CN113190726A - Method for reading CAE (computer aided engineering) modular flow analysis data, electronic equipment and storage medium - Google Patents
Method for reading CAE (computer aided engineering) modular flow analysis data, electronic equipment and storage medium Download PDFInfo
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- G06F16/90—Details of database functions independent of the retrieved data types
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- G—PHYSICS
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Abstract
The application relates to a method for reading CAE modular flow analysis data. The method comprises the following steps: acquiring first modular flow analysis data; matching with the first modular flow analysis data using target data features, the target data features comprising: a start identifier and an end identifier of the data; and storing the first modular flow analysis data with the data characteristics into a designated storage area as second modular flow analysis data, wherein the second modular flow analysis data is a subset of the first modular flow analysis data. The scheme provided by the application greatly saves the time of manual operation and can improve the speed of searching and extracting the modular flow analysis data.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a method for reading CAE modular stream analysis data, an electronic device, and a storage medium.
Background
With the continuous development and progress of injection molding production technology, mold flow analysis before product mold opening is gradually applied more widely, and is consistently recognized by professional manufacturers and technicians in the fields of product development, mold manufacturing and the like, and increasingly plays a powerful role. The best of the CAE software MOLDFLOW is the industry leading CAE software MOLDFLOW.
After the simulation analysis (i.e. mold flow analysis) before the mold opening is performed on the product, the analysis software can automatically generate a preset analysis result in the software, wherein the preset analysis result comprises an injection molding GIF (graphics interchange Format) moving picture, a product shrinkage condition, a weld line condition, a product deformation condition and the like. However, some other important analysis result information is not displayed in the result interface intuitively as a result, but is generated and stored as basic information, which is a lot of important information in the basic log information as shown in the following drawings. If the log needs to be checked, selected or used as basic data for subsequent processing, the method comprises the steps of opening software, opening an analysis scheme, opening an analysis log, checking the log line by line, selecting information required in the log, copying the information into a file required to be used, processing the copied data and the like.
Because the log has a lot of information, each search consumes a lot of time, the whole copying and pasting process also needs much time, manpower is wasted, and unpredictable errors may occur.
Disclosure of Invention
In order to overcome the problems in the related art, the application provides a method for reading CAE modular flow analysis data, and the method for reading CAE modular flow analysis data can improve the speed of searching and extracting the modular flow analysis data.
The first aspect of the present application provides a method for reading CAE modular flow analysis data, including:
acquiring first modular flow analysis data;
matching with the first modular flow analysis data using target data features, the target data features comprising: a start identifier and an end identifier of the data;
and storing the first modular flow analysis data with the target data characteristics into a designated storage area as second modular flow analysis data, wherein the second modular flow analysis data is a subset of the first modular flow analysis data.
In a first possible implementation method of the first aspect, the modular flow analysis data is basic log information of modular flow analysis, and the modular flow analysis data includes: product basic data, model detail data and filling analysis data;
the start identifier is a designated symbol and designation of the start position of one type of data;
the end marker is a designated symbol and designation of the end location of one type of data.
In a second possible implementation of the method of the first aspect, the obtaining the first modular flow analysis data includes:
acquiring a file name of first modular stream analysis data;
assigning the file name to a file variable;
the file variable acquires a storage path of the first modular flow analysis data according to the file name;
opening the deposit path through an open function;
and acquiring data under the storage path to obtain the first modular flow analysis data.
In a third possible implementation of the method of the first aspect, the matching using the target data feature with the first modular flow analysis data comprises:
importing a regular expression;
setting the regular expression as: w1+ X + W2, the W1 being the start marker, the W2 being the end marker, the X being any value between the start marker and the end marker;
and searching the first modular flow analysis data by using the regular expression.
With reference to the third possible implementation method of the first aspect, in a fourth possible implementation method, the storing the first modular stream analysis data with the target data characteristics into a designated storage area as the second modular stream analysis data includes:
assigning the first modular flow analysis data which accords with the regular expression to a variable result;
and writing the variable result into a specified storage area through a for loop to obtain the second modular stream analysis data.
In a fifth possible implementation method of the first aspect, after the storing the first modular flow analysis data with the target data characteristic in a designated storage area as the second modular flow analysis data, the method further includes:
classifying the second modular flow analysis data according to the target data characteristics;
respectively creating Excel tables according to the second modular flow analysis data of different types;
and writing the second modular flow analysis data of the same type into the same Excel table.
With reference to the fifth possible implementation method of the first aspect, in a sixth possible implementation method, after the writing the second modular flow analysis data into the Excel table, the method further includes:
and converting the data in the Excel table into a coordinate image, wherein the coordinate image comprises a scatter point coordinate graph and a line graph.
With reference to the fourth possible implementation method of the first aspect, in a seventh possible implementation method, the writing the variable result into the specified storage area through a for loop includes:
classifying the variable result according to the target data characteristics;
and respectively writing the classified variable result modules into the specified storage areas through a for loop.
A second aspect of the present application provides an electronic device, comprising:
a processor; and
a memory having executable code stored thereon, which when executed by the processor, causes the processor to perform the method as described above.
A third aspect of the application provides a non-transitory machine-readable storage medium having stored thereon executable code which, when executed by a processor of an electronic device, causes the processor to perform a method as described above.
The technical scheme provided by the application can comprise the following beneficial effects:
analyzing data by acquiring a first module flow; matching with the first modular flow analysis data using target data features, the target data features comprising: a start identifier and an end identifier of the data; and storing the first modular flow analysis data with the target data characteristics into a designated storage area as second modular flow analysis data. According to the scheme, all the module flow analysis data are screened by using the specific target data characteristics of the necessary module flow analysis data, and the module flow analysis data meeting the screening condition are stored to the specified position, so that the time of manual operation is saved, and the data searching and extracting efficiency is improved.
Another beneficial effect of this scheme is: the data are screened and extracted by the computer, so that the accuracy of the obtained data is ensured.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
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The foregoing and other objects, features and advantages of the application will be apparent from the following more particular descriptions of exemplary embodiments of the application, as illustrated in the accompanying drawings wherein like reference numbers generally represent like parts throughout the exemplary embodiments of the application.
FIG. 1 is a schematic flow chart diagram illustrating a method for reading CAE modular flow analysis data according to an embodiment of the present application;
FIG. 2 is another schematic flow chart diagram illustrating a method for reading CAE modular flow analysis data according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an electronic device shown in an embodiment of the present application.
Detailed Description
Preferred embodiments of the present application will be described in more detail below with reference to the accompanying drawings. While the preferred embodiments of the present application are shown in the drawings, it should be understood that the present application may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this application and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It should be understood that although the terms "first," "second," "third," etc. may be used herein to describe various information, these information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the present application. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present application, "a plurality" means two or more unless specifically limited otherwise.
The analysis result information generated after the existing CAE software completes the modular flow analysis contains important information and unnecessary information, when the important information part needs to be used, the software needs to be opened, the analysis scheme needs to be opened, the analysis log needs to be opened, and then the line-by-line search is carried out, so that the process is complicated, and the data is inconvenient to search and utilize.
In view of the above problems, embodiments of the present application provide a method for reading CAE modular flow analysis data, which can simplify a process of searching data, improve data searching efficiency, and facilitate data utilization.
The technical solutions of the embodiments of the present application are described in detail below with reference to the accompanying drawings.
Fig. 1 is a schematic flowchart illustrating a method for reading CAE modular stream analysis data according to an embodiment of the present application.
Referring to fig. 1, a method for analyzing data by CAE modular flow in an embodiment of the present application includes:
101. acquiring first modular flow analysis data;
the CAE (computer Aided engineering) refers to the computer Aided engineering in engineering design, and refers to the analysis of the structural mechanical properties of complex engineering and products by computer Aided solution, and the optimization of structural properties, etc., and all the links of engineering (production) are organically organized, and its key is to integrate the related information, so that it can be produced and existed in the whole life cycle of engineering (products). The CAE software can be used for static structure analysis and dynamic analysis; researching linear and nonlinear problems; analytical structures (solid), fluid, electromagnetic, etc.
The concept of mold FLOW analysis (molflow) is derived from the nomenclature of taiwan, and actually means that data simulation software is used, the simulation of injection molding is completed through a computer, the injection molding process of a mold is simulated, some data results are obtained, the feasibility of the scheme of the mold is evaluated through the results, the design scheme of the mold and the design scheme of a product are perfected, common software of plastic molds comprises molflow, Moldex3D and the like, and common aluminum alloy die casting comprises PROCAST, FLOW3D and the like.
The first module flow analysis data is all basic log information which is automatically generated by the CAE software before the die sinking of the die product and is not displayed on a result interface as an analysis result.
In the embodiment of the application, all basic log information is exported from CAE software and stored in a designated storage area, then a storage path of the storage area is assigned to a program capable of automatically reading data, and the program reads the data in the storage area by opening the storage area where the obtained storage path is located, so as to achieve acquisition of first modular flow analysis data.
102. Matching with the first modular flow analysis data using target data features, the target data features comprising: a start identifier and an end identifier of the data;
the basic log information contains many different types of data, such as product basic information and injection molding filling information, and the start identifier and the end identifier of the same type of basic log information are the same, that is, the same type of modular stream analysis data has the same characters.
In the embodiment of the present application, by using the data characteristics of the target data, that is: the first modular stream analysis data is matched with the same characters of the type of data to be viewed or utilized.
103. Storing the first modular stream analysis data with the target data characteristics into a designated storage area as the second modular stream analysis data, wherein the second modular stream analysis data is a subset of the first modular stream analysis data;
the second module flow analyzes data, namely basic log information needing to be checked and utilized;
in the embodiment of the application, the first modular stream analysis data successfully matched with the target data characteristics for matching is the second modular stream analysis data which is the basic log information needing to be checked and utilized, and the part of data is copied from the first modular stream analysis data and stored in the specified storage area.
The method comprises the steps of acquiring first modular flow analysis data; matching the target data characteristics of the second modular flow analysis data with the first modular flow analysis data, wherein the data characteristics comprise: a start identifier and an end identifier of the data; and storing the first modular flow analysis data with the target data characteristics into a designated storage area as second modular flow analysis data. According to the scheme, all the module flow analysis data are screened by using the characteristic of the target data peculiar to the necessary module flow analysis data, the module flow analysis data meeting the screening condition are stored in the designated area, when the part of the module flow analysis data needs to be checked and utilized, the designated storage area is directly opened, tedious operations such as software opening, analysis scheme opening, analysis log opening, log line-by-line checking, information needed in the log selection and the like are not needed, the time of manual operation is greatly saved, the data searching and extracting efficiency is improved, and the accuracy of the extracted data is ensured.
For ease of understanding, an application embodiment of the method for reading CAE modular stream analysis data is provided below for explanation, and referring to fig. 2, an embodiment of the method for reading CAE modular stream analysis data in the application embodiment includes:
in the embodiment of the present application, the present solution will be explained by reading and utilizing the second modular flow analysis data of the CAE software molefow by using a Python tool.
201. Acquiring first modular flow analysis data;
acquiring a file name of first modular stream analysis data;
assigning the file name to a file variable;
the file variable acquires a storage path of the first modular flow analysis data according to the file name;
opening the storage path through an open function;
and acquiring the data under the storage path to obtain the first modular flow analysis data.
The function of the file variable is to obtain the absolute address of the current file or the absolute directory where the current file is located;
the role of the open function is to open or create a file.
In the embodiment of the application, the software MOLEFLOW is opened firstly, the corresponding analysis scheme is opened, then the analysis log is opened, the analysis log is exported to the appointed storage area and a file name is appointed, then the file name is assigned to the file variable in the reading program, the file variable finds the storage path of the storage area where the file corresponding to the file name is located according to the obtained file name, the storage path of the first modular flow analysis data is obtained, the storage path obtained by opening the file variable through the open function is opened, and the data under the storage path is read to achieve the obtaining of the first modular flow analysis data.
The other realization method comprises the following steps: directly assigning a storage path of the first modular flow analysis data to a file variable, after the file variable is positioned in a storage area of the first modular flow analysis data, opening the storage path in the file variable through an open function, reading the data, and realizing the acquisition of the first modular flow analysis data.
202. Matching with the first modular flow analysis data using target data features, the target data features comprising: a start identifier and an end identifier of the data;
the modular flow analysis data is basic log information of modular flow analysis, and the modular flow analysis data comprises: product basic data, model detail data and filling analysis data;
the start identifier is a designated symbol and designation of a start position of one type of data;
the end identifier is a designated symbol and designation of an end location of one type of data.
The matching step mainly comprises:
importing a regular expression;
setting the regular expression as: w1+ X + W2, the W1 being the start marker, the W2 being the end marker, the X being any value between the start marker and the end marker;
and searching the first modular flow analysis data by using the regular expression.
Specifically, product basic data, model detail data and filling analysis data are used as second model flow analysis data for explanation. In the basic log information of the software molefiw, product basic data takes "Model files" as a start identifier, which is defined as W11, and takes "- - - - - - - - - - - - - - - - - - - - -" as an end identifier, which is defined as W21; the Model detail data is "Model tails" as the start mark, which is defined as W12, and the end mark is defined as W22; the Fill Analysis data is "Fill Analysis" as a start flag, which is defined as W13, and is defined as a finish flag, which is defined as W23.
In the embodiment of the present application, a regular expression is imported, and then the regular expression is set as W11+ X + W21, W12+ X + W22, W13+ X + W23, where X is any value existing between a start flag and an end flag, that is, data corresponding to a start flag plus any non-flag plus an end flag is matched and searched in first modular stream analysis data by using the set regular expression, where a start flag and an end flag should be in one-to-one correspondence, for example, the end flag corresponding to W11 is W21, the end flag corresponding to W12 is W22, and the end flag corresponding to W13 is W23.
It should be noted that: the example here is to set three regular expressions at the same time for matching with the first modular flow analysis data, but the scheme is not limited, and the number of the regular expressions is determined according to data that is actually needed.
203. Storing the first modular flow analysis data with the target data characteristics to a designated storage area as the second modular flow analysis data;
the second modular flow analysis data is a subset of the first modular flow analysis data.
Assigning the first modular flow analysis data which accords with the regular expression to a variable result;
and writing the variable result into a specified storage area through a for loop to obtain the second modular stream analysis data.
The function of the variable result is to receive data successfully matched with the regular expression;
the for loop is a loop statement in a programming language, and the loop statement consists of a loop body and a loop judgment condition, and the expression is as follows: for (single expression; conditional expression; end loop body).
In the embodiment of the application, data successfully matched with the regular expression is assigned to the variable result, that is, any value between one start identifier and one corresponding end identifier is assigned to the variable result, and then the value of the variable result is written into a specified storage area through a for loop to serve as second module flow analysis data.
Another more optimized implementation method is as follows:
classifying the variable result according to the target data characteristics;
and respectively writing the classified variable result sub-modules into a specified storage area through a for loop.
In the embodiment of the application, data successfully matched with the first regular expression is assigned to a first variable result, data successfully matched with the second regular expression is assigned to a second variable result, data successfully matched with a third regular expression is assigned to a third variable result, the value of the first variable result is written into a first storage area, the value of the second variable result is written into a second storage area, the value of the third variable result is written into a third storage area through for-loop, and classified storage of second modular flow analysis data is achieved.
204. Creating an Excel table, and writing the second modular flow analysis data into the Excel table;
in the embodiment of the application, the second modular flow analysis data is classified according to the target data characteristics; respectively creating Excel tables according to the second modular flow analysis data of different types, and writing the second modular flow analysis data of the same type into the same Excel table. Such as: when non-classified storage is adopted in step 203, classifying the second modular flow analysis data to obtain product basic data, model detail data and filling analysis data, wherein the model detail data comprises a plurality of sub-data such as grid types, grid matching percentages, mutual grid matching percentages, average aspect ratios of triangular units, maximum aspect ratios of triangular units, total volumes, part volumes, flow channel volumes and total projection areas, names of the sub-data are sequentially filled into a first row of an Excel table to establish the Excel table with a table header, and then corresponding data are sequentially written into corresponding columns of the Excel table respectively. When the classified storage is adopted in step 203, an Excel table is established according to the second modular stream analysis data in different storage areas, and the second modular stream analysis data in the same storage area is written into the same Excel table.
A further optimization is achieved by writing each subclass of data separately into an Excel table.
The specific program implementation logic is as follows: importing a module for creating an Excel table, specifying input second modular flow analysis data, specifying output Excel paths, defining workbook names, assigning initial variables, creating a worksheet, building an output table, opening the second modular flow analysis data, and writing the second modular flow analysis data into the Excel table row by row and column by column.
205. Converting the data in the Excel table into a coordinate image, wherein the coordinate image comprises a scatter coordinate graph and a line graph;
in the embodiment of the application, the step is used in combination with the optimization implementation method in step 204, that is, the data of the Excel table containing the sub-data is converted into a coordinate image, such as a scatter plot, a line graph and other more intuitive data display forms, so as to serve specific use requirements. For example, secondary processing from tables to various icons such as a line graph and the like is carried out on the tables corresponding to parameters such as filling time, filling volume, filling pressure, filling rate and the like one by one, so that required information in working items such as time of maximum pressure, opening time of a sequential needle valve nozzle and the like can be quickly, accurately and simply obtained, and quick and accurate numerical reference is provided for optimizing or improving quality points such as material thickness, appearance, structure, deformation and the like of a product.
The specific program implementation logic is as follows: importing a related method required by drawing-defining initial values of an x axis and a y axis-reading columns in an Excel table-assigning a first column of the Excel table to x-assigning a second column of the Excel table to a y-executing drawing command.
The method comprises the steps of acquiring first modular flow analysis data; matching with the first modular flow analysis data using target data features, the target data features comprising: a start identifier and an end identifier of the data; storing the first modular flow analysis data with the target data characteristics to a designated storage area as the second modular flow analysis data; creating an Excel table, and writing the second modular flow analysis data into the Excel table; and converting the data in the Excel table into a coordinate image, wherein the coordinate image comprises a scatter coordinate graph and a line graph. The read required second modular flow analysis data are refined and classified again, and then are stored in a partitioned mode, so that data can be searched accurately, the data searching and extracting speed is further improved, the data can be edited by converting the second modular flow analysis data into the Excel table, and the data in the Excel table are converted into coordinate images, so that the data are visualized, and the data can be conveniently looked up.
Corresponding to the embodiment of the application function implementation method, the application also provides electronic equipment and a corresponding embodiment.
Fig. 3 is a schematic structural diagram of an electronic device shown in an embodiment of the present application.
Referring to fig. 3, an electronic device 301 includes a memory 302 and a processor 303.
The Processor 303 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 302 may include various types of storage units, such as system memory, Read Only Memory (ROM), and permanent storage. Wherein the ROM may store static data or instructions that are required by the processor 303 or other modules of the computer. The persistent storage device may be a read-write storage device. The persistent storage may be a non-volatile storage device that does not lose stored instructions and data even after the computer is powered off. In some embodiments, the persistent storage device employs a mass storage device (e.g., magnetic or optical disk, flash memory) as the persistent storage device. In other embodiments, the permanent storage may be a removable storage device (e.g., floppy disk, optical drive). The system memory may be a read-write memory device or a volatile read-write memory device, such as a dynamic random access memory. The system memory may store instructions and data that some or all of the processors require at runtime. Further, the memory 302 may include any combination of computer-readable storage media, including various types of semiconductor memory chips (DRAM, SRAM, SDRAM, flash memory, programmable read-only memory), magnetic and/or optical disks, may also be employed. In some embodiments, memory 302 may include a removable storage device that is readable and/or writable, such as a Compact Disc (CD), a read-only digital versatile disc (e.g., DVD-ROM, dual layer DVD-ROM), a read-only Blu-ray disc, an ultra-density optical disc, a flash memory card (e.g., SD card, min SD card, Micro-SD card, etc.), a magnetic floppy disc, or the like. Computer-readable storage media do not contain carrier waves or transitory electronic signals transmitted by wireless or wired means.
The memory 302 has stored thereon executable code that, when processed by the processor 303, may cause the processor 303 to perform some or all of the methods described above.
The aspects of the present application have been described in detail hereinabove with reference to the accompanying drawings. In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments. Those skilled in the art should also appreciate that the acts and modules referred to in the specification are not necessarily required in the present application. In addition, it can be understood that the steps in the method of the embodiment of the present application may be sequentially adjusted, combined, and deleted according to actual needs, and the modules in the device of the embodiment of the present application may be combined, divided, and deleted according to actual needs.
Furthermore, the method according to the present application may also be implemented as a computer program or computer program product comprising computer program code instructions for performing some or all of the steps of the above-described method of the present application.
Alternatively, the present application may also be embodied as a non-transitory machine-readable storage medium (or computer-readable storage medium, or machine-readable storage medium) having stored thereon executable code (or a computer program, or computer instruction code) which, when executed by a processor of an electronic device (or electronic device, server, etc.), causes the processor to perform part or all of the various steps of the above-described method according to the present application.
Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the applications disclosed herein may be implemented as electronic hardware, computer software, or combinations of both.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems and methods according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Having described embodiments of the present application, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (10)
1. A method of reading CAE modular flow analysis data, comprising:
acquiring first modular flow analysis data;
matching with the first modular flow analysis data using target data features, the target data features comprising: a start identifier and an end identifier of the data;
storing the first modular flow analysis data with the target data characteristics into a designated storage area as second modular flow analysis data, wherein the second modular flow analysis data is a subset of the first modular flow analysis data.
2. The method for reading CAE modular flow analysis data according to claim 1, wherein:
the modular flow analysis data is basic log information of modular flow analysis, and the modular flow analysis data comprises: product basic data, model detail data and filling analysis data;
the start identifier is a designated symbol and designation of a start position of one type of data;
the end identifier is a designated symbol and designation of an end location of one type of data.
3. The method for reading CAE modular flow analysis data according to claim 1, wherein the obtaining the first modular flow analysis data comprises:
acquiring a file name of first modular stream analysis data;
assigning the file name to a file variable;
the file variable acquires a storage path of the first modular flow analysis data according to the file name;
opening the storage path through an open function;
and acquiring the data under the storage path to obtain the first modular flow analysis data.
4. The method for reading CAE modular flow analysis data according to claim 1, wherein the matching of the target data characteristics with the first modular flow analysis data comprises:
importing a regular expression;
setting the regular expression as: w1+ X + W2, the W1 being the start marker, the W2 being the end marker, the X being any value between the start marker and the end marker;
and searching the first modular flow analysis data by using the regular expression.
5. The method for reading CAE modular flow analysis data according to claim 4, wherein the storing the first modular flow analysis data with the target data characteristics to a designated storage area as the second modular flow analysis data comprises:
assigning the first modular flow analysis data which accords with the regular expression to a variable result;
and writing the variable result into a specified storage area through a for loop to obtain the second modular stream analysis data.
6. The method for reading CAE modular flow analysis data according to claim 1, wherein after storing the first modular flow analysis data with the target data characteristics in a designated storage area as the second modular flow analysis data, further comprising:
classifying the second modular flow analysis data according to the target data characteristics;
respectively creating Excel tables according to the second modular flow analysis data of different types;
and writing the second modular flow analysis data of the same type into the same Excel table.
7. The method for reading CAE modular flow analysis data according to claim 6, wherein after writing the second modular flow analysis data into the Excel table, the method further comprises:
and converting the data in the Excel table into a coordinate image, wherein the coordinate image comprises a scatter coordinate graph and a line graph.
8. The method for reading CAE modular flow analysis data as claimed in claim 5, wherein said writing said variable result into a specified storage area through a for loop comprises:
classifying the variable result according to the target data characteristics;
and respectively writing the classified variable result sub-modules into a specified storage area through a for loop.
9. An electronic device, comprising:
a processor; and
a memory having executable code stored thereon, which when executed by the processor, causes the processor to perform the method of any one of claims 1-8.
10. A non-transitory machine-readable storage medium having stored thereon executable code, which when executed by a processor of an electronic device, causes the processor to perform the method of any one of claims 1-8.
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