Affine transforms - matrix algebra

Kirill Prazdnikov Kirill.Prazdnikov at oracle.com
Thu Jul 12 05:08:18 PDT 2012


Transformation matrix consist of four vectors. In case of affine, it is 
coordinates of local orts + translation.
Accessing this vectors is the most get/set use-case.
I can not imagine where accessing individual matrix values could be used 
(useful) at all.

Does anybody uses it ?

-Kirill

On 12-Jul-12 15:23, Pavel Safrata wrote:
> I like the get(row, col) method, I think we can introduce it in 
> addition to the array conversions. Similarly we can add set(row, col, 
> value). Both just convenience methods internally calling the actual 
> property getters/setters.
>
> Pavel
>
> On 12.7.2012 11:05, Martin Desruisseaux wrote:
>> The array methods may also be useful for working on matrix 
>> coefficients using indices rather than hard-coded access to the mxx, 
>> mxy, etc. properties. For example: when the affine may contain scale, 
>> rotation, flip and translation but no shear, at least in the 2D case 
>> (I think it works in 3D too), we can compute the scale factors "as if 
>> there were no flip or rotation" by computing the square root of the 
>> sum of the square of all values (except translation) on a row or a 
>> column. Whatever we compute on rows or on columns depend on whatever 
>> we want the scale factors to be expressed relative to the axes of the 
>> source coordinate system or the target coordinate system (this is not 
>> the same if there is a rotation). For this kind of computation, 
>> looping over an array using indices - or alternatively providing a 
>> Matrix.get(row, column) method - is convenient.
>>
>>     Martin
>>
>>
>> Le 12/07/12 08:35, Pavel Safrata a écrit :
>>> Hi Kirill,
>>> you are not right with the performance, the elements are (possibly 
>>> invalid) properties so we need to call all the getters anyway, plus 
>>> construct the array, so the performance is actually worse. But the 
>>> use-case seems to be valid, especially if the other libraries 
>>> support such conversion. I just wouldn't call it 'asArray' which 
>>> suggests that the array will keep updating with the matrix changes 
>>> but rather 'toArray'. To be consistent we need to use doubles 
>>> instead of floats and we should also add a similar setter. So I 
>>> propose:
>>>
>>> public double[] toArray()
>>> public double[] toArray(double[] a)
>>> public Affine(double[] matrix)
>>> public void setTransform(double[] matrix)
>>>
>>> Where the first two will behave similarly as if it was a List of 12 
>>> doubles, the latter two will throw IllegalArgumentException if 
>>> length of the array is not 12.
>>>
>>> Regards,
>>> Pavel
>>
>
>



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