Adapting multidimensional measurements for Valentina
At first glance, adapting measurements for Valentina doesn’t seem to cause any difficulties. But is it really?
The Valentine has come a long way in the evolution of approaches to measurement description. It all started with the measurements directly in Valentina’s file. Then the measurements were placed in a separate mandatory file. In the beginning, only multisize tables of measurements were supported. But later tables for individual measurements were added. And here we are closer to the current state of affairs. While the individual measures files are more or less self-explanatory, the use of multidimensional tables may raise many questions. The first implementation of the multisize tables was oriented to the Russian standard, but since the last significant update now supports a much larger number of variants.
As the process of adapting multi-dimensional tables is very important and raises many questions, this is what we will talk about today.
Several adaptations of the tables are already available on our website: GOST 17522-72, GOST 17521-72, GOST 17916-86 and GOST 17917-86. These versions of the tables can be called “archaic” and the most difficult to adapt, but they are the ones that allowed us to develop the technology, which makes it much easier to adapt other similar tables. In one of the articles we described the difficulties encountered in processing these tables.
More modern variants such as: GOST 31399-2009, GOST 31396-2009, OST 17-325-86 or OST 17-326-81, which will be discussed next, are easier to adapt. However, as is often the case, the devil is in the details.
At first glance, all these tables are very conveniently designed. For each measurement there is its sequence number, abbreviation and most importantly the height and size offsets. This makes it much easier to adapt such a table for Valentina. It allows you to not have to calculate the offset coefficient manually, and to not have to waste time calculating corrections. Recall previous examples where you had to do it all yourself. Therefore, we are probably the only ones who have adapted these tables.
However, the fact that the table itself is broken down into fullness groups, which in turn can also be broken down into subgroups, adds a fly in the ointment to our barrel of honey. This approach allowed the authors to provide us with offsets for ease of use. Therefore, at first glance, adapting these tables is not such a difficult task. It is within anyone’s power. All that is needed is to enter the name of the measure, select the base value and the coefficients. If that were all that could be done in this situation, we probably wouldn’t even be talking about it now.
A straightforward solution has its disadvantages. For example, GOST 31396-2009 requires the creation of as many as fourteen separate files. For GOST 31399-2009 it is already ten separate table files. OST 17-326-81 has the same problem - nine tables. And only OST 17-325-86 does not have this problem. This number of tables is not convenient to use, because it forces us to constantly switch between them, and it takes time.
The first logical solution is to combine the individual subgroups of the same fullness group into a single table. However, in this case we can no longer rely on the offsets given to us by the authors. And we would have to calculate the new offsets and corrections ourselves, which is not easy to do manually. If you still have any doubts, you can try it yourself, but be warned that it cannot be done without automation. And that’s exactly the way we’ve chosen to do it.
If we only work with fullness groups, the situation improves. For GOST 31396-2009 it is six tables, GOST 31399-2009 - five tables, OST 17-325-86 - also five tables and OST 17-326-81 - already only four tables.
We have written a special programme to automate the conversion process. But before it can create a file for us, the table data must be prepared in a format that the software can understand. As you already know, they are distributed in the form of a PDF file at best, and in the worst case in the form of poor quality page scans. Therefore the first task is to transfer this data to the table processor. If possible, the data is copied directly from the file or recognized and then transferred. This step is the most time-consuming, and it already shows how time-consuming the process is. And if you add the need to calculate the coefficients and offsets yourself, it becomes just incredibly boring and complicated. Not everyone can handle it, but we can. And you will soon be able to see that.
The way the table is organised in the table processor is quite simple. In the first column the measurement numbers are recorded. The first three lines are reserved for dimensions. In our case they are height, chest circumference (size) and waist circumference (for men) or hip circumference (for women). In each column the value of the measurement is written in the corresponding line. This way, by selecting a measurement and moving along the row, you can find the value for the pairs height, size, circumference.
The first difficulties already arise in the design of this table. Text recognition applications do not always recognise numbers correctly. Especially with scans of poor quality, which are often also distorted. Therefore you should periodically correct such errors and transfer them into the table column by column. In addition to technical errors you may also encounter some very strange ones. They give rise to conspiracy theories. You may observe that the measurement values are incorrect and, in some cases, there may be missing values for one fullness group for sizes present in other groups. There are even cases where an entire group of measurements is missing. All this has to be paid attention to and even more time should be spent. Fortunately, thanks to coefficients, all this data can be corrected and restored. In a table processor, this is quite easy to do. However, we have to do all of this ourselves, there is no software that can help us understand how to correct the data.
As you might guess, this process has to be repeated as many times as the fullness groups have a standard. This is even more work.
However, it is not very convenient to work with a normal table, so such a table needs to be converted to a more convenient format. Yes, yes, we have created a separate program for that. It is responsible for converting table data to JSON.
Click to see full file listing
{
"dimensions": [
{
"number": "1",
"values": [
164,
164,
164,
164,
164,
170,
170,
170,
170,
170,
176,
176,
176,
176,
176,
182,
182,
182,
182,
182,
188,
188,
188,
188,
194,
194,
194
]
},
{
"number": "16",
"values": {
"164": [
44,
46,
48,
50,
52
],
"170": [
44,
46,
48,
50,
52
],
"176": [
44,
46,
48,
50,
52
],
"182": [
44,
46,
48,
50,
52
],
"188": [
46,
48,
50,
52
],
"194": [
48,
50,
52
]
}
}
],
"measurements": {
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},
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},
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},
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},
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},
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}
},
"98": {
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},
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},
"176": {
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},
"182": {
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},
"188": {
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},
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}
},
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},
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},
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},
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},
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},
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}
},
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},
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},
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},
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},
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},
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}
},
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},
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},
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},
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},
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},
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}
},
"7": {
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},
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},
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},
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},
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},
"194": {
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}
},
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},
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},
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},
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}
},
"10": {
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},
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},
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},
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},
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},
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}
},
"11": {
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},
"170": {
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},
"176": {
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},
"182": {
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},
"188": {
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},
"194": {
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}
},
"87": {
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},
"170": {
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},
"176": {
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},
"182": {
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},
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},
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}
},
"12": {
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},
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},
"176": {
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},
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},
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}
},
"13": {
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},
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},
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}
},
"14": {
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},
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},
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},
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}
},
"15": {
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},
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},
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}
},
"19": {
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},
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"176": {
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}
},
"20": {
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},
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},
"176": {
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},
"182": {
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},
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},
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}
},
"21": {
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},
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},
"176": {
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},
"182": {
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},
"188": {
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},
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}
},
"22": {
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},
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},
"176": {
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},
"182": {
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},
"188": {
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},
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},
"23": {
"164": {
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},
"170": {
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},
"176": {
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},
"182": {
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},
"188": {
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},
"194": {
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}
},
"24": {
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"50": 22.6,
"52": 23.0
},
"170": {
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},
"176": {
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},
"182": {
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},
"188": {
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"52": 24.6
},
"194": {
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}
},
"51": {
"164": {
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"48": 33.2,
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},
"170": {
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},
"176": {
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"52": 35.2
},
"182": {
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"50": 35.8,
"52": 36.0
},
"188": {
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"50": 36.6,
"52": 36.8
},
"194": {
"48": 37.2,
"50": 37.4,
"52": 37.6
}
},
"25": {
"164": {
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"48": 103.2,
"50": 103.2,
"52": 103.2
},
"170": {
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},
"176": {
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"50": 112.0,
"52": 112.0
},
"182": {
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}
We are now one step closer to our goal of a multidimensional table. To do this, all we need to do is convert our data into a format that Valentina understands. But before we can do that, we need to provide even more information for the program. As you might have noticed, the table has no information about the measure. Only its number. So we need to link this data to the reference table. Here you can enter the index number, abbreviation, name and description of the measurement. This can be done either by using the recognized text or by typing on the keyboard. It is a good thing that blind ten-finger typing was mastered at one time.
Click to see full file listing
{
"measurements": {
"1": {
"name": "Р",
"full_name": "Высота верхушечной точки - длина тела",
"description": "Измерение №1. Расстояние по вертикали от пола до верхушечной точки. Измеряют спереди"
},
"4": {
"name": "Втош",
"full_name": "Высота точки основания шеи сбоку",
"description": "Измерение №4. Расстояние по вертикали от пола до точки основания шеи сбоку"
},
"5": {
"name": "Впт",
"full_name": "Высота плечевой точки",
"description": "Измерение №5. Расстояние по вертикали от пола до плечевой точки"
},
"6": {
"name": "Вст",
"full_name": "Высота сосковой точки",
"description": "Измерение №6. Расстояние по вертикали от пола до сосковой точки"
},
"7": {
"name": "Влт",
"full_name": "Высота линии талии",
"description": "Измерение №7. Расстояние по вертикали от пола до точки уровня талии. Уровень талии переносят отметками с помощью антропометра на позвоночник и середину передней поверхности тела"
},
"9": {
"name": "Вк",
"full_name": "Высота коленной точки",
"description": "Измерение №9. Расстояние по вертикали от пола до коленной точки"
},
"10": {
"name": "Вшт",
"full_name": "Высота точки основания шеи сзади",
"description": "Измерение №10. Расстояние по вертикали от пола до точки основания шеи сзади"
},
"11": {
"name": "Взу",
"full_name": "Высота заднего угла подмышечной впадины",
"description": "Измерение №11. Расстояние по вертикали от пола до заднего угла подмышечной впадины. Уровень заднего угла подмышечной впадины переносят отметкой на позвоночник с помощью антропометра"
},
"12": {
"name": "Впс",
"full_name": "Высота подъягодичной складки",
"description": "Измерение №12. Расстояние но вертикали от пола до середины подъягодичной складки"
},
"13": {
"name": "Ош",
"full_name": "Обхват шеи",
"description": "Измерение №13. Ленту накладывают вокруг шеи перпендикулярно ее оси так, чтобы нижний край ленты проходил через точку основания шеи сзади. Размер читают по нижнему краю ленты"
},
"14": {
"name": "Ог1",
"full_name": "Обхват груди первый",
"description": "Измерение №14. Ленту накладывают на лопатки. По спине лента должна проходить горизонтально, касаясь верхним краем задних углов подмышечных впадин, затем по подмышечным впадинам. Спереди лента должна проходить на уровне передних углов подмышечных впадин и замыкаться на правой стороне груди. По верхнему краю ленты делают отметку спереди над правой сосковой точкой"
},
"15": {
"name": "Ог2",
"full_name": "Обхват груди второй",
"description": "Измерение №15. Ленту на лопатки. По спине лента должна проходить горизонтально, касаясь верхним краем задних углов подмышечных впадин, затем по подмышечным впадинам в плоскости косого сечения, спереди - через сосковые точки и замыкаться на правой стороне груди"
},
"16": {
"name": "Ог3",
"full_name": "Обхват груди третий",
"description": "Измерение №16. Ленту накладывают горизонтально вокруг туловища через сосковые точки и замыкают на правой стороне груди"
},
"18": {
"name": "От",
"full_name": "Обхват талии",
"description": "Измерение №18. Ленту горизонтально вокруг туловища на уровне линии талии и замыкают спереди"
},
"19": {
"name": "Об",
"full_name": "Обхват бедер с учетом выступа живота",
"description": "Измерение №19. Ленту накладывают горизонтально вокруг туловища на уровне ягодичных точек, спереди по гибкой платине, приложенной вертикально к животу, для учета выступания живота, и замыкают на правой стороне туловища"
},
"20": {
"name": "Об1",
"full_name": "Обхват бедер без учета выступа живота",
"description": "Измерение №20. Ленту накладывают горизонтально вокруг туловища на уровне ягодичных точек и замыкают на правой стороне туловища"
},
"21": {
"name": "Обед",
"full_name": "Обхват бедра",
"description": "Измерение №21. Ленту горизонтально вокруг бедра, касаясь верхним краем подъягодичной складки, и замыкают на наружной поверхности бедра"
},
"22": {
"name": "Ок",
"full_name": "Обхват колена",
"description": "Измерение №22. Ленту горизонтально вокруг ноги на уровне коленной чашечки и замыкают на наружной поверхности ноги"
},
"23": {
"name": "Ои",
"full_name": "Обхват икры",
"description": "Измерение №23. Ленту накладывают горизонтально вокруг ноги в области максимального развития икроножной мышцы и замыкают на наружной поверхности голени"
},
"24": {
"name": "Ощ",
"full_name": "Обхват щиколотки",
"description": "Измерение №24. Ленту накладывают горизонтально вокруг ноги непосредственно над внутренней лодыжкой и замыкают на наружной поверхности голени. Размер читают по нижнему краю ленты"
},
"25": {
"name": "Дсб",
"full_name": "Расстояние от линии талии до пола сбоку",
"description": "Измерение №25. Измеряют от линии талии по боковой поверхности бедра и далее вертикально до пола"
},
"26": {
"name": "Дсп",
"full_name": "Расстояние от линии талии до пола спереди",
"description": "Измерение №26. Измеряют в вертикальной плоскости от отметки уровня талии на середине передней поверхности тела (см. разм. Признак 7) через выступающую точку живота до пола. Лента должна быть натянута"
},
"27": {
"name": "Дн",
"full_name": "Длина ноги по внутренней поверхности",
"description": "Измерение №27. Измеряют по внутренне поверхности ноги расстояние от промежности до пола при слегка раздвинутых ногах. Для измерения используют сантиметровую ленту, край которой закреплен на жесткой пластине"
},
"28": {
"name": "Оп",
"full_name": "Обхват плеча",
"description": "Измерение №28. Измеряют перпендикулярно оси плеча. Лента верхним краем должна касаться заднего угла подмышечной впадины и замыкаться на наружной поверхности руки. Размер читают по верхнему краю ленты"
},
"29": {
"name": "Озап",
"full_name": "Обхват запястья",
"description": "Измерение №29. Измеряют перпендикулярно оси предплечья по лучезапястному суставу через головку локтевой кости. Ленту замыкают на наружной поверхности руки. Размер читают по нижнему краю ленты"
},
"30": {
"name": "Окис",
"full_name": "Обхват кисти с учетом большого (первого) пальца",
"description": "Измерение №30. Измеряют перпендикулярно оси кисти через пястно-фаланговый сустав первого пальца. Первый палец должен быть противопоставлен второму и прижат к нему. Ленту замыкают на наружной поверхности кисти"
},
"31": {
"name": "Шп",
"full_name": "Ширина плечевого ската",
"description": "Измерение №31. Измеряют от точки основания шеи сбоку до плечевой точки"
},
"32": {
"name": "Длуч",
"full_name": "Расстояние от точки основания шеи сбоку до лучевой точки",
"description": "Измерение №32. Измеряют от точки основания шеи сбоку через плечевую точку до лучевой точки"
},
"33": {
"name": "Дзап",
"full_name": "Расстояние от точки основания шеи сбоку до линии обхвата запястья",
"description": "Измерение №33. Измеряют от точки основания шеи сбоку через плечевую точку до линии обхвата запястья"
},
"34а": {
"name": "Впрп",
"full_name": "Расстояние от точки основания шеи сбоку до линии обхвата груди первого спереди",
"description": "Измерение №34a. Измеряют от точки основания шеи сбоку до отметки на линии обхвата груди первого спереди (см. разм. признак 14)"
},
"35а": {
"name": "Вг",
"full_name": "Расстояние от точки основания шеи сбоку до сосковой точки (высота груди)",
"description": "Измерение №35a. Измеряют от точки основания шеи сбоку до сосковой точки"
},
"36а": {
"name": "Дтп",
"full_name": "Расстояние от точки основания шеи сбоку до линии талии спереди (длина талии спереди)",
"description": "Измерение №36a. Измеряют от точки основания шеи сбоку через сосковую точку и далее вниз до линии талии"
},
"38": {
"name": "Дп",
"full_name": "Вертикальная дуга плечевой области",
"description": "Измерение №38. Измеряют в вертикальной плоскости расстояние от заднего угла подмышечной впадины через плечевой сустав до уровня заднего угла подмышечной впадины спереди"
},
"39": {
"name": "Впрз",
"full_name": "Расстояние от точки основания шеи сзади до уровня заднего угла подмышечной впадины",
"description": "Измерение №39. Измеряют от точки основания шеи сзади до уровня заднего угла подмышечной впадины, отмеченной на позвоночнике. При этом лента проходит через тонкую пластину шириной 2 см, верхний край которой должен быть расположен на уровне задних углов подмышечных впадин"
},
"40": {
"name": "Дтс",
"full_name": "Длина спины до талии с учетом выступания лопаток",
"description": "Измерение №40. Измеряют от точки основания шеи сзади до отметки уровня талии на позвоночнике через пластину (см. разм. признак 39)"
},
"43": {
"name": "Дтс1",
"full_name": "Расстояние от линии талии сзади до точки основания шеи сбоку",
"description": "Измерение №43. Измеряют параллельно позвоночнику от линии талии сзади до точки основания шеи сбоку"
},
"44": {
"name": "Двчт",
"full_name": "Дуга верхней части туловища через точку основания шеи сбоку",
"description": "Измерение №44. Лента проходит от линии талии на спине параллельно позвоночнику через точку основания шеи сбоку, через сосковую точку, далее вниз до линии талии"
},
"45": {
"name": "Шг",
"full_name": "Ширина груди",
"description": "Измерение №45. Измеряют по поверхности тела расстояние между передними углами подмышечных впадин. Нижний край ленты должен касаться отметки, сделанной при измерении обхвата груди первого"
},
"46": {
"name": "Цг",
"full_name": "Расстояние между сосковыми точками",
"description": "Измерение №46. Измеряют между сосковыми точками в горизонтальной плоскости. Размер читают по верхнему краю ленты"
},
"47": {
"name": "Шс",
"full_name": "Ширина спины",
"description": "Измерение №47. Измеряют по поверхности тела расстояние между задними углами подмышечных впадин. Нижний край ленты должен быть расположен на уровне отметки заднего угла подмышечной впадины на позвоночнике (см. разм. признак 11)"
},
"48": {
"name": "Огол",
"full_name": "Обхват головы",
"description": "Измерение №48. Измеряют через центры затылочных и лобных бугров"
},
"49": {
"name": "Дс",
"full_name": "Расстояние от линии талии до плоскости сидения",
"description": "Измерение №49. Измеряют по боку от линии талии до горизонтальной плоскости сидения"
},
"51": {
"name": "Ос",
"full_name": "Обхват подъема стопы",
"description": "Измерение №51. Ленту накладывают через заднюю наиболее выступающую вниз область пятки и высшую точку стопы и замыкают спереди"
},
"57": {
"name": "dпзр",
"full_name": "Переднезадний диаметр руки",
"description": "Измерение №57. Измеряют горизонтально на уровне заднего угла подмышечной впадины"
},
"77": {
"name": "Дпоб",
"full_name": "Дуга через паховую область",
"description": "Измерение №77. Измеряют в вертикальной плоскости от линии талии спереди через выступающую точку живота, паховую область и тонкую платину шириной до 2 см, наложенную на ягодичные точки, до линии талии сзади"
},
"87": {
"name": "Влоп",
"full_name": "Высота лопаточной точки",
"description": "Измерение №87. Расстояние по вертикали от пола до лопаточной точки"
},
"90": {
"name": "Д3п",
"full_name": "Расстояние от точки основания шеи сбоку до конца третьего пальца",
"description": "Измерение №90. Измеряют от точки основания шеи сбоку по середине плечевого ската через плечевую точку до конца третьего пальца"
},
"98": {
"name": "Втос",
"full_name": "Высота точки основания шеи спереди",
"description": "Измерение №98. Расстояние по вертикали от пола до точки основания шеи спереди"
},
"104": {
"name": "Дпс",
"full_name": "Расстояние от линии талии до подъягодичной складки",
"description": "Измерение №104. Измеряют по поверхности тела от линии талии через ягодичную точку до подъягодичной складки"
}
}
}
Also remember to set up the setting table. The basic measurement values must be selected. In other words, height and size. Yes, only them, because using a third dimension makes no sense. The values there always go in pairs with the size. So instead we will tell the program to generate the labels.
Now we are really ready. By combining all the data and running the application, we get results instantly. Instant if you don’t consider how much time was spent recognising the data.
Remember we talked about errors in table data? How do we make sure we find them all? You can’t do without special tests here. Yes, even more work. Instead of trying to go through the data ourselves and look for errors, a test can do it for us. It is through tests that we learned about recognition errors and direct errors in the tables themselves. To test the data, we assumed that all data in one table always matched the specified offset coefficient. This allowed us to write out the corresponding pairs and compare with the values in the table. This revealed an unpleasant fact. There are errors even in the values of these coefficients. Which completely undermines the blind faith in the correctness of the data in the standard table.
Only after the tests find no more discrepancies is it possible to be more confident that the data is correct.
However, why stop there? Why not try to merge the individual fullness tables into one? And yes, it is possible!
Remember our table in the table processor? We also mentioned that we don’t need to adjust the third dimension as it is always paired with the size. And that we will format it as a label. This is how all the fullness groups tables are designed. But if you have a closer look you can see the pattern. Each size is associated with more than one waist or hip circumference. If you combine the columns and put them in the right order, then this table is very similar to the complex ones that we have worked with before. This means that there is no need for separate fullness tables! So we spend some more time merging data into one huge table, convert it into JSON and in a second we get a table containing all the data of the standard. At the same time, the software has calculated the new offset and correction coefficients for us. It also correctly configured all three measurements, their limits and their steps.
The single table option was a nice bonus. But it is only possible because the authors have put in offset coefficients, which allows us to check that the data are correct.
In the end, the technology developed allowed us to create several variants of each standard. This resulted in 11 different variants, which you can find on our website in the relevant section. In fact, each table is presented in three variants:
- The simplest version, in which the data are arranged as they are in the standard itself with the same number of tables. This version is not very user-friendly, but with a little time everyone can replicate it on their own. It is enough to transfer the measure names, base values and coefficients. Be careful though, the tables in the standard may have errors.
- Each fullness group is designed as a separate file. This is much better than the previous version, as the number of tables is reduced. Offsets and corrections have been calculated separately for this.
- The best option is to have everything in one table. All the data of the fullness groups are combined into one table. Offsets and corrections are calculated separately for them.
Analysing our experience, you can conclude that the multidimensional measure scheme is over-complicated. And that it would be easier to allow users to enter raw data, i.e. the value of the measure for each pair of dimensions. However, we cannot agree with this statement. Working with offsets allows for a fairly short time to start working with measures. And is justified for simple tables, as demonstrated in the simplest example. This option is available to everyone. At the same time, one still has the opportunity to check the correctness of the data. When dealing with large amounts of data, the chance of error increases proportionately and without proper data testing there is little benefit from this approach. Practice has shown that even official documents contain a significant number of errors which can easily be put down to trivial typing errors. And it turns out that if a person has the ability to write special tests to verify the correctness of the data in the table, then there is no problem to make another step and directly generate the table file itself. Which we have successfully demonstrated. After all, Valentina relies on the correctness of your data and has no way to check its correctness. And at the same time, using corrections reduces the size of the file itself, which is a nice bonus.
We would like to point out that the existing model does not allow direct import of raw data from CSV. Of course, this could partly solve the problem of creating the file for people without programming skills. But it seems doubtful that they would be able to get the correct input data without proper testing. However, if there are people who want to implement this import mode, we will gladly accept these changes into the main Valentina source tree. For ourselves, however, we have found a more convenient way to minimise the amount of work required.
Not all multidimensional tables can be found on the Internet. Some of them are not publicly available. So if you are a Valentina user and still have such a table, you can contact us and we can help you adapt it for Valentina. We guarantee that your table will only be used for adaptation and will not be made freely available. The cost of adaptation will depend on the complexity of the work.
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