values can tend towards stability convergence；
After each node updates, that is, complete an iteration；The PageRank of each node tends towards stability after successive ignition
When, that is, the PageRank value for completing each node calculates；
S212, the PageRank value scope of setting, and each PageRank is counted according to the PageRank value of each node
Number of nodes in the range of value, the characteristics of increasing successively from upper strata to lower floor according to number of nodes, node is pressed into PageRank value
It is divided into different levels；Corresponding real physical equipment is exactly the host node, common routing node, Center Road of network end-point
By node etc., these hierarchical informations represent the importance of the map network node respectively, the node of core, by broken
Influence after bad to network circulation is bigger.In addition, it is also possible to which the known level attributes of the part of nodes provided are provided according to user
To obtain the importance degree of node.
Further, the step S3 includes following sub-step：
It is laid out between S31, corporations：Ignore the third dimension coordinate information of all nodes, it is fixed geographical by having in each corporations
The node of position is as central point；Spatial dimension shared by corporations is determined by calculating the ratio between number of nodes between different corporations
Volume, form a cube from center point, all nodes for belonging to same corporations with the central point will be placed on
In one cubical area, its space accounting equation below：
Wherein, VtRepresent the spatial volume that t-th of corporation occupies, VallRepresent the cumulative volume in whole three-dimensional layout region, Nt
Represent the total node number of t-th of corporation, NallRepresent the sum of all nodes；
It is laid out in S32, corporations, rational deployment is carried out to each corporations for being extracted in S1 first, due to its center (or part
Node) geography information it has been determined that the present invention agreement geography information of the fixation is expanded, expanded to whole corporations
Unified layout is carried out in the geographic range of determination again, is then placed into different nodes suitably according to the third dimension information of node
On z directions, so all nodes are seen from x, y attributes, just all become and also do not have third dimension information without geography information
Abstract free node, then each layer is laid out using planar forces guiding algorithm, detailed process is：
S321, the gravitation and repulsion for initializing node, gravitation existed only in adjacent node, and repulsion be then present in it is all
In node in addition to present node, making a concerted effort for each node is calculated；
The size and Orientation that S322, basis are made a concerted effort, adjustment of displacement is carried out to node；
S323, repeat step S321 and S322 operation, until the layout of system is stable.
Further, the step S4 concrete methods of realizing is：The topological model structure having been had built up to three dimensions
Opposite side is bound by way of being guided based on power, and detailed process is as follows：
S41, segmentation hop count m, the gravitational coefficients k for initializing sidepWith initial displacement S0；
S42, side is divided into the intersections of multiple nodes according to segmentation hop count m, wherein, the segmentation hop count of each edge is identical；
To the node of every a line, from left to right to its label；
S43, the principle guided according to power, it is attractive between the adjacent node on each side；The node on other sides according to
Order from left to right, the node of same order are attractive to the node of other side order；
Adjacent node is tried to achieve to present node p according to following formulaiAttraction Fs：
Fs=kp*||pi-1-pi||
kpGravitational coefficients in representative model, voluntarily set by user；pi-1And piThe position of two neighboring node is represented respectively
Put；
Node of other sides with sequence number is tried to achieve to the attraction F of present node according to following formulae：
piAnd qiRepresent two nodes of order identical on two sides；
Obtained with joint efforts according to following formula
S44, to each node, the resultant direction calculated along node moves S0；
S45, make m=2m, kp=kp/ 2, S0=S0/2；Return to step S42, carry out successive ignition；When iterations reaches
Customized maximum iteration, either system reaches stable or what is obtained is less than default threshold value with joint efforts, then stops changing
In generation, complete the binding on side.
Further, the step S5 concrete methods of realizing is：Whole topological diagram is manually adjusted, adjusts the wash with watercolours on side
Contaminate effect or the color size information of node；Then export finish node coordinate information, project earth model or other
In model, the three-dimensional network visualization under the level mapping of geographical location information is realized.
The beneficial effects of the invention are as follows：
1st, geography information half is weakened into range constraint, so still may be used on the basis of combining geographic information by the present invention
To move layout to the node of geography information limitation in certain subrange, so as to reach logic placement from part
Adjustment characteristic attractive in appearance, the characteristics of having logic placement and physical layout concurrently, can also be quickly found out the model of specific geographic information node
Enclose, different range of nodes can be set according to different degree of restriction, so as to realize that the node location of more precision visualizes feature,
Also the structural information of network is more truly reflected while attractive in appearance；
2nd, traditional layout is mostly the layout of 2 d plane picture, and the present invention is adjusted for the display of space three-dimensional,
The actual range of layout is adjusted according to number of nodes simultaneously, compares the method that conventional in layout only considers center, this method
More it is of practical significance for large complicated network, the architectural characteristic of complex network can be more clearly shown from piecemeal；
3rd, the present invention carries out layout optimization again using side binding to layout effect, and the tune to topology is completed from the angle on side
It is whole, and traditional network visualization layout is substantially the distributing adjustment carried out for point, the present invention is bound using traditional side
Algorithm carries out re-optimization to topology, improves the observable degree in space so that user can abandon more gibberish, intuitively
Ground receives the design feature of network topology.
Brief description of the drawings
Fig. 1 is the three-dimensional level network topology method for visualizing flow chart of the present invention；
Fig. 2 is the schematic diagram that the present embodiment has divided hierarchical information；
Fig. 3 is that the present embodiment calculates schematic diagram based on the side binding that power guides；
Fig. 4 is that the present embodiment carries out the three-dimensional hierarchical layout effect diagram after the binding of side.
Embodiment
Present invention utilizes the geographical location information of Node Contraction in Complex Networks, and compared with traditional placement algorithm, it is no longer
An only simple logic placement algorithm, while be also a physical layout algorithm；And for practical significance, now
To network topological diagram be logically shown mostly, but with a series of requirement such as strategic information, network node
Positional information also increasingly becomes everybody focus of attention, implements protection for key node and destroys, for geography information
It is to have certain requirements.Technical scheme is further illustrated below in conjunction with the accompanying drawings.
As shown in figure 1, a kind of three-dimensional level network topology method for visualizing of geographical location information constraint, including following step
Suddenly：
S1, node data and relation data to input pre-process, and cluster out and diverse geographic location restricted information
The associated node corporations of node；Specifically include following sub-step：
S11, real large-scale complex network topology text data is analyzed, designed needed for actual mechanical process
The data structure wanted, the relation in data is converted into the node being actually needed and side；Read in nodal information, side information, geography
Position limitation information and node level restricted information, network topology text data is converted into substantially first in computer graphical
Element；
S12, the node for finding out geographical position restricted information, searched out by RAK label clustering algorithms close with the node
The node set of cut even, marks off corporations；Detailed process is：
S121, it is that each has one label information of node distribution of geographical position restricted information, and inquires about its adjacent segments
The label information of point；If the number of nodes of each label is identical, random is currently to have geographical position restricted information
One label of node updates；If the node of label is incomplete same, the label for selecting nodes most has geographical position as this
Put the label of the node of restricted information；
S122, by the similarities and differences of label determine corporations；In obtained corporations, comprising it is one or more initial when have
The node of geographical position restricted information, these geographical position restricted informations are saved in the geography information of current affiliated corporations.
S2：All-network node is classified according to importance, and result is carried out to the mapping of third dimension information；Pass through
The importance attribute that processing obtains node is carried out to primary data.Then initialization mapping, layer are carried out to the three-dimensional information of node
Level is higher, and third dimension coordinate is also bigger, and a range of third dimension coordinate is occupied per one-level.Concrete methods of realizing is：
S21, the importance attribute for obtaining node：After primary data pre-processes, obtained using PageRank algorithms
The importance attribute of all nodes in network, reach the effect that similar betweenness attribute is judged, so as to reach to corporations' inside section
The effect that point is classified；Then node is divided into different levels by PageRank value；Including following sub-step：
S211, to each one identical PageRank value of node initializing, then according to following formula to each node i
PageRank value is updated：
In formula, PR (i) represents the PageRank value of node i；α represents damping factor, and the meaning of script is according to hyperlink
The probability browsed, use for reference here, as the selected probability of node, be taken as 0.85；N (j) represents node j and linked
Nodes；B (i) original ideas represent all combinations for having chain to i, change here with coming to represent to be connected with node i or indirect phase
Node even；The meaning that this formula is set up is that the PageRank value of each node is calculated by other interdependent nodes and obtained.
After each node updates, that is, complete an iteration；The PageRank of each node tends towards stability after successive ignition
When, that is, the PageRank value for completing each node calculates；
S212, the PageRank value scope of setting, and each PageRank is counted according to the PageRank value of each node
Number of nodes in the range of value, the characteristics of increasing successively from upper strata to lower floor according to number of nodes, node is pressed into PageRank value
It is divided into different levels；Corresponding real physical equipment is exactly the host node, common routing node, Center Road of network end-point
By node etc., these hierarchical informations represent the importance of the map network node respectively, the node of core, by broken
Influence after bad to network circulation is bigger.In addition, it is also possible to which the known level attributes of the part of nodes provided are provided according to user
To obtain the importance degree of node；
S22, the third dimension coordinate mapping for carrying out node：The three dimensions for treating layout is divided, and is divided into and node layer
Consistent z coordinate layer；Then the ratio of maximum is accounted for according to PageRank value, the z coordinate of the node is arranged to corresponding proportion
Z values, i.e., the z coordinate of node is determined by following formula：
Wherein, piFor the PageRank value of i-th of node, pmaxFor the PageRank value of maximum, ziFor the z of i-th of node
Coordinate value, zmaxFor the maximum z range of setting layout.
As shown in Fig. 2 the schematic diagram of hierarchical information has been divided, wherein bottom L3 node is most end in topology
The host node at end；Second layer L2 node is probably route intermediate transit point, is connected to many endpoint nodes；On first layer L1
Node be the superiors' (this embodiment assumes that be 3 layers, actual different levels is sorted out according to specific data), it is connection L3
The key node in region is not attached in layer.Apparent can be seen that can not mark off weight well only by the node number of degrees
The property wanted, as L2 layers important node is all connected to the node of L1 layers, so the weight that L1 layers interior joint is drawn by PageRank algorithms
The property wanted highest, but this conclusion can not be obtained only by the number of degrees.
S3：Three-dimensional layout is carried out to all-network node with reference to the three-dimensional information of mapping and the division of local geographic area；
Including following sub-step：
It is laid out between S31, corporations：Ignore the third dimension coordinate information of all nodes, it is fixed geographical by having in each corporations
The node of position is as central point；Spatial dimension shared by corporations is determined by calculating the ratio between number of nodes between different corporations
Volume, form a cube from center point, all nodes for belonging to same corporations with the central point will be placed on
In one cubical area, its space accounting equation below：
Wherein, VtRepresent the spatial volume that t-th of corporation occupies, VallRepresent the cumulative volume in whole three-dimensional layout region, Nt
Represent the total node number of t-th of corporation, NallRepresent the sum of all nodes；
It is laid out in S32, corporations, rational deployment is carried out to each corporations for being extracted in S1 first, due to its center (or part
Node) geography information it has been determined that the present invention agreement geography information of the fixation is expanded, expanded to whole corporations
Unified layout is carried out in the geographic range of determination again, is then placed into different nodes suitably according to the third dimension information of node
On z directions, so all nodes are seen from x, y attributes, just all become and also do not have third dimension information without geography information
Abstract free node, then each layer is laid out using planar forces guiding algorithm.Detailed process is：
S321, the gravitation and repulsion for initializing node, gravitation existed only in adjacent node, and repulsion be then present in it is all
In node in addition to present node, making a concerted effort for each node is calculated；
The size and Orientation that S322, basis are made a concerted effort, adjustment of displacement is carried out to node；
S323, repeat step S321 and S322 operation, until the layout of system is stable.
After the completion of layout, third dimension information is reasonably finely tuned again, so that it is determined that each corporations' inner topology
Position.In other words, first all nodes are laid out according to the guiding of two-dimentional power, then the hierarchical classification information obtained by S2
Different z values spaces arrive into different node liftings, lifted from two-dimentional to three-dimensional, as shown in Fig. 2 by be originally plane layout root
It is laid out again according to the importance obtained by S2, is placed into the level space each belonged to according to its third dimension information respectively
Scope, complete layout.
S4：Carry out the side binding of three dimensions；Concrete methods of realizing is：The topological model having been had built up to three dimensions
Structure opposite side by way of being guided based on power is bound, and detailed process is as follows：
S41, segmentation hop count m, the gravitational coefficients k for initializing sidepWith initial displacement S0；
S42, side is divided into the intersections of multiple nodes according to segmentation hop count m, wherein, the segmentation hop count of each edge is identical；
To the node of every a line, from left to right to its label；
S43, the principle guided according to power, it is attractive between the adjacent node on each side；The node on other sides according to
Order from left to right, the node of same order are attractive to the node of other side order；
Adjacent node is tried to achieve to present node p according to following formulaiAttraction Fs：
Fs=kp*||pi-1-pi||
kpGravitational coefficients in representative model, voluntarily set by user；pi-1And piThe position of two neighboring node is represented respectively
Put；
Node of other sides with sequence number is tried to achieve to the attraction F of present node according to following formulae：
piAnd qiRepresent two nodes of order identical on two sides；
Obtained with joint efforts according to following formula
S44, to each node, the resultant direction calculated along node moves S0；
S45, make m=2m, kp=kp/ 2, S0=S0/2；Return to step S42, carry out successive ignition；When iterations reaches
Customized maximum iteration, either system reaches stable or what is obtained is less than default threshold value with joint efforts, then stops changing
In generation, complete the binding on side.
The side binding based on power guiding that the present embodiment obtains calculates as shown in Figure 3, it is noted that for p2For, same
Auxiliary magnet on side only has p1And p3It is attractive to its.And the auxiliary magnet in different edge, just there is suction between the node of same sequence number
Gravitation, such as q2To p2It is attractive, and be unattractive between the different not node on same side of other sequence numbers.
After the completion of, for the degree of corner, obtaining the scrambling of whole figure will be reduced, while clearance spaces are improved, this
The effect of visualization on side is improved, while also retains the essential information of network topology structure as far as possible.The design sketch finally obtained
Should be similar to Figure 4, Fig. 4 is the schematic diagram of base point, and actual graphical is in the case where counting out and its being huge, side binding
Caused vision definition can be significantly better than before binding.
S5：Adjustment exports the three-dimensional information data of real complex network topologies position, realizes visualization；Specific implementation side
Method is：Whole topological diagram is manually adjusted, the rendering effect on side or the color size information of node are adjusted, to react not
The node of same level, or size of the different corporations of reaction etc.；Then finish node coordinate information is exported, projects earth mould
In type or other models, the three-dimensional network visualization under the level mapping of geographical location information is realized.
One of ordinary skill in the art will be appreciated that embodiment described here is to aid in reader and understands this hair
Bright principle, it should be understood that protection scope of the present invention is not limited to such especially statement and embodiment.This area
Those of ordinary skill can make according to these technical inspirations disclosed by the invention various does not depart from the other each of essence of the invention
The specific deformation of kind and combination, these deform and combined still within the scope of the present invention.
Claims (7)
1. a kind of three-dimensional level network topology method for visualizing of geographical location information constraint, it is characterised in that including following step
Suddenly：
S1, node data and relation data to input pre-process, and cluster out and diverse geographic location restricted information node
Associated node corporations；
S2：Network node is classified according to importance, and result is carried out to the mapping of third dimension information；
S3：Three-dimensional layout is carried out to all-network node with reference to the three-dimensional information of mapping and the division of local geographic area；
S4：Carry out the side binding of three dimensions；
S5：Adjustment exports the three-dimensional information data of real complex network topologies position, realizes visualization.
2. the three-dimensional level network topology method for visualizing of geographical location information constraint according to claim 1, its feature
It is, the step S1 includes following sub-step：
S11, real large-scale complex network topology text data is analyzed, designed required in actual mechanical process
Data structure, the relation in data is converted into the node being actually needed and side；Read in nodal information, side information, geographical position
Restricted information and node level restricted information, basic element network topology text data being converted into computer graphical；
S12, the node for finding out geographical position restricted information, searched out and the close phase of the node by RAK label clustering algorithms
Node set even, marks off corporations；Detailed process is：
S121, it is that each has one label information of node distribution of geographical position restricted information, and inquires about its adjacent node
Label information；If the number of nodes of each label is identical, random is the node for currently having geographical position restricted information
Update a label；If the node of label is incomplete same, the label for selecting nodes most has geographical position limit as this
The label of the node of information processed；
S122, by the similarities and differences of label determine corporations；In obtained corporations, comprising it is one or more initial when there is geography
The node of position limitation information, these geographical position restricted informations are saved in the geography information of current affiliated corporations.
3. the three-dimensional level network topology method for visualizing of geographical location information constraint according to claim 2, its feature
It is, the step S2 concrete methods of realizing is：
S21, the importance attribute for obtaining node：After primary data pre-processes, network is obtained using PageRank algorithms
In all nodes importance attribute, node is divided into different levels by PageRank value；
S22, the third dimension coordinate mapping for carrying out node：The three dimensions for treating layout is divided, and is divided into consistent with node layer
Z coordinate layer；Then the ratio of maximum is accounted for according to PageRank value, the z coordinate of the node is arranged to the z of corresponding proportion
Value, i.e., the z coordinate of node is determined by following formula：
<mrow>
<mfrac>
<msub>
<mi>p</mi>
<mi>i</mi>
</msub>
<msub>
<mi>p</mi>
<mi>max</mi>
</msub>
</mfrac>
<mo>=</mo>
<mfrac>
<msub>
<mi>z</mi>
<mi>i</mi>
</msub>
<msub>
<mi>z</mi>
<mi>max</mi>
</msub>
</mfrac>
</mrow>
Wherein, piFor the PageRank value of i-th of node, pmaxFor the PageRank value of maximum, ziFor i-th of node
Z coordinate value, zmaxFor the maximum z range of setting layout.
4. the three-dimensional level network topology method for visualizing of geographical location information constraint according to claim 3, its feature
It is, the step S21 includes following sub-step：
S211, to each one identical PageRank value of node initializing, then according to following formula to each node i
PageRank value is updated：
<mrow>
<mi>P</mi>
<mi>R</mi>
<mrow>
<mo>(</mo>
<mi>i</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mi>&alpha;</mi>
<mo>*</mo>
<munder>
<mo>&Sigma;</mo>
<mrow>
<mi>j</mi>
<mo>&Element;</mo>
<mi>B</mi>
<mrow>
<mo>(</mo>
<mi>i</mi>
<mo>)</mo>
</mrow>
</mrow>
</munder>
<mfrac>
<mrow>
<mi>P</mi>
<mi>R</mi>
<mrow>
<mo>(</mo>
<mi>j</mi>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<mi>N</mi>
<mrow>
<mo>(</mo>
<mi>j</mi>
<mo>)</mo>
</mrow>
</mrow>
</mfrac>
<mo>+</mo>
<mfrac>
<mrow>
<mo>(</mo>
<mn>1</mn>
<mo>-</mo>
<mi>&alpha;</mi>
<mo>)</mo>
</mrow>
<mi>n</mi>
</mfrac>
</mrow>
In formula, PR (i) represents the PageRank value of node i；α represents damping factor, as the selected probability of node, is taken as
0.85；N (j) represents the nodes that node j is linked；B (i) represents the node for being connected or being indirectly connected with node i；
After each node updates, that is, complete an iteration；When the PageRank of each node after successive ignition tends towards stability, i.e.,
The PageRank value for completing each node calculates；
S212, the PageRank value scope of setting, and each PageRank value model is counted according to the PageRank value of each node
Interior number of nodes is enclosed, the characteristics of being increased successively from upper strata to lower floor according to number of nodes, node is split by PageRank value
For different levels.
5. the three-dimensional level network topology method for visualizing of geographical location information constraint according to claim 3, its feature
It is, the step S3 includes following sub-step：
It is laid out between S31, corporations：Ignore the third dimension coordinate information of all nodes, will there is fixed geographical position in each corporations
Node as central point；The body of spatial dimension shared by corporations is determined by calculating the ratio between number of nodes between different corporations
Product, a cube is formed from center point, all nodes for belonging to same corporations with the central point will be placed on one
In cubical area, its space accounting equation below：
<mrow>
<mfrac>
<msub>
<mi>V</mi>
<mi>t</mi>
</msub>
<msub>
<mi>V</mi>
<mrow>
<mi>a</mi>
<mi>l</mi>
<mi>l</mi>
</mrow>
</msub>
</mfrac>
<mo>=</mo>
<mfrac>
<msub>
<mi>N</mi>
<mi>t</mi>
</msub>
<msub>
<mi>N</mi>
<mrow>
<mi>a</mi>
<mi>l</mi>
<mi>l</mi>
</mrow>
</msub>
</mfrac>
</mrow>
Wherein, VtRepresent the spatial volume that t-th of corporation occupies, VallRepresent the cumulative volume in whole three-dimensional layout region, NtRepresent
The total node number of t-th of corporation, NallRepresent the sum of all nodes；
It is laid out in S32, corporations, detailed process is：
S321, the gravitation and repulsion for initializing node, gravitation are existed only in adjacent node, and repulsion is then present in all remove and worked as
In node beyond front nodal point, making a concerted effort for each node is calculated；
The size and Orientation that S322, basis are made a concerted effort, adjustment of displacement is carried out to node；
S323, repeat step S321 and S322 operation, until the layout of system is stable.
6. the three-dimensional level network topology method for visualizing of geographical location information constraint according to claim 5, its feature
It is, the step S4 concrete methods of realizing is：The topological model structure having been had built up to three dimensions based on power by being led
The mode opposite side drawn is bound, and detailed process is as follows：
S41, segmentation hop count m, the gravitational coefficients k for initializing sidepWith initial displacement S0；
S42, side is divided into the intersections of multiple nodes according to segmentation hop count m, wherein, the segmentation hop count of each edge is identical；To every
The node of a line, from left to right to its label；
S43, the principle guided according to power, it is attractive between the adjacent node on each side；The node on other sides is according to from a left side
It is attractive to the node of other side order to the order on the right side, the node of same order；
Adjacent node is tried to achieve to present node p according to following formulaiAttraction Fs：
Fs=kp*||pi-1-pi||
kpGravitational coefficients in representative model, voluntarily set by user；pi-1And piThe position of two neighboring node is represented respectively；
Node of other sides with sequence number is tried to achieve to the attraction F of present node according to following formulae：
<mrow>
<msub>
<mi>F</mi>
<mi>e</mi>
</msub>
<mo>=</mo>
<mfrac>
<mn>1</mn>
<mrow>
<mo>|</mo>
<mo>|</mo>
<msub>
<mi>p</mi>
<mi>i</mi>
</msub>
<mo>-</mo>
<msub>
<mi>q</mi>
<mi>i</mi>
</msub>
<mo>|</mo>
<mo>|</mo>
</mrow>
</mfrac>
</mrow>
piAnd qiRepresent two nodes of order identical on two sides；
Obtained with joint efforts according to following formula
<mrow>
<msub>
<mi>F</mi>
<msub>
<mi>p</mi>
<mi>i</mi>
</msub>
</msub>
<mo>=</mo>
<msub>
<mi>k</mi>
<mi>p</mi>
</msub>
<mo>*</mo>
<mrow>
<mo>(</mo>
<mo>|</mo>
<mo>|</mo>
<msub>
<mi>p</mi>
<mrow>
<mi>i</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msub>
<mo>-</mo>
<msub>
<mi>p</mi>
<mi>i</mi>
</msub>
<mo>|</mo>
<mo>|</mo>
<mo>+</mo>
<mo>|</mo>
<mo>|</mo>
<msub>
<mi>p</mi>
<mi>i</mi>
</msub>
<mo>-</mo>
<msub>
<mi>p</mi>
<mrow>
<mi>i</mi>
<mo>+</mo>
<mn>1</mn>
</mrow>
</msub>
<mo>|</mo>
<mo>|</mo>
<mo>)</mo>
</mrow>
<mo>+</mo>
<munder>
<mo>&Sigma;</mo>
<mrow>
<mi>O</mi>
<mo>&Element;</mo>
<mi>E</mi>
</mrow>
</munder>
<mfrac>
<mn>1</mn>
<mrow>
<mo>|</mo>
<mo>|</mo>
<msub>
<mi>p</mi>
<mi>i</mi>
</msub>
<mo>-</mo>
<msub>
<mi>q</mi>
<mi>i</mi>
</msub>
<mo>|</mo>
<mo>|</mo>
</mrow>
</mfrac>
<mo>;</mo>
</mrow>
S44, to each node, the resultant direction calculated along node moves S0；
S45, make m=2m, kp=kp/ 2, S0=S0/2；Return to step S42, carry out successive ignition；When iterations reaches self-defined
Maximum iteration, either system reaches stable or making a concerted effort of obtaining is less than default threshold value, then stops iteration, completion
The binding on side.
7. the three-dimensional level network topology method for visualizing of geographical location information constraint according to claim 1, its feature
It is, the step S5 concrete methods of realizing is：Whole topological diagram is manually adjusted, adjusts the rendering effect or section on side
The color size information of point；Then finish node coordinate information is exported, is projected in earth model or other models, realizes ground
Manage the three-dimensional network visualization under the level mapping of positional information.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710778028.1A CN107623594A (en) | 2017-09-01 | 2017-09-01 | A kind of three-dimensional level network topology method for visualizing of geographical location information constraint |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710778028.1A CN107623594A (en) | 2017-09-01 | 2017-09-01 | A kind of three-dimensional level network topology method for visualizing of geographical location information constraint |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN107623594A true CN107623594A (en) | 2018-01-23 |
Family
ID=61088236
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710778028.1A Pending CN107623594A (en) | 2017-09-01 | 2017-09-01 | A kind of three-dimensional level network topology method for visualizing of geographical location information constraint |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107623594A (en) |
Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109120465A (en) * | 2018-10-23 | 2019-01-01 | 中国人民解放军战略支援部队信息工程大学 | Target area network topology division methods based on die body |
| CN109241224A (en) * | 2018-08-24 | 2019-01-18 | 武汉中地数码科技有限公司 | A kind of geographical big data method for visualizing and system based on topological correlation |
| CN109245921A (en) * | 2018-08-24 | 2019-01-18 | 电子科技大学 | A kind of network topology structure method for visualizing in irregular area |
| CN109255722A (en) * | 2018-08-22 | 2019-01-22 | 电子科技大学 | A kind of complex network step analysis system and method based on neighbours' topology |
| CN109410314A (en) * | 2018-04-28 | 2019-03-01 | 武汉思普崚技术有限公司 | The method and device of topological structure dynamic rendering based on three-dimensional space |
| CN109960766A (en) * | 2019-01-07 | 2019-07-02 | 西南科技大学 | For the visualization presentation of network structure data and exchange method under immersive environment |
| CN109962811A (en) * | 2019-01-07 | 2019-07-02 | 西南科技大学 | A kind of increment type stable state layout method for time-varying network data |
| CN110213091A (en) * | 2019-05-23 | 2019-09-06 | 复旦大学 | Automate Topology Algorithm |
| CN111046516A (en) * | 2019-06-06 | 2020-04-21 | 哈尔滨安天科技集团股份有限公司 | Three-dimensional layout method and device for complex network topology and storage equipment |
| CN111079058A (en) * | 2019-12-16 | 2020-04-28 | 武汉大学 | Network node representation method and device based on node importance |
| WO2020168682A1 (en) * | 2019-02-21 | 2020-08-27 | 清华大学 | Network space coordinate system creation method and apparatus based on autonomous system |
| CN113536663A (en) * | 2021-06-17 | 2021-10-22 | 山东大学 | Graph visualization method and system based on ring constraint and stress model |
| CN115241976A (en) * | 2022-07-27 | 2022-10-25 | 国网江苏省电力有限公司电力科学研究院 | Power distribution network monitoring data visualization method, computer equipment and storage medium |
| CN115964546A (en) * | 2023-01-06 | 2023-04-14 | 中国海洋大学 | Vortex migration channel extraction and visualization method based on edge binding |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102202012A (en) * | 2011-05-30 | 2011-09-28 | 中国人民解放军总参谋部第五十四研究所 | Group dividing method and system of communication network |
| CN103793525A (en) * | 2014-02-21 | 2014-05-14 | 江苏唯实科技有限公司 | MapReduce model graph node authority value calculation method based on local iteration |
| CN104008165A (en) * | 2014-05-29 | 2014-08-27 | 华东师范大学 | Club detecting method based on network topology and node attribute |
| CN105101093A (en) * | 2015-09-10 | 2015-11-25 | 电子科技大学 | Network topology visualization method with respect to geographical location information |
| CN106934422A (en) * | 2017-03-16 | 2017-07-07 | 浙江工业大学 | Hierarchical visual abstraction method based on improved force guide diagram layout |
-
2017
- 2017-09-01 CN CN201710778028.1A patent/CN107623594A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102202012A (en) * | 2011-05-30 | 2011-09-28 | 中国人民解放军总参谋部第五十四研究所 | Group dividing method and system of communication network |
| CN103793525A (en) * | 2014-02-21 | 2014-05-14 | 江苏唯实科技有限公司 | MapReduce model graph node authority value calculation method based on local iteration |
| CN104008165A (en) * | 2014-05-29 | 2014-08-27 | 华东师范大学 | Club detecting method based on network topology and node attribute |
| CN105101093A (en) * | 2015-09-10 | 2015-11-25 | 电子科技大学 | Network topology visualization method with respect to geographical location information |
| CN106934422A (en) * | 2017-03-16 | 2017-07-07 | 浙江工业大学 | Hierarchical visual abstraction method based on improved force guide diagram layout |
Non-Patent Citations (4)
| Title |
|---|
| DANNY HOLTEN等: ""Force‐Directed Edge Bundling for Graph Visualization"", 《COMPUTER GRAPHICS FORUM》 * |
| 何逍: "复杂网络的可视化显示", 《中国优秀硕士学位论文全文数据库 基础科学辑》 * |
| 张倬: "基于地理位置信息约束的网络拓扑可视化方法研究", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
| 韩路: "基于核心图的标签传播社团划分算法", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
Cited By (21)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109410314A (en) * | 2018-04-28 | 2019-03-01 | 武汉思普崚技术有限公司 | The method and device of topological structure dynamic rendering based on three-dimensional space |
| CN109255722A (en) * | 2018-08-22 | 2019-01-22 | 电子科技大学 | A kind of complex network step analysis system and method based on neighbours' topology |
| CN109255722B (en) * | 2018-08-22 | 2020-09-18 | 电子科技大学 | Complex network hierarchical analysis system and method based on neighbor topology |
| CN109241224A (en) * | 2018-08-24 | 2019-01-18 | 武汉中地数码科技有限公司 | A kind of geographical big data method for visualizing and system based on topological correlation |
| CN109245921A (en) * | 2018-08-24 | 2019-01-18 | 电子科技大学 | A kind of network topology structure method for visualizing in irregular area |
| CN109120465A (en) * | 2018-10-23 | 2019-01-01 | 中国人民解放军战略支援部队信息工程大学 | Target area network topology division methods based on die body |
| CN109120465B (en) * | 2018-10-23 | 2021-07-02 | 中国人民解放军战略支援部队信息工程大学 | Target area network topology division method based on motif |
| CN109960766A (en) * | 2019-01-07 | 2019-07-02 | 西南科技大学 | For the visualization presentation of network structure data and exchange method under immersive environment |
| CN109962811A (en) * | 2019-01-07 | 2019-07-02 | 西南科技大学 | A kind of increment type stable state layout method for time-varying network data |
| WO2020168682A1 (en) * | 2019-02-21 | 2020-08-27 | 清华大学 | Network space coordinate system creation method and apparatus based on autonomous system |
| US11943249B2 (en) | 2019-02-21 | 2024-03-26 | Tsinghua University | Cyberspace coordinate system creation method and apparatus based on autonomous system |
| CN110213091B (en) * | 2019-05-23 | 2021-06-04 | 复旦大学 | Automatic topological method |
| CN110213091A (en) * | 2019-05-23 | 2019-09-06 | 复旦大学 | Automate Topology Algorithm |
| CN111046516A (en) * | 2019-06-06 | 2020-04-21 | 哈尔滨安天科技集团股份有限公司 | Three-dimensional layout method and device for complex network topology and storage equipment |
| CN111046516B (en) * | 2019-06-06 | 2023-11-10 | 安天科技集团股份有限公司 | Three-dimensional layout method and device for complex network topology and storage equipment |
| CN111079058A (en) * | 2019-12-16 | 2020-04-28 | 武汉大学 | Network node representation method and device based on node importance |
| CN113536663A (en) * | 2021-06-17 | 2021-10-22 | 山东大学 | Graph visualization method and system based on ring constraint and stress model |
| CN113536663B (en) * | 2021-06-17 | 2023-08-25 | 山东大学 | Graph visualization method and system based on ring constraint and stress model |
| CN115241976A (en) * | 2022-07-27 | 2022-10-25 | 国网江苏省电力有限公司电力科学研究院 | Power distribution network monitoring data visualization method, computer equipment and storage medium |
| CN115241976B (en) * | 2022-07-27 | 2023-11-17 | 国网江苏省电力有限公司电力科学研究院 | Power distribution network monitoring data visualization method, computer equipment and storage medium |
| CN115964546A (en) * | 2023-01-06 | 2023-04-14 | 中国海洋大学 | Vortex migration channel extraction and visualization method based on edge binding |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107623594A (en) | A kind of three-dimensional level network topology method for visualizing of geographical location information constraint | |
| US10083517B2 (en) | Segmentation of an image based on color and color differences | |
| Jünger et al. | Graph drawing software | |
| Vanegas et al. | Procedural generation of parcels in urban modeling | |
| Bahrehmand et al. | Optimizing layout using spatial quality metrics and user preferences | |
| Tamassia et al. | Automatic graph drawing and readability of diagrams | |
| CN115269751B (en) | Method for constructing geographic entity space-time knowledge graph ontology library | |
| Liu et al. | Contextual fuzzy cognitive map for decision support in geographic information systems | |
| Frishman et al. | Multi-level graph layout on the GPU | |
| US8605092B2 (en) | Method and apparatus of animation planning for a dynamic graph | |
| CN109711018A (en) | A kind of Size Dwelling Design method of 2 d-to-3 d | |
| CN108759840A (en) | A kind of indoor and outdoor integrated three-dimensional navigation path planning method | |
| CN103309944B (en) | A kind of cultural symbol method realizing map library management | |
| CN108052580A (en) | A kind of space-time data immersion visual analysis method based on multilayer related network | |
| CN104463948A (en) | Seamless visualization method for three-dimensional virtual reality system and geographic information system | |
| Gronemann et al. | Drawing clustered graphs as topographic maps | |
| Wu et al. | A contour tree based visualization for exploring data with uncertainty | |
| CN107730536A (en) | A kind of high speed correlation filtering object tracking method based on depth characteristic | |
| CN103838829A (en) | Raster vectorization system based on hierarchical boundary-topology search model | |
| Whiting et al. | Topology of urban environments | |
| CN103678593B (en) | A kind of interactive space scene search method described based on spatial scene sketch | |
| CN106709171A (en) | Repeat mode discovery-based printed pattern generation method | |
| Xu et al. | Blockplanner: City block generation with vectorized graph representation | |
| CN104036013B (en) | The formal notion computational methods of blog data based on attribute topology | |
| CN113822232A (en) | Pyramid attention-based scene recognition method, training method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20180123 |