Java 专有XML文件（Roche LC480.ixo文件）中的二进制字段编码/序列化格式

我最近收到了一个由罗氏LightCycler 480仪器生成的示例导出文件。它使用专有的XML格式，我还没有找到它的规范

从这些类型的文件中，我想提取一些与我的目的相关的信息。尽管其中大部分可以轻松解析和解释，但它包含大量（未添加的）二进制/序列化数据的base 64编码字段，表示整数和/或浮点数数组。可以在中找到指向示例文件的链接

我已经在这篇文章的末尾包含了一些片段。

AcquisitionTable

包含总共

19个
这样的编码
项
条目。这可能表示整数（
SampleNo
）和浮点（
1
）值的数组

如何将解码的字节转换为整数或浮点值对我来说仍然不清楚。当base 64解码时，每个项目以以下（十六进制）6字节序列开始：

42 41 52 5A 00 00 ...    // ['B','A','R','Z','\0','\0', ...]

请注意，虽然我期望每个“项目”包含相同数量的数字（或本表中的“行”），但我观察到类似项目的解码字节数不同：对于
Fluor1
为5654，对于
Fluor2
为5530

此外，对于我怀疑包含（顺序）整数的数组，可以观察到一种模式：

SampleNo : ... 1F F5 1F 07 2F 19 2F 2B 2F 3D 2F 4F 2F 61 2F 00 73 2F 85 2F 97 2F A9 2F BB 2F CD 2F DF 2F F1 2F 00 03 3F 15 3F 27 ...
Cycles   : ... 1F FF 1F 11 2F 23 2F 35 2F 47 2F 59 2F 6B 2F 00 7D 2F 8F 2F A1 2F B3 2F C5 2F D7 2F E9 2F FB 2F 00 0D 3F 1F 3F 31 ...
Gain     : ... 1F EE 1F 00 2F 12 2F 24 2F 36 2F 00 48 2F 5A 2F 6C 2F 7E 2F 90 2F A2 2F B4 2F C6 2F 00 D8 2F EA 2F FC 2F 0E 3F 20 3F 32 ...

它看起来像是一对字节，其中第二个字节增加了
0x12
（18），并且在最后一个字节的半字节分别为
3
、
D
或
8
的情况下，偶尔会增加一组3个字节，其中
0x00
作为第二个字节

我想知道编码/序列化格式的类型是否对任何人都是显而易见的（或者，更好的是，如果有人有这种文件格式的规范）

我相信用于创建这些文件的软件目前是基于Java的，但它有Windows/MFC/C++产品的历史

<obj name="AcquisitionTable" class="AcquisitionTable" version="1">
    <prop name="Count">2400</prop>
    <prop name="ChannelCount">6</prop>
    <list name="Columns" count="19">
        <item name="SampleNo">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</item>
        <item name="ProgramNo">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</item>


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。。。剪断

        <item 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</item>

        <item name="Gain6">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</item>
    </list>
</obj>

在中国，CCCQ/CCQQQ8/CCQ8/CCQ8/CCQ8/CQ8/CQ8/PCFFF7/QopJW8/P9-SGGG8/P9-SG8/P8/G8/G8/G8/一个中国政府军的一个研究基金会对一个中国政府军的一个关于一个GGwwwwwwwwwwwfffffffffffffffffffffffffffffffffffff8/G8/G8（G8/P9/P9/P9/P9/P9/P9/P9的说法，或者或者是一个GGGGGGGGGGGGG8/P8/P8/G8/P9的说法，或者或者或者或者是一个中国某某某某某某某某某某某某某某ZSL2LRIGCL0LiXIFMTC+5Rt4hzC+ZQ/YhM4）vvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvDGLG9X7NCCB2BC6NTQIDGRG+Jc+qIn2B0bzHoMLdgzqRvoeagz2CMb0nkOUjnYNRv8eHw/2Dsb+eZ35gXcLxvCd4InC9wHH/p2uhHcD
#!/usr/bin/env python3

import base64
from collections import OrderedDict, defaultdict
from values import values

def splitme(name, sep):
    splitted = base64.b64decode(values[name]+'==').split(sep)
    print("{:<12} [{}; {}] separated in {} chunks: {}".format(
            name,
            len(values[name]), len(base64.b64decode(values[name]+'==')),
            len(splitted),
            [len(i) for i in splitted]))
    return splitted

if __name__ == '__main__':
    allchunks = defaultdict(list)
    separator = b'\r'
    print("separating by:", separator)
    for key in values:
        data = splitme(key, sep=separator)
        for i, item in enumerate(data):
            allchunks[item].append((key, i))
    print("Common chunks:")
    for location in [value for item, value in allchunks.items() if len(value)>1]:
        print(location)

separating by: b'\r'
SampleNo     [1536; 1152] separated in 5 chunks: [174, 271, 271, 271, 161]
ProgramNo    [1531; 1148] separated in 6 chunks: [47, 271, 271, 271, 271, 12]
SegmentNo    [1531; 1148] separated in 5 chunks: [169, 271, 271, 271, 162]

separating by: b'\t'
SampleNo     [1536; 1152] separated in 5 chunks: [204, 271, 271, 271, 131]
ProgramNo    [1531; 1148] separated in 5 chunks: [76, 271, 271, 271, 255]
SegmentNo    [1531; 1148] separated in 5 chunks: [199, 271, 271, 271, 132]

separating by: b'\n'
Gain1        [3046; 2284] separated in 10 chunks: [81, 271, 271, 271, 271, 271, 271, 271, 271, 26]  

def splitme(name):
    data = base64.b64decode(values[name]+'==')
    hit = 0
    index = 0
    countit = 0
    splits = []
    while hit >= 0 and countit < 500:
        countit += 1
        hit = data[index+1:].find(0)
        index += hit+1
        if hit >= 0:
            splits.append(index)
    lastindex = -1
    splitted = []
    if splits:
        for index in splits:
            splitted.append(data[lastindex+1:index])
            lastindex = index
    else:
        splitted = [data]

separating by: 0x0
SampleNo     [1536; 1152] separated in 70 chunks: [4, 0, 3, 17, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16]
ProgramNo    [1531; 1148] separated in 71 chunks: [4, 0, 3, 2, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 12]
SegmentNo    [1531; 1148] separated in 69 chunks: [4, 0, 3, 18, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16]
CycleNo      [1531; 1148] separated in 71 chunks: [4, 0, 3, 2, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 12]
Time         [11944; 8958] separated in 63 chunks: [4, 0, 3, 45, 14, 42, 76, 46, 172, 110, 109, 15, 81, 90, 111, 108, 78, 46, 175, 141, 88, 209, 74, 117, 156, 170, 59, 107, 78, 103, 125, 171, 103, 170, 191, 333, 154, 187, 11, 257, 149, 208, 173, 156, 153, 412, 72, 55, 207, 131, 131, 274, 284, 238, 19, 241, 247, 13, 74, 558, 763, 8, 0]
Temperature  [6731; 5048] separated in 14 chunks: [4, 0, 3, 394, 186, 543, 177, 173, 530, 534, 371, 714, 373, 1032]
Error        [398; 298] separated in 21 chunks: [4, 0, 3, 2, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 12]
Fluor1       [7539; 5654] separated in 38 chunks: [4, 0, 3, 31, 13, 7, 7, 426, 331, 218, 187, 11, 10, 13, 7, 6, 7, 48, 45, 217, 840, 6, 7, 14, 7, 6, 7, 7, 6, 1178, 8, 6, 1147, 7, 6, 141, 630, 2]
...
Gain1        [3046; 2284] separated in 145 chunks: [4, 0, 3, 9, 7, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 8, 7, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 8, 7, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 8, 7, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 8, 7, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 8, 7, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 8, 7, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 8, 7, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 8, 7, 16, 16, 16, 16]
...

DARZ = Double[]
LARZ = Time? Havent decoded this
FORM = Double[][] (has 96 DARZ fields), this is the only field where byte 6 is 01x
Empty = Just a bunch of 0-1-2 

For the first three types the first four bytes thus identify the type.
byte 1-4            = TypeID
byte 5-8            = The size of the element  (BigEndian)
byte 9-12           = Checksum?
byte 13 - 13+length = the actual data.

Header DARZ (5 bytes including null terminator)
Null bytes (2 bytes)
Block size (1 byte)
Null bytes (2 bytes)
Array size (1 byte)
Array of Doubles / Float64 (8 bytes each one)
End mark (1 byte)

class CycleFloat64(FieldSet):
    def createFields(self):
        yield CString(self, "DARZ Header")
        yield Bytes(self, "6 bytes", 0x6)
        yield Float64(self, "Value 1")
        yield Float64(self, "Value 2")
        yield Float64(self, "Value 3")
        yield Bytes(self, "1 byte", 0x1)