## check status detail
## required_tables PASS All core tables are present.
## unique_Lake_ID PASS 0 duplicate Lake_ID position (0 means none).
## unique_Event_ID PASS 0 duplicate Event_ID position (0 means none).
## event_to_lake_foreign_key PASS All events link to a known lake.
## event_alignment_MP_Abundance PASS missing=0; extra=0; duplicate=0
## event_alignment_Morphology_Composition PASS missing=0; extra=0; duplicate=0
## event_alignment_Size_Composition PASS missing=0; extra=0; duplicate=0
## event_alignment_Polymer_Composition PASS missing=0; extra=0; duplicate=0
## table:required_columns PASS All required columns are present.
## table:unique_primary_identifier PASS 0 duplicate identifier row(s).
## table:non_negative_abundance PASS 0 invalid abundance value(s).
## table:required_columns PASS All required columns are present.
## table:unique_primary_identifier PASS 0 duplicate identifier row(s).
## table:percentage_bounds PASS 0 component value(s) outside 0-100%.
## table:percentage_closure PASS 0 complete profile(s) outside 100 +/- 0.2 %.
## table:required_columns PASS All required columns are present.
## table:unique_primary_identifier PASS 0 duplicate identifier row(s).
## table:percentage_bounds PASS 0 component value(s) outside 0-100%.
## table:percentage_closure PASS 0 complete profile(s) outside 100 +/- 0.2 %.
## table:required_columns PASS All required columns are present.
## table:unique_primary_identifier PASS 0 duplicate identifier row(s).
## table:percentage_bounds PASS 0 component value(s) outside 0-100%.
## table:percentage_closure PASS 0 complete profile(s) outside 100 +/- 0.2 %.
## coordinate_ranges PASS 0 lake coordinate row(s) outside valid ranges.
## abundance_units PASS Observed unit(s): particles L^-1
## method_foreign_key PASS All event Method_ID values resolve.
##
## Summary:
##
## PASS
## 26check_database() validates identifiers, cross-table
event alignment, abundance ranges, composition closure, coordinates,
abundance units and method links.
## Lake_Name Season_Global n mean sd median IQR se ci_low ci_high
## 1 Demo Reference Coastal Monsoon 1 42.30 NA 42.30 0 NA NA NA
## 2 Demo Reference Coastal Post-monsoon 1 37.40 NA 37.40 0 NA NA NA
## 3 Demo Reference Coastal Pre-monsoon 1 34.20 NA 34.20 0 NA NA NA
## 4 Demo Reference Coastal Winter 1 28.10 NA 28.10 0 NA NA NA
## 5 Demo Reference East Monsoon 1 38.25 NA 38.25 0 NA NA NA
## 6 Demo Reference East Post-monsoon 1 33.00 NA 33.00 0 NA NA NA## Lake_Name Season_Global Fibres_pct Fragments_pct Films_pct Beads_pct
## 1 Demo Reference Coastal Monsoon 36 28 18 18
## 2 Demo Reference Coastal Post-monsoon 38 27 20 15
## 3 Demo Reference Coastal Pre-monsoon 34 29 22 15
## 4 Demo Reference Coastal Winter 32 30 20 18
## 5 Demo Reference East Monsoon 44 31 22 3
## 6 Demo Reference East Post-monsoon 46 30 18 6
## dominant_component shannon n_profiles
## 1 Fibres 1.341552 1
## 2 Fibres 1.327658 1
## 3 Fibres 1.343455 1
## 4 Fibres 1.356362 1
## 5 Fibres 1.162603 1
## 6 Fibres 1.195863 1## Lake_Name Season_Global Fine_LT250_pct Intermediate_250_1000_pct
## 1 Demo Reference Coastal Monsoon 74 18
## 2 Demo Reference Coastal Post-monsoon 78 14
## 3 Demo Reference Coastal Pre-monsoon 70 22
## 4 Demo Reference Coastal Winter 66 26
## 5 Demo Reference East Monsoon 71 18
## 6 Demo Reference East Post-monsoon 75 14
## Coarse_GT1000_pct dominant_component shannon n_profiles
## 1 8 Fine_LT250 0.7335398 1
## 2 8 Fine_LT250 0.6711140 1
## 3 8 Fine_LT250 0.7848389 1
## 4 8 Fine_LT250 0.8265376 1
## 5 11 Fine_LT250 0.7946321 1
## 6 11 Fine_LT250 0.7338176 1## Lake_Name Season_Global PE_pct PP_pct PET_PES_pct PA_Nylon_pct PS_EPS_pct
## 1 Demo Reference Coastal Monsoon 25.00000 23.07692 18.26923 8.653846 12.50000
## 2 Demo Reference Coastal Post-monsoon 25.74257 25.74257 14.85149 8.910891 13.86139
## 3 Demo Reference Coastal Pre-monsoon 26.53061 22.44898 18.36735 9.183673 12.24490
## 4 Demo Reference Coastal Winter 27.08333 20.83333 17.70833 9.375000 11.45833
## 5 Demo Reference East Monsoon 24.50980 23.52941 17.64706 7.843137 12.74510
## 6 Demo Reference East Post-monsoon 24.27184 25.24272 18.44660 7.766990 13.59223
## PVC_pct OtherPolymer_pct dominant_component shannon n_profiles
## 1 6.730769 5.769231 PE 1.813435 1
## 2 4.950495 5.940595 PE 1.787780 1
## 3 5.102041 6.122449 PE 1.797908 1
## 4 7.291667 6.250001 PE 1.821498 1
## 5 7.843137 5.882353 PE 1.819700 1
## 6 4.854369 5.825243 PP 1.785148 1For a multisite database, random row splitting can place observations
from the same lake in both training and testing sets.
cross_validate_mp() therefore defaults to grouped
validation by Lake_ID.
cv <- cross_validate_mp(
db,
MP_Mean ~ Season_Global + Lake_Type,
method = "lognormal_lm",
group = "Lake_ID"
)
cv$overall## n groups RMSE MAE bias R2_predictive
## 1 24 6 4.820031 4.046157 0.0334341 0.3890025Polymer, morphology and size profiles are compositional.
limpidR provides closure checks, CLR transformation and
Aitchison distance. Zero handling is explicit through the
pseudocount argument.
pol <- db$Polymer_Composition
cols <- c("PE_pct", "PP_pct", "PET_PES_pct", "PA_Nylon_pct",
"PS_EPS_pct", "PVC_pct", "OtherPolymer_pct")
head(clr_transform(pol, cols))## Polymer_ID Event_ID Lake_ID Lake_Name PE_pct PP_pct PET_PES_pct PA_Nylon_pct
## 1 DPO001 DEVT001 DL001 Demo Urban North 23.59551 22.47191 19.10112 8.988764
## 2 DPO002 DEVT002 DL001 Demo Urban North 22.34043 23.40425 19.14894 8.510638
## 3 DPO003 DEVT003 DL001 Demo Urban North 21.21212 24.24242 19.19192 8.080808
## 4 DPO004 DEVT004 DL001 Demo Urban North 22.10526 27.36842 15.78947 8.421053
## 5 DPO005 DEVT005 DL002 Demo Urban West 23.65591 21.50538 19.35484 9.677419
## 6 DPO006 DEVT006 DL002 Demo Urban West 23.15789 23.15789 20.00000 9.473684
## PS_EPS_pct PVC_pct OtherPolymer_pct Polymer_Richness Polymer_Shannon Polymer_Profile_N
## 1 12.35955 6.741573 6.741572 7 1.831021 20
## 2 12.76596 7.446809 6.382979 7 1.832753 20
## 3 13.13131 8.080808 6.060607 7 1.832306 20
## 4 14.73684 5.263158 6.315789 7 1.799705 20
## 5 11.82796 7.526882 6.451613 7 1.839394 20
## 6 12.63158 5.263158 6.315789 7 1.813436 20
## Sum_pct Composition_Level QA_Note clr_PE_pct clr_PP_pct
## 1 100 Lake-event summary Synthetic deterministic example. 0.6253334 0.5765432
## 2 100 Lake-event summary Synthetic deterministic example. 0.5691004 0.6156204
## 3 100 Lake-event summary Synthetic deterministic example. 0.5184357 0.6519671
## 4 100 Lake-event summary Synthetic deterministic example. 0.5973274 0.8109015
## 5 100 Lake-event summary Synthetic deterministic example. 0.6181945 0.5228843
## 6 100 Lake-event summary Synthetic deterministic example. 0.6324921 0.6324921
## clr_PET_PES_pct clr_PA_Nylon_pct clr_PS_EPS_pct clr_PVC_pct clr_OtherPolymer_pct
## 1 0.4140243 -0.3397476 -0.021293794 -0.6274296 -0.6274298
## 2 0.4149497 -0.3959806 0.009484544 -0.5295119 -0.6836626
## 3 0.4183522 -0.4466452 0.038862597 -0.4466452 -0.7343271
## 4 0.2608552 -0.3677535 0.191862262 -0.8377571 -0.6554357
## 5 0.4175238 -0.2756235 -0.074952722 -0.5269378 -0.6810885
## 6 0.4858886 -0.2613258 0.026356305 -0.8491124 -0.6667910## 1 2 3 4 5 6 7 8
## 2 0.14679749
## 3 0.27620745 0.12947327
## 4 0.41280836 0.43880166 0.49509046
## 5 0.15136557 0.18068087 0.27946108 0.53374085
## 6 0.25972886 0.36080637 0.46796366 0.35026202 0.36243744
## 7 0.27302731 0.24511804 0.28932239 0.35211542 0.30067036 0.41578410
## 8 0.39262977 0.44119536 0.51325485 0.11278717 0.50371990 0.27931220 0.35678535
## 9 0.28385238 0.28443757 0.34502101 0.65089530 0.13254043 0.47253803 0.37919570 0.61534234
## 10 0.27333765 0.29804144 0.37237325 0.45547002 0.24447235 0.41623175 0.16435372 0.42506585
## 11 0.26640450 0.32160197 0.40907398 0.28936196 0.32323760 0.27298560 0.20121320 0.23171394
## 12 0.40080229 0.46677006 0.54901670 0.21486779 0.49690659 0.24212513 0.39067714 0.10210728
## 13 0.26657374 0.35853559 0.46298742 0.35557784 0.38797486 0.30774468 0.37661765 0.35392938
## 14 0.29783834 0.36506080 0.45453152 0.28650466 0.43276462 0.29003396 0.38741741 0.29786810
## 15 0.35505479 0.39847955 0.46976034 0.25120878 0.49208236 0.30886548 0.42362061 0.27714162
## 16 0.42274386 0.44778463 0.50183468 0.25328578 0.55761686 0.35186924 0.47458086 0.29033355
## 17 0.17951795 0.27110377 0.38251538 0.44026320 0.24093974 0.32542740 0.30496922 0.42025999
## 18 0.18313650 0.17805642 0.25792154 0.44361291 0.21800110 0.38456426 0.24436244 0.44465428
## 19 0.26420078 0.17315800 0.17679199 0.48148629 0.27290617 0.46666494 0.25712390 0.49876519
## 20 0.38782393 0.43785256 0.51023624 0.24935407 0.51547151 0.25730914 0.45893245 0.23456317
## 21 0.22265482 0.27964783 0.37546279 0.55080865 0.17160668 0.40478149 0.32288447 0.52083113
## 22 0.30180533 0.41556777 0.52801586 0.37296787 0.39717989 0.17031325 0.43005229 0.30538572
## 23 0.16998189 0.18106131 0.26781835 0.40013389 0.21326815 0.30142772 0.24603741 0.37913189
## 24 0.44232585 0.50502944 0.58412210 0.20928772 0.54595297 0.35551870 0.39113448 0.17484545
## 9 10 11 12 13 14 15 16
## 2
## 3
## 4
## 5
## 6
## 7
## 8
## 9
## 10 0.29212617
## 11 0.41437690 0.20260482
## 12 0.59950497 0.42287535 0.22060112
## 13 0.50698608 0.39973943 0.33044170 0.38040148
## 14 0.55732828 0.44423224 0.33668783 0.33938452 0.11006593
## 15 0.61714504 0.50352607 0.37257437 0.33106250 0.21129231 0.10123144
## 16 0.68106502 0.56926530 0.42525398 0.35051819 0.30501981 0.19496750 0.09373963
## 17 0.34312011 0.27769570 0.28933446 0.42636933 0.17764461 0.25504987 0.34227995 0.42848655
## 18 0.31266877 0.26903697 0.31136943 0.46841699 0.26338148 0.29955830 0.36028574 0.43027972
## 19 0.34257939 0.32399680 0.37854181 0.53389388 0.37041008 0.38066777 0.41637023 0.46687298
## 20 0.63484700 0.52589222 0.36251324 0.26267921 0.28802504 0.19252441 0.12705840 0.12233810
## 21 0.22122208 0.24129935 0.33578359 0.51296558 0.32956230 0.40062573 0.47899904 0.55803282
## 22 0.50156782 0.41220037 0.28400743 0.26901107 0.22418651 0.23371019 0.28249632 0.34816737
## 23 0.31200919 0.26590865 0.25019252 0.38706222 0.27442227 0.28548565 0.32931241 0.38929871
## 24 0.65191033 0.43705225 0.27317349 0.20033502 0.31142275 0.27568920 0.28032233 0.31564828
## 17 18 19 20 21 22 23
## 2
## 3
## 4
## 5
## 6
## 7
## 8
## 9
## 10
## 11
## 12
## 13
## 14
## 15
## 16
## 17
## 18 0.14685449
## 19 0.27637704 0.12958617
## 20 0.39374962 0.41945058 0.47532642
## 21 0.15199749 0.17881427 0.27693816 0.51564415
## 22 0.26152108 0.36021468 0.46623018 0.25139211 0.36303133
## 23 0.17571204 0.12121336 0.18789916 0.35224234 0.20787436 0.29274358
## 24 0.39416429 0.44262936 0.51461275 0.26531206 0.50559161 0.28662716 0.39490071calculate_risk() intentionally does not ship a universal
polymer-hazard weighting scheme. Supply the abundance reference and any
polymer hazard values used in your study, and report them in the methods
section.