Vector field dynamic display method and device, electronic equipment and storage medium

Abstract

The present application relates to the technical field of computer graphics rendering, and particularly relates to a vector field dynamic display method and device, electronic equipment and storage medium, the embodiment of the present application obtains a plurality of data sets with large time intervals, constructs an accumulation matrix through vector data, matches position data in two adjacent data sets according to the reordering mode of the accumulation matrix, forms a vector path queue, forms a plurality of vector field data sets through interpolation according to the vector path queue, and displays according to the vector data set. Since the data amount is small, the amount of calculation is small during processing, the delay is small, and the response speed is fast. The vector path is planned through the position matching mode, the vector field data is generated through the vector interpolation mode, so that the expansion of the vector field data set is realized, the picture smoothness is high, and the requirements of smoothness and response speed during rendering are considered.

Description

Technical Field

[0001] This invention relates to the field of computer graphics rendering technology, and in particular to a method, apparatus, electronic device, and storage medium for dynamic display of vector fields. Background Technology

[0002] Vector fields refer to data fields that include direction and magnitude, and their forms include, but are not limited to, wind fields (wind speed, wind direction), flow fields (flow velocity and direction), and wave fields (wave height, wave direction). Data formats include, but are not limited to, rectangular regular grids, irregular triangular grids, and scattered points. Through the dynamic display of vector fields, users can quickly and vividly show the changes in fluid fields, and it has broad application scenarios in the fields of pollutant dispersion control and water transport.

[0003] Traditional methods for displaying vector field graphics involve installing graphics rendering software on a computing terminal, importing the vector field data, and then displaying it. This method, besides requiring software installation, also demands expertise in graphic analysis and viewing, making it relatively complex to operate. An improved approach is to upload the vector field data to a server, where it is rendered, and the result is then displayed through a web browser.

[0004] However, for vector field data to achieve accurate rendering, it either needs to be large in size, leading to high computational load, slow response time, and latency, or its size needs to be reduced to improve response time. However, after reducing the vector field data, the displayed image often appears jerky and choppy, affecting the viewing experience and the results of dynamic analysis of the vector field.

[0005] Therefore, it is necessary to develop and design a method for dynamically displaying vector fields. Summary of the Invention

[0006] The present invention provides a method, apparatus, electronic device and storage medium for dynamic display of vector fields, which solves the problem in the prior art that it is not easy to achieve both smoothness and fast response when rendering based on vector field data.

[0007] In a first aspect, embodiments of the present invention provide a method for dynamically displaying a vector field, comprising:

[0008] Multiple first vector field datasets are obtained, wherein the first vector field datasets represent the vector direction and magnitude of multiple predetermined points at the same time node;

[0009] Multiple accumulation matrices are constructed based on the multiple first vector field datasets. Multiple vector path queues are planned by matching the multiple accumulation matrices with the multiple first vector field datasets. The accumulation matrix represents the multiple predicted point positions determined based on multiple point positions and multiple vectors.

[0010] Based on the multiple vector path queues, multiple second vector field datasets are generated by vector interpolation, and the multiple second vector field datasets are displayed sequentially.

[0011] In one possible implementation, the step of constructing multiple accumulation matrices based on the multiple first vector field datasets, and planning multiple vector path queues by matching the multiple accumulation matrices with the multiple first vector field datasets, includes:

[0012] According to the positional order of the points, the point position data and vector data of each of the multiple first vector field datasets are arranged, and the rearranged first vector field datasets are used as third vector field datasets, thereby obtaining multiple third vector field datasets.

[0013] From each of the plurality of third vector field datasets, point location data and vector data are extracted to construct a first point location matrix and a first vector matrix, thereby obtaining a plurality of first point location matrices and a plurality of first vector matrices;

[0014] Based on the node time difference, the multiple first point position matrices, and the multiple first vector matrices, multiple first accumulation matrices are constructed, wherein the node time difference is the time difference between two adjacent third vector field datasets;

[0015] According to the positional order of the points, the point position data of each of the multiple first accumulation matrices are arranged, and the rearranged first accumulation matrix is ​​used as the second accumulation matrix, thereby obtaining multiple second accumulation matrices;

[0016] Multiple vector path queues are constructed based on the multiple second accumulation matrices and the multiple first point position matrices.

[0017] In one possible implementation, constructing multiple first accumulation matrices based on the node time difference, the multiple first point location matrices, and the multiple first vector matrices includes:

[0018] Based on the first formula, node time difference, the plurality of first point position matrices, and the plurality of first vector matrices, construct a plurality of first accumulation matrices.

[0019]

[0020] In the formula, This is the first cumulative matrix. This is the position matrix of the first point. For node time difference, This is the first vector matrix.

[0021] In one possible implementation, constructing multiple vector path queues based on the plurality of second accumulation matrices and the plurality of first point location matrices includes:

[0022] The plurality of second accumulation matrices and the plurality of first point position matrices are sorted according to the time node order;

[0023] Extract point location data from the first and second point location matrix in a preset order, use the extracted point location data as source location data, use the first and second point location matrix as target point location matrix, create a new vector path queue, and add the source location data to the first position of the vector path queue. The first and second point location matrix is ​​the matrix that is ranked first among the plurality of first point location matrices.

[0024] The target location is obtained based on the source location data and the target accumulation matrix, wherein the target accumulation matrix is ​​an accumulation matrix constructed based on the target point location matrix, and the target location is the position of the data in the target accumulation matrix determined based on the source location data;

[0025] The location data of the target location is extracted from the post-point location matrix, the extracted location data is added to the end of the vector path queue, and the extracted location data is used as the source location data. The post-point location matrix is ​​the first point location matrix that is connected to the target point location matrix after the target point location matrix among the plurality of first point location matrices.

[0026] If the subsequent point position matrix is ​​not the last matrix among the plurality of first point position matrices, then the subsequent point position matrix is ​​used as the target point position matrix, and the process jumps to the step of obtaining the target position based on the source position data and the target accumulation matrix;

[0027] Otherwise, if the data at the first position of the vector path queue is not the data at the last position of the first and second position matrix, then proceed to the step of extracting the position data from the first and second position matrix in a preset order.

[0028] In one possible implementation, before constructing the plurality of vector path queues based on the plurality of second accumulation matrices and the plurality of first point location matrices, the following is included:

[0029] Calculate the differences between the plurality of second accumulation matrices and the plurality of first point position matrices to obtain a plurality of difference matrices;

[0030] The extreme values ​​of the multiple difference matrices are extracted respectively to obtain multiple extreme values;

[0031] If any of the multiple extreme values ​​has an absolute value exceeding a threshold, then the multiple third vector field datasets are adjusted, and the process returns to the step of arranging the point location data and vector data of each of the multiple first vector field datasets according to the position order of the points.

[0032] In one possible implementation, generating multiple second vector field datasets based on the multiple vector path queues via vector interpolation includes:

[0033] For each of the plurality of vector path queues, perform the following steps:

[0034] Obtain the display time point;

[0035] The first target location data and the second target location data are determined based on the display time node, wherein the first target location data and the second target location data are the location data corresponding to the two time nodes closest to the display time node in the vector path queue;

[0036] Based on the first target location data, the second target location data, and the display time node, determine the display location data and display vector data;

[0037] Based on the display time node, the display location data and the display vector data are added to the second vector field dataset.

[0038] In one possible implementation, determining the display location data and display vector data based on the first target location data, the second target location data, and the display time node includes:

[0039] Based on the second formula, the first target location data, the second target location data, and the display time node, the display location data and display vector data are determined, wherein the second formula is:

[0040]

[0041] In the formula, To display location data, This is the location data for the first target. For the location data of the second target, The time node corresponding to the location data of the first target. The time node corresponding to the location data of the second target. To display time points, To display vector data, This is the vector data for the first target location. This is the vector data for the location of the second target point.

[0042] Secondly, embodiments of the present invention provide a vector field dynamic display device for implementing the vector field dynamic display method as described in the first aspect or any possible implementation thereof, the vector field dynamic display device comprising:

[0043] The data acquisition module is used to acquire multiple first vector field datasets, wherein the first vector field datasets represent the vector direction and magnitude of multiple predetermined points at the same time node;

[0044] The vector path planning module is used to construct multiple accumulation matrices based on the multiple first vector field datasets, and to plan multiple vector path queues by matching the multiple accumulation matrices with the multiple first vector field datasets. The accumulation matrix represents multiple predicted point positions determined based on multiple point positions and multiple vectors.

[0045] as well as,

[0046] The vector display module is used to generate multiple second vector field datasets by vector interpolation based on the multiple vector path queues, and to display the multiple second vector field datasets in sequence.

[0047] Thirdly, embodiments of the present invention provide an electronic device, including a memory and a processor, wherein the memory stores a computer program executable on the processor, and the processor executes the computer program to implement the steps of the method as described in the first aspect or any possible implementation of the first aspect.

[0048] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method as described in the first aspect or any possible implementation thereof.

[0049] The beneficial effects of the embodiments of the present invention compared with the prior art are as follows:

[0050] This invention discloses a method for dynamically displaying vector fields. First, it acquires multiple first vector field datasets, each representing the vector direction and magnitude of multiple predetermined points at the same time node. Then, it constructs multiple accumulation matrices based on these first vector field datasets. By matching these accumulation matrices with the first vector field datasets, it plans multiple vector path queues. Each accumulation matrix represents multiple predicted point positions determined by multiple point locations and multiple vectors. Finally, based on the multiple vector path queues, it generates multiple second vector field datasets through vector interpolation and displays them sequentially. This invention acquires multiple datasets with large time intervals, constructs accumulation matrices from the vector data, matches positional data in two adjacent datasets by reordering the accumulation matrices to form vector path queues, and then uses interpolation to form multiple vector field datasets, which are then displayed. Due to the relatively small data volume, the processing computation is low, latency is low, and response speed is fast. Vector paths are planned by position matching and vector field data is generated by vector interpolation, thereby expanding the vector field dataset. The screen is smooth, balancing the requirements of smooth rendering and responsiveness. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 This is a flowchart of the vector field dynamic display method provided by the embodiments of the present invention;

[0053] Figure 2 This is a schematic diagram of the vector field display principle provided by an embodiment of the present invention;

[0054] Figure 3 This is a schematic diagram of the vector path queue construction process provided by an embodiment of the present invention;

[0055] Figure 4 This is a functional block diagram of the vector field dynamic display device provided in the embodiments of the present invention;

[0056] Figure 5 This is a functional block diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0057] In the following description, specific details such as particular system structures and techniques are set forth for illustrative purposes and not for limitation, so as to provide a thorough understanding of embodiments of the invention. However, those skilled in the art will understand that the invention can be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, and methods are omitted so as not to obscure the description of the invention with unnecessary detail.

[0058] To make the objectives, technical solutions, and advantages of the present invention clearer, specific embodiments will be described below in conjunction with the accompanying drawings.

[0059] The embodiments of the present invention will be described in detail below. This example is implemented based on the technical solution of the present invention, and provides detailed implementation methods and specific operation processes. However, the protection scope of the present invention is not limited to the following embodiments.

[0060] Figure 1 A flowchart of a vector field dynamic display method provided for an embodiment of the present invention.

[0061] like Figure 1 As shown, a flowchart illustrating the implementation of the vector field dynamic display method provided by an embodiment of the present invention is presented, and is described in detail below:

[0062] In step 101, multiple first vector field datasets are obtained, wherein the first vector field datasets represent the vector direction and magnitude of multiple predetermined points at the same time node.

[0063] For example, such as Figure 2 As shown in the figure, this diagram illustrates the principle of vector field display provided by an embodiment of the present invention.

[0064] In some applications, vector field data can be data of various forms and sources, such as wind fields downloaded from the internet, flow fields calculated by numerical simulation software, wave fields, etc. Essentially, the data is a series of data points in the form of (t, x, y, u, v), where t represents the time corresponding to the vector data, x and y represent the coordinate positions, and u and v represent the magnitude of the vector in the horizontal and vertical directions, respectively. The combination of uv can represent vectors of arbitrary size and direction. Collecting data points from the same moment together yields a vector field dataset. Displaying the vectors within the data points on their position coordinates, and further showing the vector field dataset frame by frame, creates a dynamic visual representation of the vector field.

[0065] As mentioned earlier, when the time density of a vector field dataset is high—in other words, the time interval between two adjacent vector field datasets is small—the dynamic visuals of the vector field dataset are smooth, but the computational load and data volume are large, and network transmission is prone to latency. For example, after clicking a command, there is a waiting period before the visuals are generated. Conversely, when the time density of a vector dataset is low, the rendered dynamic visuals appear jerky and not smooth.

[0066] like Figure 2 As shown, multiple vectors move from left to right. If there is a large time interval between two images, a sense of jump will be produced. For example, it is unclear whether the vector marked with a hollow circle at the top in the image corresponds to the vector marked with a hollow square at the top in the next moment, or to the vector marked with a hollow rectangle at the top.

[0067] In order to reduce the time density of the vector field while ensuring smoothness, the embodiments of the present invention plan the walking path of the vector based on the time interval of Jiaotong University, and generate multiple vector datasets based on the walking path by vector interpolation. Then, the screen is rendered based on the generated vector datasets, which can achieve the effect of balancing smoothness and fast response.

[0068] To achieve the above effects, the embodiments of the present invention are described in the following two steps.

[0069] In step 102, multiple accumulation matrices are constructed based on the multiple first vector field datasets. Multiple vector path queues are planned by matching the multiple accumulation matrices with the multiple first vector field datasets. The accumulation matrix represents the multiple predicted point positions determined based on multiple point positions and multiple vectors.

[0070] In some embodiments, step 102 includes:

[0071] According to the positional order of the points, the point position data and vector data of each of the multiple first vector field datasets are arranged, and the rearranged first vector field datasets are used as third vector field datasets, thereby obtaining multiple third vector field datasets.

[0072] From each of the plurality of third vector field datasets, point location data and vector data are extracted to construct a first point location matrix and a first vector matrix, thereby obtaining a plurality of first point location matrices and a plurality of first vector matrices;

[0073] Based on the node time difference, the multiple first point position matrices, and the multiple first vector matrices, multiple first accumulation matrices are constructed, wherein the node time difference is the time difference between two adjacent third vector field datasets;

[0074] According to the positional order of the points, the point position data of each of the multiple first accumulation matrices are arranged, and the rearranged first accumulation matrix is ​​used as the second accumulation matrix, thereby obtaining multiple second accumulation matrices;

[0075] Multiple vector path queues are constructed based on the multiple second accumulation matrices and the multiple first point position matrices.

[0076] In some implementations, constructing multiple first accumulation matrices based on node time differences, the multiple first point location matrices, and the multiple first vector matrices includes:

[0077] Based on the first formula, node time difference, the plurality of first point position matrices, and the plurality of first vector matrices, construct a plurality of first accumulation matrices.

[0078]

[0079] In the formula, This is the first cumulative matrix. This is the position matrix of the first point. For node time difference, This is the first vector matrix.

[0080] In some implementations, constructing multiple vector path queues based on the plurality of second accumulation matrices and the plurality of first point location matrices includes:

[0081] The plurality of second accumulation matrices and the plurality of first point position matrices are sorted according to the time node order;

[0082] Extract point location data from the first and second point location matrix in a preset order, use the extracted point location data as source location data, use the first and second point location matrix as target point location matrix, create a new vector path queue, and add the source location data to the first position of the vector path queue. The first and second point location matrix is ​​the matrix that is ranked first among the plurality of first point location matrices.

[0083] The target location is obtained based on the source location data and the target accumulation matrix, wherein the target accumulation matrix is ​​an accumulation matrix constructed based on the target point location matrix, and the target location is the position of the data in the target accumulation matrix determined based on the source location data;

[0084] The location data of the target location is extracted from the post-point location matrix, the extracted location data is added to the end of the vector path queue, and the extracted location data is used as the source location data. The post-point location matrix is ​​the first point location matrix that is connected to the target point location matrix after the target point location matrix among the plurality of first point location matrices.

[0085] If the subsequent point position matrix is ​​not the last matrix among the plurality of first point position matrices, then the subsequent point position matrix is ​​used as the target point position matrix, and the process jumps to the step of obtaining the target position based on the source position data and the target accumulation matrix;

[0086] Otherwise, if the data at the first position of the vector path queue is not the data at the last position of the first and second position matrix, then proceed to the step of extracting the position data from the first and second position matrix in a preset order.

[0087] In some implementations, before constructing multiple vector path queues based on the plurality of second accumulation matrices and the plurality of first point location matrices, the following steps are included:

[0088] Calculate the differences between the plurality of second accumulation matrices and the plurality of first point position matrices to obtain a plurality of difference matrices;

[0089] The extreme values ​​of the multiple difference matrices are extracted respectively to obtain multiple extreme values;

[0090] If any of the multiple extreme values ​​has an absolute value exceeding a threshold, then the multiple third vector field datasets are adjusted, and the process returns to the step of arranging the point location data and vector data of each of the multiple first vector field datasets according to the position order of the points.

[0091] For example, in an embodiment of the present invention, a predicted position matrix is ​​constructed based on the current position, vector value and time difference with the next vector field dataset in the vector field dataset, and the predicted position matrix is ​​mapped and associated with the position matrix of the next vector field dataset to construct the path of each vector from the current vector field time to the next vector field time.

[0092] This invention uses a first formula to determine the first accumulation matrix:

[0093]

[0094] In the formula, This is the first cumulative matrix. This is the position matrix of the first point. For node time difference, This is the first vector matrix.

[0095] In the formula, the first point position matrix is ​​a matrix constructed based on the positions of multiple points in the vector field dataset, the first vector matrix is ​​a matrix constructed based on the positions of multiple points in the vector field dataset, and the first vector matrix is ​​a matrix constructed based on the multiple vectors in the vector field dataset.

[0096] The accumulated matrix obtained using the first formula is the matrix for predicting the position of the point at the next time step based on the vector. The predicted position matrix obtained through the above process does not correspond to the first position matrix. Therefore, in this embodiment of the invention, after obtaining the accumulated matrix, the positions are sorted according to the midpoint positions of the accumulated matrix. This sorting method is the same as the arrangement method of the first position matrix. For example, the positions are first sorted by x-coordinate, the sorted position data is divided into multiple groups, and each group is then sorted by y-coordinate, thus obtaining the second accumulated matrix.

[0097] In terms of constructing a vector path based on the second accumulated matrix, the embodiments of the present invention first sort the multiple second accumulated matrices according to the corresponding time nodes. For example, the multiple second accumulated matrices correspond to time nodes t2, t3, t4, t5, t6, and t7. It should be noted that these multiple second accumulated matrices are generated by the first position matrix corresponding to the time nodes t1, t2, t3, t4, t5, and t6.

[0098] Then, data is extracted from the position matrices of multiple first points corresponding to times t2, t3, t4, t5, t6, and t7 to form a vector path queue. Figure 3 The corresponding process is illustrated. In the figure, the first accumulation matrix 301 at time t1 is rearranged according to its coordinate positions to generate the second accumulation matrix 302 at time t2. For example, when the data A11, A22, and A32 located in the first accumulation matrix 301 are rearranged to generate the second accumulation matrix 302, the positions of the three data points are assigned to the first row, first column, second column, and third column, respectively. At this time, we extract data B11, B12, and B13 from the first row, first column, second column, and third column positions in the first position matrix 303 at time t2, and add them to the queues of the first row, first column, second row, second column, and third row, third column elements in the first position matrix at time t1, respectively.

[0099] Following the steps above, multiple vector path queues are constructed, which are essentially queues of location data for multiple vectors at different time points.

[0100] Furthermore, in some application scenarios, after constructing the second accumulated matrix but before constructing the vector path queue, the second accumulated matrix is ​​verified. The verification method involves calculating the difference between the second accumulated matrix and the first point position matrix based on time points. For example, calculating the difference between the second accumulated matrix at time t2 and the first point position matrix at time t2. Since the second accumulated matrix is ​​a position prediction matrix, the difference between the second accumulated matrix and the first point position matrix may have a large deviation. Therefore, in this embodiment of the invention, the value with the largest absolute value from the difference matrix is ​​selected for judgment. If this value exceeds a threshold, the data in the vector field dataset can be adjusted so that the difference between the second accumulated matrix and the first point position matrix is ​​reduced to within the threshold range.

[0101] In step 103, multiple second vector field datasets are generated by vector interpolation based on the multiple vector path queues, and the multiple second vector field datasets are displayed in sequence.

[0102] In some embodiments, step 103 includes:

[0103] For each of the plurality of vector path queues, perform the following steps:

[0104] Obtain the display time point;

[0105] The first target location data and the second target location data are determined based on the display time node, wherein the first target location data and the second target location data are the location data corresponding to the two time nodes closest to the display time node in the vector path queue;

[0106] Based on the first target location data, the second target location data, and the display time node, determine the display location data and display vector data;

[0107] Based on the display time node, the display location data and the display vector data are added to the second vector field dataset.

[0108] In some implementations, determining the display location data and display vector data based on the first target location data, the second target location data, and the display time node includes:

[0109] Based on the second formula, the first target location data, the second target location data, and the display time node, the display location data and display vector data are determined, wherein the second formula is:

[0110]

[0111] In the formula, To display location data, This is the location data for the first target. For the location data of the second target, The time node corresponding to the location data of the first target. The time node corresponding to the location data of the second target. To display time points, To display vector data, This is the vector data for the first target location. This is the vector data for the location of the second target point.

[0112] For example, after obtaining multiple vector path queues, the data can be expanded using interpolation. For instance, multiple time nodes t120, t121, t122, t123...t129 (display time nodes) can be linearly inserted at times t1 and t2. Based on these time nodes, multiple positional data points are then linearly inserted into each of the multiple vector path queues, thus expanding the vector path queue data. After expansion, data is extracted from the multiple vector path queues according to the time nodes. These data are then merged to form a dataset, and finally, the merged datasets are displayed according to the time nodes, forming the rendered image.

[0113] Regarding location data augmentation, the implementation of this invention employs a second formula:

[0114]

[0115] In the formula, To display location data, This is the location data for the first target. For the location data of the second target, The time node corresponding to the location data of the first target. The time node corresponding to the location data of the second target. To display time points, To display vector data, This is the vector data for the first target location. This is the vector data for the location of the second target point.

[0116] The above formula expands the location data. In some scenarios, the vector is also expanded. The principle of vector expansion is the same as that of location expansion. It involves inserting data into two vectors that are adjacent in time through a data insertion algorithm.

[0117] This invention discloses a method for dynamically displaying vector fields. First, it acquires multiple first vector field datasets, each representing the vector direction and magnitude of multiple predetermined points at the same time point. Then, it constructs multiple accumulation matrices based on these first vector field datasets. Multiple vector path queues are planned by matching these accumulation matrices with the first vector field datasets. Each accumulation matrix represents the predicted positions of multiple points determined by multiple points and vectors. Finally, multiple second vector field datasets are generated using vector interpolation based on the multiple vector path queues, and these second vector field datasets are displayed sequentially. This invention acquires multiple datasets with large time intervals, constructs accumulation matrices using vector data, matches positional data in two adjacent datasets by reordering the accumulation matrices, forms vector path queues, and uses interpolation to form multiple vector field datasets, which are then displayed. Due to the relatively small data volume, the processing computation is low, latency is low, and response speed is fast. Vector paths are planned by position matching and vector field data is generated by vector interpolation, thereby expanding the vector field dataset. The screen is smooth, balancing the requirements of smooth rendering and responsiveness.

[0118] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0119] The following are embodiments of the apparatus of the present invention. For details not described in detail, please refer to the corresponding method embodiments described above.

[0120] Figure 4 This is a functional block diagram of the vector field dynamic display device provided in the embodiments of the present invention, with reference to... Figure 4 The vector field dynamic display device includes: a data acquisition module 401, a vector path planning module 402, and a vector display module 403, wherein:

[0121] The data acquisition module 401 is used to acquire multiple first vector field datasets, wherein the first vector field datasets represent the vector direction and magnitude of multiple predetermined points at the same time node;

[0122] The vector path planning module 402 is used to construct multiple accumulation matrices based on the multiple first vector field datasets, and to plan multiple vector path queues by matching the multiple accumulation matrices with the multiple first vector field datasets. The accumulation matrix represents multiple predicted point positions determined based on multiple point positions and multiple vectors.

[0123] The vector display module 403 is used to generate multiple second vector field datasets by vector interpolation based on the multiple vector path queues, and to display the multiple second vector field datasets in sequence.

[0124] Figure 5 This is a functional block diagram of the electronic device provided in an embodiment of the present invention. For example... Figure 5 As shown, the electronic device 5 of this embodiment includes a processor 500 and a memory 501, wherein the memory 501 stores a computer program 502 that can run on the processor 500. When the processor 500 executes the computer program 502, it implements the steps of the various vector field dynamic display methods and embodiments described above, for example... Figure 1 Steps 101 to 103 are shown.

[0125] For example, the computer program 502 may be divided into one or more modules / units, which are stored in the memory 501 and executed by the processor 500 to complete the present invention.

[0126] The electronic device 5 can be a desktop computer, laptop, handheld computer, cloud server, or other computing device. The electronic device 5 may include, but is not limited to, a processor 500 and a memory 501. Those skilled in the art will understand that... Figure 5 This is merely an example of electronic device 5 and does not constitute a limitation on electronic device 5. It may include more or fewer components than shown, or combine certain components, or different components. For example, electronic device 5 may also include input / output devices, network access devices, buses, etc.

[0127] The processor 500 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0128] The memory 501 can be an internal storage unit of the electronic device 5, such as a hard disk or memory. The memory 501 can also be an external storage device of the electronic device 5, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the memory 501 can include both internal and external storage units of the electronic device 5. The memory 501 is used to store the computer program 502 and other programs and data required by the electronic device 5. The memory 501 can also be used to temporarily store data that has been output or will be output.

[0129] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the aforementioned method embodiments, and will not be repeated here.

[0130] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0131] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0132] In the embodiments provided by this invention, it should be understood that the disclosed devices / electronic devices and methods can be implemented in other ways. For example, the device / electronic device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0133] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0134] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0135] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above-described embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various methods and apparatus embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0136] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for dynamically displaying a vector field, characterized in that, include: Multiple first vector field datasets are obtained. The first vector field datasets represent the vector direction and magnitude of multiple predetermined points at the same time node. The vector field is a data field that includes direction and magnitude. The vector field forms include wind field containing wind speed and wind direction, flow field containing flow velocity and flow direction, and wave field containing wave height and wave direction. Multiple accumulation matrices are constructed based on the multiple first vector field datasets. Multiple vector path queues are planned by matching the multiple accumulation matrices with the multiple first vector field datasets, including: According to the positional order of the points, the point position data and vector data of each of the multiple first vector field datasets are arranged, and the rearranged first vector field datasets are used as third vector field datasets, thereby obtaining multiple third vector field datasets. From each of the plurality of third vector field datasets, point location data and vector data are extracted to construct a first point location matrix and a first vector matrix, thereby obtaining a plurality of first point location matrices and a plurality of first vector matrices; Based on the node time difference, the multiple first point position matrices, and the multiple first vector matrices, multiple first accumulation matrices are constructed, wherein the accumulation matrix represents the multiple predicted point positions determined based on the multiple point positions and multiple vectors, and the node time difference is the time difference between two adjacent third vector field datasets; According to the positional order of the points, the point position data of each of the multiple first accumulation matrices are arranged, and the rearranged first accumulation matrix is ​​used as the second accumulation matrix, thereby obtaining multiple second accumulation matrices; Based on the plurality of second accumulation matrices and the plurality of first point position matrices, construct a plurality of vector path queues; Based on the multiple vector path queues, multiple second vector field datasets are generated by vector interpolation, and the multiple second vector field datasets are rendered sequentially.

2. The vector field dynamic display method according to claim 1, characterized in that, The construction of multiple first accumulation matrices based on node time differences, the multiple first point position matrices, and the multiple first vector matrices includes: The node time difference, the multiple first point location matrices, and the multiple first vector matrices are input into a first formula to obtain multiple first accumulation matrices, wherein the first formula is: In the formula, This is the first cumulative matrix. This is the position matrix of the first point. For node time difference, This is the first vector matrix.

3. The vector field dynamic display method according to claim 1, characterized in that, The step of constructing multiple vector path queues based on the multiple second accumulation matrices and the multiple first point position matrices includes: The plurality of second accumulation matrices and the plurality of first point position matrices are sorted according to the time node order; Extract point location data from the first and second point location matrix in a preset order, use the extracted point location data as source location data, use the first and second point location matrix as target point location matrix, create a new vector path queue, and add the source location data to the first position of the vector path queue. The first and second point location matrix is ​​the matrix that is ranked first among the plurality of first point location matrices. The target location is obtained based on the source location data and the target accumulation matrix, wherein the target accumulation matrix is ​​an accumulation matrix constructed based on the target point location matrix, and the target location is the position of the data in the target accumulation matrix determined based on the source location data; The location data of the target location is extracted from the post-point location matrix, the extracted location data is added to the end of the vector path queue, and the extracted location data is used as the source location data. The post-point location matrix is ​​the first point location matrix that is connected to the target point location matrix after the target point location matrix among the plurality of first point location matrices. If the subsequent point position matrix is ​​not the last matrix among the plurality of first point position matrices, then the subsequent point position matrix is ​​used as the target point position matrix, and the process jumps to the step of obtaining the target position based on the source position data and the target accumulation matrix; Otherwise, if the data at the first position of the vector path queue is not the data at the last position of the first and second position matrix, then proceed to the step of extracting the position data from the first and second position matrix in a preset order.

4. The vector field dynamic display method according to claim 1, characterized in that, Before constructing multiple vector path queues based on the multiple second accumulation matrices and the multiple first point location matrices, the process includes: Calculate the differences between the plurality of second accumulation matrices and the plurality of first point position matrices to obtain a plurality of difference matrices; The extreme values ​​of the multiple difference matrices are extracted respectively to obtain multiple extreme values; If any of the multiple extreme values ​​has an absolute value exceeding a threshold, then the multiple third vector field datasets are adjusted, and the process returns to the step of arranging the point location data and vector data of each of the multiple first vector field datasets according to the position order of the points.

5. The vector field dynamic display method according to any one of claims 1-4, characterized in that, The step of generating multiple second vector field datasets based on the multiple vector path queues through vector interpolation includes: For each of the plurality of vector path queues, perform the following steps: Obtain the display time point; The first target location data and the second target location data are determined based on the display time node, wherein the first target location data and the second target location data are the location data corresponding to the two time nodes closest to the display time node in the vector path queue; Based on the first target location data, the second target location data, and the display time node, determine the display location data and display vector data; Based on the display time node, the display location data and the display vector data are added to the second vector field dataset.

6. The vector field dynamic display method according to claim 5, characterized in that, The step of determining the display location data and display vector data based on the first target location data, the second target location data, and the display time node includes: Based on the second formula, the first target location data, the second target location data, and the display time node, the display location data and display vector data are determined, wherein the second formula is: In the formula, To display location data, This is the location data for the first target. For the location data of the second target, The time node corresponding to the location data of the first target. The time node corresponding to the location data of the second target. To display time points, To display vector data, This is the vector data for the first target location. This is the vector data for the location of the second target point.

7. A vector field dynamic display device, characterized in that, For implementing the vector field dynamic display method as described in any one of claims 1-6, the vector field dynamic display device comprises: The data acquisition module is used to acquire multiple first vector field datasets, wherein the first vector field datasets represent the vector direction and magnitude of multiple predetermined points at the same time node; The vector path planning module is used to construct multiple accumulation matrices based on the multiple first vector field datasets, and to plan multiple vector path queues by matching the multiple accumulation matrices with the multiple first vector field datasets. The accumulation matrix represents multiple predicted point positions determined based on multiple point positions and multiple vectors. as well as, The vector display module is used to generate multiple second vector field datasets by vector interpolation based on the multiple vector path queues, and to display the multiple second vector field datasets in sequence.

8. An electronic device comprising a memory and a processor, wherein the memory stores a computer program executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 6 above.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 6 above.

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