Time sequence visualization sequence frame generation method, controller and storage medium

Abstract

The invention relates to the technical field of model processing, particularly provides a time sequence visualization sequence frame generation method, a controller and a storage medium, and aims to solve the problem that a time sequence visualization sequence frame cannot accurately reflect change conditions of a data field model at different times. In order to achieve the purpose, the method comprises the steps of obtaining three-dimensional data field model data at multiple moments to construct a three-dimensional data field model, obtaining a scalar attribute value in a scalar field data set at each moment, and performing color mapping processing on visual display of the three-dimensional data field model at the corresponding moment, and obtaining a color mapping result of the three-dimensional data field model at each moment, and further determining a time sequence visualization sequence frame. According to the method, the three-dimensional data field model at each moment is subjected to color mapping according to the scalar attribute value at the corresponding moment to determine the time sequence visualization sequence frame, so that the problem that the sequence frame is not completely continuous is avoided, and the finally determined sequence frame can accurately reflect the change condition of the three-dimensional data field model at different times.

Description

Technical Field

[0001] The present application relates to the technical field of model processing, and specifically provides a method for generating a temporal visualization sequence frame, a controller and a storage medium. Background Art

[0002] A three-dimensional data field model refers to a data field defined in a three-dimensional space, which is usually used to describe the spatial distribution and changes of physical phenomena, geographic information or other complex systems. The time series visualization display of the three-dimensional data field model can convert the three-dimensional data field model that changes over time into an intuitive graphical representation based on the time series data, thereby showing the state and changes of the data at different time points, so as to better understand and analyze the changing trends and characteristics of the data. In the prior art, a single three-dimensional data field model is usually used in combination with time points for processing, thereby obtaining a time series visualization sequence frame.

[0003] Among them, the sequence frame is used to describe a continuous sequence of images such as videos, animations or games. It is composed of a series of static images arranged in a certain order and can be used to play continuously in a short period of time to produce dynamic effects. In the prior art, a difference dynamic filling processing method is usually used to combine the three-dimensional data field model and the key timeline to obtain the time-series visualization sequence frame corresponding to the three-dimensional data field model. However, this method may cause the sequence frame to be incompletely continuous, and even cause the time-series visualization process of the three-dimensional data field model to be stuck, drop frames and other problems, and cannot accurately display the state and changes of the data field at different times.

[0004] Accordingly, a new solution is needed in the art to solve the above problems. Application Contents

[0005] The present application aims to solve the above technical problem, that is, to solve the problem that the time series visualization sequence frames cannot accurately reflect the changes of the data field model at different times.

[0006] In a first aspect, the present application provides a method for generating a temporal visualization sequence frame, comprising:

[0007] Acquire three-dimensional data field model data at at least one moment to construct a three-dimensional data field model;

[0008] Acquire a scalar field data set corresponding to the three-dimensional data field model data at each moment, wherein the scalar field data set is a data set containing scalar attribute values ​​for representing the three-dimensional data field model at the corresponding moment;

[0009] According to the scalar attribute value in the scalar field data set at each moment, color mapping processing is performed on the three-dimensional data field model at the moment, so as to obtain a color mapping result of the three-dimensional data field model at the moment;

[0010] According to the color mapping result of the three-dimensional data field model at each moment, a time-series visualization sequence frame of the three-dimensional data field model is determined.

[0011] In a technical solution of the above-mentioned method for generating a temporal visualization sequence frame,

[0012] The step of performing color mapping processing on the three-dimensional data field model at each moment according to the scalar attribute value in the scalar field data set at the moment to obtain the color mapping result of the three-dimensional data field model at the moment includes:

[0013] Determine the color mapping range of the three-dimensional data field model according to all scalar attribute values ​​in the scalar field data set at all times;

[0014] According to the color mapping range, obtaining a mapping relationship between the scalar attribute value and the color parameter;

[0015] Determine, according to the mapping relationship, a color parameter corresponding to each scalar value attribute value in the scalar field data set at each moment;

[0016] According to the color parameter corresponding to each scalar value attribute value in the scalar field data set at each moment, the color parameter of each point of the three-dimensional data field model at the corresponding moment is determined to obtain the color mapping result of the three-dimensional data field model at the moment.

[0017] In a technical solution of the above-mentioned method for generating a temporal visualization sequence frame,

[0018] Determining the color mapping range of the three-dimensional data field model according to all scalar attribute values ​​in the scalar field data set at all times includes:

[0019] According to the scalar field data set at all times, normalizing all the scalar attribute values;

[0020] Determining a maximum scalar value and a minimum scalar value among all the scalar attribute values ​​after normalized data processing;

[0021] A color mapping range of the three-dimensional data field model is determined according to the maximum scalar value and the minimum scalar value.

[0022] In a technical solution of the above-mentioned method for generating a temporal visualization sequence frame,

[0023] The step of determining the time series visualization sequence frames of the three-dimensional data field model according to the color mapping result of the three-dimensional data field model at each moment includes:

[0024] Acquire a superposition time of the three-dimensional data field model and at least one geometric model, wherein the superposition time is a time when the three-dimensional data field model and the at least one geometric model are superimposed and displayed among all the times corresponding to the three-dimensional data field model data;

[0025] Performing a superposition process of at least one of the geometric models on the three-dimensional data field model at each superposition moment to obtain a geometric model superposition result of the three-dimensional data field model at each superposition moment;

[0026] According to the geometric model superposition results of the three-dimensional data field model at all the superposition moments and the color mapping result of the three-dimensional data field model at each moment, the time-series visualization sequence frame of the three-dimensional data field model is determined.

[0027] In a technical solution of the above-mentioned method for generating a temporal visualization sequence frame,

[0028] The performing superposition processing of at least one of the geometric models on the three-dimensional data field model at each superposition moment to obtain the geometric model superposition result of the three-dimensional data field model at each superposition moment includes:

[0029] For each superposition moment, determining at least one geometric model of the current superposition moment;

[0030] Performing contour extraction on the determined geometric model to obtain at least one corresponding geometric model contour;

[0031] The three-dimensional data field model at the current superposition moment and the at least one geometric model outline are superimposed in the same coordinate system to obtain a geometric model superposition effect of the three-dimensional data field model at the current superposition moment.

[0032] In a technical solution of the above-mentioned method for generating a temporal visualization sequence frame,

[0033] The step of determining the time-series visualization sequence frames of the three-dimensional data field model includes:

[0034] For each moment, according to the color mapping result of the three-dimensional data field model at the current moment, determine the visualization display result of the three-dimensional data field model at the current moment;

[0035] Determine the time series visualization frame at the current moment according to the visualization display result of the three-dimensional data field model at the current moment;

[0036] The time series visualization frames at all moments are arranged in time order to obtain the time series visualization sequence frames, and the time series visualization sequence frames are used to represent the visualization display process of the three-dimensional data field model at all moments.

[0037] In a technical solution of the above-mentioned method for generating a temporal visualization sequence frame,

[0038] The step of acquiring the three-dimensional data field model data at at least one moment to construct the three-dimensional data field model includes:

[0039] Acquire at least one 3D data field model file of at least one moment, and read and parse the 3D data field model file using multi-threading technology to obtain the 3D data field model data in each 3D data field model file, so as to determine the 3D data field model data of the at least one moment;

[0040] Determining a target coordinate system according to a file format of the three-dimensional data field model file;

[0041] The three-dimensional data field model is constructed in the target coordinate system according to the three-dimensional data field model data at at least one moment.

[0042] In a technical solution of the above-mentioned method for generating a temporal visualization sequence frame,

[0043] The step of obtaining a scalar field data set corresponding to the three-dimensional data field model data at each moment includes:

[0044] Determine, according to the three-dimensional data field model file at each moment, a physical property value or a statistical error value associated with each coordinate point of the three-dimensional data field model in the target coordinate system;

[0045] Determine a scalar attribute value associated with each coordinate point according to at least one of the physical attribute value and the statistical error value associated with each coordinate point;

[0046] The scalar data set at the corresponding moment is determined according to the scalar attribute value associated with each coordinate point.

[0047] In a second aspect, a controller is provided, comprising at least one processor; and a memory communicatively connected to the at least one processor; wherein a computer program is stored in the memory, and when the computer program is executed by the at least one processor, the method described in any one of the technical solutions of the above-mentioned method for generating a time-series visualization sequence frame is implemented.

[0048] In a third aspect, a computer-readable storage medium is provided, wherein a plurality of program codes are stored therein, wherein the program codes are suitable for being loaded and run by a processor to execute the method described in any one of the technical solutions of the above-mentioned method for generating a temporal visualization sequence frame.

[0049] The above one or more technical solutions of this application have at least one or more of the following Beneficial effects:

[0050] In the case of adopting the above technical solution, the present application can obtain the three-dimensional data field model data of at least one moment to construct the three-dimensional data field model, obtain the scalar field data set corresponding to the three-dimensional data field model data at each moment, and perform color mapping processing on the visualization display of the three-dimensional data field model at the corresponding moment according to the scalar attribute value in the scalar field data set at each moment, and determine the time series visualization sequence frame of the three-dimensional data field model according to the color mapping result of the three-dimensional data field model at each moment. Through the above configuration method, the three-dimensional data field model at each moment can be color mapped by the scalar attribute value of the three-dimensional data field model at each moment, so that the final obtained time series visualization sequence frame can accurately reflect the change of the scalar attribute value of the three-dimensional data field model in the time dimension through the color change during the dynamic display process. In this way, by determining the three-dimensional data field model at each moment by the scalar attribute value to determine each frame in the time series visualization sequence frame, it is possible to avoid the situation where one or more frames are missing in the time series visualization sequence frame, reduce the problem of frame jamming and frame dropping of the time series visualization sequence frame, and then realize the accurate display of the change of the scalar attribute value of the three-dimensional data field model at different times by the time series visualization sequence frame. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The preferred embodiments of the present application are described below in conjunction with the accompanying drawings, in which:

[0052] Figure 1 It is a flowchart of the main steps of a method for generating a time series visualization sequence frame according to an embodiment of the present application;

[0053] Figure 2 This is a flowchart of the main steps of an implementation method of a time series visualization sequence frame generation method according to an embodiment of the present application;

[0054] Figure 3 is a schematic diagram of a timing file selection interface for obtaining multiple timing files in an embodiment of the present application;

[0055] Figure 4 is a schematic diagram of visualization results of a three-dimensional data field model corresponding to the first time series file in an embodiment of the present application;

[0056] FIG5 is a schematic diagram of a dynamic visualization result of a visualization sequence frame in an embodiment of the present application;

[0057] 6 is a schematic diagram of a dynamic visualization result of a visualization sequence frame after a three-dimensional data field model is superimposed on a geometric model in an embodiment of the present application;

[0058] Figure 7 It is a schematic diagram of the main structure of a controller according to an embodiment of the present application. DETAILED DESCRIPTION

[0059] Some embodiments of the present application are described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present application and are not intended to limit the protection scope of the present application.

[0060] In the description of the present application, "module" and "processor" may include hardware, software or a combination of the two. A module may include hardware circuits, various suitable sensors, communication ports, memory, and may also include software parts, such as program code, or a combination of software and hardware. The processor may be a central processing unit, a microprocessor, an image processor, a digital signal processor or any other suitable processor. The processor has data and / or signal processing functions. The processor may be implemented in software, hardware or a combination of the two. Computer-readable storage media include any suitable medium that can store program code, such as a disk, a hard disk, an optical disk, a flash memory, a read-only memory, a random access memory, etc. The term "A and / or B" means all possible combinations of A and B, such as only A, only B or A and B. The term "at least one A or B" or "at least one of A and B" has a similar meaning to "A and / or B" and may include only A, only B or A and B. The singular terms "one" and "the" may also include plural forms.

[0061] See attached Figure 1 , Figure 1 FIG. 1 is a flow chart of the main steps of a method for generating a temporal visualization sequence frame according to an embodiment of the present application. Figure 1 As shown, the method for generating a temporal visualization sequence frame in the embodiment of the present application mainly includes the following steps S101 to S104.

[0062] Step S101: Acquire three-dimensional data field model data of at least one moment to construct a three-dimensional data field model.

[0063] In this embodiment, the three-dimensional data field model is a data model used to represent continuous distribution in three-dimensional space, and is mainly used to describe physical quantities or attributes that change continuously in three-dimensional space. The three-dimensional data field model can describe the data distribution in three-dimensional space through a series of grid points, and each grid point records the data value at that position, which may include physical quantities such as temperature, pressure or concentration, thereby constructing the data distribution of the entire three-dimensional space.

[0064] In this embodiment, the three-dimensional data field model data may include the three-dimensional space coordinate system required to construct the three-dimensional data field model, and may also include the physical value and statistical error value associated with each coordinate point of the three-dimensional data field model at each moment.

[0065] In one implementation, step S101 may further include steps S1011 to S1013:

[0066] Step S1011: Obtain at least one 3D data field model file of at least one moment, and use multi-threading technology to read and parse the 3D data field model file to obtain the 3D data field model data in each 3D data field model file to determine the 3D data field model data of at least one moment.

[0067] Step S1012: Determine the target coordinate system according to the file format of the three-dimensional data field model file.

[0068] Step S1013: constructing a three-dimensional data field model in a target coordinate system according to the three-dimensional data field model data at at least one moment.

[0069] In this embodiment, step S1011 can use multi-threading technology to batch read the three-dimensional data field model files. Each three-dimensional data field model file can contain three-dimensional data field model data at a time. The three-dimensional data field model data can include various data required to build a three-dimensional model, such as geometric data, texture and material data, and animation data.

[0070] In one implementation, step S1012 may specifically include: if the file format of the three-dimensional data field model file is a stereolithography (STereo Lithography, STL) format or a 3D manufacturing (3D Manufacturing Format, 3MF) format, the target coordinate system may be determined as a Cartesian coordinate system; if the file format of the three-dimensional data field model file is a cylindrical surface tessellation language (Surface Tessellation Language, STL) format, the target coordinate system may be determined as a cylindrical coordinate system.

[0071] In one implementation, step S1013 may specifically include: processing the 3D data field model data at each moment, and extracting the 3D spatial coordinates of each point of the 3D data field model in the target coordinate system. If the geometric shape of the 3D data field model does not change at all moments, a 3D data field model may be constructed using the 3D data field model data at the first moment or any other moment, and the 3D data field model may be visualized and rendered using a visualization toolkit (Vtk).

[0072] In some other implementations, only the three-dimensional data field model at one time may be visually rendered, and the three-dimensional data field models at other times may be hidden and not displayed.

[0073] Step S102: Obtain the scalar field data set corresponding to the three-dimensional data field model data at each moment.

[0074] In this embodiment, the scalar field data set is a data set containing scalar attribute values ​​for representing the three-dimensional data field model at a corresponding moment.

[0075] In this embodiment, the three-dimensional data field model data may include the coordinate data of each point in the three-dimensional space coordinate system where the three-dimensional data field model is located. The scalar field data set may include the scalar attribute value associated with each point of the three-dimensional data field model. The data in the scalar field data set may change according to different times.

[0076] In one implementation, the scalar field data set may exist in the form of a function, for example, the scalar T may be a three-variable function of x, y, and z, that is, T = f(x, y, z), where (x, y, z) are the coordinates of a point in a three-dimensional space coordinate system, and T is used to represent the scalar attribute value corresponding to the point.

[0077] In one implementation, step S102 may further include steps S1021 to S1023:

[0078] Step S1021: determining the physical property value or statistical error value associated with each coordinate point of the three-dimensional data field model in the target coordinate system according to the three-dimensional data field model file at each moment.

[0079] Step S1022: Determine the scalar attribute value associated with each coordinate point according to at least one of the physical attribute value and the statistical error value associated with each coordinate point.

[0080] Step S1023: Determine the scalar data set at the corresponding moment according to the scalar attribute value associated with each coordinate point.

[0081] In this embodiment, the scalar attribute value can have two data source types, namely, physical attribute value and statistical error value. The physical attribute value can be the actual value of a physical quantity such as temperature, air pressure, humidity, etc. The statistical error value can be the difference between the actual value obtained by the physical attribute value and the corresponding objective true value.

[0082] In one implementation, in step S1022, one of the physical property values ​​or the statistical error values ​​can be selected according to user needs to determine the scalar property value, and then the final scalar data set at each moment can be determined. Alternatively, a type of scalar property value can be randomly selected to determine the final scalar data set, both of which will not affect the normal implementation of this embodiment.

[0083] In other implementations, step S1022 can simultaneously determine a scalar data set including a physical value of an attribute as a scalar attribute value, and a scalar data set including a statistical error value as a scalar attribute value, and respectively perform color mapping processing of the subsequent step S103 on the two scalar data sets, so as to show the user the data changes of the two scalar attribute values ​​of the three-dimensional data field model in the time dimension. In some implementations, the scalar attribute values ​​can also be switched in the user display interface, all within the protection scope of the embodiments of the present application.

[0084] Step S103: performing color mapping processing on the three-dimensional data field model at each moment according to the scalar attribute value in the scalar field data set at that moment, and obtaining a color mapping result of the three-dimensional data field model at that moment.

[0085] In this embodiment, the color mapping process refers to mapping the scalar attributes in the data set to the color space. Different colors are selected for representation according to different scalar values ​​of various parts in the data set.

[0086] In one implementation, step S103 may further include steps S1031 to S1034:

[0087] Step S1031: Determine the color mapping range of the three-dimensional data field model according to all scalar attribute values ​​in the scalar field data set at all times.

[0088] Step S1032: Obtain a mapping relationship between scalar attribute values ​​and color parameters according to the color mapping range.

[0089] Step S1033: Determine the color parameter corresponding to each scalar value attribute value in the scalar field data set at each moment according to the mapping relationship.

[0090] Step S1034: according to the color parameter corresponding to each scalar value attribute value in the scalar field data set at each moment, determine the color parameter of each point of the three-dimensional data field model at the corresponding moment, and obtain the color mapping result of the three-dimensional data field model at that moment.

[0091] In this implementation, the scalar attribute value may be mapped to different colors according to the size of the scalar attribute value. The smaller the scalar attribute value, the lighter the corresponding color, and the larger the scalar attribute value, the darker the corresponding color.

[0092] In one implementation, step S1031 may further include steps S10311 to S10313:

[0093] Step S10311: Based on the scalar field data set at all times, all scalar attribute values ​​are normalized.

[0094] Step S10312 determines the maximum scalar value and the minimum scalar value among all scalar attribute values ​​after normalized data processing.

[0095] Step S10313: Determine the color mapping range of the three-dimensional data field model according to the maximum scalar value and the minimum scalar value.

[0096] In this embodiment, the normalized data processing is used to standardize the scalar attribute values ​​according to preset rules to eliminate the differences between all scalar attribute values, making the overall data more comparable.

[0097] In this embodiment, the maximum scalar value refers to the maximum value of all scalar attribute values; the minimum scalar value refers to the minimum value of all scalar attribute values. By determining the maximum scalar value and the minimum scalar value, all scalar attribute values ​​of different sizes can be mapped to the same color mapping range, thereby achieving unified mapping of colors corresponding to all scalar attribute values.

[0098] In one implementation, step S10312 may first obtain the maximum scalar value and the minimum scalar value in the scalar field data set at each moment, and then determine the maximum scalar value and the minimum scalar value in all scalar attribute values ​​at all moments from the maximum scalar value and the minimum scalar value in all scalar field data sets.

[0099] In this embodiment, the color parameter of step S1032 refers to a numerical value or code used to describe and represent a color. For example, the color parameter may be a color parameter of the type of luminous (Red Green Blue, RGB) color parameter, reflective (Cyan Magenta Yellow Black, CMYK) color parameter, or brightness (Luminosity Red-Green Yellow-Blue, Lab) color parameter.

[0100] In this embodiment, the mapping relationship is used to store the corresponding relationship between the scalar attribute value and the color parameter. In step S1032, a corresponding color parameter can be assigned to each scalar attribute value according to the size of the scalar attribute value to obtain the mapping relationship.

[0101] Step S1034 can implement mapping from scalar attribute values ​​to color parameters through a color mapping function, wherein the color mapping function is a function used in VTK technology to implement model visualization, which can convert numerical data into RGB color values, so that the visualization effect in the three-dimensional data field model represents different data features.

[0102] In this embodiment, by mapping the scalar attribute values ​​at all times into the same color mapping range, the changes of the three-dimensional data field model in different time dimensions can be reflected, avoiding the problem of the scalar attribute values ​​changing at different times while the three-dimensional data field model remains unchanged, which meets the actual user's needs for building a three-dimensional data field model.

[0103] Step S104: determining a time-series visualization sequence frame of the three-dimensional data field model according to the color mapping result of the three-dimensional data field model at each moment.

[0104] In this embodiment, the color mapping result may be a visualization effect of the three-dimensional data field model that completes the color mapping at all times. A time-series visualization sequence frame is a continuous image sequence used to describe a video, animation, or game, and may be composed of a series of static images with timestamps. The time-series visualization sequence frame may be arranged in chronological order and each image frame may be played sequentially and continuously, thereby producing a dynamic effect.

[0105] In one implementation, step S104 may further include steps S1041 to S1043:

[0106] Step S1041: Obtain the superposition moment of the three-dimensional data field model and at least one geometric model.

[0107] Step S1042: performing at least one geometric model superposition process on the three-dimensional data field model at each superposition moment to obtain a geometric model superposition result of the three-dimensional data field model at each superposition moment.

[0108] Step S1043: Determine the time-series visualization sequence frame of the three-dimensional data field model according to the geometric model superposition results of the three-dimensional data field model at all superposition moments and the color mapping result of the three-dimensional data field model at each moment.

[0109] In this embodiment, the superposition time may be a time when the three-dimensional data field model and at least one geometric model are superimposed and displayed among all the time points corresponding to the three-dimensional data field model data.

[0110] In one implementation, before step S1041 , it can be determined whether it is necessary to display the superposition effect of the three-dimensional data field model and the geometric model according to user needs. If necessary, proceed to step S1041 .

[0111] In this embodiment, there may be multiple superposition moments in all moments to superimpose and display the three-dimensional data field model and the geometric model. Each superposition moment may correspond to a moment of the three-dimensional data field model data. For each superposition moment, the three-dimensional data field model corresponding to the superposition moment may be superimposed with one or more data field models, which does not affect the normal implementation of this embodiment.

[0112] In one implementation, step S1041 can obtain the geometric model data file by the user selecting the geometric model to be superimposed, and determine the superimposition time according to the corresponding time of the geometric model data file.

[0113] In this embodiment, the geometric model data file may be in a computer-aided design (CAD) model format.

[0114] In one implementation, step S1042 may further include:

[0115] Step S10421: For each superposition moment, determine at least one geometric model of the current superposition moment.

[0116] Step S10422: extract the contour of the determined geometric model to obtain at least one corresponding geometric model contour.

[0117] Step S10423: superimpose the three-dimensional data field model at the current superposition moment and at least one geometric model outline in the same coordinate system to obtain a geometric model superposition effect of the three-dimensional data field model at the current superposition moment.

[0118] In this embodiment, in step S10421, at least one geometric model corresponding to each moment may be constructed in advance based on the acquired geometric model data file at each moment.

[0119] In this embodiment, the outline of the geometric model may be an edge line of the geometric model, that is, a boundary of the geometric model.

[0120] In one implementation, the coordinate value of each point of the geometric model in the three-dimensional space coordinate system can be extracted from the geometric model data file, and then the geometric model can be constructed in the target coordinate system using VTK technology so that the geometric model and the three-dimensional data field model can be superimposed in the same coordinate system.

[0121] In one implementation, in step S10422, a clipping filter in VTK technology may be used to extract the contour of the geometric model in the target coordinate system. For example, a vtkFeatureEdges filter may be used to obtain the contour line of the geometric model, or a vtkClipPolyData filter may be used to obtain the geometric model contour data of the geometric model.

[0122] In one implementation, step S1043 may further include:

[0123] Step S10431: for each moment, determine the visualization display result of the three-dimensional data field model at the current moment according to the color mapping result of the three-dimensional data field model at the current moment.

[0124] Step S10432: Determine the temporal visualization frame at the current moment according to the visualization display result of the three-dimensional data field model at the current moment.

[0125] Step S10433: Arrange the time series visualization frames at all moments in chronological order to obtain time series visualization sequence frames.

[0126] In this embodiment, the time-series visualization sequence frames are used to represent the visualization display process of the three-dimensional data field model at all times.

[0127] In this implementation, the time series visualization frame may be a visualization display image or image file of the three-dimensional data field model at a moment.

[0128] In one embodiment, step S10432 can save the time series visualization frame of the current moment into a model file, and set a timestamp for the model file according to the current moment, so that the subsequent step S10433 arranges the model files of all moments in timestamp order to generate the final time series visualization sequence frame.

[0129] In an application scenario according to an embodiment of the present application, please refer to the attached Figure 2 , attached Figure 2 FIG. 1 is a flow chart of the main steps of an implementation method of a time series visualization sequence frame generation method according to an embodiment of the present application. Figure 2 As shown, this embodiment may further include steps S201 to S206:

[0130] Step S201: Read and analyze data field files at different times to obtain data field model data.

[0131] In this embodiment, the data field file may be a time sequence file, which can be obtained by obtaining a time sequence file uploaded or selected by a user through a user interaction interface. Figure 3 , attached Figure 3 1 is a schematic diagram of a timing file selection interface for obtaining multiple timing files in an embodiment of the present application. In some other implementations, the order of the timing files can be adjusted in real time according to user needs.

[0132] Step S202: pre-processing the data field model data.

[0133] In this embodiment, the preprocessing may include operations such as determining the type of scalar field data corresponding to the data field model data, determining whether to superimpose with the geometric model contour, and determining the coordinate system for constructing the data field model. The type of scalar field data may include physical values ​​and statistical error values, and the coordinate system may include a Cartesian coordinate system and a cylindrical coordinate system.

[0134] Step S203: constructing a three-dimensional data field model according to the preprocessed data field model data.

[0135] In this embodiment, the data field model can be constructed based on the data field model data in the first time series file. Figure 4 , attached Figure 4 is a schematic diagram of the visualization result of the three-dimensional data field model corresponding to the first time series file in the embodiment of the present application. Figure 4 As shown, Figure 4 The data field model in is the three-dimensional data field model corresponding to the first time series file.

[0136] Among them, Figure 4 In the Time Dynamic box, Time is used to indicate the time corresponding to the current three-dimensional data field model, and its drop-down box can display the time of all input time series files; DataSource is used to indicate the type of scalar field data, that is, physical value (Result) or statistical error (Rlt Error); Max and Min are used to indicate the maximum and minimum values ​​of the scalar field data at the current moment, respectively; showOutline is used to indicate whether to display the outline of the superposition of the data field model and the geometric model; TimeStart is used to indicate the start button for time series dynamic visualization of the three-dimensional data field model in chronological order.

[0137] Step S204: Obtain the scalar field color mapping range of the three-dimensional data field model.

[0138] In this embodiment, the scalar field color mapping range may be determined according to the maximum and minimum values ​​of all scalar field data, in the same manner as determining the color mapping range in step S1031 above.

[0139] Step S205: Determine the color mapping result of the three-dimensional data field model.

[0140] Step S206: Generate a time series visualization sequence frame.

[0141] In one implementation, please refer to FIG. 5, which is a main schematic diagram of the dynamic visualization result of the visualization sequence frame in the embodiment of the present application. As shown in FIG. 5, FIG. 5 is a visualization sequence frame including three moments, wherein FIG. 5(a), FIG. 5(b) and FIG. 5(c) are each a visualization frame, and each visualization frame is arranged in chronological order and visualized in sequence to display the dynamic visualization result of the visualization sequence frame.

[0142] In one implementation, if the user chooses to display the visualization result of the superposition of the three-dimensional data field model and the geometric model outline, this implementation may further include:

[0143] Step S301: Read and parse geometric model files at different times to obtain geometric model data.

[0144] In this embodiment, the geometric model data may include data required to construct the geometric model and scalar field data of the geometric model.

[0145] Step S302: construct a geometric model according to the geometric model data, and perform color mapping on the geometric model.

[0146] In this embodiment, the data required to construct the geometric model may include the coordinate data of the geometric model in the spatial coordinate system for constructing the three-dimensional data field model, so that the geometric model can be constructed in the same coordinate system as the three-dimensional data field model.

[0147] In one implementation, a unified color mapping range may be determined based on the scalar field data of the three-dimensional data field model and the geometric model, thereby achieving color mapping within the same color mapping range.

[0148] Step S303: extracting the outline of the geometric model after color mapping.

[0149] Step S304: superimpose the outline of the geometric model with the three-dimensional data field model, and proceed to step S206.

[0150] In one implementation, please refer to FIG6, which is a schematic diagram of the dynamic visualization result of the visualization sequence frame after the three-dimensional data field model in the embodiment of the present application is superimposed with the geometric model. As shown in FIG6, FIG6 is a visualization sequence frame superimposed with the geometric model outline at three moments, wherein FIG6 (a), FIG6 (b) and FIG6 (c) are visualization frames at different moments, and each visualization frame is arranged in chronological order and visualized in sequence to display the dynamic visualization result of the visualization sequence frame superimposed with the geometric model outline.

[0151] Based on the methods described in steps S101 to S104 above, this embodiment can perform color mapping on the three-dimensional data field model at each moment through the scalar attribute value of the three-dimensional data field model at each moment, so that the final obtained time series visualization sequence frame can accurately reflect the changes in the scalar attribute value of the three-dimensional data field model in the time dimension through the color changes during the dynamic display process. In this way, by determining the three-dimensional data field model at each moment by the scalar attribute value to determine each frame in the time series visualization sequence frame, it is possible to avoid the situation where one or more frames are missing in the time series visualization sequence frame, reduce the problem of frame freeze and drop of the time series visualization sequence frame, and thus realize the accurate display of the changes in the scalar attribute value of the three-dimensional data field model at different times by the time series visualization sequence frame.

[0152] It should be pointed out that although the various steps in the above embodiments are described in a specific order, those skilled in the art can understand that in order to achieve the effect of the present application, different steps do not have to be performed in such an order, they can be performed simultaneously or in other orders. These adjusted schemes are equivalent to the technical schemes described in this application, and therefore will also fall within the scope of protection of this application.

[0153] It is understood by those skilled in the art that the present application implements all or part of the processes in the time series visualization sequence frame generation method of any of the above embodiments, and can also be completed by instructing related hardware through a computer program, and the computer program can be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of each of the above method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc.

[0154] Another aspect of the present application also provides a computer-readable storage medium.

[0155] In an embodiment of a computer-readable storage medium according to the present application, the computer-readable storage medium may be configured to store a program for executing the method for generating a time-series visualization sequence frame in the above-mentioned method embodiment, and the program may be loaded and run by a processor to implement the above-mentioned method for generating a time-series visualization sequence frame. For ease of explanation, only the parts related to the embodiment of the present application are shown. For specific technical details not disclosed, please refer to the method part of the embodiment of the present application. The computer-readable storage medium may be a storage device formed by various electronic devices. Optionally, the computer-readable storage medium in the embodiment of the present application is a non-temporary computer-readable storage medium.

[0156] Another aspect of the present application also provides a controller.

[0157] In an embodiment of a controller according to the present application, the controller may include at least one processor; and a memory connected to the at least one processor in communication; wherein a computer program is stored in the memory, and when the computer program is executed by the at least one processor, the method for generating a time-series visualization sequence frame described in any of the above embodiments is implemented. Figure 7 , Figure 7 FIG. 4 exemplarily shows that the memory 11 and the processor 12 are communicatively connected via a bus.

[0158] So far, the technical solutions of the present application have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present application is obviously not limited to these specific embodiments. Without departing from the principles of the present application, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present application.

Claims

1. A method for generating a temporal visualization sequence frame, characterized in that: The method comprises: Acquire three-dimensional data field model data at at least one moment to construct a three-dimensional data field model; Acquire a scalar field data set corresponding to the three-dimensional data field model data at each moment, wherein the scalar field data set is a data set containing scalar attribute values ​​for representing the three-dimensional data field model at the corresponding moment; According to the scalar attribute value in the scalar field data set at each moment, color mapping processing is performed on the three-dimensional data field model at the moment, so as to obtain a color mapping result of the three-dimensional data field model at the moment; According to the color mapping result of the three-dimensional data field model at each moment, a time-series visualization sequence frame of the three-dimensional data field model is determined.

2. The method for generating a temporal visualization sequence frame according to claim 1, characterized in that: The step of performing color mapping processing on the three-dimensional data field model at each moment according to the scalar attribute value in the scalar field data set at the moment to obtain the color mapping result of the three-dimensional data field model at the moment includes: Determine the color mapping range of the three-dimensional data field model according to all scalar attribute values ​​in the scalar field data set at all times; According to the color mapping range, obtaining a mapping relationship between the scalar attribute value and the color parameter; Determine, according to the mapping relationship, a color parameter corresponding to each scalar value attribute value in the scalar field data set at each moment; According to the color parameter corresponding to each scalar value attribute value in the scalar field data set at each moment, the color parameter of each point of the three-dimensional data field model at the corresponding moment is determined to obtain the color mapping result of the three-dimensional data field model at the moment.

3. The method for generating time series visualization sequence frames according to claim 2, characterized in that: Determining the color mapping range of the three-dimensional data field model according to all scalar attribute values ​​in the scalar field data set at all times includes: According to the scalar field data set at all times, normalizing all the scalar attribute values; Determining a maximum scalar value and a minimum scalar value among all the scalar attribute values ​​after normalized data processing; A color mapping range of the three-dimensional data field model is determined according to the maximum scalar value and the minimum scalar value.

4. The method for generating time series visualization sequence frames according to claim 1, characterized in that: The step of determining the time series visualization sequence frames of the three-dimensional data field model according to the color mapping result of the three-dimensional data field model at each moment includes: Acquire a superposition time of the three-dimensional data field model and at least one geometric model, wherein the superposition time is a time when the three-dimensional data field model and the at least one geometric model are superimposed and displayed among all the times corresponding to the three-dimensional data field model data; Performing a superposition process of at least one of the geometric models on the three-dimensional data field model at each superposition moment to obtain a geometric model superposition result of the three-dimensional data field model at each superposition moment; According to the geometric model superposition results of the three-dimensional data field model at all the superposition moments and the color mapping result of the three-dimensional data field model at each moment, the time-series visualization sequence frame of the three-dimensional data field model is determined.

5. The method for generating time series visualization sequence frames according to claim 4, characterized in that: The performing superposition processing of at least one of the geometric models on the three-dimensional data field model at each superposition moment to obtain the geometric model superposition result of the three-dimensional data field model at each superposition moment includes: For each superposition moment, determining at least one geometric model of the current superposition moment; Performing contour extraction on the determined geometric model to obtain at least one corresponding geometric model contour; The three-dimensional data field model at the current superposition moment and the at least one geometric model outline are superimposed in the same coordinate system to obtain a geometric model superposition effect of the three-dimensional data field model at the current superposition moment.

6. The method for generating a temporal visualization sequence frame according to claim 1 or claim 4, characterized in that: The step of determining the time-series visualization sequence frames of the three-dimensional data field model includes: For each moment, according to the color mapping result of the three-dimensional data field model at the current moment, determine the visualization display result of the three-dimensional data field model at the current moment; Determine the time series visualization frame at the current moment according to the visualization display result of the three-dimensional data field model at the current moment; The time series visualization frames at all moments are arranged in time order to obtain the time series visualization sequence frames, and the time series visualization sequence frames are used to represent the visualization display process of the three-dimensional data field model at all moments.

7. The method for generating time series visualization sequence frames according to claim 1, characterized in that: The step of acquiring the three-dimensional data field model data at at least one moment to construct the three-dimensional data field model includes: Acquire at least one 3D data field model file of at least one moment, and read and parse the 3D data field model file using multi-threading technology to obtain the 3D data field model data in each 3D data field model file, so as to determine the 3D data field model data of the at least one moment; Determining a target coordinate system according to a file format of the three-dimensional data field model file; The three-dimensional data field model is constructed in the target coordinate system according to the three-dimensional data field model data at at least one moment.

8. The method for generating time series visualization sequence frames according to claim 7, characterized in that: The step of obtaining a scalar field data set corresponding to the three-dimensional data field model data at each moment includes: Determine, according to the three-dimensional data field model file at each moment, a physical property value or a statistical error value associated with each coordinate point of the three-dimensional data field model in the target coordinate system; Determine a scalar attribute value associated with each coordinate point according to at least one of the physical attribute value and the statistical error value associated with each coordinate point; The scalar data set at the corresponding moment is determined according to the scalar attribute value associated with each coordinate point.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein the program executes the method for generating a temporal visualization sequence frame according to any one of claims 1 to 8 when running.

10. A controller comprising a memory and a processor, characterized in that: The memory stores a computer program, and the processor is configured to execute the method for generating a temporal visualization sequence frame according to any one of claims 1 to 8 through the computer program.

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