R Under development (unstable) (2025-04-26 r88181 ucrt) -- "Unsuffered Consequences" Copyright (C) 2025 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > # CRAN OMP THREAD LIMIT > Sys.setenv("OMP_THREAD_LIMIT" = 1) > > library(testthat) > library(shapr) Attaching package: 'shapr' The following object is masked from 'package:testthat': setup > > test_check("shapr") -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: gaussian * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: gaussian * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain_forecast()` ---------------------------------------- i Feature names extracted from the model contains `NA`. Consistency checks between model and data is therefore disabled. i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 128`, and is therefore set to `2^n_features = 128`. -- Explanation overview -- * Model class: * Approach: empirical * Iterative estimation: FALSE * Number of feature-wise Shapley values: 7 * Number of observations to explain: 2 -- Main computation started -- i Using 128 of 128 coalitions. -- Starting `shapr::explain_forecast()` ---------------------------------------- i Feature names extracted from the model contains `NA`. Consistency checks between model and data is therefore disabled. i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 64`, and is therefore set to `2^n_features = 64`. -- Explanation overview -- * Model class: * Approach: empirical * Iterative estimation: FALSE * Number of feature-wise Shapley values: 6 * Number of observations to explain: 2 -- Main computation started -- i Using 64 of 64 coalitions. -- Starting `shapr::explain_forecast()` ---------------------------------------- i Feature names extracted from the model contains `NA`. Consistency checks between model and data is therefore disabled. i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: empirical * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 2 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain_forecast()` ---------------------------------------- i Feature names extracted from the model contains `NA`. Consistency checks between model and data is therefore disabled. i `max_n_coalitions` is `NULL` or larger than or `2^n_groups = 4`, and is therefore set to `2^n_groups = 4`. -- Explanation overview -- * Model class: * Approach: empirical * Iterative estimation: FALSE * Number of group-wise Shapley values: 2 * Number of observations to explain: 2 -- Main computation started -- i Using 4 of 4 coalitions. -- Starting `shapr::explain_forecast()` ---------------------------------------- i Feature names extracted from the model contains `NA`. Consistency checks between model and data is therefore disabled. i `max_n_coalitions` is `NULL` or larger than or `2^n_groups = 4`, and is therefore set to `2^n_groups = 4`. -- Explanation overview -- * Model class: * Approach: empirical * Iterative estimation: FALSE * Number of group-wise Shapley values: 2 * Number of observations to explain: 2 -- Main computation started -- i Using 4 of 4 coalitions. -- Starting `shapr::explain_forecast()` ---------------------------------------- i Feature names extracted from the model contains `NA`. Consistency checks between model and data is therefore disabled. i `max_n_coalitions` is `NULL` or larger than or `2^n_groups = 4`, and is therefore set to `2^n_groups = 4`. -- Explanation overview -- * Model class: * Approach: empirical * Iterative estimation: FALSE * Number of group-wise Shapley values: 2 * Number of observations to explain: 2 -- Main computation started -- i Using 4 of 4 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- -- Explanation overview -- * Model class: * Approach: independence * Iterative estimation: TRUE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- iterative computation started -- -- Iteration 1 ----------------------------------------------------------------- i Using 6 of 32 coalitions, 6 new. -- Iteration 2 ----------------------------------------------------------------- i Using 8 of 32 coalitions, 2 new. -- Iteration 3 ----------------------------------------------------------------- i Using 10 of 32 coalitions, 2 new. -- Iteration 4 ----------------------------------------------------------------- i Using 12 of 32 coalitions, 2 new. -- Iteration 5 ----------------------------------------------------------------- i Using 14 of 32 coalitions, 2 new. -- Iteration 6 ----------------------------------------------------------------- i Using 16 of 32 coalitions, 2 new. -- Iteration 7 ----------------------------------------------------------------- i Using 18 of 32 coalitions, 2 new. -- Iteration 8 ----------------------------------------------------------------- i Using 20 of 32 coalitions, 2 new. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: gaussian * Iterative estimation: TRUE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- iterative computation started -- -- Iteration 1 ----------------------------------------------------------------- i Using 6 of 32 coalitions, 6 new. -- Iteration 2 ----------------------------------------------------------------- i Using 8 of 32 coalitions, 2 new. -- Iteration 3 ----------------------------------------------------------------- i Using 12 of 32 coalitions, 4 new. -- Iteration 4 ----------------------------------------------------------------- i Using 14 of 32 coalitions, 2 new. -- Iteration 5 ----------------------------------------------------------------- i Using 16 of 32 coalitions, 2 new. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_groups = 32`, and is therefore set to `2^n_groups = 32`. -- Explanation overview -- * Model class: * Approach: gaussian * Iterative estimation: TRUE * Number of group-wise Shapley values: 5 * Number of observations to explain: 3 -- iterative computation started -- -- Iteration 1 ----------------------------------------------------------------- i Using 6 of 32 coalitions, 6 new. -- Iteration 2 ----------------------------------------------------------------- i Using 8 of 32 coalitions, 2 new. -- Iteration 3 ----------------------------------------------------------------- i Using 12 of 32 coalitions, 4 new. -- Iteration 4 ----------------------------------------------------------------- i Using 14 of 32 coalitions, 2 new. -- Iteration 5 ----------------------------------------------------------------- i Using 16 of 32 coalitions, 2 new. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: empirical * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: empirical * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: ctree * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: ctree * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- -- Explanation overview -- * Model class: * Approach: ctree * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 10 of 32 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- -- Explanation overview -- * Model class: * Approach: ctree * Iterative estimation: FALSE * Number of group-wise Shapley values: 3 * Number of observations to explain: 3 -- Main computation started -- i Using 6 of 8 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: empirical * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: empirical * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: empirical * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: empirical * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: empirical * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: ctree * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: ctree * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: gaussian * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain()` at 2025-04-28 13:56:28 -------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: gaussian * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 * Computations (temporary) saved at: 'D:\temp\2025_04_28_13_50_16_8940\Rtmpe4qWrW\shapr_obj_257647c5c1024.rds' -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: independence, empirical, gaussian, and copula * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: independence, empirical, gaussian, and copula * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: independence, empirical, gaussian, and copula * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: empirical * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: gaussian, gaussian, gaussian, and gaussian * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: independence, empirical, independence, and empirical * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: independence, empirical, independence, and empirical * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: vaeac * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. OMP: Warning #96: Cannot form a team with 48 threads, using 1 instead. OMP: Hint Consider unsetting KMP_DEVICE_THREAD_LIMIT (KMP_ALL_THREADS), KMP_TEAMS_THREAD_LIMIT, and OMP_THREAD_LIMIT (if any are set). -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: vaeac * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: vaeac * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: vaeac * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: vaeac * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`. -- Explanation overview -- * Model class: * Approach: gaussian * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- i `max_n_coalitions` is `NULL` or larger than or `2^n_groups = 32`, and is therefore set to `2^n_groups = 32`. -- Explanation overview -- * Model class: * Approach: gaussian * Iterative estimation: FALSE * Number of group-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 32 of 32 coalitions. -- Starting `shapr::explain()` ------------------------------------------------- -- Explanation overview -- * Model class: * Approach: independence * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 18 of 32 coalitions. -- Convergence info v Converged after 18 coalitions: Maximum number of iterations reached! Maximum number of coalitions reached! -- Final estimated Shapley values (sd) none Solar.R Wind Temp Month 1: 42.444 (0.00) -3.389 (0.80) 7.949 (0.62) 14.864 (3.27) -4.626 (2.39) 2: 42.444 (0.00) 3.083 (0.62) -3.561 (0.36) -4.635 (0.97) -6.028 (1.03) 3: 42.444 (0.00) 3.732 (0.60) -18.903 (0.68) -1.043 (1.40) -3.556 (1.36) Day 1: -2.196 (2.47) 2: -2.738 (0.96) 3: 2.202 (0.96) -- Starting `shapr::explain()` ------------------------------------------------- -- Explanation overview -- * Model class: * Approach: independence * Iterative estimation: FALSE * Number of feature-wise Shapley values: 5 * Number of observations to explain: 3 -- Main computation started -- i Using 20 of 32 coalitions. -- Convergence info v Converged after 20 coalitions: Maximum number of iterations reached! Maximum number of coalitions reached! -- Final estimated Shapley values (sd) none Solar.R Wind Temp Month 1: 42.444 (0.00) -4.331 (0.59) 7.521 (0.79) 17.475 (0.29) -5.006 (0.72) 2: 42.444 (0.00) 2.873 (0.55) -4.405 (0.35) -4.707 (0.16) -4.967 (0.50) 3: 42.444 (0.00) 3.354 (0.18) -18.354 (0.16) -1.828 (0.06) -2.822 (0.21) Day 1: -3.057 (0.29) 2: -2.673 (0.16) 3: 2.082 (0.06) [ FAIL 0 | WARN 0 | SKIP 55 | PASS 51 ] ══ Skipped tests (55) ══════════════════════════════════════════════════════════ • On CRAN (55): 'test-asymmetric-causal-output.R:14:1', 'test-asymmetric-causal-setup.R:4:3', 'test-asymmetric-causal-setup.R:232:3', 'test-asymmetric-causal-setup.R:256:3', 'test-asymmetric-causal-setup.R:321:3', 'test-forecast-output.R:2:1', 'test-forecast-setup.R:7:3', 'test-forecast-setup.R:36:3', 'test-forecast-setup.R:114:3', 'test-forecast-setup.R:139:3', 'test-forecast-setup.R:166:3', 'test-forecast-setup.R:228:3', 'test-forecast-setup.R:302:3', 'test-forecast-setup.R:352:3', 'test-forecast-setup.R:448:3', 'test-forecast-setup.R:521:3', 'test-iterative-output.R:1:1', 'test-iterative-setup.R:79:3', 'test-iterative-setup.R:313:3', 'test-iterative-setup.R:398:3', 'test-plot.R:1:1', 'test-regression-output.R:1:1', 'test-regression-setup.R:11:3', 'test-regression-setup.R:49:3', 'test-regression-setup.R:177:3', 'test-regression-setup.R:235:3', 'test-regression-setup.R:297:3', 'test-regression-setup.R:338:3', 'test-regular-output.R:1:1', 'test-regular-setup.R:5:3', 'test-regular-setup.R:38:3', 'test-regular-setup.R:121:3', 'test-regular-setup.R:243:3', 'test-regular-setup.R:262:3', 'test-regular-setup.R:320:3', 'test-regular-setup.R:397:3', 'test-regular-setup.R:558:3', 'test-regular-setup.R:681:3', 'test-regular-setup.R:797:3', 'test-regular-setup.R:818:3', 'test-regular-setup.R:876:3', 'test-regular-setup.R:934:3', 'test-regular-setup.R:1040:3', 'test-regular-setup.R:1152:3', 'test-regular-setup.R:1225:3', 'test-regular-setup.R:1269:3', 'test-regular-setup.R:1794:3', 'test-regular-setup.R:1829:3', 'test-regular-setup.R:1852:3', 'test-semi-deterministic-output.R:1:1', 'test-semi-deterministic-setup.R:2:3', 'test-semi-deterministic-setup.R:23:3', 'test-semi-deterministic-setup.R:48:3', 'test-semi-deterministic-setup.R:97:3', 'test-semi-deterministic-setup.R:126:3' [ FAIL 0 | WARN 0 | SKIP 55 | PASS 51 ] > > proc.time() user system elapsed 208.64 6.89 221.98