JP2007249338A - Analysis result information compression program, analysis result information expansion program, storage medium storing analysis result information compression program, storage medium storing analysis result information expansion program, analysis result information compressing device, analysis result information expanding device, analysis result information compression method and analysis result information expansion method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a program for efficiently compressing an analysis result by applying predetermined conversion processing to an analysis result in an analysis method in which it is impossible to recalculate the whole from a partial analysis result information. <P>SOLUTION: The values of a plurality of predetermined structure parameters to be used for numerical analysis are read as variable dependency information (S300), and conversion information is generated (S302). Then, the result information of numerical analysis is converted based on the conversion information (S306), and the result information of the converted numerical analysis is compressed (S308). <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to a program for compressing and expanding analysis result information obtained by numerical analysis such as electromagnetic field analysis and thermal fluid analysis.

  When examining the design of electronic equipment products and verifying defects using a numerical analysis device that performs electromagnetic field analysis and thermal fluid analysis, the analysis is performed under various analysis conditions and the results are compared. For this reason, it is necessary to store a large amount of analysis results in a storage device. In such a case, an analysis result information compression program and an analysis result expansion program for compressing and storing the analysis result and expanding it when necessary are used.

In the compression method disclosed in Patent Document 1, feature points are extracted from all analysis result information, and the information of the portion is completely stored. For other parts, a limited number of bits are allocated to generate quantized data. Further, when there is a past analysis result that has the same quantized data, the information is compressed by recording a reference to the file without saving it in the file. Also, at the time of deployment, the property of the original analysis method is utilized in that when the incomplete analysis result is re-analyzed as an initial value, the original analysis result is restored at high speed.
Japanese Patent Application Laid-Open No. 2003-46391

  However, the method disclosed in Patent Document 1 is completely complete when there is no property that the original analysis result is restored at high speed when re-analysis is performed using the incomplete analysis result as an initial value in the original analysis method. Information cannot be restored at high speed. Therefore, it has been impossible to use the analysis result information compression / decompression method in such a case. Moreover, even if a compression method such as the run length method or LZ method that has been conventionally used is applied to the analysis result information, there are many discontinuous points in the analysis result distribution, so that a sufficient compression effect can be obtained. I could not do it.

  The present invention has been made to solve the above-described problems, and an object of the present invention is to perform a predetermined conversion process on the analysis result to compress the analysis result, and to perform the compressed analysis. It is to provide a program that expands the results.

  According to one aspect of the present invention, there is provided a program for causing a computer having a calculation unit and a storage unit to execute a process for compressing numerical analysis result information, wherein the calculation unit is used in numerical analysis. A step of reading a predetermined structural parameter value from the storage unit as variable dependency information, a step of generating a conversion information from the variable dependency information, and a calculation unit converting a plurality of result information based on the conversion information A step, a step in which the calculation unit compresses the converted result information, and a step in which the calculation unit stores the compressed result information in the storage unit.

  Preferably, the step of generating the conversion parameter includes a step of assigning an identification number for each value indicated by the variable dependency information, and a step of writing an association between the value indicated by the variable dependency information and the identification number as conversion information in the storage unit. The step of converting the result information includes, for each identification number, obtaining a compression target representative value in the distribution of the compression target value in the result information, an identification number, and a representative value obtained for each identification number, respectively. A step of associating and writing to the storage unit; a step of calculating a difference between the representative value and each compression target value; and a step of associating the identification number with the calculated difference.

  Preferably, the step of compressing the converted result information compresses using the redundancy of the result information.

Preferably, the step of compressing the converted result information is performed by the LZ method.
Preferably, the value to be compressed is an exponent part of the result information.

  According to another aspect of the present invention, there is provided a program for causing a computer having a calculation unit and a storage unit to execute processing for expanding compressed numerical analysis result information, wherein the calculation unit is a compressed numerical value. The step of reading the analysis result information and the association used when compressing the result information from the storage unit, and the step of expanding the numerical analysis result information compressed using the association used when the calculation unit compresses With.

  Preferably, the association used when compressing is inverse transformation in which variable dependency information, which is a value of a plurality of predetermined structural parameters, used in numerical analysis is associated with an identification number assigned for each variable dependency information. A first association in which information, an identification number, and a representative value of a value to be compressed among the result information obtained for each identification number are associated, and the step of expanding includes: Expanding the result information into a second association in which the identification number and the difference between the representative value and the value to be compressed are associated; and the second association based on the first association, Expanding the association with the compression target value, and inversely converting the compression target value associated with the identification number into result information based on the inverse transform information.

Preferably, the step of expanding to the second association is performed by the LZ method.
According to still another aspect of the present invention, a computer-readable storage medium storing the analysis result information compression program is provided.

  According to still another aspect of the present invention, a computer-readable storage medium storing the analysis result information expansion program is provided.

  According to still another aspect of the present invention, there is provided an analysis result information compression apparatus for executing processing for compressing numerical analysis result information, and reading values of a plurality of predetermined structural parameters used in numerical analysis as variable dependence information. Means for generating conversion information from variable dependency information, means for converting a plurality of result information based on the conversion information, means for compressing the converted result information, and compressed Means for storing the result information.

  According to still another aspect of the present invention, there is provided an analysis result information expansion device for executing processing for expanding compressed numerical analysis result information, when compressing compressed numerical analysis result information and result information. Means for reading the used association and means for developing the result information of the numerical analysis compressed using the association used when compressing.

  According to still another aspect of the present invention, there is provided an analysis result information expansion method for executing a process of compressing numerical analysis result information, wherein a plurality of predetermined structural parameter values used in numerical analysis are variable-dependent information. A step of reading as, a step of generating conversion information from the variable dependency information, a step of converting a plurality of result information based on the conversion information, a step of compressing the converted result information, and a step of storing the compressed result information With.

  According to still another aspect of the present invention, there is provided an analysis result information compression method for executing a process of expanding compressed numerical analysis result information, and compresses the compressed numerical analysis result information and result information. A step of reading the association used sometimes, and a step of developing the result information of the numerical analysis compressed using the association used for compression.

  According to the present invention, the analysis result distribution can be made continuous by performing a predetermined conversion process on the analysis result. Thereby, a higher compression effect can be obtained. In addition, if you reanalyze the original analysis method with an incomplete analysis result as the initial value, even if there is no property that the original analysis result is restored at high speed, the complete analysis result information is compressed and saved It becomes possible to do. Thereby, the storage capacity of the secondary storage device can be utilized more effectively.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings. In the following description, the same parts are denoted by the same reference numerals. Their names and functions are also the same. Therefore, detailed description thereof will not be repeated.

  As will be apparent from the following description, the analysis result information compression / decompression program according to the present invention compresses the analysis result distribution with continuity by performing a predetermined conversion process on the analysis result. In addition, the compressed analysis result can be expanded.

(1. System configuration of the present invention)
FIG. 1 is a conceptual diagram showing an example of a computer 100 that executes a program according to the present invention.

  In FIG. 1, a computer 100 for executing an analysis result information compression program and an analysis result information expansion program includes an optical disk drive 108 for reading information on an optical disk such as a CD-ROM (Compact Disc Read-Only Memory), and the like. A computer main body 102 provided with an FD drive 106 for reading and writing information on a flexible disk (FD) 116, a display 104 as a display device connected to the computer main body 102, and also connected to the computer main body 102. A keyboard 110 and a mouse 112 as input devices.

FIG. 2 is a block diagram showing the configuration of the computer 100. As shown in FIG.
As shown in FIG. 2, in addition to the optical disk drive 108 and the FD drive 106, the computer main body 102 constituting the computer 100 includes a CPU (Central Processing Unit) 120 connected to a bus 126 and a ROM (Read Only). A memory 122 including a memory (RAM) and a random access memory (RAM), a direct access memory device such as a hard disk 124, and a communication interface 128 for exchanging data with the outside are included. A CD-ROM 118 is attached to the optical disk drive 108. An FD 116 is attached to the FD drive 106.

  Also, in the hard disk 124, analysis target information 200 in which physical property information indicating the physical properties of the analysis target and the like are stored, a program 202 for performing numerical analysis, and an analysis result for compressing the result of the numerical analysis A compression program 204, an analysis result expansion program 206 for expanding the compressed analysis result, and the like are stored. Also included is analysis result information 208 which is a storage area for storing analysis result information, and compression information 210 for storing information obtained by compressing the analysis result. Here, for example, the analysis target information and the analysis result information may be supplied from an external database via the communication interface 128. The program 202 that executes numerical analysis performs numerical analysis such as electromagnetic field analysis and thermal fluid analysis.

  The CPU 120 functioning as an arithmetic processing unit executes processing corresponding to the above-described program using the memory 122 as a working memory. Here, the program 202 for performing numerical analysis may be executed by an external CPU via the communication interface 128, and only the analysis result information may be read. Further, the analysis result compression program 204 and the analysis result expansion program 206 may be executed by different CPUs.

  The CD-ROM 118 may be another medium, such as a DVD-ROM (Digital Versatile Disc) or a memory card, as long as it can record information such as a program installed in the computer main body. In this case, the computer main body 102 is provided with a drive device that can read these media.

  The analysis result information compression program and analysis result information expansion program of the present invention (hereinafter collectively referred to as “analysis result compression / decompression program”) are software executed by the CPU 120 as described above. Generally, such software is stored and distributed in a storage medium such as the CD-ROM 118 and the FD 116, read from the storage medium by the optical disk drive 108 or the FD drive 106, and temporarily stored in the hard disk 124. Alternatively, when the computer 100 is connected to the network, it is temporarily copied from the server on the network to the hard disk 124. Then, the data is further read from the hard disk 124 to the RAM in the memory 122 and executed by the CPU 120. In the case of network connection, the program may be directly loaded into the RAM and executed without being stored in the hard disk 124.

  The computer hardware itself and its operating principle shown in FIGS. 1 and 2 are general. Therefore, the most essential part of the present invention is software stored in a storage medium such as the FD 116, the CD-ROM 118, and the hard disk 124.

  As a general tendency, various program modules are prepared as a part of a computer operating system, and an application program generally calls a module in a predetermined arrangement to advance processing. . In such a case, the module itself is not included in the software itself, and the analysis result compression / decompression processing can be performed only in cooperation with the operating system on the computer. However, as long as a general platform is used, it is not necessary to distribute the software including such modules, and the software itself not including these modules and the storage medium storing the software (and the software distributing on the network). Data signal) can be considered to constitute the embodiment.

(2. Analysis result compression / decompression method)
The analysis result compression / decompression method according to the present invention will be described below.

FIG. 3 is a flowchart showing a flow of processing for compressing the analysis result.
A process for compressing the analysis result will be described with reference to FIG.

  First, in step S300, as initialization processing, a value on which a variable to be analyzed depends is input as “variable dependency information”. Specifically, it refers to a plurality of predetermined values taken by at least one structural parameter of the structure included in the analysis region. The value on which the variable depends indicates, for example, a number that appears in a calculation formula used to calculate the variable a if a certain variable a is calculated.

  In step S302, an identification number is assigned for each value indicated by the variable dependency information and set as “conversion information”. With this conversion information, the identification number is known from the variable dependence information. That is, the variable dependence information and the identification number are associated with each other.

  In step S304, the analysis result information of the numerical analysis is read. In step S306, the analysis result information is converted based on the conversion information. Here, first, a distribution of values to be compressed among the analysis result information is obtained for each identification number. A representative value of values to be compressed is obtained from the distribution. The representative value is a median value or an average value of the values to be compressed, obtained from the distribution. Preferably, the representative value is an integer. Based on the representative value, the analysis result information read in step S304 is converted. For example, the difference between the representative value and the compression target value is taken, and the difference is replaced with the analysis result.

  In step S308, information compression is performed. Here, the analysis result information converted in step S306 is compressed by a compression method using redundancy. Examples of compression methods using redundancy include the LZ method and the run length method. In step S310, the generated compressed analysis result information is output.

  In step S312, end determination is performed. It is determined whether or not a predetermined end condition is satisfied, for example, the number of times of input of the analysis result information reaches a specified number of times of input. If the end condition is not satisfied (No in step S312), the analysis result is input again (step S304). If the termination condition is satisfied (Yes in step S312), the compression process is terminated.

If the above processing is followed, the analysis result can be compressed.
FIG. 4 is a flowchart showing a flow of processing for expanding a compressed analysis result.

  With reference to FIG. 4, the process of expanding the analysis result compressed by the process shown in FIG. 3 will be described.

  In step S400, the variable dependence information and conversion information read in the analysis result compression process shown in FIG. 3 are input.

  In step S402, “inverse conversion information” is set based on the conversion information. With this inverse transformation information, variable dependency information can be determined from the identification number. That is, the reverse conversion information is associated with the identification number and the variable dependence information.

  In step S404, compressed analysis result information is input. Here, the association between the identification number used when the compression process is performed and the representative value obtained for each identification number is also input.

  In step S406, the compressed analysis result information is expanded. Thereby, information in which the converted analysis result information and the identification number are associated is obtained. Then, the association between the converted analysis result information and the identification number based on the association between the identification number and the representative value input in step S404 is expanded into the association between the identification number and the analysis result information.

  In step S408, the association obtained in step S406 is converted into analysis result information using inverse conversion information. In step S410, the analysis result information generated in step S408 is output.

  In step S412, end determination is performed. It is determined whether or not a predetermined end condition is satisfied, for example, the number of times of input of the compressed analysis result information reaches a specified number. If the end condition is not satisfied (No in step S412), the analysis result is input again (step S404). If the end condition is satisfied (Yes in step S412), the compression process ends.

  If the above process is followed, the analysis result compressed by the process shown in FIG. 3 can be developed.

(3. Implementation on computer 100)
The analysis result information compression / decompression method according to the present invention can be implemented as computer software by the following procedure.

The procedure is summarized below.
FIG. 5 is a flowchart for specifically explaining the flow of the compression processing shown in FIG.

  With reference to FIG. 5, the compression process performed by CPU 120 in accordance with analysis result compression program 204 will be described.

  In step S500, the CPU 120 reads from the analysis target information 200 in the hard disk 124 a value on which the variable to be analyzed depends as variable dependency information. Specifically, it refers to a plurality of predetermined values taken by at least one structural parameter of the structure included in the analysis region. At this time, variable dependency information may be input via the keyboard 110.

  In step S502, the CPU 120 generates conversion information. Here, an identification number is assigned for each value indicated by the variable dependency information read in step S500. With this conversion information, the identification number is known from the value indicated by the variable dependency information. That is, in the conversion information, the value indicated by the variable dependency information is associated with the identification number.

  In step S <b> 504, the CPU 120 writes the conversion information into the compression information 210 in the hard disk 124.

  In step S506, the CPU 120 reads the analysis result from the analysis result information 208. Note that the analysis result information here may be read from the outside via the communication interface 128.

  In step S510, CPU 120 obtains a median value of values to be compressed in the analysis result information for each identification number. Specifically, it is as follows. At each position in the analysis area, the value of the structure parameter used in the conversion information is given. That is, since each position corresponds to an identification number based on the conversion information, a distribution of values to be compressed at each position can be obtained for each identification number. Based on this distribution, a representative value is calculated for each identification number. Here, the median value is calculated as the representative value.

  In step S <b> 512, CPU 120 writes a table in which the identification number and the median are associated with each other in compressed information 210 in hard disk 124.

  In step S514, the CPU 120 sets a difference between the median value and the value to be compressed as a correction value. The corrected value and the identification number are output in association with each other.

  In step S516, CPU 120 performs information compression processing. Specifically, the association between the value corrected in step S514 and the identification number is compressed by the LZ method or the like. The LZ method is a compression method that uses pattern redundancy of information. By compressing the types of codes constituting the pattern, efficient compression can be performed. In step S514, the corrected value is biased to a value close to zero. Because of this bias, efficient compression is performed.

  In step S518, the CPU 120 writes the compressed information into the compressed information 210 in the hard disk 124.

  In step S520, CPU 120 makes an end determination. When CPU 120 determines whether or not a predetermined end condition is satisfied, for example, the number of times of input of analysis result information reaches a specified number of times, and CPU 120 determines that the end condition is not satisfied (No in step S520). ) Again input the analysis result (step S506). If it is determined that the termination condition is satisfied (Yes in step S520), the compression process is terminated.

  If the above processing is performed, the computer 100 can compress the analysis result information.

  FIG. 6 is a flowchart for specifically explaining the flow of the expansion process shown in FIG.

  With reference to FIG. 6, the expansion process performed by CPU 120 in accordance with analysis result expansion program 206 will be described.

  In step S600, the CPU 120 reads information such as variable dependency information and conversion information read in step S500 from the compression information 210 written in the hard disk 124 during the compression process.

  In step S602, CPU 120 generates reverse conversion information based on the information read in step S600. With this inverse conversion information, the value indicated by the variable dependency information can be determined from the identification number.

  In step S <b> 604, the CPU 120 reads compressed analysis result information from the compression information 210 in the hard disk 124. At this time, the association written in the compression information 210 when the analysis result information is compressed is also read.

  In step S608, the CPU 120 expands the compressed analysis result information by the LZ method or the like. Thereby, the converted analysis result information converted in step S514 is obtained.

  In step S610, CPU 120 expands the information obtained in step S608 based on the association between the identification number and the median value read in step S604. Thereby, the original analysis result information is obtained.

  In step S612, CPU 120 outputs the analysis result information obtained in step S610.

  In step S614, CPU 120 makes an end determination. When CPU 120 determines whether or not a predetermined end condition is satisfied, for example, the number of times of input of analysis result information reaches a specified number of times, and CPU 120 determines that the end condition is not satisfied (No in step S614). ), The analysis result is input again (step S604). If it is determined that the termination condition is satisfied (Yes in step S614), the compression process is terminated.

  If the processing as described above is performed, the computer 100 can expand the analysis result information compressed by the analysis result compression program 204.

(4. Example of compressed / expanded analysis result information)
The following is an example using the analysis result information compression / decompression program of the present invention.

(4.1 Example of compressed analysis result information)
FIG. 7 is a flowchart showing the flow of processing for compressing analysis results during analysis execution.

  With reference to FIG. 7, a description will be given of a process of recording in a secondary storage medium while sequentially compressing analysis results by an analysis result information compression program according to the present invention in a scene where analysis is performed. Here, as an example, time domain electromagnetic field analysis is performed using a FDTD (Finite Differential Time Domain) method on a circuit board, and the analysis result is compressed.

  The FDTD method is a numerical calculation method by differentiating Maxwell's electromagnetic field equation. First, an analysis region is divided by a lattice, and an electric field is arranged at the center of each side of the lattice, and a magnetic field is arranged at the center of each surface. Then, when Maxwell's equations are differentiated, the electric and magnetic fields are arranged at positions that are spatially shifted by half a cell and temporally by a half time step. Here, the following equations (1) and (2) can be obtained by deriving the unknown electric field to be obtained, the known electric field adjacent to the unknown magnetic field one time step before, and the relational expression that works between the known magnetic fields from the Maxwell equation based on electromagnetism. It becomes like this.

In the formula, bold indicates that the variable is a vector.
Equation (1) is an electric field E (vector) of n time steps, and equation (2) is a relational equation of magnetic field H (vector) of (n + 1/2) time steps. However, Δt, μ, ε, and σ are time step, magnetic permeability, dielectric constant, and conductivity, respectively.

  By updating the unknown electric field and unknown magnetic field in units of a certain time step Δt based on these, the electromagnetic field behavior of the entire analysis region can be obtained in the time domain. Therefore, even when the analysis is performed under one condition, the electromagnetic field distribution at a plurality of times is obtained as the analysis result.

  The analysis result compression program of the present invention compresses the electromagnetic field distribution at a certain time as a unit. Therefore, even during analysis execution by FDTD, compression processing is performed every time the analysis result is output. The timing for outputting the analysis result is determined by the analysis result output designation given to the analysis program. As the specified condition, for example, the analysis time is from 0 to 1 nanosecond, and output is performed every 0.1 nanosecond.

In the following, a process for recording in a secondary storage medium while sequentially compressing analysis results in a scene where FDTD is executed will be described. Here, the two-dimensional distribution on the xy plane of the electric field variable E in the z direction (hereinafter referred to as variable E _z ) is compressed. Specifically, the exponent part of the single precision floating point of the variable E _z is compressed by the LZ method. Further, the conductivity at the position where the electric field variable exists is used as the variable dependence information, and the median value is used as the representative value of the distribution to be compressed.

  First, in step S700, FDTD is initialized. Here, analysis conditions and the like are read. The analysis conditions are the dimensions of the lattice cells necessary to divide the analysis object into cells, the analysis time, the electric field in the analysis region, the initial value of the magnetic field, the initial value of the voltage, the dielectric disposed in the analysis region, These are the coordinate value and physical property value of the conductor.

FIG. 8 is a diagram showing the distribution of the cell medium given to FDTD.
With reference to FIG. 8, the distribution of the cell medium given to the FDTD will be described. As shown in FIG. 8, in order to execute FDTD, the analysis region is divided into cells. The cell 80 includes a dielectric, and the cell 82 includes a conductor cell.

  Returning to FIG. 7, in step S702, variable dependency information is set. Here, as described above, the conductivity at the position where the electric field variable exists is set.

FIG. 9 is a diagram showing the conductivity distribution depending on the variable E _z , which is obtained by the interpolation method at the position where the variable E _z exists based on the cell medium distribution of FIG. 8.

The variable dependency information will be described with reference to FIG. FIG. 9 shows a dielectric interior 90, a conductor interior 92, and dielectric / conductor boundary portions 94 and 96. In addition, numbers are sequentially assigned to adjacent cells. Cells 1, 2 and 10 indicate the inside of the dielectric, cells 3 to 5 and 7 to 9 indicate the dielectric / conductor boundary, and cell 6 indicates the inside of the conductor. In order to calculate the variable E _z , the electrical conductivity of the dielectric interior 90, the conductor interior 92, and the dielectric / conductor boundary portions 94 and 96 as shown in FIG. 9 is required. In step S702, these conductivity is set as a variable dependent variable information E _z. The conductivity inside the dielectric 90 is zero, the conductivity inside the conductor 92 is 5.7e7 (S / m), the conductivity of the boundary portion 94 between the dielectric and the conductor is 1.425e7 (S / m), and the dielectric The conductivity of the body / conductor boundary portion 96 is 2.85e7 (S / m).

  Returning to FIG. 7, in step S704, conversion information is generated according to the variable dependency information set in step S702. Further, the conversion information is written to the secondary storage medium.

  Table 1 is a table in which the conductivity given as the variable dependency information in step S702 is associated with the identification number (hereinafter referred to as ID) assigned for each conductivity value. The association between the conductivity and the ID assigned for each conductivity value is used as conversion information.

Returning to FIG. 7, in step S706, FDTD is executed.
In step S708, it is determined whether it is time to output the analysis result. As described above, the timing for outputting the analysis result can be specified according to the input condition. If it is not the timing to output the analysis result (No in step S708), the process proceeds to step S716. If the output timing is reached (Yes in step S708), the analysis result information is converted (step S710).

  In step S710, the analysis result is compressed. The following table is given as an analysis result.

Table 2 is a table showing the value of the variable E _z in the cells 1 to 10 shown in FIG. 9 as an analysis result. In this table, the electrical conductivity of each cell, the ID corresponding to the electrical conductivity, and the value of the exponent part when the analysis result information is expressed in single precision floating point representation are associated. However, the value of the exponent part is expressed in hexadecimal.

FIG. 10 is a diagram showing a floating-point number format.
With reference to FIG. 10, the floating point number format of IEEE (Institute of Electrical and Electronics Engineers) standard will be described. In FIG. 10, 23 bits from 0 to 22 indicate the mantissa part f of the decimal representation. 8 bits from 23 to 30 indicate the exponent part e. Reference numeral 31 denotes a code part s. Thus, the value expressed in single precision (32 bits) based on the IEEE standard is (−1) ^s 2 ^e-127 (1.f). In this example, the exponent part e when the analysis result is expressed by the single precision floating point expression described above is compressed.

  The process returns to step S710 in FIG. Here, first, for each ID, the distribution of the value of the exponent part to be compressed, specifically, the maximum value Max (ID) and the minimum value Min (ID) are obtained. From these values, the representative value of the index value for each ID is obtained by the following equation (3). Here, the representative value is the median value Mid (ID). However, the remainder is rounded down to make the value an integer.

Mid (ID) = (Max (ID) + Min (ID)) / 2 (3)
The ID and the median value Mid (ID) obtained as described above are output in association with each other. Further, this association is written in the secondary storage medium.

  Table 3 is a table showing an example in which the median value Mid (ID) is obtained for ID0 to ID2. It can be seen that the median value Mid (ID) is obtained from the minimum value Min (ID) and the maximum value Max (ID) according to the equation (3).

Next, the value of the exponent part to be compressed is converted according to the following equation (4).
(Value of exponent part converted) = (value of exponent part) −Mid (ID) (4)
Then, the cell, the ID, and the converted exponent value are associated.

  Table 4 is a table showing the results calculated for the cells 1 to 10 shown in Table 2 according to the equation (4). As shown in Table 4, the value of the exponent part to be compressed is biased to a value close to zero.

  In step S712, as shown in Table 4, the association between the cell, ID, and converted exponent value is compressed by the LZ method.

In step S714, the compressed analysis result information is written to the secondary storage medium.
In step S716, end determination is performed. It is determined whether or not a predetermined end condition is satisfied, such as the number of times the analysis result information is input reaches a specified number, and if the end condition is not satisfied (No in step S716), the analysis time is updated ( Step S718). If the termination condition is satisfied (Yes in step S716).

  If it carries out as mentioned above, in the scene which performs FDTD, the analysis result compression program which concerns on this invention can record to a secondary storage medium, compressing an analysis result sequentially.

  Table 5 is a table showing input / output data sizes when actual analysis result information is compressed by applying the analysis result information compression program of the present invention.

  The average data size after compression is 8106.394 with respect to the data size 33150 before compression. Thereby, it turns out that it compressed with the average compression rate as shown in Table 5.

(4.2 Example of expanding compressed analysis result information)
FIG. 11 is a flowchart showing a flow of processing for sequentially expanding and displaying the compressed analysis result information when analyzing the analysis result.

  Referring to FIG. 11, when analyzing the analysis result, the analysis result expansion program according to the present invention sequentially reads out and expands the analysis result information compressed and stored in the secondary storage, and displays it as a display device. Processing to be displayed on the screen will be described. It is assumed that the analysis result information is compressed and stored in the secondary storage as described in (4.1) above. Further, here, a process to be developed for displaying on a display device will be described, but the present invention can also be used for developing for post-processing analysis calculation from the analysis result information of the present invention.

In step S1100, the display device is initialized.
In step S1102, variable dependency information is set. Here, the variable dependence information set in step S702 of FIG. 7 is read.

  In step S1104, inverse conversion information is generated. Here, it produces | generates based on the conversion information produced | generated by step S704 of FIG. From the reverse conversion information, variable dependency information can be obtained from the ID.

  In step S1106, display conditions are set. The display condition is, for example, analysis time.

  In step S1108, the compressed analysis result written in the secondary storage medium in step S714 of FIG. 7 is read. At this time, the association between the ID obtained in step S712 and the median value obtained for each ID is also read.

  In step S1110, the information read in step S1108 is expanded by the LZ method. Thereby, information in which the cell, the ID, and the converted exponent value are associated is obtained.

  In step S1112, the value of the original exponent part is obtained from the information obtained in step S1110 by associating the ID with the median value obtained for each ID. As a result, the original analysis result information is output.

  In step S1114, information set in the display condition is displayed on the display device together with the original analysis result information obtained in step S1112.

  In step S1116, end determination is performed. It is determined whether or not a predetermined end condition is satisfied, such as the number of times the analysis result information is displayed reaches a specified number, and if the end condition is not satisfied (No in step S1116), the display condition is updated ( Step S1118). If the termination condition is satisfied (Yes in step S1116), the process is terminated.

  In this way, when analyzing the analysis result, the analysis result expansion program according to the present invention sequentially reads out and expands the analysis result information compressed and stored in the secondary storage, and displays it as a display device. Can be displayed.

  As described above, the analysis result information compression / decompression program according to the present invention can compress and save the analysis result of the numerical analysis. Further, the compressed analysis result can be expanded. As a result, when comparison is made in storage areas of the same capacity, results under more analysis conditions can be saved than when uncompressed analysis conditions are stored. In addition, the results under more analysis conditions can be developed. Therefore, when numerical design such as electromagnetic field analysis or thermal fluid analysis is used to study the design of electromagnetic off-the-shelf products and verify faults, more analysis conditions are required when compared with storage areas of the same capacity. It can be saved and used for examination and verification.

  The embodiment disclosed this time should be considered as illustrative in all points and not restrictive. The scope of the present invention is defined by the terms of the claims, rather than the description above, and is intended to include any modifications within the scope and meaning equivalent to the terms of the claims.

It is a conceptual diagram which shows an example of the computer 100 which runs the program which concerns on this invention. It is a figure which shows the structure of this computer 100 in a block diagram format. It is the flowchart shown about the flow of the process for compressing an analysis result. It is the flowchart shown about the flow of the process which expand | deploys the compressed analysis result. FIG. 4 is a flowchart for specifically explaining the flow of compression processing shown in FIG. 3. FIG. FIG. 5 is a flowchart for specifically explaining the flow of expansion processing shown in FIG. 4. FIG. It is a flowchart which shows the flow of the process which compresses an analysis result during analysis execution. It is a figure showing distribution of the cell medium given to FDTD. FIG. 9 is a diagram showing a conductivity distribution depending on a variable E _z obtained by an interpolation method for a conductivity at a position where the variable E _z exists based on the cell medium distribution of FIG. 8. It is a figure which shows a floating point number format. It is a flowchart which shows the flow of the process which expands and displays the compressed analysis result information sequentially, when analyzing an analysis result.

Explanation of symbols

  80,82 cells, 90 dielectric interior, 92 conductor interior, 94,96 dielectric / conductor boundary, 100 computer, 102 computer body, 104 display, 106 FD drive, 108 optical disk drive, 110 keyboard, 112 mouse, 116 FD , 118 CD-ROM, 120 CPU, 122 memory, 124 hard disk, 126 bus, 128 communication interface, 200 analysis target information, 202 analysis execution program, 204 analysis result compression program, 206 analysis result expansion program, 208 analysis result information 210 Compression information.

Claims (14)

A program for causing a computer having a calculation unit and a storage unit to execute processing for compressing numerical analysis result information,
A step of reading the values of a plurality of predetermined structural parameters from the storage unit as variable dependency information used in the numerical analysis by the arithmetic unit;
The arithmetic unit generating conversion information from the variable dependence information;
The arithmetic unit converting a plurality of the result information based on the conversion information;
The arithmetic unit compressing the converted result information;
An analysis result information compression program, comprising: the arithmetic unit storing the compressed result information in the storage unit. The step of generating the conversion parameter includes:
Assigning an identification number for each value indicated by the variable dependency information;
Writing the association between the value indicated by the variable dependency information and the identification number as the conversion information in the storage unit,
The step of converting the result information includes:
For each identification number, obtaining a representative value of the compression target in a distribution of values to be compressed among the result information; and
Associating the identification number with the representative value obtained for each identification number, and writing to the storage unit;
Calculating a difference between the representative value and each compression target value;
The analysis result information compression program according to claim 1, further comprising: associating the identification number with the calculated difference.   The analysis result information compression program according to claim 2, wherein the step of compressing the converted result information compresses using the redundancy of the result information.   The analysis result information compression program according to claim 3, wherein the step of compressing the converted result information is compressed by an LZ method.   The analysis result information compression program according to claim 4, wherein the compression target value is an exponent part of the result information. A program for causing a computer having a calculation unit and a storage unit to execute a process of expanding compressed numerical analysis result information,
Reading the compressed numerical analysis result information and the association used when compressing the result information from the storage unit;
An analysis result information expansion program comprising: a step of expanding the compressed numerical analysis result information using the association used when the calculation unit performs the compression. The association used when compressing is
Variable conversion information that is a value of a plurality of predetermined structural parameters used in the numerical analysis, and inverse conversion information in which an identification number assigned to each of the variable dependency information is associated;
A first association in which the identification number is associated with a representative value of the compression target value of the result information obtained for each identification number;
The expanding step includes
Expanding the compressed numerical analysis result information into a second association in which the identification number and the difference between the representative value and the compression target value are associated;
Expanding the second association into an association between the identification number and the value to be compressed based on the first association;
The analysis result information expansion program according to claim 6, further comprising: reversely converting the compression target value associated with the identification number into result information based on the reverse conversion information.   The analysis result information expansion program according to claim 7, wherein the step of expanding to the second association is expanded by an LZ method.   A computer-readable storage medium storing the analysis result information compression program according to claim 1.   A computer-readable storage medium storing the analysis result information expansion program according to claim 6. An analysis result information compression device that executes processing for compressing numerical analysis result information,
Means for reading the values of a plurality of predetermined structural parameters as variable-dependent information used in the numerical analysis;
Means for generating conversion information from the variable dependency information;
Means for converting a plurality of the result information based on the conversion information;
Means for compressing the transformed result information;
An analysis result information compression apparatus comprising: means for storing the compressed result information. An analysis result information expansion device for executing processing for expanding compressed numerical analysis result information,
Means for reading the compressed numerical analysis result information and the association used when compressing the result information;
An analysis result information expansion device comprising: means for expanding the compressed numerical analysis result information using the association used at the time of compression. An analysis result information expansion method for executing processing for compressing numerical analysis result information,
Reading the values of a plurality of predetermined structural parameters used as the variable dependency information in the numerical analysis;
Generating conversion information from the variable dependency information;
Converting a plurality of the result information based on the conversion information;
Compressing the converted result information;
An analysis result information compression method comprising: storing the compressed result information. An analysis result information compression method for executing a process of expanding compressed numerical analysis result information,
Reading the compressed numerical analysis result information and the association used when compressing the result information;
Expanding the compressed numerical analysis result information using the association used when compressing the analysis result information.

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