Micaps fourth-class lattice point data lossless compression algorithm

A technology of lossless data and compression algorithm, applied in electrical components, code conversion, etc., can solve the problems of large files, unreachable compression ratio, limited ratio of Micaps data compression, etc., and achieve the effect of high data compression ratio

Active Publication Date: 2016-08-17
CNOOC INFORMATION TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The previous data format caused the generated files to be too large, which is not conducive to the long-term storage and flow of data. A large amount of meteorological data had to be abandoned due to insufficient funds to purchase hard drives.
In addition, traditional WinRaR or WinZip compression tools, because of their universality, have a very limited compression ratio for Micaps data and cannot achieve a higher compression ratio

Method used

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  • Micaps fourth-class lattice point data lossless compression algorithm
  • Micaps fourth-class lattice point data lossless compression algorithm
  • Micaps fourth-class lattice point data lossless compression algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0039] The fourth type grid data file of Micaps data is:

[0040] diamond 4 at 20 o'clock on March 19, 2015 ECMWF_ sea level pressure analysis

[0041]

[0042] The header file of grid forecast data using ECMWF of a certain day is:

[0043] diamond 4 at 20 o'clock on March 19, 2015 ECMWF_ sea level pressure analysis

[0044]

[0045] The compressed head style is: 0501503192000252536018000009001450037045240

[0046] The previous data block is:

[0047]

[0048] When compressing, first multiply each number by 10 and adjust the unit to 0.1 of the original unit.

[0049]

[0050] The compressed data is:

[0051] 117117114111102101100103098097101103106107103107111113117118117118118118118120121120118122120120118124126124123122122...

[0052] Combining the header file and the data block, the complete compressed data file is:

[0053] 0501503192000252536018000009001450037045240117117114111102101100103098097101103106107103107111113117118117118118118118120121120118122120120118124126124123122122...

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Abstract

The invention relates to a Micaps fourth-class lattice point data lossless compression algorithm which comprises the steps of compressing a head of Micaps fourth-class lattice point data, i.e. redefining a head format of the data, wherein a compressed head file has 47 bits in total; carrying out processing and compression on a data part of the Micaps fourth-class lattice point data, i.e. firstly, multiplying each piece of data by 10, regulating the unit into 0.1 of the original unit, and then according to a level indicating bit corresponding to the head file, removing first two repeated bits of the front part of each piece of data; combining the head file with the compressed data part to obtain a complete compressed data file; and recompressing the data file by adopting libzip, finally generating a '.zim4' file, calculating a HASH value for the recompressed file and storing the HASH value. According to the invention, the storage utilization rate can be effectively improved, and the Micaps fourth-class lattice point data lossless compression algorithm is convenient for the internet and even a Beidou system to carry out transmission.

Description

Technical field [0001] The present invention relates to a data compression method, in particular to a lossless compression algorithm of Micaps fourth type grid data. Background technique [0002] At present, the Micaps data is developed by the China Meteorological Administration for the convenience of meteorological professionals to browse and transmit data, including a total of 26 data formats. In the early days of Micaps data design, the amount of data was small because the weather forecast at that time was relatively low in terms of time resolution and spatial resolution. With the improvement of the technical level of weather forecasting, especially the improvement of the computing power of large-scale computers, the temporal and spatial resolution of numerical forecasting can be greatly improved, which has caused a blowout of weather data. The previous data format caused the generated files to be too large, which was not conducive to the long-term preservation and flow of da...

Claims

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Application Information

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IPC IPC(8): H03M7/30
Inventor 王强生
Owner CNOOC INFORMATION TECH
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