[GRASS-user] Multiple to one question

[Adam Dershowitz, Ph.D., P.E.]

On Apr 14, 2009, at 9:51 AM, Vincent Bain wrote:

> Hmmm, not sure you understood what I suggested (or maybe I did not  
> catch
> your point of view !). Let's consider you add two measures a week for
> point A (cat=1), and 1 measure monthly for point B (cat=2), then after
> one year you have :
> * in table1 (cat integer):
> 2 recors (cat=1 and cat=2)
>
> * in table2 (cat integer, mes float):
> 116 records (104 records with cat=1 and 12 records with cat=2).

Thank you.  I didn't understand before (I thought that you meant a  
column for each measurement date).  But this does explain it, and it  
makes a lot of sense.

--Adam
>
>
> Where is there a problem for you ?
> Hope this helps,
>
> VB
>
>
> Le mardi 14 avril 2009 à 09:38 -0700, Adam Dershowitz, Ph.D., P.E. a
> écrit :
>> On Apr 14, 2009, at 4:06 AM, Moritz Lennert wrote:
>>
>>> On 14/04/09 08:37, Vincent Bain wrote:
>>>> Hello Adam,
>>>> maybe another solution in this case would be a set of 2 tables :
>>>> * one linking to the geometry, that is containing nothing but cat
>>>> values,
>>>> * another one, containing a cat column (related to the "geometric"
>>>> table) and different data columns corresponding to your sampling.
>>>
>>> I think that if all you want is calculate some means or similar
>>> across dates and then display the results, Vincent's solution is the
>>> easiest.
>>>
>>> But you could also use layers [1]:
>>>
>>> layer 1 = January round of sampling
>>> layer 2 = February round of sampling
>>> etc.
>>>
>>> You would have to give each point a category value in each layer (cf
>>> v.category) and then either create separate tables for each period
>>> linking each to one of the layers or at least create some obvious
>>> cat values (i.e. 100s for January, 200s for February, etc) and link
>>> on single table to all the layers, but with different cat values in
>>> each layer.
>>>
>>>
>>> Moritz
>>>
>>> [1] See "Vector object categories and attribute management" on http://grass.osgeo.org/grass64/manuals/html64_user/vectorintro.html
>>> for a quick introduction
>>
>> Thanks,
>>
>> But, the problem with both of these approaches, columns, and layers,
>> (Vincent or Moritz version) is that I don't have consistent times for
>> each site.  So, at site A I might have 5 samples, once a month and at
>> site B I have 2 samples, one each year, and site C I have a few  
>> spread
>> over a few years.
>> So both of those approaches essentially need to have a column, or
>> layer, for each possible time of sampling.  But that is not really
>> appropriate for the quasi-random times of the samples.
>>
>>
>>>
>>>
>>>> Does this help ?
>>>> VB
>>>> Le lundi 13 avril 2009 à 14:23 -0700, Adam Dershowitz a écrit :
>>>>> I am trying to set up a new project in Grass, and I have a
>>>>> question  about the best approach.
>>>>> I have different vector locations, and at each one there were
>>>>> multiple  samples taken.  At the moment I have each sample as a
>>>>> row in a data  base.
>>>>> My question is how best to put this data into a set of vector
>>>>> points.
>>>>> I believe that I can do it in either of two ways (of not others).
>>>>> 1)  I can create a vector point at each location, then I think
>>>>> that I  can have multiple cats for that object.  So I think I can
>>>>> do cat=1,3,6  for a given location.
>>>>> Will that work OK?
>>>>> 2)  I can just create different vector objects, that happen to be
>>>>> at  the identical location, and have each one point to a different
>>>>> cat.
>>>>>
>>>>> If the above is not clear, here is a bit more detailed example.
>>>>> At location A there was a sample collected on 1/1 with a value of
>>>>> 2.1,  on 2/2 with a value of 2.2 and on 3/3 with a value of 3.3
>>>>>
>>>>> The above data is already 3 rows in a database.
>>>>>
>>>>> I want to be able to display data about point A (say, average
>>>>> value or  things like that).  Should I just create a vector point
>>>>> A and then do  cat=1,2,3 or should I create 3 different vector
>>>>> points at A, each one  having a different cat?
>>>>>
>>>>> Any guidance about the benefits or limitations each approach (or
>>>>> any  other approach to consider) would be greatly appreciated.
>>>>>
>>>>> Thanks,
>>>>>
>>>>> --Adam
>>>>>
>>>>>
>>>>>
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>>
>