CN108959420A - The method of spatio-temporal data visualization interface rapidly locating - Google Patents
The method of spatio-temporal data visualization interface rapidly locating Download PDFInfo
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- CN108959420A CN108959420A CN201810589561.8A CN201810589561A CN108959420A CN 108959420 A CN108959420 A CN 108959420A CN 201810589561 A CN201810589561 A CN 201810589561A CN 108959420 A CN108959420 A CN 108959420A
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Abstract
The present invention relates to a kind of methods of spatio-temporal data visualization interface rapidly locating, comprising: is stored in database after wind profile instrument data are carried out data prediction；Data are read from database, data are subjected to structured storage to locally；Step 3: space-time data being realized into data visualization with drafting instrument；Local index cache set is established, according to the index to be checked being likely to occur, the Spatial Dimension index domain that normal data is concentrated carries out " sorting out again " storage, establishes the mapping relations of index with evidence to be fetched；Inquiry request is received from visualization interface, inquiry request is converted to the search index of preset format.
Description
Technical field
The method of spatio-temporal data visualization interface rapidly locating.
Background technique
Under the background of big data era, the data of each production field are all in that magnanimity formula increases, especially marine hydrology
Meteorological field.In face of the data of these magnanimity, the processing being standardized and storage are first had to, then in certain circumstances, is needed
These data are intuitively visualized, this to data important feature it is effective presentation, the announcement of objective law, section
The raising etc. for grinding development efficiency all has great importance.Thus need to find quick, efficient data in R&D process
Querying method, in this way, can just effectively improve visualization experience, editor's data are more smooth, quick.In previous research and development technology,
Under the premise of reduction is interacted with database, local data is often directly traversed, to search the data for needing to inquire.This side
The inquiry data of formula have the disadvantage that (1) this inquiry mode has certain advantage in the inquiry of small data quantity, in data
Amount is when becoming larger, and inquiry velocity often obvious slack-off, inefficiency is not able to satisfy the requirement of mass inquiry.(2) it is unfavorable for standard
Determine the specified data that bit manipulation person needs.(3) the local operation resource of waste.
At present in the processing of maritime meteorology survey data, wind profile instrument observational data is very important data, for grinding
The wind speed rule for studying carefully atmospheric boundary layer is significant.But the research for maritime meteorology survey data processing system, both at home and abroad
It is not perfect, in addition the visualization processing requirement to mass data, a set of efficiently and accurately, the query scheme of low time delay and its data
Processing system becomes the hot and difficult issue of current research.
Summary of the invention
The object of the present invention is to provide a kind of methods of spatio-temporal data visualization interface rapidly locating, utilize number
According to the convenience of structuring, specific data is quickly searched by assigned indexes, guarantees the high efficiency in space-time data analysis link
And real-time, technical solution are as follows:
A kind of method of spatio-temporal data visualization interface rapidly locating, includes the following steps
Step 1: being stored in database after wind profile instrument data are carried out data prediction；
Step 2: data are read from database, it is by data progress structured storage to local, i.e., special according to the structure of data
Sign carries out indexing processing and calculation processing: visualization interface can be divided into the one-dimensional space, two-dimensional space, three-dimensional space, more higher-dimension
Data be often mapped to two dimension or three bit spaces shown, data are carried out according to particular display environment to index place
Reason, the format after data processing are standard data set format { Si(I, D) | i=1,2 ..., I representation space dimension index
Domain, D indicate the data field under the Spatial dimensionality.The data of unified format are saved among local set later；
Step 3: space-time data being realized into data visualization with drafting instrument, shows the velocity vector of each layer data of measuring point
Situation, the data shown in graphics display area, VELOCITY DISTRIBUTION show that arrow direction represents wind direction, arrow in form of arrows
Size represents wind speed, and each column of the data after visualization are all a data samples, and every a line is that the subitem of sample data becomes
Amount, variable can be the characteristic an of data sample or the set of the physical quantity measured under specific spacetime coordinate, visualize
Interface is vector sectional view, and display format is tabular form, and visualization interface at this time is that data can inquire state；
Step 4: local index cache set Q, Q ∈ { I } is established, according to the index to be checked being likely to occur, by normal data
The Spatial Dimension index domain of concentration carries out " sorting out again " storage, establishes the mapping relations of index with evidence to be fetched；
Step 5: receiving inquiry request from visualization interface, inquiry request is converted to the search index Q of preset format
(xi)；
Step 6: if local standard data set there are data and indexed cache collection be sky, need to carry out step 4 point
Generic operation, according to the inquiry request Q (x of step 5i), if including currently Q (x in index cache seti), then the number mapped
It is extracted according to collection；
Step 7: the data set extracted in step 6 being navigated into current display column, net is recalculated according to the component of data
The color of vector arrows and deflection direction on lattice point.
The method of spatio-temporal data visualization interface rapidly locating proposed by the invention has fully considered ocean
With ductility when background data base interactive operation during the multi-dimensional nature and magnanimity of data, and research and development visualization model, simulate
Distributed storage data thought, reduces the feedback time of data query, optimizes the user experience of visualization interface.
Detailed description of the invention
Fig. 1 flow diagram
Fig. 2 data prediction flow diagram
Fig. 3 data standard file
Fig. 4 data loading
Fig. 5 data show interface
Fig. 6 simulation comparison
Fig. 7 data list
Specific embodiment
It is an object of the invention to overcome the above-mentioned deficiency of existing inquiry mode, simulation combines the number of Distributed Storage
According to access high efficiency, and the improved method for sufficiently examining inquiry mode on this basis.Spatio-temporal data visualization interface is quick
The method of location data is specifically exactly simulation distribution formula storage thought, local data progress " classification " is stored again, then
According to specified " index ", batch query specifies data in the data after classification, so that data query is more efficient, quasi-
Really, the feedback time of data query is reduced, scalability is improved, optimizes the user experience of visualization interface.Specific step is as follows:
1, the quality control and pretreatment of data
Data loading should include the quality control and preprocessing module of data before, specifically,
Step 1: original observed data to be carried out to the conversion of data format according to preparatory data storage scheme；
Step 2: the data after conversion are carried out quality control treatments according to demarcating file；
Step 3: processing such as the abnormality value removing of progress data, noise jamming are eliminated, sensor lag is corrected；
Step 4: judge whether data are qualified, and if unqualified return to second and third step data processing again, if qualified,
Carry out the 5th step；
Step 5: generating normative document and data loading.
2, reading data is to memory
Visualized data needs the physical oceanography element of initial data carrying out calculation processing, forms the new change that can be shown
Amount.The potential feature of data and mode can be more clearly from expressed by new variables data, can be convenient observer preferably
Observe data.So needing to carry out calculation processing to all data by preset rules after reading initial data, specifically
Computation processing method depends on the structure feature of specific oceanographic data and specific figure shows interface.In the same of data processing
When, it needs to carry out filling index according to data processing method, guarantees the uniqueness of every data and the relevance of other data.
3, Image Rendering
Oceanographic data displaying is ever-changing, and this method is the velocity vector situation based on each layer data for showing measuring point, speed
Degree vector is the numerical value that each survey layer data east component and speed north component calculate after superposition.It is shown in graphics display area
Show that the data after data processing, VELOCITY DISTRIBUTION are shown in form of arrows, arrow direction represents wind direction, and arrow size represents wind
Speed.In visuals, measuring point data to be shown can be controlled on figure, it, can be from figure when finding that a certain data are unreasonable
The survey layer data is directly deleted in shape.
Each column of data after visualization are all a data samples, and every a line is the subitem variable of sample data, are become
Amount can be the characteristic an of data sample or the set of the physical quantity measured under specific spacetime coordinate, to network inputs sample
This basic demand is each sample variables set having the same.The visualization interface is vector sectional view, display format
For tabular form, so the visualization interface dimension in the first step is two dimension.
In order to improve drafting speed, the drafting of vector arrows can be stored in display list in advance, every time on mesh point
It need to only show that list can realize drafting when showing vector arrows.Specific step is as follows:
Step 1: by the drafting deposit display list of vector arrows；
Step 2: handling mesh point one by one, vector arrows on the mesh point are calculated according to the component of gridden data
Color and deflection direction；
Step 3: calling display list to draw vector arrows according to color and direction.
4, local index cache set Q is established
According to the index to be checked being likely to occur, the Spatial Dimension index domain progress " sorting out again " that normal data is concentrated is deposited
Storage, the index mapping relations of foundation are xi→yij, xiIndicate i-th of sample, yijIndicate the number of variable in j-th of sample.It will
The result of processing is stored in one piece of continuous memory space using hashing technique, i.e. Hash principle.
5, inquiry request is returned
Graphical interfaces is visualization interface, it can carries out edit operation to display figure, such as deletes sample and variable number
According to highlighted sample and variable data etc..When observer carries out graphic element edit operation, can be passed back from foreground interface currently
Index { the x of measuring point or measuring point collectioni| i=1,2 ... }, xi∈Q。
6, processing result is returned to visualization interface
If local standard data set there are data and indexed cache collection be sky, need to carry out step 4 classification behaviour
Make.According to the inquiry request Q (x of step 5i), it is inquired using Hash table, that is, uses hash function by xiIt is converted to corresponding
Array index, and navigate to the space and obtain yijIf including currently Q (x in index cache seti), then the data mapped
Collection extracts, and the data set of extraction is navigated to current display column, is recalculated according to the component of data and is sweared on mesh point
Measure color and the deflection direction of arrow.
Claims (1)
1. a kind of method of spatio-temporal data visualization interface rapidly locating, includes the following steps
Step 1: being stored in database after wind profile instrument data are carried out data prediction；
Step 2: from database read data, by data carry out structured storage to local, i.e., according to the structure feature of data into
Row indexes processing and calculation processing: visualization interface can be divided into the one-dimensional space, two-dimensional space, three-dimensional space, the number of more higher-dimension
It is shown according to two-dimentional or three bit spaces are often mapped to, is carried out data according to particular display environment to index processing, number
It is standard data set format { S according to the format after processingi(I, D) | i=1,2 ..., I representation space dimension indexes domain, D table
Show the data field under the Spatial dimensionality.The data of unified format are saved among local set later；
Step 3: space-time data being realized into data visualization with drafting instrument, shows the velocity vector feelings of each layer data of measuring point
Condition, the data shown in graphics display area, VELOCITY DISTRIBUTION show that arrow direction represents wind direction in form of arrows, and arrow is big
Small to represent wind speed, each column of the data after visualization are all a data samples, and every a line is the subitem variable of sample data,
Variable can be the characteristic an of data sample or the set of the physical quantity measured under specific spacetime coordinate, visualization interface
For vector sectional view, display format is tabular form, and visualization interface at this time is that data can inquire state；
Step 4: establishing local index cache set Q, Q ∈ { I }, according to the index to be checked being likely to occur, normal data is concentrated
Spatial Dimension index domain carry out " sorting out again " storage, establish index and the mapping relations of evidence to be fetched；
Step 5: receiving inquiry request from visualization interface, inquiry request is converted to the search index Q (x of preset formati)；
Step 6: if local standard data set there are data and indexed cache collection be sky, need to carry out step 4 classification behaviour
Make, according to the inquiry request Q (x of step 5i), if including currently Q (x in index cache seti), then the data set mapped
It extracts；
Step 7: the data set extracted in step 6 being navigated into current display column, mesh point is recalculated according to the component of data
The color of upper vector arrows and deflection direction.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109684388A (en) * | 2018-12-29 | 2019-04-26 | 成都信息工程大学 | A kind of meteorological data index and visual analysis method based on hypercube lattice tree |
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| WO2015162280A1 (en) * | 2014-04-24 | 2015-10-29 | Cathx Research Ltd | 3d point clouds |
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| CN102831644A (en) * | 2012-07-09 | 2012-12-19 | 哈尔滨工程大学 | Marine environment information three-dimensional visualization method |
| WO2015162280A1 (en) * | 2014-04-24 | 2015-10-29 | Cathx Research Ltd | 3d point clouds |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109684388A (en) * | 2018-12-29 | 2019-04-26 | 成都信息工程大学 | A kind of meteorological data index and visual analysis method based on hypercube lattice tree |
| CN109684388B (en) * | 2018-12-29 | 2023-07-25 | 成都信息工程大学 | Meteorological data index and visual analysis method based on super-cubic grid tree |
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Application publication date: 20181207 |