Running 'testthat.R' [123s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
  > # This file is part of the standard setup for testthat.
  > # It is recommended that you do not modify it.
  > #
  > # Where should you do additional test configuration?
  > # Learn more about the roles of various files in:
  > # * https://r-pkgs.org/tests.html
  > # * https://testthat.r-lib.org/reference/test_package.html#special-files
  > 
  > library(testthat)
  > library(sgsR)
  > 
  > test_check("sgsR")
  terra 1.7.71
  
  Attaching package: 'terra'
  
  The following objects are masked from 'package:testthat':
  
      compare, describe
  
  
  Attaching package: 'dplyr'
  
  The following objects are masked from 'package:terra':
  
      intersect, union
  
  The following object is masked from 'package:testthat':
  
      matches
  
  The following objects are masked from 'package:stats':
  
      filter, lag
  
  The following objects are masked from 'package:base':
  
      intersect, setdiff, setequal, union
  
  Linking to GEOS 3.9.3, GDAL 3.5.2, PROJ 8.2.1; sf_use_s2() is TRUE
  Reading layer `access' from data source 
    `D:\RCompile\CRANpkg\lib\4.2\sgsR\extdata\access.shp' using driver `ESRI Shapefile'
  Simple feature collection with 167 features and 2 fields
  Geometry type: MULTILINESTRING
  Dimension:     XY
  Bounding box:  xmin: 431100 ymin: 5337700 xmax: 438560 ymax: 5343240
  Projected CRS: UTM_Zone_17_Northern_Hemisphere
  Reading layer `inventory_polygons' from data source 
    `D:\RCompile\CRANpkg\lib\4.2\sgsR\extdata\inventory_polygons.shp' 
    using driver `ESRI Shapefile'
  Simple feature collection with 632 features and 3 fields
  Geometry type: MULTIPOLYGON
  Dimension:     XY
  Bounding box:  xmin: 431100 ymin: 5337700 xmax: 438560 ymax: 5343240
  Projected CRS: UTM_Zone_17_Northern_Hemisphere
  Creating covariance matrix.
  calculating per pixel distance to provided access layer
  
  |---------|---------|---------|---------|
  =========================================
                                            
  calculating per pixel distance to provided access layer
  
  |---------|---------|---------|---------|
  =========================================
                                            
  Implementing proportional allocation of samples.
  Implementing proportional allocation of samples.
  Implementing proportional allocation of samples.
  Implementing proportional allocation of samples.
  Implementing proportional allocation of samples.
  Implementing proportional allocation of samples.
  Implementing proportional allocation of samples.
  Implementing optimal allocation of samples based on variability of 'zq90'.
  Forcing 100 total samples.
  Forcing 100 total samples.
  Implementing allocation of samples based on user-defined weights.
  Implementing allocation of samples based on user-defined weights.
  Implementing equal allocation of samples.
  Implementing equal allocation of samples.
  Implementing proportional allocation of samples.
  Implementing proportional allocation of samples.
  Implementing proportional allocation of samples.
  Implementing proportional allocation of samples.
  Implementing optimal allocation of samples based on variability of 'zq90'.
  Implementing equal allocation of samples.
  Implementing allocation of samples based on user-defined weights.
  Implementing optimal allocation of samples based on variability of 'zq90'.
  Implementing equal allocation of samples.
  Implementing equal allocation of samples.
  Implementing proportional allocation of samples.
  Implementing proportional allocation of samples.
  Implementing proportional allocation of samples.
  calculating per pixel distance to provided access layer
  
  |---------|---------|---------|---------|
  =========================================
                                            
  calculating per pixel distance to provided access layer
  calculating per pixel distance to provided access layer
  'rse' not perfectly divisible by 'increment'. Selecting closest sample size (rse = 0.2) based on values.
  'rse' not perfectly divisible by 'increment'. Selecting closest sample size (rse = 0.05) based on values.
  Column coordinate names are lowercase - converting to uppercase.
  Column coordinate names are lowercase - converting to uppercase.
  Column coordinate names are lowercase - converting to uppercase.
  Column coordinate names are lowercase - converting to uppercase.
  'existing' does not contain data for desired metrics. Extracting sample data from 'mraster'.
  Samples will be added until 5 is reached or until sampling ratios are all >= 1.
  Quantile [9,1] - A total of 3 samples have been allocated.
  Quantile [8,1] - A total of 2 samples have been allocated.
  A total of 5 new samples added.
  Creating covariance matrix.
  'existing' does not contain data for desired metrics. Extracting sample data from 'mraster'.
  Threshold of 0.8 provided. Samples will be added until sampling ratios are >= 0.8.
  Quantile [5,1] - A total of 4 samples have been allocated.
  Quantile [4,3] - A total of 4 samples have been allocated.
  Quantile [1,2] - A total of 7 samples have been allocated.
  A total of 15 new samples added.
  'existing' does not contain data for desired metrics. Extracting sample data from 'mraster'.
  Threshold of 0.8 with a tolerance of 0.025 provided. Samples will be added until sampling ratios are >= 0.775.
  Quantile [9,1] - A total of 3 samples have been allocated.
  Quantile [8,1] - A total of 6 samples have been allocated.
  Quantile [2,2] - A total of 4 samples have been allocated.
  Quantile [8,2] - A total of 9 samples have been allocated.
  Quantile [4,2] - A total of 2 samples have been allocated.
  Quantile [1,2] - A total of 3 samples have been allocated.
  Quantile [1,1] - A total of 2 samples have been allocated.
  A total of 29 new samples added.
  'existing' does not contain data for desired metrics. Extracting sample data from 'mraster'.
  16 samples are located where metric values are NA.
  Samples will be added until 300 is reached or until sampling ratios are all >= 1.
  Quantile [9,1] - A total of 2 samples have been allocated.
  Quantile [8,1] - A total of 6 samples have been allocated.
  Quantile [2,2] - A total of 4 samples have been allocated.
  Quantile [8,2] - A total of 8 samples have been allocated.
  Quantile [1,2] - A total of 3 samples have been allocated.
  Quantile [5,2] - A total of 2 samples have been allocated.
  Quantile [4,2] - A total of 2 samples have been allocated.
  Quantile [2,1] - A total of 2 samples have been allocated.
  Quantile [4,3] - A total of 9 samples have been allocated.
  Quantile [9,1] - A total of 1 samples have been allocated.
  Quantile [7,1] - A total of 4 samples have been allocated.
  Quantile [8,2] - A total of 3 samples have been allocated.
  Quantile [1,2] - A total of 2 samples have been allocated.
  Quantile [5,1] - A total of 5 samples have been allocated.
  Quantile [2,2] - A total of 3 samples have been allocated.
  Quantile [8,1] - A total of 2 samples have been allocated.
  Quantile [5,2] - A total of 2 samples have been allocated.
  Quantile [7,1] - A total of 3 samples have been allocated.
  Quantile [3,3] - A total of 5 samples have been allocated.
  Quantile [8,2] - A total of 3 samples have been allocated.
  Quantile [10,2] - A total of 6 samples have been allocated.
  Quantile [2,1] - A total of 2 samples have been allocated.
  Quantile [5,1] - A total of 5 samples have been allocated.
  Quantile [1,2] - A total of 1 samples have been allocated.
  Quantile [6,2] - A total of 1 samples have been allocated.
  Quantile [7,1] - A total of 3 samples have been allocated.
  Quantile [3,3] - A total of 5 samples have been allocated.
  Quantile [7,3] - A total of 1 samples have been allocated.
  Quantile [9,2] - A total of 5 samples have been allocated.
  Quantile [2,3] - A total of 4 samples have been allocated.
  Quantile [6,2] - A total of 1 samples have been allocated.
  Quantile [10,2] - A total of 4 samples have been allocated.
  Quantile [8,2] - A total of 2 samples have been allocated.
  Quantile [5,1] - A total of 4 samples have been allocated.
  Quantile [2,1] - A total of 2 samples have been allocated.
  Quantile [4,3] - A total of 4 samples have been allocated.
  Quantile [9,2] - A total of 4 samples have been allocated.
  Quantile [4,2] - A total of 1 samples have been allocated.
  Quantile [4,1] - A total of 3 samples have been allocated.
  Quantile [7,2] - A total of 2 samples have been allocated.
  Quantile [7,3] - A total of 1 samples have been allocated.
  Quantile [3,1] - A total of 2 samples have been allocated.
  Quantile [1,3] - A total of 2 samples have been allocated.
  Quantile [10,2] - A total of 4 samples have been allocated.
  Quantile [6,1] - A total of 4 samples have been allocated.
  Quantile [1,1] - A total of 1 samples have been allocated.
  Quantile [8,2] - A total of 3 samples have been allocated.
  Quantile [6,3] - A total of 2 samples have been allocated.
  Quantile [9,2] - A total of 5 samples have been allocated.
  Quantile [4,2] - A total of 1 samples have been allocated.
  Quantile [5,1] - A total of 4 samples have been allocated.
  Quantile [7,2] - A total of 2 samples have been allocated.
  Quantile [3,1] - A total of 2 samples have been allocated.
  Quantile [10,2] - A total of 4 samples have been allocated.
  Quantile [5,2] - A total of 1 samples have been allocated.
  Quantile [8,2] - A total of 2 samples have been allocated.
  Quantile [6,1] - A total of 3 samples have been allocated.
  Quantile [1,1] - A total of 1 samples have been allocated.
  Quantile [3,3] - A total of 3 samples have been allocated.
  Quantile [9,2] - A total of 3 samples have been allocated.
  Quantile [3,1] - A total of 2 samples have been allocated.
  Quantile [6,3] - A total of 2 samples have been allocated.
  Quantile [6,2] - A total of 1 samples have been allocated.
  Quantile [10,2] - A total of 4 samples have been allocated.
  Quantile [5,1] - A total of 3 samples have been allocated.
  Quantile [7,2] - A total of 1 samples have been allocated.
  Quantile [8,2] - A total of 2 samples have been allocated.
  Quantile [6,1] - A total of 4 samples have been allocated.
  Quantile [9,2] - A total of 5 samples have been allocated.
  Quantile [5,2] - A total of 1 samples have been allocated.
  Quantile [6,2] - A total of 1 samples have been allocated.
  Quantile [1,3] - A total of 1 samples have been allocated.
  Quantile [7,2] - A total of 2 samples have been allocated.
  Quantile [6,3] - A total of 2 samples have been allocated.
  Quantile [4,2] - A total of 1 samples have been allocated.
  Quantile [9,1] - A total of 1 samples have been allocated.
  Quantile [5,1] - A total of 2 samples have been allocated.
  Quantile [8,2] - A total of 2 samples have been allocated.
  Quantile [1,3] - A total of 1 samples have been allocated.
  Quantile [5,2] - A total of 2 samples have been allocated.
  Quantile [10,2] - A total of 4 samples have been allocated.
  Quantile [6,2] - A total of 1 samples have been allocated.
  Quantile [9,2] - A total of 4 samples have been allocated.
  Quantile [7,1] - A total of 4 samples have been allocated.
  Quantile [1,3] - A total of 1 samples have been allocated.
  Quantile [5,1] - A total of 3 samples have been allocated.
  Quantile [1,1] - A total of 1 samples have been allocated.
  Quantile [3,1] - A total of 1 samples have been allocated.
  Quantile [8,2] - A total of 2 samples have been allocated.
  Quantile [4,1] - A total of 2 samples have been allocated.
  Quantile [4,3] - A total of 5 samples have been allocated.
  Quantile [7,2] - A total of 2 samples have been allocated.
  Quantile [2,2] - A total of 1 samples have been allocated.
  Quantile [10,2] - A total of 5 samples have been allocated.
  Quantile [3,1] - A total of 2 samples have been allocated.
  Quantile [7,1] - A total of 3 samples have been allocated.
  Quantile [7,3] - A total of 1 samples have been allocated.
  Quantile [1,2] - A total of 1 samples have been allocated.
  Quantile [2,3] - A total of 2 samples have been allocated.
  Quantile [4,1] - A total of 2 samples have been allocated.
  Quantile [8,2] - A total of 2 samples have been allocated.
  Quantile [5,3] - A total of 3 samples have been allocated.
  Quantile [2,2] - A total of 1 samples have been allocated.
  Quantile [3,3] - A total of 3 samples have been allocated.
  Quantile [9,2] - A total of 3 samples have been allocated.
  Quantile [8,2] - A total of 2 samples have been allocated.
  Quantile [1,2] - A total of 1 samples have been allocated.
  Quantile [6,2] - A total of 1 samples have been allocated.
  Quantile [4,1] - A total of 2 samples have been allocated.
  Quantile [10,2] - A total of 4 samples have been allocated.
  Quantile [9,2] - A total of 3 samples have been allocated.
  Quantile [6,1] - A total of 4 samples have been allocated.
  Quantile [1,3] - A total of 1 samples have been allocated.
  Quantile [3,2] - A total of 1 samples have been allocated.
  Quantile [8,2] - A total of 1 samples have been allocated.
  A total of 300 new samples added.
  'existing' does not contain data for desired metrics. Extracting sample data from 'mraster'.
  'existing' column coordinate names are lowercase - converting to uppercase.
  'existing' does not contain data for desired metrics. Extracting sample data from 'mraster'.
  An access layer has been provided. An internal buffer of 50 m and an external buffer of 200 m have been applied.
  Column coordinates names for 'existing' are lowercase - converting to uppercase.
  Sub-sampling based on ALL 'existing' metric distributions. Ensure only attributes of interest are included.
  Implementing proportional allocation of samples.
  Sub-sampling based on ALL 'existing' metric distributions. Ensure only attributes of interest are included.
  Sub-sampling based on ALL 'existing' metric distributions. Ensure only attributes of interest are included.
  Sub-sampling based on 'raster' distributions.
  Using `zq90` as sampling constraint.
  Implementing proportional allocation of samples.
  K-means being performed on 3 layers with 50 centers.
  K-means being performed on 3 layers with 25 centers.
  K-means being performed on 3 layers with 5 centers.
  K-means being performed on 3 layers with 5 centers.
  K-means being performed on 1 layers with 20 centers.
  Using 'Queinnec' sampling method.
  Implementing proportional allocation of samples.
  Processing strata : 1
  Processing strata : 2
  Processing strata : 3
  Processing strata : 4
  Using 'Queinnec' sampling method.
  Implementing equal allocation of samples.
  Processing strata : 1
  Processing strata : 2
  Processing strata : 3
  Processing strata : 4
  Using 'Queinnec' sampling method.
  Implementing allocation of samples based on user-defined weights.
  Processing strata : 1
  Processing strata : 2
  Processing strata : 3
  Processing strata : 4
  Using 'Queinnec' sampling method.
  'weights' was specified but 'allocation = optim' - did you mean to use 'allocation = manual'?
  Implementing optimal allocation of samples based on variability of 'zq90'.
  Forcing 100 total samples.
  Processing strata : 1
  Processing strata : 2
  Processing strata : 3
  Processing strata : 4
  16 samples are located where strata values are NA.
  Implementing proportional allocation of samples.
  Using 'Queinnec' sampling method.
  'existing' samples being included in 'nSamp' total.
  Implementing proportional allocation of samples.
  Processing strata : 1
  'include = TRUE & remove = TRUE' - Stratum 1 overrepresented - 45 samples removed.
  Processing strata : 2
  'include = TRUE & remove = TRUE' - Stratum 2 overrepresented - 45 samples removed.
  Processing strata : 3
  'include = TRUE & remove = TRUE' - Stratum 3 overrepresented - 45 samples removed.
  Processing strata : 4
  'include = TRUE & remove = TRUE' - Stratum 4 overrepresented - 45 samples removed.
  Using 'Queinnec' sampling method.
  Using 'Queinnec' sampling method.
  Using 'Queinnec' sampling method.
  Using 'Queinnec' sampling method.
  Using 'Queinnec' sampling method.
  Using 'Queinnec' sampling method.
  Using 'Queinnec' sampling method.
  Implementing equal allocation of samples.
  An access layer has been provided. An internal buffer of 50 m and an external buffer of 200 m have been applied.
  Processing strata : 1
  Using 'Queinnec' sampling method.
  Implementing proportional allocation of samples.
  Processing strata : 1
  Processing strata : 2
  Processing strata : 3
  Processing strata : 4
  Processing strata : 5
  'sraster' has factor values. Converting to allow mapping.
  Using 'Queinnec' sampling method.
  Implementing proportional allocation of samples.
  An access layer has been provided. An external buffer of 100 m have been applied.
  Processing strata : 1
  Buffered area contains 6097 available candidates. Sampling to reach 40 starting.
  Processing strata : 2
  Buffered area contains 6085 available candidates. Sampling to reach 40 starting.
  Processing strata : 3
  Buffered area contains 6066 available candidates. Sampling to reach 40 starting.
  Processing strata : 4
  Buffered area contains 6116 available candidates. Sampling to reach 40 starting.
  Processing strata : 5
  Buffered area contains 6042 available candidates. Sampling to reach 40 starting.
  'sraster' has factor values. Converting to allow mapping.
  Using 'Queinnec' sampling method.
  Implementing proportional allocation of samples.
  Processing strata : 1
  Processing strata : 2
  Processing strata : 3
  Processing strata : 4
  Processing strata : 5
  Implementing proportional allocation of samples.
  Processing strata : 1
  Processing strata : 2
  Processing strata : 3
  Processing strata : 4
  Implementing proportional allocation of samples.
  Processing strata : 1
  Processing strata : 2
  Processing strata : 3
  Processing strata : 4
  Using 'Queinnec' sampling method.
  Implementing proportional allocation of samples.
  Processing strata : 1
  Buffered area contains 12454 available candidates. Sampling to reach 5 starting.
  Processing strata : 2
  Buffered area contains 9494 available candidates. Sampling to reach 5 starting.
  Processing strata : 3
  Buffered area contains 8088 available candidates. Sampling to reach 5 starting.
  Processing strata : 4
  Buffered area contains 8202 available candidates. Sampling to reach 5 starting.
  Using 'Queinnec' sampling method.
  Implementing proportional allocation of samples.
  Processing strata : 1
  Buffered area contains 17306 available candidates. Sampling to reach 5 starting.
  Processing strata : 2
  Buffered area contains 11160 available candidates. Sampling to reach 5 starting.
  Processing strata : 3
  Buffered area contains 9892 available candidates. Sampling to reach 5 starting.
  Processing strata : 4
  Buffered area contains 10044 available candidates. Sampling to reach 5 starting.
  Using 'Queinnec' sampling method.
  'existing' samples being included in 'nSamp' total.
  Implementing proportional allocation of samples.
  Processing strata : 1
  Processing strata : 2
  'include = TRUE & remove = TRUE' - Stratum 2 overrepresented - 45 samples removed.
  Processing strata : 3
  'include = TRUE & remove = TRUE' - Stratum 3 overrepresented - 45 samples removed.
  Processing strata : 4
  'include = TRUE & remove = TRUE' - Stratum 4 overrepresented - 45 samples removed.
  Using 'Queinnec' sampling method.
  'existing' samples being included in 'nSamp' total.
  Implementing proportional allocation of samples.
  Processing strata : 1
  Processing strata : 2
  'include = TRUE & remove = FALSE' - Stratum 2 overrepresented by 45 samples but have not been removed. Expect a higher total 'nSamp' in output.
  Processing strata : 3
  'include = TRUE & remove = FALSE' - Stratum 3 overrepresented by 45 samples but have not been removed. Expect a higher total 'nSamp' in output.
  Processing strata : 4
  'include = TRUE & remove = FALSE' - Stratum 4 overrepresented by 45 samples but have not been removed. Expect a higher total 'nSamp' in output.
  Using 'Queinnec' sampling method.
  'existing' samples being included in 'nSamp' total.
  Implementing proportional allocation of samples.
  Processing strata : 1
  Processing strata : 2
  Strata : 2 required no sample additions. Keeping all existing samples.
  Processing strata : 3
  Strata : 3 required no sample additions. Keeping all existing samples.
  Processing strata : 4
  Strata : 4 required no sample additions. Keeping all existing samples.
  Using 'Queinnec' sampling method.
  Implementing proportional allocation of samples.
  Processing strata : 1
  Processing strata : 2
  Processing strata : 3
  Processing strata : 4
  Using 'Queinnec' sampling method.
  Processing strata : 1
  Processing strata : 2
  Processing strata : 3
  Processing strata : 4
  Using 'Queinnec' sampling method.
  Implementing proportional allocation of samples.
  nSamp of 25 is not perfectly divisible based on strata distribution. nSamp of 24 will be returned. Use 'force = TRUE' to brute force to 25.
  An access layer has been provided. An internal buffer of 50 m and an external buffer of 200 m have been applied.
  Processing strata : 1
  Processing strata : 2
  Buffered area contains 9494 available candidates. Sampling to reach 6 starting.
  Processing strata : 3
  Buffered area contains 8088 available candidates. Sampling to reach 6 starting.
  Processing strata : 4
  Buffered area contains 8202 available candidates. Sampling to reach 6 starting.
  Using 'Queinnec' sampling method.
  'mraster' was specified but 'allocation = equal' - did you mean to use 'allocation = optim'?
  Implementing equal allocation of samples.
  Processing strata : 1
  Processing strata : 2
  Processing strata : 3
  Processing strata : 4
  Using 'Queinnec' sampling method.
  'weights' was specified but 'allocation = equal' - did you mean to use 'allocation = manual'?
  Implementing equal allocation of samples.
  Processing strata : 1
  Processing strata : 2
  Processing strata : 3
  Processing strata : 4
  Using 'random' sampling method. Ignoring 'existing', 'include', 'remove' if provided.
  Implementing equal allocation of samples.
  Processing strata : 1
  Processing strata : 2
  Processing strata : 3
  Processing strata : 4
  Using 'Queinnec' sampling method.
  Implementing allocation of samples based on user-defined weights.
  Processing strata : 1
  Processing strata : 2
  Processing strata : 3
  Processing strata : 4
  Using 'Queinnec' sampling method.
  Using 'random' sampling method. Ignoring 'existing', 'include', 'remove' if provided.
  Implementing allocation of samples based on user-defined weights.
  Processing strata : 1
  Processing strata : 2
  Processing strata : 3
  Processing strata : 4
  Using 'Queinnec' sampling method.
  Implementing optimal allocation of samples based on variability of 'zq90'.
  Processing strata : 1
  Processing strata : 2
  Processing strata : 3
  Processing strata : 4
  Using 'Queinnec' sampling method.
  Using 'Queinnec' sampling method.
  'weights' was specified but 'allocation = optim' - did you mean to use 'allocation = manual'?
  Implementing optimal allocation of samples based on variability of 'zq90'.
  Processing strata : 1
  Processing strata : 2
  Processing strata : 3
  Processing strata : 4
  Using 'random' sampling method. Ignoring 'existing', 'include', 'remove' if provided.
  Implementing optimal allocation of samples based on variability of 'zq90'.
  Processing strata : 1
  Processing strata : 2
  Processing strata : 3
  Processing strata : 4
  16 samples in 'existing' are located where strata values are NA. Expect 16 additional samples in output.
  'sraster' has factor values. Converting to allow mapping.
  Using 'random' sampling method. Ignoring 'existing', 'include', 'remove' if provided.
  Implementing proportional allocation of samples.
  Processing strata : 1
  Processing strata : 2
  Processing strata : 3
  Processing strata : 4
  Processing strata : 5
  Processing strata : 6
  Processing strata : 7
  Processing strata : 8
  Processing strata : 9
  Processing strata : 10
  Processing strata : 11
  Processing strata : 12
  Processing strata : 13
  Processing strata : 14
  Processing strata : 15
  Processing strata : 16
  Processing strata : 17
  Processing strata : 18
  Processing strata : 19
  Processing strata : 20
  Using 'Queinnec' sampling method.
  Implementing proportional allocation of samples.
  Processing strata : 1
  Processing strata : 2
  Processing strata : 3
  Processing strata : 4
  Using 'random' sampling method. Ignoring 'existing', 'include', 'remove' if provided.
  Implementing proportional allocation of samples.
  Processing strata : 1
  Processing strata : 2
  Processing strata : 3
  Processing strata : 4
  An access layer has been provided. An internal buffer of 50 m and an external buffer of 400 m have been applied.
  Processing strata : 1
  Processing strata : 2
  Processing strata : 3
  Processing strata : 4
  Mapping stratifications.
  K-means being performed on 3 layers with 4 centers.
  Stacking srasters and their combination (strata).
  Mapping stratifications.
  'existing' column coordinate names are lowercase - converting to uppercase.
  'existing' does not contain attributes with the same names as 'raster'. Extracting metrics.
  'existing' does not contain attributes with the same names as 'raster'. Extracting metrics.
  Masking resulted in an output of 76 potential sample units.
  'existing' does not contain attributes with the same names as 'raster'. Extracting metrics.
  'existing' does not contain attributes with the same names as 'raster'. Extracting metrics.
  An access layer has been provided. An external buffer of 300 m have been applied.
  Masking resulted in an output of 119 potential sample units.
  'existing' does not contain attributes with the same names as 'raster'. Extracting metrics.
  An access layer has been provided. An external buffer of 300 m have been applied.
  An access layer has been provided. An external buffer of 100 m have been applied.
  An access layer has been provided. An internal buffer of 20 m and an external buffer of 100 m have been applied.
  An access layer has been provided. An internal buffer of 50 m and an external buffer of 200 m have been applied.
  An access layer has been provided. An external buffer of 100 m have been applied.
  Masking resulted in an output of 68 potential sample units.
  An access layer has been provided. An internal buffer of 20 m and an external buffer of 100 m have been applied.
  Masking resulted in an output of 58 potential sample units.
  Masking resulted in an output of 68 potential sample units.
  An access layer has been provided. An internal buffer of 50 m and an external buffer of 100 m have been applied.
  More than 2 layers in `mraster`. Only first 2 layers will be used.
  More than 2 layers in `mraster`. Only first 2 layers will be used.
  More than 2 layers in `mraster`. Only first 2 layers will be used.
  More than 2 layers in `mraster`. Only first 2 layers will be used.
  More than 2 layers in `mraster`. Only first 2 layers will be used.
  More than 2 layers in `mraster`. Only first 2 layers will be used.
  Strata 1: couldn't select required number of samples: 0 instead of 200 
  
  Writing layer `temp' to data source 
    `D:\temp\RtmpuSet86/temp.shp' using driver `ESRI Shapefile'
  Writing 200 features with 1 fields and geometry type Point.
  Output samples written to disc.
  Output samples written to disc.
  Output raster written to disc.
  [ FAIL 1 | WARN 81 | SKIP 19 | PASS 509 ]
  
  ══ Skipped tests (19) ══════════════════════════════════════════════════════════
  • On CRAN (19): 'test-calculate_coobs.R:2:3', 'test-calculate_distance.R:12:3',
    'test-calculate_lhsOpt.R:2:3', 'test-calculate_pop.R:12:3',
    'test-calculate_pop.R:17:3', 'test-calculate_pop.R:36:3',
    'test-sample_ahels.R:36:3', 'test-sample_balanced.R:33:3',
    'test-sample_balanced.R:40:3', 'test-sample_balanced.R:45:3',
    'test-sample_clhs.R:31:3', 'test-sample_clhs.R:46:3',
    'test-sample_srs.R:27:3', 'test-sample_sys_strat.R:37:3',
    'test-sample_systematic.R:2:3', 'test-sample_systematic.R:13:3',
    'test-sample_systematic.R:31:3', 'test-sample_systematic.R:41:3',
    'test-sample_systematic.R:54:3'
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Failure ('test-sample_existing_balanced.R:35:3'): sample_existing_balanced should produce a balanced sample ──
  `props` (`actual`) not equal to `sample_props` (`expected`).
  
    `dim(actual)`: 4
  `dim(expected)`: 2
  
  `dimnames(actual)[[1]]`:   "1" "2" "3" "4"
  `dimnames(expected)[[1]]`: "1" "3"        
  
    `actual`: 0.25 0.25 0.25 0.25
  `expected`:  0.5  0.5          
  
  [ FAIL 1 | WARN 81 | SKIP 19 | PASS 509 ]
  Error: Test failures
  In addition: Warning messages:
  1: Using an external vector in selections was deprecated in tidyselect 1.1.0.
  ℹ Please use `all_of()` or `any_of()` instead.
    # Was:
    data %>% select(X)
  
    # Now:
    data %>% select(all_of(X))
  
  See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>. 
  2: Using an external vector in selections was deprecated in tidyselect 1.1.0.
  ℹ Please use `all_of()` or `any_of()` instead.
    # Was:
    data %>% select(Y)
  
    # Now:
    data %>% select(all_of(Y))
  
  See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>. 
  Execution halted