Last updated on 2020-08-07 01:49:34 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.2.1 | 11.17 | 240.16 | 251.33 | OK | |
| r-devel-linux-x86_64-debian-gcc | 1.2.1 | 11.21 | 172.85 | 184.06 | OK | |
| r-devel-linux-x86_64-fedora-clang | 1.2.1 | 298.63 | NOTE | |||
| r-devel-linux-x86_64-fedora-gcc | 1.2.1 | 302.49 | NOTE | |||
| r-devel-windows-ix86+x86_64 | 1.2.1 | 39.00 | 273.00 | 312.00 | OK | |
| r-patched-linux-x86_64 | 1.2.1 | 14.25 | 231.08 | 245.33 | OK | |
| r-patched-solaris-x86 | 1.2.1 | 389.60 | ERROR | |||
| r-release-linux-x86_64 | 1.2.1 | 12.98 | 234.50 | 247.48 | OK | |
| r-release-macos-x86_64 | 1.2.1 | NOTE | ||||
| r-release-windows-ix86+x86_64 | 1.2.1 | 39.00 | 292.00 | 331.00 | OK | |
| r-oldrel-macos-x86_64 | 1.2.1 | NOTE | ||||
| r-oldrel-windows-ix86+x86_64 | 1.2.1 | 24.00 | 226.00 | 250.00 | OK |
Version: 1.2.1
Check: dependencies in R code
Result: NOTE
Namespace in Imports field not imported from: ‘rgdal’
All declared Imports should be used.
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-patched-solaris-x86, r-release-macos-x86_64, r-oldrel-macos-x86_64
Version: 1.2.1
Check: tests
Result: ERROR
Running ‘testthat.R’ [85s/104s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(assignR)
>
> test_check("assignR")
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---------------------------------------
------------------------------------------
rescale function uses linear regression model,
the summary of this model is:
-------------------------------------------
--------------------------------------
Call:
lm(formula = tissue.iso ~ isoscape.iso[, 1])
Residuals:
Min 1Q Median 3Q Max
-38.625 -3.897 0.313 4.261 22.994
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -75.93649 1.29661 -58.57 <2e-16 ***
isoscape.iso[, 1] 0.39330 0.01993 19.74 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 7.826 on 208 degrees of freedom
Multiple R-squared: 0.6519, Adjusted R-squared: 0.6503
F-statistic: 389.6 on 1 and 208 DF, p-value: < 2.2e-16
---------------------------------------
------------------------------------------
rescale function uses linear regression model,
the summary of this model is:
-------------------------------------------
--------------------------------------
Call:
lm(formula = tissue.iso ~ isoscape.iso[, 1])
Residuals:
Min 1Q Median 3Q Max
-38.575 -3.848 0.273 4.207 23.026
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -75.94258 1.30067 -58.39 <2e-16 ***
isoscape.iso[, 1] 0.39367 0.02002 19.67 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 7.844 on 208 degrees of freedom
Multiple R-squared: 0.6503, Adjusted R-squared: 0.6487
F-statistic: 386.8 on 1 and 208 DF, p-value: < 2.2e-16
---------------------------------------
------------------------------------------
rescale function uses linear regression model,
the summary of this model is:
-------------------------------------------
--------------------------------------
Call:
lm(formula = tissue.iso ~ isoscape.iso[, 1])
Residuals:
Min 1Q Median 3Q Max
-38.625 -3.897 0.313 4.261 22.994
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -75.93649 1.29661 -58.57 <2e-16 ***
isoscape.iso[, 1] 0.39330 0.01993 19.74 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 7.826 on 208 degrees of freedom
Multiple R-squared: 0.6519, Adjusted R-squared: 0.6503
F-statistic: 389.6 on 1 and 208 DF, p-value: < 2.2e-16
NO isoscape values found at the following locations:
-39.8194445, 38.5611111
-99.09, 19.2
-99.09, 19.2
-99.09, 19.2
-101.3, 20.72
-101.37, 20.73
-99.5, 17.55
-99.5, 17.55
-99.5, 18.9
-100.07, 19.09
-100.07, 19.09
-101.15265, 20.0074
-101.15265, 20.0074
-101.15289, 20.0092
-101.15265, 20.0074
-101.15265, 20.0074
-101.15265, 20.0074
-101.15265, 20.0074
-101.6, 19.47
-98.98, 18.7
-99.06, 18.8
-99.08, 18.86
-99.25, 18.75
-97.77, 17.8
-97.77, 17.8
-101.14604, 20.01137
-101.15265, 20.0074
-101.14527, 19.99508
-101.15265, 20.0074
-101.15265, 20.0074
-101.15265, 20.0074
-101.15265, 20.0074
-101.15265, 20.0074
-6.0833, 53.1833
-6.0833, 53.1833
-6.0833, 53.1833
-6.0833, 53.1833
-6.0833, 53.1833
-6.0833, 53.1833
-0.3, 39.3833
-0.3, 39.3833
-0.3, 39.3833
-0.3, 39.3833
-0.6917, 54.5717
-0.6917, 54.5717
-0.6917, 54.5717
-0.6917, 54.5717
-0.6917, 54.5717
-0.6917, 54.5717
-0.6917, 54.5717
-0.867, 54.4
-2.1986, 55.3175
-2.3042, 54.7081
-2.1886, 54.2269
0.8419, 52.6147
0.8419, 52.6147
-4.1678, 56.8581
-4.1678, 56.8581
-4.1678, 56.8581
-4.1678, 56.8581
28.2333, 45.1833
13.0833, 44.0333
13.0833, 44.0333
27.7333, 52.0667
27.7333, 52.0667
27.7333, 52.0667
27.7333, 52.0667
16.7639, 52.1347
16.7639, 52.1347
16.7639, 52.1347
26.5056, 58.595
26.5056, 58.595
26.5056, 58.595
26.4278, 58.4611
26.4278, 58.4611
26.4278, 58.4611
-0.378, 46.361
-0.378, 46.361
-0.378, 46.361
-0.248, 46.401
-0.244, 46.088
-4.037, 48.578
-4.037, 48.578
-4.037, 48.578
-2.578, 47.519
1.462, 48.297
1.578, 48.192
1.385, 48.337
1.276, 48.249
1.276, 48.249
3.711, 49.825
3.711, 49.825
3.711, 49.825
3.711, 49.825
3.711, 49.825
42.817, 62.017
42.817, 62.017
42.817, 62.017
42.817, 62.017
42.817, 62.017
55.767, 57.267
55.767, 57.267
55.767, 57.267
55.767, 57.267
55.767, 57.267
38.783, 55
38.783, 55
38.783, 55
38.783, 55
38.783, 55
19.117, 48.567
19.117, 48.567
19.117, 48.567
19.117, 48.567
-1.75, 53.783
-2.35, 55
-2.95, 54.333
1.933, 42.433
24.2525, 65.8506
24.2333, 65.8167
24.2839, 65.8522
24.2833, 65.8681
30.85, 59.0333
30.4, 60.15
30.4, 60.15
30.4, 60.15
30.4, 60.15
27.25, 69.5
27.25, 69.5
27.25, 69.5
27.25, 69.5
27.25, 69.5
25.3333, 63.2667
26.1, 63.2
26.1, 63.2
25.6, 63.05
26.1, 63.2
27.5833, 66.5
27.3333, 66.75
27.3333, 66.75
27.3333, 66.75
27.3333, 66.75
29.2833, 64.9667
29, 64.8333
29, 64.6833
29.5, 65.2167
29.5333, 64.9167
29, 64.6833
14.1128, 49.2639
14.1583, 49.2939
14.1528, 49.2989
14.2, 49.2528
22.7667, 62.0333
22.7667, 62.0333
22.95, 62.15
22.95, 62.3167
22.95, 62.15
23.3333, 61.9167
6.0178, 52.0939
6.1, 52.2308
6.0719, 52.2308
6.115, 52.29
6.0619, 52.1608
14.1356, 49.2778
14.1292, 49.2764
── 1. Error: calRaster can correctly uses known-origin tissue data to rescale a
is.character(proj) is not TRUE
Backtrace:
1. testthat::expect_warning(calRaster(known = d_diffPorj, isoscape = d2h_world))
6. assignR::calRaster(known = d_diffPorj, isoscape = d2h_world)
8. rgdal:::spTransform(known, crs(isoscape))
10. rgdal:::spTransform(xSP, CRSobj, ...)
11. rgdal:::get_aoi(x)
12. rgdal::project(t(bbox(obj))[, 1:2], tg, inv = TRUE, use_aoi = FALSE)
13. base::stopifnot(is.character(proj))
---------------------------------------
------------------------------------------
rescale function uses linear regression model,
the summary of this model is:
-------------------------------------------
--------------------------------------
Call:
lm(formula = tissue.iso ~ isoscape.iso[, 1])
Residuals:
Min 1Q Median 3Q Max
-38.625 -3.897 0.313 4.261 22.994
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -75.93649 1.29661 -58.57 <2e-16 ***
isoscape.iso[, 1] 0.39330 0.01993 19.74 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 7.826 on 208 degrees of freedom
Multiple R-squared: 0.6519, Adjusted R-squared: 0.6503
F-statistic: 389.6 on 1 and 208 DF, p-value: < 2.2e-16
---------------------------------------
------------------------------------------
rescale function uses linear regression model,
the summary of this model is:
-------------------------------------------
--------------------------------------
Call:
lm(formula = tissue.iso ~ isoscape.iso[, 1])
Residuals:
Min 1Q Median 3Q Max
-38.625 -3.897 0.313 4.261 22.994
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -75.93649 1.29661 -58.57 <2e-16 ***
isoscape.iso[, 1] 0.39330 0.01993 19.74 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 7.826 on 208 degrees of freedom
Multiple R-squared: 0.6519, Adjusted R-squared: 0.6503
F-statistic: 389.6 on 1 and 208 DF, p-value: < 2.2e-16
── 2. Error: pdRaster can correctly calculate ratio of odds
for two l
is.character(proj) is not TRUE
Backtrace:
1. testthat::expect_warning(oddsRatio(asn, s12_diffProj))
6. assignR::oddsRatio(asn, s12_diffProj)
8. rgdal:::spTransform(inputP, crs(pdR))
10. rgdal:::spTransform(xSP, CRSobj, ...)
11. rgdal:::get_aoi(x)
12. rgdal::project(t(bbox(obj))[, 1:2], tg, inv = TRUE, use_aoi = FALSE)
13. base::stopifnot(is.character(proj))
---------------------------------------
------------------------------------------
rescale function uses linear regression model,
the summary of this model is:
-------------------------------------------
--------------------------------------
Call:
lm(formula = tissue.iso ~ isoscape.iso[, 1])
Residuals:
Min 1Q Median 3Q Max
-38.625 -3.897 0.313 4.261 22.994
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -75.93649 1.29661 -58.57 <2e-16 ***
isoscape.iso[, 1] 0.39330 0.01993 19.74 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 7.826 on 208 degrees of freedom
Multiple R-squared: 0.6519, Adjusted R-squared: 0.6503
F-statistic: 389.6 on 1 and 208 DF, p-value: < 2.2e-16
── 3. Error: pdRaster can correctly calculate posterior probabilities of origin
is.character(proj) is not TRUE
Backtrace:
1. testthat::expect_warning(pdRaster(r, unknown = un, mask = mask_diffProj))
6. assignR::pdRaster(r, unknown = un, mask = mask_diffProj)
8. rgdal:::spTransform(mask, crs(r[[1]]))
10. rgdal:::spTransform(xSP, CRSobj, ...)
11. rgdal:::get_aoi(x)
12. rgdal::project(t(bbox(obj))[, 1:2], tg, inv = TRUE, use_aoi = FALSE)
13. base::stopifnot(is.character(proj))
|
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|
|======================================================================| 100%
|
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|
|=================================== | 50%
|
|======================================================================| 100%
---------------------------------------
------------------------------------------
rescale function uses linear regression model,
the summary of this model is:
-------------------------------------------
--------------------------------------
Call:
lm(formula = tissue.iso ~ isoscape.iso[, 1])
Residuals:
Min 1Q Median 3Q Max
-38.625 -3.897 0.313 4.261 22.994
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -75.93649 1.29661 -58.57 <2e-16 ***
isoscape.iso[, 1] 0.39330 0.01993 19.74 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 7.826 on 208 degrees of freedom
Multiple R-squared: 0.6519, Adjusted R-squared: 0.6503
F-statistic: 389.6 on 1 and 208 DF, p-value: < 2.2e-16
---------------------------------------
------------------------------------------
rescale function uses linear regression model,
the summary of this model is:
-------------------------------------------
--------------------------------------
Call:
lm(formula = tissue.iso ~ isoscape.iso[, 1])
Residuals:
Min 1Q Median 3Q Max
-38.625 -3.897 0.313 4.261 22.994
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -75.93649 1.29661 -58.57 <2e-16 ***
isoscape.iso[, 1] 0.39330 0.01993 19.74 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 7.826 on 208 degrees of freedom
Multiple R-squared: 0.6519, Adjusted R-squared: 0.6503
F-statistic: 389.6 on 1 and 208 DF, p-value: < 2.2e-16
══ testthat results ═══════════════════════════════════════════════════════════
[ OK: 68 | SKIPPED: 0 | WARNINGS: 17 | FAILED: 3 ]
1. Error: calRaster can correctly uses known-origin tissue data to rescale a map of
environmental isotope values to a map of tissue value (and associated uncertainty)
using a linear regression model. (@test_calRaster.R#59)
2. Error: pdRaster can correctly calculate ratio of odds
for two locations (points or polygons) of geographic origin (@test_oddsRatio.R#59)
3. Error: pdRaster can correctly calculate posterior probabilities of origin
for a sample based on its isotope ratio (@test_pdRaster.R#40)
Error: testthat unit tests failed
Execution halted
Flavor: r-patched-solaris-x86