tests/testthat/test-netVolumeCalculator.R
In bcgov/BCForestGroundSample: BC forest ground sample compilation
test_that("netVolumeCalculator.R: total net volume is not correctly calculated.", {
library(data.table)
library(testthat)
## check the error
# 1. number of row is right, ncol is not right
logvolmatrix <- data.table(log_v_0 = 1:5,
log_v_1 = 5:9,
log_v_2 = c(5:7, NA, NA)) ## has 5 rows and 3 columns
merchlogmatrix <- data.table(log_vm_1 = 1:5,
log_vm_2 = 5:9,
log_vm_3 = 7:11) ## has 5 rows and 3 columns
soundtable <- data.table(log_s_1 = rep(100, 5),
log_s_2 = rep(80, 5),
log_s_3 = rep(70, 5),
log_s_4 = rep(60, 5)) ## has 5 rows and 4 columns
expect_error(netVolumeCalculator(grossVolMatrix = logvolmatrix,
grossMerchVolMatrix = merchlogmatrix,
netFactorMatrix = soundtable))
# 2. number of row is wrong and number of col is right
logvolmatrix <- data.table(log_v_0 = 1:5,
log_v_1 = 5:9,
log_v_2 = c(5:7, NA, NA)) ## has 5 rows and 3 columns
merchlogmatrix <- data.table(log_vm_1 = 1:3,
log_vm_2 = 5:7) ## has 5 rows and 3 columns
soundtable <- data.table(log_s_1 = rep(100, 5),
log_s_2 = rep(80, 5)) ## has 5 rows and 4 columns
expect_error(netVolumeCalculator(grossVolMatrix = logvolmatrix,
grossMerchVolMatrix = merchlogmatrix,
netFactorMatrix = soundtable))
## check missing
# 1. missing grossVolMatrix
merchlogmatrix <- data.table(log_vm_1 = 1:5,
log_vm_2 = 5:9)
soundtable <- data.table(log_s_1 = rep(100, 5),
log_s_2 = rep(80, 5))
netvols <- netVolumeCalculator(grossMerchVolMatrix = merchlogmatrix,
netFactorMatrix = soundtable)
expect_equal(netvols$VOL_NET, rep(0, 5)) ## total net volume should be 0
# 2. missing grossMerchVolMatrix
logvolmatrix <- data.table(log_v_0 = 1:5,
log_v_1 = 5:9,
log_v_2 = c(5:7, NA, NA))
soundtable <- data.table(log_s_1 = rep(100, 5),
log_s_2 = rep(80, 5))
netvols <- netVolumeCalculator(grossVolMatrix = logvolmatrix,
netFactorMatrix = soundtable)
expect_equal(netvols$VOL_NETM, rep(0, 5)) ## total net merchantable volume should be 0
# 3. missing netFactorMatrix, default is 100
logvolmatrix <- data.table(log_v_0 = 1:5,
log_v_1 = 5:9,
log_v_2 = c(5:7, NA, NA))
# log_v_0 log_v_1 log_v_2
# 1: 1 5 5 ## sum 11
# 2: 2 6 6 ## sum 14
# 3: 3 7 7 ## sum 17
# 4: 4 8 NA ## sum 12
# 5: 5 9 NA ## sum 14
merchlogmatrix <- data.table(log_vm_1 = 11:15,
log_vm_2 = 15:19)
# log_vm_1 log_vm_2
# 1: 11 15 ## sum 26
# 2: 12 16 ## sum 28
# 3: 13 17 ## sum 30
# 4: 14 18 ## sum 32
# 5: 15 19 ## sum 34
netvols <- netVolumeCalculator(grossVolMatrix = logvolmatrix,
grossMerchVolMatrix = merchlogmatrix)
expect_equal(netvols$VOL_NET, c(11, 14, 17, 12, 14))
expect_equal(netvols$VOL_NETM, c(26, 28, 30, 32, 34))
## check the outputs along with sas compiler
##
randomsasoutputs <- data.table(CLSTR_ID = c("DME1-0015-TO1", "3471-0060-DO1",
"3233-0008-OR1", "DAR2-0075-QO1", "DLL1-0122-Q 1", "4791-0027-NO1",
"3471-0085-NO1", "0222-0132-QO1", "3233-0098-NO1", "4701-0019-QO1"),
PLOT = c("I", "I", "I", "I", "I", "E", "N", "I", "E", "N"),
TREE_NO = c("007", "190", "001", "006", "005", "004", "009", "002", "008", "008"),
LOG_V_0 = c(0.0263937121083685, 0.0558437896715244, 0.1372710526282, 0.161758575305153, 0.199839244940211,
0.177951797578219, 0.132231271911848, 0.063166631832148,
0.0944535578549054, 0.359025311630049),
LOG_V_1 = c(0.374263721199455,
0.816875171810426, 2.05134993767047, 2.54955686910342, 1.80787396175441,
2.96626538566636, 2.29546297048104, 1.01327433254549, 0.907124781656755,
5.24519234468211),
LOG_V_2 = c(0.104848023327086,
0.699368020720212, 0.672634858706612, 1.21754218393219, 0.272798981144663,
1.18126510996936, 1.22809306802828, 0.32902011036264, 0.521546199170711,
8.61426020320531),
LOG_V_3 = c(0.109452683516522,
0.336698018374717, 0.741850461283993, 0.559192046479827,
1.10872291994219, 1.66715748410779, 0.847882207671338, 0.00371100232733636,
1.16400224162801, 2.39078583203937),
LOG_V_4 = c(NA, NA, 0.379500532304309, NA, 1.11666862811339,
NA, NA, NA, NA, 1.55768349040926),
LOG_VM_1 = c(0.374263721199455, 0.816875171810426,
2.05134993767047, 2.54955686910342, 1.80787396175441, 2.96626538566636,
2.29546297048104, 1.01327433254549, 0.907124781656755, 5.24519234468211),
LOG_VM_2 = c(0.104848023327086,
0.699368020720212, 0.672634858706612, 1.21754218393219, 0.272798981144663,
1.18126510996936, 1.22809306802828, 0.321425912307692, 0.521546199170711,
8.61426020320531),
LOG_VM_3 = c(0.0987970266543662,
0.325252800027074, 0.741850461283993, 0.547939452695515,
1.10872291994219, 1.65528116925591, 0.835549050355266, NA,
1.15137606170672, 2.39078583203937),
LOG_VM_4 = c(NA, NA, 0.366825048596119, NA, 1.10931278208351,
NA, NA, NA, NA, 1.54901282282335),
LOG_S_1 = c(100, 100, 96, 100, 100, 94, 100, 100,
100, 100),
LOG_S_2 = c(100,
100, 100, 100, 100, 90, 100, 100, 100, 100),
LOG_S_3 = c(100, 100, 100, 100, 100, 100, 100,
100, 100, 100),
LOG_S_4 = c(NA,
NA, 100, NA, 100, NA, NA, NA, NA, 100),
VOL_NET = c(0.614958140151431, 1.90878500057688,
3.89506200298164, 4.48804967482059, 4.50590373589486, 5.68586023533012,
4.50366951809251, 1.40917207706761, 2.68712678031038, 18.1669471819661),
VOL_NETM = c(0.577908771180906,
1.84149599255771, 3.75060630875038, 4.31503850573113, 4.29870864492476,
5.50670923075472, 4.35910508886459, 1.33470024485318, 2.58004704253418,
17.7992512027501))
# CLSTR_ID PLOT TREE_NO LOG_V_0 LOG_V_1 LOG_V_2 LOG_V_3 LOG_V_4 LOG_VM_1
# 1: DME1-0015-TO1 I 007 0.02639371 0.3742637 0.1048480 0.109452684 NA 0.3742637
# 2: 3471-0060-DO1 I 190 0.05584379 0.8168752 0.6993680 0.336698018 NA 0.8168752
# 3: 3233-0008-OR1 I 001 0.13727105 2.0513499 0.6726349 0.741850461 0.3795005 2.0513499
# 4: DAR2-0075-QO1 I 006 0.16175858 2.5495569 1.2175422 0.559192046 NA 2.5495569
# 5: DLL1-0122-Q 1 I 005 0.19983924 1.8078740 0.2727990 1.108722920 1.1166686 1.8078740
# 6: 4791-0027-NO1 E 004 0.17795180 2.9662654 1.1812651 1.667157484 NA 2.9662654
# 7: 3471-0085-NO1 N 009 0.13223127 2.2954630 1.2280931 0.847882208 NA 2.2954630
# 8: 0222-0132-QO1 I 002 0.06316663 1.0132743 0.3290201 0.003711002 NA 1.0132743
# 9: 3233-0098-NO1 E 008 0.09445356 0.9071248 0.5215462 1.164002242 NA 0.9071248
# 10: 4701-0019-QO1 N 008 0.35902531 5.2451923 8.6142602 2.390785832 1.5576835 5.2451923
# LOG_VM_2 LOG_VM_3 LOG_VM_4 LOG_S_1 LOG_S_2 LOG_S_3 LOG_S_4 VOL_NET VOL_NETM
# 1: 0.1048480 0.09879703 NA 100 100 100 NA 0.6149581 0.5779088
# 2: 0.6993680 0.32525280 NA 100 100 100 NA 1.9087850 1.8414960
# 3: 0.6726349 0.74185046 0.366825 96 100 100 100 3.8950620 3.7506063
# 4: 1.2175422 0.54793945 NA 100 100 100 NA 4.4880497 4.3150385
# 5: 0.2727990 1.10872292 1.109313 100 100 100 100 4.5059037 4.2987086
# 6: 1.1812651 1.65528117 NA 94 90 100 NA 5.6858602 5.5067092
# 7: 1.2280931 0.83554905 NA 100 100 100 NA 4.5036695 4.3591051
# 8: 0.3214259 NA NA 100 100 100 NA 1.4091721 1.3347002
# 9: 0.5215462 1.15137606 NA 100 100 100 NA 2.6871268 2.5800470
# 10: 8.6142602 2.39078583 1.549013 100 100 100 100 18.1669472 17.7992512
netvols <- netVolumeCalculator(grossVolMatrix = randomsasoutputs[, paste("LOG_V_", 0:4, sep = ""), with = FALSE],
grossMerchVolMatrix = randomsasoutputs[, paste("LOG_VM_", 1:4, sep = ""), with = FALSE],
netFactorMatrix = randomsasoutputs[, paste("LOG_S_", 1:4, sep = ""), with = FALSE])
expect_equal(netvols$VOL_NET, randomsasoutputs$VOL_NET)
expect_equal(netvols$VOL_NETM, randomsasoutputs$VOL_NETM)
})
bcgov/BCForestGroundSample documentation built on May 25, 2019, 3:21 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
test_that("netVolumeCalculator.R: total net volume is not correctly calculated.", {
library(data.table)
library(testthat)
## check the error
# 1. number of row is right, ncol is not right
logvolmatrix <- data.table(log_v_0 = 1:5,
log_v_1 = 5:9,
log_v_2 = c(5:7, NA, NA)) ## has 5 rows and 3 columns
merchlogmatrix <- data.table(log_vm_1 = 1:5,
log_vm_2 = 5:9,
log_vm_3 = 7:11) ## has 5 rows and 3 columns
soundtable <- data.table(log_s_1 = rep(100, 5),
log_s_2 = rep(80, 5),
log_s_3 = rep(70, 5),
log_s_4 = rep(60, 5)) ## has 5 rows and 4 columns
expect_error(netVolumeCalculator(grossVolMatrix = logvolmatrix,
grossMerchVolMatrix = merchlogmatrix,
netFactorMatrix = soundtable))
# 2. number of row is wrong and number of col is right
logvolmatrix <- data.table(log_v_0 = 1:5,
log_v_1 = 5:9,
log_v_2 = c(5:7, NA, NA)) ## has 5 rows and 3 columns
merchlogmatrix <- data.table(log_vm_1 = 1:3,
log_vm_2 = 5:7) ## has 5 rows and 3 columns
soundtable <- data.table(log_s_1 = rep(100, 5),
log_s_2 = rep(80, 5)) ## has 5 rows and 4 columns
expect_error(netVolumeCalculator(grossVolMatrix = logvolmatrix,
grossMerchVolMatrix = merchlogmatrix,
netFactorMatrix = soundtable))
## check missing
# 1. missing grossVolMatrix
merchlogmatrix <- data.table(log_vm_1 = 1:5,
log_vm_2 = 5:9)
soundtable <- data.table(log_s_1 = rep(100, 5),
log_s_2 = rep(80, 5))
netvols <- netVolumeCalculator(grossMerchVolMatrix = merchlogmatrix,
netFactorMatrix = soundtable)
expect_equal(netvols$VOL_NET, rep(0, 5)) ## total net volume should be 0
# 2. missing grossMerchVolMatrix
logvolmatrix <- data.table(log_v_0 = 1:5,
log_v_1 = 5:9,
log_v_2 = c(5:7, NA, NA))
soundtable <- data.table(log_s_1 = rep(100, 5),
log_s_2 = rep(80, 5))
netvols <- netVolumeCalculator(grossVolMatrix = logvolmatrix,
netFactorMatrix = soundtable)
expect_equal(netvols$VOL_NETM, rep(0, 5)) ## total net merchantable volume should be 0
# 3. missing netFactorMatrix, default is 100
logvolmatrix <- data.table(log_v_0 = 1:5,
log_v_1 = 5:9,
log_v_2 = c(5:7, NA, NA))
# log_v_0 log_v_1 log_v_2
# 1: 1 5 5 ## sum 11
# 2: 2 6 6 ## sum 14
# 3: 3 7 7 ## sum 17
# 4: 4 8 NA ## sum 12
# 5: 5 9 NA ## sum 14
merchlogmatrix <- data.table(log_vm_1 = 11:15,
log_vm_2 = 15:19)
# log_vm_1 log_vm_2
# 1: 11 15 ## sum 26
# 2: 12 16 ## sum 28
# 3: 13 17 ## sum 30
# 4: 14 18 ## sum 32
# 5: 15 19 ## sum 34
netvols <- netVolumeCalculator(grossVolMatrix = logvolmatrix,
grossMerchVolMatrix = merchlogmatrix)
expect_equal(netvols$VOL_NET, c(11, 14, 17, 12, 14))
expect_equal(netvols$VOL_NETM, c(26, 28, 30, 32, 34))
## check the outputs along with sas compiler
##
randomsasoutputs <- data.table(CLSTR_ID = c("DME1-0015-TO1", "3471-0060-DO1",
"3233-0008-OR1", "DAR2-0075-QO1", "DLL1-0122-Q 1", "4791-0027-NO1",
"3471-0085-NO1", "0222-0132-QO1", "3233-0098-NO1", "4701-0019-QO1"),
PLOT = c("I", "I", "I", "I", "I", "E", "N", "I", "E", "N"),
TREE_NO = c("007", "190", "001", "006", "005", "004", "009", "002", "008", "008"),
LOG_V_0 = c(0.0263937121083685, 0.0558437896715244, 0.1372710526282, 0.161758575305153, 0.199839244940211,
0.177951797578219, 0.132231271911848, 0.063166631832148,
0.0944535578549054, 0.359025311630049),
LOG_V_1 = c(0.374263721199455,
0.816875171810426, 2.05134993767047, 2.54955686910342, 1.80787396175441,
2.96626538566636, 2.29546297048104, 1.01327433254549, 0.907124781656755,
5.24519234468211),
LOG_V_2 = c(0.104848023327086,
0.699368020720212, 0.672634858706612, 1.21754218393219, 0.272798981144663,
1.18126510996936, 1.22809306802828, 0.32902011036264, 0.521546199170711,
8.61426020320531),
LOG_V_3 = c(0.109452683516522,
0.336698018374717, 0.741850461283993, 0.559192046479827,
1.10872291994219, 1.66715748410779, 0.847882207671338, 0.00371100232733636,
1.16400224162801, 2.39078583203937),
LOG_V_4 = c(NA, NA, 0.379500532304309, NA, 1.11666862811339,
NA, NA, NA, NA, 1.55768349040926),
LOG_VM_1 = c(0.374263721199455, 0.816875171810426,
2.05134993767047, 2.54955686910342, 1.80787396175441, 2.96626538566636,
2.29546297048104, 1.01327433254549, 0.907124781656755, 5.24519234468211),
LOG_VM_2 = c(0.104848023327086,
0.699368020720212, 0.672634858706612, 1.21754218393219, 0.272798981144663,
1.18126510996936, 1.22809306802828, 0.321425912307692, 0.521546199170711,
8.61426020320531),
LOG_VM_3 = c(0.0987970266543662,
0.325252800027074, 0.741850461283993, 0.547939452695515,
1.10872291994219, 1.65528116925591, 0.835549050355266, NA,
1.15137606170672, 2.39078583203937),
LOG_VM_4 = c(NA, NA, 0.366825048596119, NA, 1.10931278208351,
NA, NA, NA, NA, 1.54901282282335),
LOG_S_1 = c(100, 100, 96, 100, 100, 94, 100, 100,
100, 100),
LOG_S_2 = c(100,
100, 100, 100, 100, 90, 100, 100, 100, 100),
LOG_S_3 = c(100, 100, 100, 100, 100, 100, 100,
100, 100, 100),
LOG_S_4 = c(NA,
NA, 100, NA, 100, NA, NA, NA, NA, 100),
VOL_NET = c(0.614958140151431, 1.90878500057688,
3.89506200298164, 4.48804967482059, 4.50590373589486, 5.68586023533012,
4.50366951809251, 1.40917207706761, 2.68712678031038, 18.1669471819661),
VOL_NETM = c(0.577908771180906,
1.84149599255771, 3.75060630875038, 4.31503850573113, 4.29870864492476,
5.50670923075472, 4.35910508886459, 1.33470024485318, 2.58004704253418,
17.7992512027501))
# CLSTR_ID PLOT TREE_NO LOG_V_0 LOG_V_1 LOG_V_2 LOG_V_3 LOG_V_4 LOG_VM_1
# 1: DME1-0015-TO1 I 007 0.02639371 0.3742637 0.1048480 0.109452684 NA 0.3742637
# 2: 3471-0060-DO1 I 190 0.05584379 0.8168752 0.6993680 0.336698018 NA 0.8168752
# 3: 3233-0008-OR1 I 001 0.13727105 2.0513499 0.6726349 0.741850461 0.3795005 2.0513499
# 4: DAR2-0075-QO1 I 006 0.16175858 2.5495569 1.2175422 0.559192046 NA 2.5495569
# 5: DLL1-0122-Q 1 I 005 0.19983924 1.8078740 0.2727990 1.108722920 1.1166686 1.8078740
# 6: 4791-0027-NO1 E 004 0.17795180 2.9662654 1.1812651 1.667157484 NA 2.9662654
# 7: 3471-0085-NO1 N 009 0.13223127 2.2954630 1.2280931 0.847882208 NA 2.2954630
# 8: 0222-0132-QO1 I 002 0.06316663 1.0132743 0.3290201 0.003711002 NA 1.0132743
# 9: 3233-0098-NO1 E 008 0.09445356 0.9071248 0.5215462 1.164002242 NA 0.9071248
# 10: 4701-0019-QO1 N 008 0.35902531 5.2451923 8.6142602 2.390785832 1.5576835 5.2451923
# LOG_VM_2 LOG_VM_3 LOG_VM_4 LOG_S_1 LOG_S_2 LOG_S_3 LOG_S_4 VOL_NET VOL_NETM
# 1: 0.1048480 0.09879703 NA 100 100 100 NA 0.6149581 0.5779088
# 2: 0.6993680 0.32525280 NA 100 100 100 NA 1.9087850 1.8414960
# 3: 0.6726349 0.74185046 0.366825 96 100 100 100 3.8950620 3.7506063
# 4: 1.2175422 0.54793945 NA 100 100 100 NA 4.4880497 4.3150385
# 5: 0.2727990 1.10872292 1.109313 100 100 100 100 4.5059037 4.2987086
# 6: 1.1812651 1.65528117 NA 94 90 100 NA 5.6858602 5.5067092
# 7: 1.2280931 0.83554905 NA 100 100 100 NA 4.5036695 4.3591051
# 8: 0.3214259 NA NA 100 100 100 NA 1.4091721 1.3347002
# 9: 0.5215462 1.15137606 NA 100 100 100 NA 2.6871268 2.5800470
# 10: 8.6142602 2.39078583 1.549013 100 100 100 100 18.1669472 17.7992512
netvols <- netVolumeCalculator(grossVolMatrix = randomsasoutputs[, paste("LOG_V_", 0:4, sep = ""), with = FALSE],
grossMerchVolMatrix = randomsasoutputs[, paste("LOG_VM_", 1:4, sep = ""), with = FALSE],
netFactorMatrix = randomsasoutputs[, paste("LOG_S_", 1:4, sep = ""), with = FALSE])
expect_equal(netvols$VOL_NET, randomsasoutputs$VOL_NET)
expect_equal(netvols$VOL_NETM, randomsasoutputs$VOL_NETM)
})
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.