Example of a master_matrix object containing preselected sites
Source:R/data_documentation.R
m_matrix_pre.RdA S3 object of class master_matrix.
See function prepare_master_matrix.
Format
A list of 6 elements:
- data_matrix
data.frame with 6276 rows and 10 columns
- preselected_sites
data.frame with 5 rows and 11 columns
- region
object of class SpatVector
- mask
NULL
- raster_base
object of class SpatRaster
- PCA_results
list of length 4
Examples
m_matrix_pre <- read_master(system.file("extdata/m_matrix_pre.rds",
package = "biosurvey"))
print(m_matrix_pre)
#> data_matrix:
#> Longitude Latitude Mean_temperature Max_temperature Min_temperature
#> 1 -116.4167 32.58333 146 329 9
#> 2 -116.2500 32.58333 148 333 7
#> 3 -116.0833 32.58333 155 342 9
#> 4 -115.9167 32.58333 198 387 37
#> 5 -115.7500 32.58333 215 403 46
#> 6 -115.5833 32.58333 221 412 45
#> Annual_precipitation Prec_wettest_month Prec_driest_month PC1
#> 1 400 76 1 -2.052589
#> 2 320 60 1 -2.170276
#> 3 237 39 1 -2.213166
#> 4 235 45 0 -1.421165
#> 5 233 45 0 -1.129137
#> 6 148 25 0 -1.203997
#> PC2
#> 1 -0.4190674
#> 2 -0.2378053
#> 3 0.1379122
#> 4 1.6995256
#> 5 2.2733643
#> 6 2.6227359
#> ...
#>
#> preselected_sites:
#> Site Longitude Latitude Mean_temperature Max_temperature
#> 1 Chamela -105.04479 19.50090 261 338
#> 2 Los Tuxtlas -95.07419 18.58489 236 312
#> 3 Chajul -90.94067 16.17000 256 337
#> 4 Parque de Tlalpan -99.19778 19.29139 119 222
#> 5 Parque Chipinque -100.35940 25.61750 184 297
#> Min_temperature Annual_precipitation Prec_wettest_month Prec_driest_month
#> 1 157 833 222 1
#> 2 163 3084 538 62
#> 3 176 2639 459 48
#> 4 5 1131 232 10
#> 5 54 474 113 9
#> PC1 PC2
#> 1 1.3232071 1.2137988
#> 2 6.0028213 -2.6143030
#> 3 5.2791589 -1.1364551
#> 4 -1.1445335 -3.8541911
#> 5 -0.9409087 -0.6585544
#>
#> region:
#> class : SpatVector
#> geometry : polygons
#> dimensions : 1, 11 (geometries, attributes)
#> extent : -118.4042, -86.7014, 14.55055, 32.71846 (xmin, xmax, ymin, ymax)
#> coord. ref. : +proj=longlat +datum=WGS84 +no_defs
#> names : FIPS ISO2 ISO3 UN NAME AREA POP2005 REGION
#> type : <fact> <fact> <fact> <int> <fact> <int> <num> <int>
#> values : MX MX MEX 484 Mexico 190869 1.043e+08 19
#> SUBREGION LON LAT
#> <int> <num> <num>
#> 13 -102.5 23.95
#>
#> mask:
#> Empty
#>
#> raster_base:
#> class : SpatRaster
#> dimensions : 109, 190, 1 (nrow, ncol, nlyr)
#> resolution : 0.1666667, 0.1666667 (x, y)
#> extent : -118.3333, -86.66667, 14.5, 32.66667 (xmin, xmax, ymin, ymax)
#> coord. ref. : lon/lat WGS 84 (with axis order normalized for visualization)
#> source(s) : memory
#> name : base
#> min value : 1
#> max value : 1
#>
#> PCA_results:
#> Standard deviations (1, .., p=6):
#> [1] 1.85897633 1.31688362 0.68864096 0.55601299 0.13046926 0.09810958
#>
#> Rotation (n x k) = (6 x 6):
#> PC1 PC2 PC3 PC4 PC5
#> Mean_temperature 0.39994229 0.4945928 -0.12773440 0.1628971 -0.4869211
#> Max_temperature 0.09712785 0.6872795 0.35741410 -0.5278992 0.2447188
#> Min_temperature 0.46929210 0.2323324 -0.36245067 0.5051401 0.3400470
#> Annual_precipitation 0.48542331 -0.2999469 -0.02539578 -0.2601344 0.5940718
#> Prec_wettest_month 0.45736594 -0.2910001 -0.28009210 -0.5342494 -0.4526740
#> Prec_driest_month 0.40688805 -0.2332326 0.80341276 0.2941566 -0.1719113
#> PC6
#> Mean_temperature 0.5616765
#> Max_temperature -0.2278232
#> Min_temperature -0.4728823
#> Annual_precipitation 0.5031501
#> Prec_wettest_month -0.3706043
#> Prec_driest_month -0.1359816