dhis2-devs team mailing list archive

[Knut Staring <knutst@xxxxxxxxx>]

On Fri, Sep 25, 2009 at 1:32 PM, Ola Hodne Titlestad <olatitle@xxxxxxxxx>wrote:

>
> 2009/9/25 Bob Jolliffe <bobjolliffe@xxxxxxxxx>
>
> Hi Jason
>>
>> 2009/9/25 Jason Pickering <jason.p.pickering@xxxxxxxxx>
>>
>>> Hi there.
>>>
>>> My basic issue with the category/category combo is that it appears to be
>>> a one-to-one relationship with data elements. If I look at the data model,
>>> there is a one-to-one relationship between dataelement and categorycomboid.
>>> For a given category combo, you can have multiple options. So, you can
>>> establish a relationship for a given data element and a group of category
>>> options.
>>>
>>> Let me try and describe the issue. We have a set of data elements related
>>> to malaria for this example. We would like to be able to pivot the data on
>>> other dimensions dimensions (Data element, age, disease, patient status).
>>> Obviously there are other dimensions that are pivotable (orgunit, period,
>>> dataset)
>>>
>>> The data elements look like this. I have put the dimensions in square
>>> brackets, and the dimensional elements into curly brackets.
>>>
>>> [Data element, Age, Disease, Patient status]
>>> Deaths Confirmed Malaria total (composed of) {All ages, Malaria Cases,
>>> Deaths}
>>> Deaths Confirmed Malaria 1 to Under 5 Years  {1-5, Malaria Cases, Deaths}
>>>
>>> Deaths Confirmed Malaria Over 5 Years {Over 5, Malaria Cases, Deaths}
>>> Deaths Confirmed Malaria Under 1 Year {Under 1, Malaria Cases, Deaths}
>>> IP Discharge Confirmed Malaria total (composed of) {All ages, Malaria
>>> Cases, IP}
>>> IP Discharge Confirmed Malaria 1 to Under 5 Years {1-5, Malaria Cases,
>>> IP}
>>> IP Discharge Confirmed Malaria Over 5 Years {Over 5, Malaria Cases,
>>> Deaths}
>>> IP Discharge Confirmed Malaria Under 1 Year {Under 1, Malaria Cases,
>>> Deaths}
>>> OPD 1st Attendance Confirmed Malaria total (composed of) {All ages,
>>> Malaria Cases, OPD}
>>> OPD 1st Attendance Confirmed Malaria 1 to Under 5 Years {1-5, Malaria
>>> Cases, OPD}
>>> OPD 1st Attendance Confirmed Malaria Over 5 Years {Over 5, Malaria Cases,
>>> OPD}
>>> OPD 1st Attendance Confirmed Malaria Under 1 Year {Under 1, Malaria
>>> Cases, OPD}
>>>
>>> OK,  I hope this is pretty clear. Obviously, there are more data elements
>>> (Typhoid, Yellow fever, etc). I might want to know how many Under 1 deaths I
>>> have had for all diseases, or how many OPD cases I have had for each
>>> disease. How can I do this with the existing data model? It is not obvious
>>> to me because there is no relationship between dimensional elements
>>> (categoryoptions) to each other. Category options can be related through a
>>> cateogry combination, but since data elements can only be assigned a single
>>> category option, the dimensionality is broken once it gets time to pull the
>>> data into a pivot table.
>>>
>>
>> I think you mean datelements can be assigned a single categorycombo?  I
>> have found the multi-dimensional model confusing but I am not convinced that
>> it is broken.  All of the dimensionality is indeed captured but we seem to
>> be missing the convenience methods in the API and the UI to make use of it.
>>
>>
>>>
>>>  In the incomplete example that I gave yesterday, I established a
>>> one-to-many relationship between a data element and a dimension. If I
>>> understand the current data model, I would have to create a separate
>>> categorycombo  for each of these data elements, and assign this
>>> categorycombo to the data element. Now, I might be able to unfold the
>>> dimensions using the categories and categorycombos. I it is not apparent how
>>> the dimensional elements correspond themselves to a particular dimension, as
>>> there is no relation for this in the database as I can see it.
>>>
>>
>> As I see it, from the reporting/analysis perspective the categorycombo is
>> of little use.  It is simply a convenience to indicate the dimensions which
>> exist for the dataelement.  Which is why I have been referring to it a
>> dimensionset.  The relation between a dimension and its dimensional element
>> is captured through the categoryComboCategoryAssociations.
>>
>> I think you are right and the whole categorycombo could be done away with
>> by simpling having a one to many relationship between dataelements and
>> dimensions (categories).  Though the categoryCombo does seem useful when
>> creating datelements in the user interface.  There may be many dataelements
>> which share the same dimensionsets.  For example Age/Disease/Patient Status
>> in your example above.  So this set is given a name which allows it to be
>> easily reused across dataelements.  The downside being that it creates an
>> extra layer of indirection to get at particular dimensional elements.  This
>> results in the SQL efficiency issue you refer to below.
>>
>>
>>>  As (Johan pointed out a few mails ago, if I understand him correctly)
>>> is  different categorycombo's can be created for individual data elements,
>>> and assigned to these elements. However, this seems to be 1) incredibly
>>> inefficient and 2) does not establish any relationship between dimensional
>>> elements and dimensions. Perhaps it is there, and maybe it has been done in
>>> SL, but the SQL is not apparent to me at all.
>>>
>>>  It would appear to me, looking from an SQL perspective, that a
>>> one-to-many relationship between a data element, a dimension (category) and
>>> dimensional element (category combo) would be much more effieicnet, and
>>> highly usable from an SQL perspective.
>>
>>
>> Agreed.  As I said above, I don't think the current model is broken, but
>> it has an extra indirection level.
>>
>>
>>> As I mentioned in my mail, I am not sure how easy this would be to
>>> implement in a procedural language like Java, but I assume it should be
>>> possible to either do it this way, or rewrite my Postgres proprietary query
>>> in standard SQL (which there are ways to do with ANSI SQL).  This would
>>> require modification to the data model (similar to the table I provided
>>> yesterday) and modification to the UI to allow users to 1) select a
>>> dimension (category) 2) Select a dimensional element for the given
>>> dimension.  This would populate the table with a dataelementid, a
>>> dimensionid (categoryid) and a dimensional element (cateogryoptionid).
>>>
>>
>> It should certainly be possible to implement this UI interface with the
>> current datamodel.  step (1) would involve selecting a dimension from the
>> dimensionset associated with the dataelement.  I think this is currently
>> lacking.
>>
>>
>
> I think I am starting to see Jason's problem a bit clearer now. A
> limitation to only be able to pull data from one dataset (one categorycombo)
> into a report or OLAP cube is not enough. We need this restriction when
> dealing with raw data, e.g. in data entry and import/export, but for reports
> and analysis I think we need to come up with a more flexible solution along
> the lines of what Jason is suggesting. I think the exisiting model can be
> used though, but more flexibility is needed in the report table UI. I think
> we could have a OLAP cube builder (or ideally also an Excel pivot table
> designer/generator) as part of or extension to the report table UI we have
> today.
>

I am no expert on this, but Mondrian has virtual cubes, meant for combining
data from different cubes. As we know, OpenHealth Elements are making use of
such functionality. Maybe some discussion with the people behind it would be
in order. Jiri will be in Geneva next week (focusing on FluID), perhaps a
chat with him (over lunch or dinner?) could be arranged.

Knut


> When generating cubes/ datamarts with dimensions (data element categories)
> it should be possible to pick categories freely and completely independent
> on categorycombos. As long as two data elements share one category it should
> be possible to ask for a datamart with those two data elements and that
> shared category with values breaken up by that category's options. Similar
> to the table Jason is requesting, Data Element, Category, CategoryOption.
> This will involve aggregation across the category options, and produce a
> much more flexible view to the data than what is necessary when entering
> data in a form.
>
> Ola
> ------------
>
>
>>
>>> My gut feeling this is exactly the same functionality as has currently
>>> been implemented for organizational units. Users can define a hierarchy for
>>> organizational units, and then assign them to
>>> categories/dimension/organizational group sets, decide whether the groups
>>> are compulsory and exlusive, and then assign a particular organizational
>>> unit to a particular group (which is analogous to a dimensional element).
>>> Organizational group sets define the dimension, and one-to-one assignment of
>>> an organizational unit to a particular organizational group defines which
>>> dimensional element the organizational unit is a member of. These dimensions
>>> can then be used in PivotTable analyses, where the orgunitgroupsets become
>>> dimensions, and orgunitgroups become dimensional elements..
>>>
>>
>> This model is also supported in SDMX ie. composing hierarchies of
>> dataelements.  I suppose it comes down to naming.  Our model allows a single
>> dataelement which contains multiple dimensions within it.  The hierarchical
>> model has multiple dataelements which can be grouped hierarchically for the
>> purpose of aggregation.  In the end the effect is the same.  Possibly this
>> is similar to what we do with dataelement groups.
>>
>>
>>>
>>> I beleive that data elements are no different than organizational units.
>>> They should be able to be grouped into some sort of hierarchy and pivoted on
>>> any dimension.  Data elements groups establish a one-to-many relationship
>>> between data elements and a data element group, but there is no concept of
>>> how data element groups relate to each other.
>>> I think this is perhaps the same concept you mention, ReportSet.
>>>
>>
>> Not really.  The ReportSet would have no real significance from your
>> perspective - rather it would be a way to define the set of (ragged)
>> datasets which form a particular input form.
>>
>>
>>> I suspect we would need to potentially rethink the entire concept of
>>> multidimensionality if we really wanted to get it right. It would see to me
>>> that the DHIS datamodel and associated aggregation methods have been
>>> hardwired into aggregation across time (period) and geography (orgunit).
>>> What we can do with PivotTables and (and OLAP) is to aggregate across any
>>> possible dimension, slicing as you mention ,on any dimension . I am not sure
>>> this will be so simple to implement but I think there is a way to do it,
>>> without major modifications.
>>>
>>
>> Having the existing two fixed or mandatory dimensions is not necessarily a
>> bad thing.  But we must also be able to aggregate across the others
>> (currently hidden behind the categorycombo veil).  If the day goes well I'll
>> give you a stylesheet later for picking them out of a dxf file.  But
>> probably we do want to push this unravelling into the API.
>>
>> In the meantime (since you are out docbook champion) I've attached a
>> simple (and incomplete) stylesheet for making a docbook rendition of dxf
>> metadata.  I've been using this to try and make it easier to look at
>> different databases and how they have implemented dimensions.
>>
>> Run xsltproc (or some other xslt processor) on dxf2docbook.xsl with a dxf
>> metadata file as as a source file.
>>
>> Regards
>> Bob
>>
>>
>>> I am not sure it solves the SDMX issue. There are potential issues
>>> related to "ragged" dimensions and how these get handled. Some data elements
>>> might have three dimensions, while others may have more. I have not thought
>>> about this in detail, but know it is an issue with cross-tab queries in SQL.
>>> You normally have to know how many dimensions you are working with in order
>>> to perform a cross-tab, but there are dynamic solutions. Perhaps this could
>>> be dealt with somehow in SDMX.
>>>
>>> Anyway ,I am rambling. Hope this mail helps though to push my point
>>> further. Once I get the SQL from SL, I will see if perhaps it has been done
>>> already, and that I am just writing long emails for nothing. :)
>>>
>>> Regards,
>>>  Jason
>>>
>>>
>>>
>>>
>>>
>>> On Fri, Sep 25, 2009 at 10:44 AM, Bob Jolliffe <bobjolliffe@xxxxxxxxx>
>>> wrote:
>>> > Hi Jason and Johan
>>> >
>>> > I'm really pleased to see you having this discussion as I have been
>>> > grappling with a similar issue which involves unravelling categories,
>>> > category options and combos into something more familiar.  I have
>>> reached
>>> > similar conclusions regarding nomenclature:
>>> >
>>> > category = dimension
>>> > categorycombo - I have been calling a dimension set (it bears a strong,
>>> and
>>> > useful, resemblance to xslt:attribute-set)
>>> > category option - I like your suggestion of DimensionalElement.  I am
>>> going
>>> > to start calling it that too.
>>> >
>>> > In my case I need to export (and import data) into a standard format
>>> called
>>> > sdmx.  So whereas in the DHIS2 native DXF we export datavalues with
>>> > effectively three dimensions (source, period, categorycombooption) the
>>> last
>>> > dimension is a sort of uber-dimension.  Like a peppercorn or a cardamon
>>> > seed, when you break it open it explodes its rich complexity of
>>> dimensions.
>>> >
>>> > In sdmx we need the dimensions exploded.  So data values look like:
>>> >
>>> > <dataset>
>>> >   <datavalue name="TB test given" uid="44344 ...44" gender="Male"
>>> age="0-5"
>>> > value="32" />
>>> >    <datavalue name="TB test given" uid="44344 ...44" gender="Female"
>>> > age="0-5" value="38" />
>>> > ..
>>> > </dataset>
>>> >
>>> > My approach to unpicking the dimensions from the dxf file is to
>>> transform it
>>> > with an xslt transformation which is still incomplete but seems to work
>>> > well.
>>> >
>>> > One other nomenclatures issue which has surfaced as a result is what we
>>> call
>>> > a "dataset".  In DHIS2, if I understand correctly, a dataset
>>> corresponds
>>> > roughly to all the dataelements which might occur on a datacollection
>>> form.
>>> > If we view all dataelements as having just the three "dimensions" then
>>> all
>>> > is well, but if we explode the actual dimensions then we have an
>>> issue.  In
>>> > the sdmx model a dataset consists only of dataelements with the same
>>> > dimensionset.  After discussing this with Ola we have reached the
>>> conclusion
>>> > that we need another level of grouping, primarily for the UI - eg
>>> FormSet or
>>> > ReportSet which allows us to group related datasets.  But that is an
>>> aside
>>> > from what you are talking about.
>>> >
>>> > I know that you guys can do magic with sql, but it seems that we should
>>> try
>>> > to capture some of this and place it down in the datamodel API.  It
>>> occurs
>>> > to me that for a multidimensional dataelement we might benefit from
>>> some
>>> > utility methods to retrieve slices and dices which might assist in
>>> > constructing the pivot tables around dimensions.  Does this sound like
>>> the
>>> > right thing to do.
>>> >
>>> > Regards
>>> > Bob
>>> >
>>> > 2009/9/24 <johansa@xxxxxxxxxx>
>>> >>
>>> >> Jason,
>>> >> I will leave to others to comment the code, but I have a few
>>> comments...
>>> >>
>>> >> > I have done a bit more thinking on this, and would like to offer
>>> some
>>> >> > more examples up for discussion.
>>> >> >
>>> >> > Basically, we have a lot of data elements that are somehow related
>>> to
>>> >> > each other, similar to my kooky example in my original mail. I
>>> assume
>>> >> > this is fairly common throughout other HMIS systems. Here,  malaria
>>> >> > attendance is broken down into various dimensions/category by
>>> patient
>>> >> > type (outpatient, inpatient, and deaths) and by age (under 1 ,1-5
>>> and
>>> >> > over 5). But say you want to be able to pivot to look at outpatient,
>>> >> > inpatient and deaths totals (i.e. summed up by age). Well, you could
>>> >> > create a separate data element for this, but it sure would be nice
>>> to
>>> >> > be able to Pivot the data somehow.
>>> >>
>>> >> In the Sierra Leone db, Edem and Romain set up views that pulled the
>>> >> categories through into a "Category" pivot field, which you can then
>>> use
>>> >> to get what you want. Simply tick the categories (see below) you want
>>> to
>>> >> see, and group them together in excel. Maybe Edem and Romain can help
>>> >> further here.
>>> >>
>>> >>
>>> >> > Dimension ? Category
>>> >> > Dimensional element ? Category option ? Category combo ( I think)
>>> >>
>>> >> The right symbol disappeared from my reply-mail here, but some
>>> >> clarification:
>>> >>
>>> >> Crosstab Dimension (age AND gender) = Category combo
>>> >> Dimension (age, gender) = Category
>>> >> Dimensional element (inpatient, outpatient, death, under1, 1-5, and
>>> over
>>> >> 5) = Category option
>>> >>
>>> >> So by assigning a DE the category combo of "gender_age", you get 9
>>> >> dimensional elements, 3 category options (in category age) by 3
>>> category
>>> >> options (in category gender)
>>> >>
>>> >> Johan
>>> >>
>>> >>
>>> >>
>>> >>
>>> >> > Anyway, here is the helper table I created.
>>> >> >
>>> >> > CREATE TABLE test_dataelementcategorycombo
>>> >> > (
>>> >> >   test_dataelementid integer NOT NULL,
>>> >> >   test_dataelementcategoryid integer NOT NULL,
>>> >> >   test_dataelementcategorycomboid integer NOT NULL,
>>> >> >   CONSTRAINT pk_testdataelementcategory PRIMARY KEY
>>> >> > (test_dataelementid, test_dataelementcategoryid,
>>> >> > test_dataelementcategorycomboid)
>>> >> > )
>>> >> > WITH (OIDS=FALSE);
>>> >> >
>>> >> > So this is  a real simple table which references a data element, a
>>> >> > data element category, and a data element combo. The reference to a
>>> >> > data element category may be redundant, but anyway, lets leave it in
>>> >> > for now.
>>> >> >
>>> >> > I populated the table with some data, which will be used to assign
>>> >> > dimensions to data elements. It looks like this in my DB, which
>>> looks
>>> >> > like this.
>>> >> >
>>> >> > 309;25250;25251
>>> >> > 309;25257;25255
>>> >> > 348;25250;25252
>>> >> > 348;25257;25255
>>> >> > 455;25250;25253
>>> >> > 455;25257;25255
>>> >> >
>>> >> > but of course this is meaningless to you. What do these values
>>> >> > correspond
>>> >> > to?
>>> >> >
>>> >> > "OPD 1st Attendance Clinical Case of Malaria Under 1
>>> Year";"Age";"Under
>>> >> > 1"
>>> >> > "OPD 1st Attendance Clinical Case of Malaria 1 to Under 5
>>> >> > Years";"Age";"Age 1-5"
>>> >> > "OPD 1st Attendance Clinical Case of Malaria Over 5
>>> Years";"Age";"Over
>>> >> > 5"
>>> >> > "OPD 1st Attendance Clinical Case of Malaria Under 1 Year";"Patient
>>> >> > status";"OPD"
>>> >> > "OPD 1st Attendance Clinical Case of Malaria 1 to Under 5
>>> >> > Years";"Patient status";"OPD"
>>> >> > "OPD 1st Attendance Clinical Case of Malaria Over 5 Years";"Patient
>>> >> > status";"OPD"
>>> >> >
>>> >> > which can be produced by the following view.
>>> >> >
>>> >> > CREATE OR REPLACE VIEW vw_dataelements_dimensions AS
>>> >> >  SELECT dataelement.name, dataelementcategory.name AS dimension,
>>> >> > dataelementcategoryoption.name AS dimension_element
>>> >> >    FROM dataelement
>>> >> >    JOIN test_dataelementcategorycombo ON
>>> >> > test_dataelementcategorycombo.test_dataelementid =
>>> >> > dataelement.dataelementid
>>> >> >    JOIN dataelementcategory ON dataelementcategory.categoryid =
>>> >> > test_dataelementcategorycombo.test_dataelementcategoryid
>>> >> >    JOIN dataelementcategoryoption ON
>>> >> > test_dataelementcategorycombo.test_dataelementcategorycomboid =
>>> >> > dataelementcategoryoption.categoryoptionid;
>>> >> >
>>> >> > So, that view just provides a human readable view of those integers
>>> >> > that I populated in the the test_dataelementcategorycombo table I
>>> >> > created above.  This table just assigns particular data elements to
>>> >> > different category options (dimensional elements).
>>> >> >
>>> >> > OK, so far so good, but the problem now is, how to use this with the
>>> >> > aggregatedatavalue table? If we try and join this table directly, we
>>> >> > will have issues with duplicates in the pivot table, so we need to
>>> >> > transform the data slightly.
>>> >> >
>>> >> > This should do the trick.
>>> >> >
>>> >> > SELECT * FROM crosstab
>>> >> >       (
>>> >> > 'SELECT name, dimension, dimension_element FROM
>>> >> > vw_dataelements_dimensions ORDER BY 1,2,3',
>>> >> > 'SELECT DISTINCT dimension from vw_dataelements_dimensions ORDER BY
>>> 1
>>> >> > ASC'
>>> >> >       )
>>> >> > as
>>> >> > (
>>> >> > name character varying(230),
>>> >> > age character varying(160),
>>> >> > status character varying(160)
>>> >> > );
>>> >> >
>>> >> >
>>> >> > which returns this record set
>>> >> >
>>> >> > "OPD 1st Attendance Clinical Case of Malaria 1 to Under 5
>>> Years";"Age
>>> >> > 1-5";"OPD"
>>> >> > "OPD 1st Attendance Clinical Case of Malaria Over 5 Years";"Over
>>> >> > 5";"OPD"
>>> >> > "OPD 1st Attendance Clinical Case of Malaria Under 1 Year";"Under
>>> >> > 1";"OPD"
>>> >> >
>>> >> >
>>> >> > OK, admittedly, I cheated a bit and used the crosstab function of
>>> >> > Postgresql, but I assume that this query could be rewritten with a
>>> few
>>> >> > more lines of code in standard SQL or some procedural language like
>>> >> > Java. Now, this record set looks like something that I can almost
>>> use
>>> >> > with the aggregateddatavalue table simply by joining up the table on
>>> >> > the appropriate dataelementid and pulling everything into a pivot
>>> >> > table.  I would not have any duplicated values and would have
>>> columns
>>> >> > like data element name, period, orgunit, age, patient status and of
>>> >> > course the value of the data element.  I hope that part is pretty
>>> >> > clear. Just join up that table to the aggregateddata table, and you
>>> >> > have pretty much what is needed to pull the data directly into a
>>> >> > PivotTable for further analysis.
>>> >> >
>>> >> > This is not a complete example, but it is very close to what I need
>>> >> > here ,and I think this type of functionality would be much more
>>> useful
>>> >> > than the current data element categories functionality. Basically,
>>> all
>>> >> > that would be required, at least initially, would be another user
>>> >> > interface screen to allow the definition of which category(ies) and
>>> >> > category options a data element is a member of. The rest could ,in
>>> the
>>> >> > first instance be executed with custom SQL (obviously, I am partial
>>> to
>>> >> > this language and hobbled by the fact that I do not know Java), but
>>> >> > eventually this would need to be implemented somehow in Java.
>>> >> >
>>> >> >  I am not sure if this really solves all of the issues surrounding
>>> >> > multidimensional analysis of data elements, but it seems to solve
>>> the
>>> >> > issues that I am having by trying to assign some sort of dimensional
>>> >> > hierarchy to data elements (similar to the exclusive/compulsory
>>> >> > functionality of orgunits). Any thoughts on this?
>>> >> >
>>> >> > Best regards,
>>> >> > Jason
>>> >> >
>>> >> >
>>> >> >
>>> >> >
>>> >> > On Wed, Sep 16, 2009 at 10:28 PM, Jason Pickering
>>> >> > <jason.p.pickering@xxxxxxxxx> wrote:
>>> >> >>
>>> >> >>
>>> >> >> On Wed, Sep 16, 2009 at 10:13 PM, <johansa@xxxxxxxxxx> wrote:
>>> >> >>>
>>> >> >>> >> However, there does seem to be the ability to assign
>>> dimensions,
>>> >> >>> there
>>> >> >>> >> does
>>> >> >>> >> not seem to be the ability to assign particular elements within
>>> >> >>> those
>>> >> >>> >> dimensions to a particular DHIS data element.
>>> >> >>>
>>> >> >>>
>>> >> >>> Just some more clarification here: you can make category combos
>>> which
>>> >> >>> you
>>> >> >>> assign to data elements. However, it is not possible to assign
>>> just
>>> >> >>> specific parts of a category combo (only some of the category
>>> options)
>>> >> >>> to
>>> >> >>> a data element.
>>> >> >>
>>> >> >> Yes, this was exactly what I wanted. Assigning different categories
>>> >> >> would
>>> >> >> seem to break the dimensionality.
>>> >> >>
>>> >> >>>
>>> >> >>> Then you must make a specific category (as the only one in
>>> >> >>> or part of a new category combo) with just those options. It can
>>> be
>>> >> >>> hell;
>>> >> >>> in Tajikistan there were way over 20 categories I think, at least
>>> 10
>>> >> >>> just
>>> >> >>> on various age groups.
>>> >> >>>
>>> >> >>> Johan
>>> >> >>>
>>> >> >>
>>> >> >> This was my fear.
>>> >> >>
>>> >> >> I will need to do some testing and see. I still fear it is not
>>> exactly
>>> >> >> the
>>> >> >> intended functionality.
>>> >> >>
>>> >> >> Basically, I think I need something akin to the
>>> exclusive/compulsory
>>> >> >> groups
>>> >> >> that are in place for organizational units, but instead, for
>>> arbitrary
>>> >> >> dimensions. I will give a try and see what happens.
>>> >> >>
>>> >> >> Thanks,
>>> >> >> Jason
>>> >> >>
>>> >> >>
>>> >> >>
>>> >> >>
>>> >> >>
>>> >> >
>>> >>
>>> >>
>>> >>
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>>> >
>>>
>>>
>>
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-- 
Cheers,
Knut Staring