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## 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.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.