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mapr's Introduction
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graceli8 nemochina2008 nsm120 engine1922 yangxhcaf wendyanthony han-tun corersky kevcaz changsongyangmapr's Issues
Create S3 generics for each top level fxn, dispatching on various inputs
inputs:
- spocc classes
- rgbif classes
- data.frame - would need to check for certain columns I suppose
Fix fxn name conflicts
<r> library(spocc)
<r> library(spoccutils)
Loading required package: ggplot2
Attaching package: ‘spoccutils’
The following objects are masked from ‘package:spocc’:
bbox2wkt, spocc_capwords, spocc_colClasses, wkt2bboxAdd shiny methods back in?
Add non-base R imports
replace httr with crul
Automatically generate metadata
moved from ropensci/spocc#8
summary:
Possibly provide functions for generating metadata for a dataset, including:
- temporal fields:
beginDate,endDate - spatial fields:
wkt(wkt string),bbox(just give both in case user is confused by wkt) - taxonomic fields:
classificationSystem(url ref and name),taxonomicClassification(data.frame maybe w/ cols: taxonRankName, taxonRankValue, commonName)
Have map_leaflet by default add metadata to tooltip
Seems like most users would want metadata on tooltips, see about adding this by default - does so for gists already, nice
use markdown docs
Error with map_ggplot
library("dismo")
#> Loading required package: raster
#> Loading required package: sp
g <- gbif('Batrachoseps', 'luciae', geo = TRUE, end = 300)
#> Loading required namespace: jsonlite
#> 1954 records found
#> 0-300 records downloaded
mapr::map_ggplot(g, "lon", "lat")
#> Error: The parameter 'point_color' has been replaced by 'color'Created on 2019-01-14 by the reprex package (v0.2.1)
Session info
devtools::session_info()
#> ─ Session info ──────────────────────────────────────────────────────────
#> setting value
#> version R version 3.4.4 (2018-03-15)
#> os Ubuntu 18.04.1 LTS
#> system x86_64, linux-gnu
#> ui X11
#> language en_US
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
#> tz Europe/Paris
#> date 2019-01-14
#>
#> ─ Packages ──────────────────────────────────────────────────────────────
#> package * version date lib source
#> assertthat 0.2.0 2017-04-11 [1] CRAN (R 3.4.4)
#> backports 1.1.3 2018-12-14 [1] CRAN (R 3.4.4)
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#> bindrcpp 0.2.2 2018-03-29 [1] CRAN (R 3.4.4)
#> callr 3.1.1 2018-12-21 [1] CRAN (R 3.4.4)
#> cli 1.0.1 2018-09-25 [1] CRAN (R 3.4.4)
#> codetools 0.2-15 2016-10-05 [4] CRAN (R 3.4.2)
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#> crosstalk 1.0.0 2016-12-21 [1] CRAN (R 3.4.4)
#> desc 1.2.0 2018-05-01 [1] CRAN (R 3.4.4)
#> devtools 2.0.1 2018-10-26 [1] CRAN (R 3.4.4)
#> digest 0.6.18 2018-10-10 [1] CRAN (R 3.4.4)
#> dismo * 1.1-4 2017-01-09 [1] CRAN (R 3.4.4)
#> dotCall64 1.0-0 2018-07-30 [1] CRAN (R 3.4.4)
#> dplyr 0.7.8 2018-11-10 [1] CRAN (R 3.4.4)
#> evaluate 0.12 2018-10-09 [1] CRAN (R 3.4.4)
#> fields 9.6 2018-01-29 [1] CRAN (R 3.4.4)
#> foreign 0.8-69 2017-06-21 [4] CRAN (R 3.4.2)
#> fs 1.2.6 2018-08-23 [1] CRAN (R 3.4.4)
#> ggplot2 3.1.0 2018-10-25 [1] CRAN (R 3.4.4)
#> glue 1.3.0.9000 2019-01-06 [1] Github (tidyverse/glue@3f7012c)
#> gtable 0.2.0 2016-02-26 [1] CRAN (R 3.4.4)
#> highr 0.7 2018-06-09 [1] CRAN (R 3.4.4)
#> htmltools 0.3.6 2017-04-28 [1] CRAN (R 3.4.4)
#> htmlwidgets 1.3 2018-09-30 [1] CRAN (R 3.4.4)
#> httpuv 1.4.5.1 2018-12-18 [1] CRAN (R 3.4.4)
#> jsonlite 1.6 2018-12-07 [1] CRAN (R 3.4.4)
#> knitr 1.21 2018-12-10 [1] CRAN (R 3.4.4)
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#> lattice 0.20-35 2017-03-25 [4] CRAN (R 3.4.2)
#> lazyeval 0.2.1 2017-10-29 [1] CRAN (R 3.4.4)
#> leaflet 2.0.2 2018-08-27 [1] CRAN (R 3.4.4)
#> magrittr 1.5 2014-11-22 [1] CRAN (R 3.4.4)
#> mapr 0.4.0.9100 2019-01-14 [1] local
#> maps 3.3.0 2018-04-03 [1] CRAN (R 3.4.4)
#> maptools 0.9-4 2018-09-19 [1] CRAN (R 3.4.4)
#> memoise 1.1.0 2017-04-21 [1] CRAN (R 3.4.4)
#> mime 0.6 2018-10-05 [1] CRAN (R 3.4.4)
#> munsell 0.5.0 2018-06-12 [1] CRAN (R 3.4.4)
#> pillar 1.3.1 2018-12-15 [1] CRAN (R 3.4.4)
#> pkgbuild 1.0.2 2018-10-16 [1] CRAN (R 3.4.4)
#> pkgconfig 2.0.2 2018-08-16 [1] CRAN (R 3.4.4)
#> pkgload 1.0.2 2018-10-29 [1] CRAN (R 3.4.4)
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#> promises 1.0.1 2018-04-13 [1] CRAN (R 3.4.4)
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#> purrr 0.2.5 2018-05-29 [1] CRAN (R 3.4.4)
#> R6 2.3.0 2018-10-04 [1] CRAN (R 3.4.4)
#> raster * 2.8-4 2018-11-03 [1] CRAN (R 3.4.4)
#> Rcpp 1.0.0 2018-11-07 [1] CRAN (R 3.4.4)
#> remotes 2.0.2 2018-10-30 [1] CRAN (R 3.4.4)
#> rlang 0.3.1 2019-01-08 [1] CRAN (R 3.4.4)
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#> scales 1.0.0 2018-08-09 [1] CRAN (R 3.4.4)
#> sessioninfo 1.1.1 2018-11-05 [1] CRAN (R 3.4.4)
#> shiny 1.2.0 2018-11-02 [1] CRAN (R 3.4.4)
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#> testthat 2.0.1 2018-10-13 [1] CRAN (R 3.4.4)
#> tibble 2.0.0 2019-01-04 [1] CRAN (R 3.4.4)
#> tidyselect 0.2.5 2018-10-11 [1] CRAN (R 3.4.4)
#> usethis 1.4.0.9000 2019-01-03 [1] Github (r-lib/usethis@85bf30a)
#> withr 2.1.2 2018-03-15 [1] CRAN (R 3.4.4)
#> xfun 0.4 2018-10-23 [1] CRAN (R 3.4.4)
#> xtable 1.8-3 2018-08-29 [1] CRAN (R 3.4.4)
#> yaml 2.2.0 2018-07-25 [1] CRAN (R 3.4.4)
#>
#> [1] /home/maelle/R/x86_64-pc-linux-gnu-library/3.4
#> [2] /usr/local/lib/R/site-library
#> [3] /usr/lib/R/site-library
#> [4] /usr/lib/R/libraryadd dotightubfiles
ggplot2 new version fixes
Take spoccutils off CRAN at some point
shoot for June 2016 just to give people time to switch away to mapr/scrubr
fix non-ascii strings in datasets
map_plot is really slow
not sure where the slow point is
make sure works with ggmap new ver
I hope to release a new version of ggmap in a week (August 7) to comply with some cran standards. You still have the possibility of using Google with the source = "google" argument to geocode.
You can load the new version with devtools::install_github("dkahle/ggmap")
packages in docs
- remove link to htmltools docs
- put rgbif in suggests as used in egs
ggmap make defunct - a PITA
Add vignette
Make methods for some sp spatial classes?
Already import sp, so maybe should make some methods for spatial classes to make this more widely useful
Error with map_plot
library("mapr")
library("spocc")
spp <- c('Danaus plexippus', 'Accipiter striatus', 'Pinus contorta')
dat <- occ(query = spp, from = 'gbif', has_coords = TRUE, limit = 50)
dat <- fixnames(dat)
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
#> Warning: Unknown or uninitialised column: 'name'.
map_plot(dat, cex = 1, pch = 10)
#> Error in plot.xy(xy.coords(x, y), type = type, ...): formal argument "cex" matched by multiple actual arguments
Created on 2019-01-14 by the reprex package (v0.2.1)
Session info
devtools::session_info()
#> ─ Session info ──────────────────────────────────────────────────────────
#> setting value
#> version R version 3.4.4 (2018-03-15)
#> os Ubuntu 18.04.1 LTS
#> system x86_64, linux-gnu
#> ui X11
#> language en_US
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
#> tz Europe/Paris
#> date 2019-01-14
#>
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#> package * version date lib source
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#> bindrcpp 0.2.2 2018-03-29 [1] CRAN (R 3.4.4)
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#> cli 1.0.1 2018-09-25 [1] CRAN (R 3.4.4)
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#> evaluate 0.12 2018-10-09 [1] CRAN (R 3.4.4)
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#> fs 1.2.6 2018-08-23 [1] CRAN (R 3.4.4)
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#> gtable 0.2.0 2016-02-26 [1] CRAN (R 3.4.4)
#> highr 0.7 2018-06-09 [1] CRAN (R 3.4.4)
#> htmltools 0.3.6 2017-04-28 [1] CRAN (R 3.4.4)
#> htmlwidgets 1.3 2018-09-30 [1] CRAN (R 3.4.4)
#> httpcode 0.2.0 2016-11-14 [1] CRAN (R 3.4.4)
#> httpuv 1.4.5.1 2018-12-18 [1] CRAN (R 3.4.4)
#> httr 1.4.0 2018-12-11 [1] CRAN (R 3.4.4)
#> jsonlite 1.6 2018-12-07 [1] CRAN (R 3.4.4)
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#> mapproj 1.2.6 2018-03-29 [1] CRAN (R 3.4.4)
#> mapr * 0.4.0.9100 2019-01-14 [1] local
#> maps 3.3.0 2018-04-03 [1] CRAN (R 3.4.4)
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#> pkgconfig 2.0.2 2018-08-16 [1] CRAN (R 3.4.4)
#> pkgload 1.0.2 2018-10-29 [1] CRAN (R 3.4.4)
#> plyr 1.8.4 2016-06-08 [1] CRAN (R 3.4.4)
#> prettyunits 1.0.2 2015-07-13 [1] CRAN (R 3.4.4)
#> processx 3.2.1 2018-12-05 [1] CRAN (R 3.4.4)
#> promises 1.0.1 2018-04-13 [1] CRAN (R 3.4.4)
#> ps 1.3.0 2018-12-21 [1] CRAN (R 3.4.4)
#> purrr 0.2.5 2018-05-29 [1] CRAN (R 3.4.4)
#> R6 2.3.0 2018-10-04 [1] CRAN (R 3.4.4)
#> rbison 0.7.0 2018-10-25 [1] CRAN (R 3.4.4)
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#> Rcpp 1.0.0 2018-11-07 [1] CRAN (R 3.4.4)
#> rebird 1.0.0 2018-09-27 [1] CRAN (R 3.4.4)
#> remotes 2.0.2 2018-10-30 [1] CRAN (R 3.4.4)
#> rgbif 1.1.0 2018-10-19 [1] CRAN (R 3.4.4)
#> rgeos 0.4-2 2018-11-08 [1] CRAN (R 3.4.4)
#> ridigbio 0.3.5 2017-02-16 [1] CRAN (R 3.4.4)
#> rlang 0.3.1 2019-01-08 [1] CRAN (R 3.4.4)
#> rmarkdown 1.11 2018-12-08 [1] CRAN (R 3.4.4)
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#> rvertnet 0.7.0 2018-04-17 [1] CRAN (R 3.4.4)
#> rworldmap 1.3-6 2016-02-03 [1] CRAN (R 3.4.4)
#> scales 1.0.0 2018-08-09 [1] CRAN (R 3.4.4)
#> sessioninfo 1.1.1 2018-11-05 [1] CRAN (R 3.4.4)
#> shiny 1.2.0 2018-11-02 [1] CRAN (R 3.4.4)
#> sp 1.3-1 2018-06-05 [1] CRAN (R 3.4.4)
#> spam 2.2-1 2018-12-20 [1] CRAN (R 3.4.4)
#> spocc * 0.9.0 2018-11-15 [1] CRAN (R 3.4.4)
#> stringi 1.2.4 2018-07-20 [1] CRAN (R 3.4.4)
#> stringr 1.3.1 2018-05-10 [1] CRAN (R 3.4.4)
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#>
#> [1] /home/maelle/R/x86_64-pc-linux-gnu-library/3.4
#> [2] /usr/local/lib/R/site-library
#> [3] /usr/lib/R/site-library
#> [4] /usr/lib/R/libraryVignette missing title
How to create & map a convex hull from a set of points?
I hope this isn't too lazy of me?
My use case is simple to describe:
- I'd like to make a simple convex hull of occurrences for a species. (simple)
- From that convex hull I'd like to compute how many countries the convex hull covers (less simple)
In conservation biology a convex hull seems also to be known as the extent of occurrence (EOO) of a species (e.g. figure 1a here: http://www.int-res.com/articles/esr2008/6/n006p127.pdf ). This would be a popular use-case for mapr & occurrence data I think.
Q2 is slightly subtler. The convex hull could be composed from say four occurrence records, each in a different country, but the simple convex hull could conceivably cover more than four different countries. I want to know ALL the different countries that are at least partially covered by the convex hull between the pts, not just the country of origin of the points/occurrences. Identity of the countries overlapped by the EOO is key too, not just a numerical count of how many.
More tests
Pkg name change
To reflect focus on just maps. Cleaning all in scrubr now
Replace leafletR with leaflet
on cran now, easier
Data cleaning (from `spocc` issue)
from spocc issue ropensci/spocc#44
From discussion on ropensci/spocc#43
- Check for impossible values of lat and long
- Check for contextually wrong values. That is, if 99 out of 100 lat/long coordinates are within the continental US, but 1 is in China, then perhaps something is wrong with that one point
- Check for points in the wrong country, or points outside of a known country
- Check for points in a particular habitat, or must be outside of a partciular habitat
- Check for possible duplicate occurrence records across GBIF + other data sources (see discussion below)
- Check for points that are at 0/0. Seems to be quite a few of these. Can't be right. Remove these.
Do colored markers by default in map functions
- map_leaflet
- map_ggplot
- map_ggmap
- map_plot
Deduplication
moved from ropensci/spocc#122
- Match on dataset identifiers - possible only in some cases, e.g. if data from vertnet and idigbio, then possible problems
- Match on all fields given? e.g., run a ordination type analysis and return records that cluster together
- Match on similar lat/long pairs
- Cluster simply by taxonomy, then refine further, e.g,. same taxon names from different providers more likely to be dups than from within the same provider
- ...
Related
- Some may not care about dups
- Some may want to only collapse certain dups, and not others
- ...
Discussion with alex/matt
- Dedup based on
institutioncode :catalog number(if i'm remembering correctly)
fix pop in map_leaflet
ignore vignette on cran to avoid cran bullshit
support class `occ_data` from rgbif package
We support gbif class that comes from rgbif::occ_search already but just not the output from rgbif::occ_data
map idea: heat map of species per cell
duplicate something like what this pkg does
library(monographaR)
data(monographaR_examples)
mapDiversity(monographaR_examples$map_data, resolution = 1, plot = TRUE, plot.with.grid = TRUE, legend = TRUE, export = FALSE)
Clean data based on dataset identifiers
Moved from ropensci/spocc#92
perhaps this is possible:
if user gets data from GBIF + at least 1 other source, and that source feeds in, at least in part, to GBIF, then GBIF may include the dataset identifers from the source, and we can look for that to match on...
Add legend to map_plot when > 1 taxon
Wait for spocc minor version before cran push
using `name` param doesn't work if already a column called "name"
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