CN117115330B - Visual rendering method for diffusion effect of continuous time line of WEB terminal map - Google Patents
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- 238000009792 diffusion process Methods 0.000 title claims abstract description 68
- 238000009877 rendering Methods 0.000 title claims abstract description 46
- 230000000694 effects Effects 0.000 title claims abstract description 35
- 238000000034 method Methods 0.000 title claims abstract description 25
- 230000000007 visual effect Effects 0.000 title claims abstract description 20
- 238000004040 coloring Methods 0.000 claims abstract description 17
- 238000004422 calculation algorithm Methods 0.000 claims description 16
- 238000013500 data storage Methods 0.000 claims description 8
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 7
- 238000004364 calculation method Methods 0.000 description 7
- 238000012800 visualization Methods 0.000 description 7
- 238000001514 detection method Methods 0.000 description 3
- 238000007405 data analysis Methods 0.000 description 2
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- 230000008520 organization Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 239000003344 environmental pollutant Substances 0.000 description 1
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- G—PHYSICS
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Abstract
The invention relates to the technical field of map rendering, and provides a visual rendering method for a diffusion effect of a continuous timeline of a WEB-side map, which comprises the following steps: s1, generating a grid index file of a diffusion model; s2, identifying the type identification of the grid index file; s3, generating a single-band raster data file, and adding all single-band raster data file names to corresponding raster index file name data rows; s4, generating a single-band raster data file, and adding the single-band raster data file name of the time point to a raster index file name data row; s5, issuing a grid index file; s6, acquiring a grid index file; s7, identifying the type identification of the grid index file; s8, generating all grid layers; s9, generating an incremental grid layer; if the type identification of the grid index file of the diffusion model is changed into the fixed-length grid index file, stopping timing polling; s10, performing visual rendering of the diffusion effect; s11, coloring is completed; s12, presenting a diffusion effect.
Description
Technical Field
The invention relates to the technical field of map rendering, in particular to a visual rendering method for a diffusion effect of a continuous timeline of a WEB terminal map.
Background
In the current digital age, map visualization plays an important role in a variety of fields, from navigation applications to geographic data analysis, requiring efficient and accurate map rendering. However, the conventional map rendering method has limitations in some cases, particularly in the aspect of visualization involving diffusion effects on a map.
Conventional map rendering methods typically use complex image processing techniques to convert map data into a visualized image based on raster or vector data. However, these methods can be challenging when continuous timeline diffusion effects on a map need to be represented. Visualization of diffusion effects requires simulation of diffusion effects at different points in time on a map, e.g., atmospheric pollutant diffusion, water pollutant diffusion, etc., which is difficult to achieve with conventional rendering methods.
Although some map rendering engines and libraries exist on the market at present, their capabilities are still limited when dealing with continuous timeline diffusion effects, and there is still much room for improvement in high performance rendering and diffusion effect visualization.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a visual rendering method for the diffusion effect of a continuous time line of a WEB terminal map, which realizes more accurate and more efficient map diffusion effect visualization.
The invention provides a visual rendering method of a diffusion effect of a continuous time line of a WEB terminal map, which comprises the following steps:
s1, a server application creates a diffusion file data storage directory, and generates a grid index file of a diffusion model under the diffusion file data storage directory;
s2, identifying the type identifier of the grid index file, if the grid index file is a fixed-length grid index file, entering a step S3, and if the grid index file is an increment grid index file, entering a step S4;
s3, the server side generates a single-band raster data file based on the original data of the diffusion model, the single-band raster data file is stored in the same directory corresponding to the raster index file, and all single-band raster data file names are added to the corresponding raster index file name data row;
s4, the server side generates a corresponding single-band raster data file based on the original data continuous time point of the diffusion model, the single-band raster data file is stored in the same directory corresponding to the raster index file, the single-band raster data file name of the time point is added to a corresponding raster index file name data row, and after all time points are generated, the type identification of the raster index file is changed into a fixed-length raster index file;
s5, the server application finishes publishing the grid index file output in the step S3 and the step S4;
s6, the WEB terminal map acquires the grid index file issued by the server terminal application;
s7, identifying the type identifier of the obtained grid index file by the WEB side map, entering a step S8 if the grid index file is a fixed-length grid index file, and entering a step S9 if the grid index file is an increment grid index file;
s8, creating a grid layer group, generating all grid layers according to the diffusion model grid index file name data row, and inserting the grid layers into the grid layer group;
s9, creating a grid layer group, periodically polling the diffusion model grid index file name data row, and if an increment grid index file exists, generating an increment grid layer and inserting the increment grid layer into the grid layer group; if the type identification of the grid index file of the diffusion model is changed into a fixed-length grid index file, stopping timing polling;
s10, reading a corresponding grid layer in the grid layer group according to the time point sequence, and executing visual rendering of the diffusion effect;
s11, the map rendering engine reads the pixel data of the grid layer, calculates the gray value of the pixel, and changes the gray value of the pixel through a coloring algorithm to complete coloring;
and S12, the map engine presents a corresponding time point diffusion effect.
Further, step S13 is further included in step S10 and step S11;
s13, reading source data of the grid layer, if the grid index file type is designated as a river channel water body type, executing a step S14, otherwise, executing a step S11;
and S14, the map rendering engine reads the pixel data of the grid image layer, if the pixels of the mask image layer are not water bodies, the pixel values are changed into transparent, otherwise, the gray values of the pixels are calculated, and the gray values of the pixels are changed through a coloring algorithm to complete coloring.
Further, the shading algorithm comprises a linear color interpolation shading algorithm or a gradient color interpolation shading algorithm.
Further, in step S13, a maximum value and a minimum value of source data of the raster layer are acquired.
The beneficial effects of this application are: 1. the organization structure of the grid index file is introduced, so that the data of the diffusion model can be efficiently stored under the condition of different time lengths. The structure has the advantages of supporting the data storage of the time point diffusion model with any time length and supporting the capability of calculating and publishing and rendering at the same time, thereby avoiding long-time calculation waiting and realizing more accurate and more efficient map diffusion effect visualization. 2. The method adopts the imaging pixel detection and coloring mode based on the grid index file, and only calculates the size of a visible window during rendering, which is irrelevant to the map range. The method has relatively less and constant calculated amount in rendering, so that the performance bottleneck problem caused by vector element rendering calculation under a large range or large data volume can be effectively solved. The user can obtain a higher-quality visual effect on the premise of keeping smooth rendering.
Drawings
FIG. 1 is a schematic block diagram of a flow of the present invention;
FIG. 2 is a specific format of a fixed-length grid index file;
FIG. 3 is a specific format of an increment grid index file.
Detailed Description
The invention is further described in connection with the following detailed description, in order to make the technical means, the creation characteristics, the achievement of the purpose and the effect of the invention easy to understand.
As shown in fig. 1, the present invention provides a visual rendering method for a diffusion effect of a continuous timeline of a WEB map, which includes the following steps:
s1, a server application creates a diffusion file data storage directory, and generates a grid index file of a diffusion model under the diffusion file data storage directory.
The specific format of the grid index file of the diffusion model is shown in fig. 2 and 3, and the structure is described as follows;
format: plain text
The structure is as follows:
first row: type= [ type ], [ type ] represents any type;
second row: continuity= [ fixed|dynamic ], [ fixed ] represents a fixed-length diffusion grid index file, and [ dynamic ] represents an incremental diffusion model grid index file;
line n: index file name.
S2, identifying the type identification of the grid index file, if the grid index file is the fixed-length grid index file, entering a step S3, and if the grid index file is the increment grid index file, entering a step S4. The fixed-length raster index file represents that all raster data in the file is calculated, and the raster index is not added in the later period. The delta raster index file represents the variable raster data content within this file.
S3, the server side generates a single-band raster data file (GeoTiff) by applying the original data based on the diffusion model, the single-band raster data file is stored in the same directory corresponding to the raster index file, and all single-band raster data file names are added to the corresponding raster index file name data row.
S4, the server side generates a corresponding single-band raster data file by applying the original data continuous time points based on the diffusion model, the single-band raster data file is stored in the same directory corresponding to the raster index file, the single-band raster data file name of the time point is added to a corresponding raster index file name data row, after all the time points are generated, the type identification of the raster index file is changed to be a fixed-length raster index file, so that the method is suitable for long-time calculation, overlong waiting period is avoided, and simultaneous calculation and rendering are realized subsequently.
S5, the server application finishes publishing the grid index file output in the step S3 and the step S4.
S6, the WEB terminal map acquires a grid index file issued by the server terminal application.
S7, identifying the type identifier of the obtained grid index file by the WEB side map, if the grid index file is the fixed-length grid index file, entering a step S8, and if the grid index file is the increment grid index file, entering a step S9.
And S8, creating a grid layer group, generating all grid layer groups according to the diffusion model grid index file name data row, and inserting the grid layer groups.
S9, creating a raster pattern layer group, periodically polling a diffusion model raster index file name data row, and if an increment raster index file exists, generating an increment raster pattern layer and inserting the increment raster pattern layer into the raster pattern layer group; and if the type identification of the grid index file of the diffusion model is changed into the fixed-length grid index file, stopping timing polling.
And S10, reading a corresponding grid layer in the grid layer group according to the time point sequence, and executing visual rendering of the diffusion effect.
And S11, the map rendering engine reads the pixel data of the grid layer, calculates the gray value of the pixel, and changes the gray value of the pixel through a coloring algorithm to complete coloring.
And S12, the map engine presents a corresponding time point diffusion effect.
The application introduces an organization structure of the grid index file, and can allow data of a diffusion model to be efficiently stored under the condition of different time lengths. The structure has the advantages of supporting the data storage of the time point diffusion model with any time length and supporting the capability of calculating and publishing and rendering at the same time, thereby avoiding long-time calculation waiting and realizing more accurate and more efficient map diffusion effect visualization.
The method adopts the imaging pixel detection and coloring mode based on the grid index file, and only calculates the size of the visible window during rendering, which is irrelevant to the map range. The method has relatively less and constant calculated amount in rendering, so that the performance bottleneck problem caused by vector element rendering calculation under a large range or large data volume can be effectively solved. The user can obtain a higher-quality visual effect on the premise of keeping smooth rendering.
In one embodiment, step S13 is further included in step S10 and step S11.
S13, reading source data of the grid layer, if the grid index file type is designated as the river channel water body type, executing the step S14, otherwise, executing the step S11.
S14, the map rendering engine reads the pixel data of the grid layer, if the pixels of the mask layer are not water bodies, the pixel values are changed into transparent, otherwise, the gray values of the pixels are calculated, and the gray values of the pixels are changed through a coloring algorithm to complete coloring.
The type of river channel water, which may also be referred to as space-bearing mask region, generates non-directional spatial region data due to diffusion effects, and when there is a river channel boundary (i.e., mask region) in a sealed space (mask region) or like a river, diffusion effects beyond the mask region boundary should be removed (i.e., not rendered).
In one embodiment, the shading algorithm comprises a linear color interpolation shading algorithm or a gradient color interpolation shading algorithm.
Based on the read detection and coloring of the pixel data, the invention provides a high degree of customization of diffusion rendering effect for users. By using different pixel color interpolation coloring algorithms, a user can customize the diffusion effect according to different environmental requirements. The high customization can enable a user to adapt to different application scenes better, so that more accurate data analysis results and display effects are obtained.
In one embodiment, in step S13, the maximum value and the minimum value of the source data of the raster layer are acquired. The maximum and minimum values of the source data of the raster layer are used to determine the Range of the rasterized pixel rendering for achieving the effect of gradient color or gradient rendering, while also reversing the calculation of the current diffusion density value to support the gray value through the pixel.
While the fundamental and principal features of the invention and advantages of the invention have been shown and described, it will be apparent to those skilled in the art that the invention is not limited to the details of the foregoing exemplary embodiments, but may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
Furthermore, it should be understood that although the present disclosure describes embodiments, not every embodiment is provided with a separate embodiment, and that this description is provided for clarity only, and that the disclosure is not limited to the embodiments described in detail below, and that the embodiments described in the examples may be combined as appropriate to form other embodiments that will be apparent to those skilled in the art.
Claims (4)
1. A visual rendering method for a diffusion effect of a continuous time line of a WEB terminal map is characterized by comprising the following steps of: the method comprises the following steps:
s1, a server application creates a diffusion file data storage directory, and generates a grid index file of a diffusion model under the diffusion file data storage directory;
s2, identifying the type identifier of the grid index file, if the grid index file is a fixed-length grid index file, entering a step S3, and if the grid index file is an increment grid index file, entering a step S4;
s3, the server side generates a single-band raster data file based on the original data of the diffusion model, the single-band raster data file is stored in the same directory corresponding to the raster index file, and all single-band raster data file names are added to the corresponding raster index file name data row;
s4, the server side generates a corresponding single-band raster data file based on the original data continuous time point of the diffusion model, the single-band raster data file is stored in the same directory corresponding to the raster index file, the single-band raster data file name of the time point is added to a corresponding raster index file name data row, and after all time points are generated, the type identification of the raster index file is changed into a fixed-length raster index file;
s5, the server application finishes publishing the grid index file output in the step S3 and the step S4;
s6, the WEB terminal map acquires the grid index file issued by the server terminal application;
s7, identifying the type identifier of the obtained grid index file by the WEB side map, entering a step S8 if the grid index file is a fixed-length grid index file, and entering a step S9 if the grid index file is an increment grid index file;
s8, creating a grid layer group, generating all grid layers according to the diffusion model grid index file name data row, and inserting the grid layers into the grid layer group;
s9, creating a grid layer group, periodically polling the diffusion model grid index file name data row, and if an increment grid index file exists, generating an increment grid layer and inserting the increment grid layer into the grid layer group; if the type identification of the grid index file of the diffusion model is changed into a fixed-length grid index file, stopping timing polling;
s10, reading a corresponding grid layer in the grid layer group according to the time point sequence, and executing visual rendering of the diffusion effect;
s11, the map rendering engine reads the pixel data of the grid layer, calculates the gray value of the pixel, and changes the gray value of the pixel through a coloring algorithm to complete coloring;
and S12, the map engine presents a corresponding time point diffusion effect.
2. The visual rendering method for the diffusion effect of the continuous timeline of the WEB terminal map according to claim 1, wherein the visual rendering method is characterized by comprising the following steps of: step S13 is further included in step S10 and step S11;
s13, reading source data of the grid layer, if the grid index file type is designated as a river channel water body type, executing a step S14, otherwise, executing a step S11;
and S14, the map rendering engine reads the pixel data of the grid image layer, if the pixels of the mask image layer are not water bodies, the pixel values are changed into transparent, otherwise, the gray values of the pixels are calculated, and the gray values of the pixels are changed through a coloring algorithm to complete coloring.
3. The visual rendering method for the diffusion effect of the continuous timeline of the WEB terminal map according to claim 2, wherein the visual rendering method is characterized by comprising the following steps of: the shading algorithm comprises a linear color interpolation shading algorithm or a gradient color interpolation shading algorithm.
4. The visual rendering method for the diffusion effect of the continuous timeline of the WEB terminal map according to claim 2, wherein the visual rendering method is characterized by comprising the following steps of: in step S13, a maximum value and a minimum value of source data of the raster layer are acquired.
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