[R-sig-Geo] quadracount on multitype points
Guy.Bayegnak at gov.ab.ca
Wed Sep 13 01:08:37 CEST 2017
Thanks a lot for your response and suggestion Rolf. Yes, by "quadrant" I mean the little sub-windows. My problem is the following:
We have collected thousands of groundwater samples across a vast area, and analysed them. Based on the analysis we are able to assign a "type" to each water sample. When plotted, there seems to be a spatial trend in water type. But a given area may have more than one water type, usually with a dominant type (most frequently occurring). What I am trying to do is identify the dominant type for each sub-region /sub-windows but show the count side by side, for example:
y [0,0.801) [0.801,1.6]
[0.5,1] Off = 36 Off = 6
On = 3 On = 39
[0,0.5) Off = 4 Off = 36
On = 42 On = 6
I think I can achieve what I am looking for with your suggestion. Once I get the table list, I will copy the numbers side by side manually.
From: Rolf Turner [mailto:r.turner at auckland.ac.nz]
Sent: September 12, 2017 3:45 PM
To: Guy Bayegnak <Guy.Bayegnak at gov.ab.ca>
Cc: r-sig-geo at r-project.org; Adrian.Baddeley at curtin.edu.au; Ege Rubak <rubak at math.aau.dk>
Subject: Re: [R-sig-Geo] quadracount on multitype points
On 13/09/17 02:11, Guy Bayegnak wrote:
> Dear all,
> I am working on a multitype point pattern, and I'd like to estimate
> how many of each type of point occurs into each quadrant. I know it is
> possible to use the quandracount on split marks as follows using
> spatstats: quadratcount(split(marks)). But the result produces as many
> windows as they are marks. I am wondering is there is a way to know
> many occurrence of each type there is per quadrant and to plot it in a
> single grid.
You really should start by mentioning that you are dealing with the spatstat package.
It's not clear to me what you are after. A minimal reproducible example would be helpful. I presume that by "quadrant" you mean one of the four equal sub-windows formed by bisecting your (rectangular) window vertically and horizontally.
If my presumption is correct then perhaps
(where "X" is your point pattern) does what you want. E.g.:
> y [0,0.801) [0.801,1.6]
> [0.5,1] 36 36
> [0,0.5) 34 36
> y [0,0.801) [0.801,1.6]
> [0.5,1] 35 39
> [0,0.5) 42 36
Is this something like what you wish to achieve?
Technical Editor ANZJS
Department of Statistics
University of Auckland
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