-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy path0_0_Combine_BGC_SUs.Rmd
381 lines (332 loc) · 18.9 KB
/
0_0_Combine_BGC_SUs.Rmd
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
---
title: "Combine BGC SUs into single SU"
author: "Will MacKenzie"
date: "13/09/2021"
output: html_document
---
```{r setup, include=FALSE}
require(data.table)
require(tidyverse)
require(dplyr)
require(data.tree)
source("./_functions/_TreetoTable.R")
source("./_functions/_TabletoTree.R")
```
#### Import becdb
```{r set folders, include=FALSE}
require(DBI) #loads odbc as well
becdb <- dbConnect(odbc::odbc(), .connection_string = "Driver={Microsoft Access Driver (*.mdb, *.accdb)}; DBQ=D:/OneDrive - Government of BC/BECdb_Working/BECdb_ver13_2024.accdb;")
BGCs <- dbReadTable(becdb, "tblBGC_Units_v12") %>% select(BGC_Label, BGC_NoSpace, BGC_Zone)
SiteSeries<- dbReadTable(becdb, "tblBEC_SiteSeries_v12_unique") %>% filter(Status == "Current") %>% select(BGC_NoSpace, SS_NoSpace, SS_Label)
dbDisconnect(becdb)
BGCs_noSS <- anti_join(BGCs , SiteSeries)
# becdb <- dbConnect(odbc::odbc(), .connection_string = "Driver={Microsoft Access Driver (*.mdb, *.accdb)}; DBQ=D:/BECdb_Working/BECdb_ver12_2021_reduced.accdb;")
# dbWriteTable(becdb, "BGCs_NoSS", BGCs_noSS, overwrite = TRUE, batch_rows = 1)
# dbDisconnect(becdb)
```
#### Import all BECMaster tables in /raw_data folder
```{r set folders, include=FALSE}
require(DBI) #loads odbc as well
becmaster <- dbConnect(odbc::odbc(), .connection_string = "Driver={Microsoft Access Driver (*.mdb, *.accdb)}; DBQ=D:/BECMaster/BECMaster_fixing.accdb;")
plot.env <- dbReadTable(becmaster, "BECMaster_fixing_Env") %>% mutate(Longitude = ifelse(Longitude<0, Longitude, 0-Longitude))
# ADMIN<- dbReadTable(becmaster, "BECMaster_fixing_Admin")
# VEG <- dbReadTable(becmaster, "BECMaster_fixing_Veg")
env.fields <- colnames(plot.env)
odbc::odbcListColumns(becmaster, table = "BECMaster_fixing_ENV")
dbDisconnect(becmaster)
```
### Combine all current SU tables into a single AllBGC SU table
CaribooNew
CassiarNew
Coastnew
ColumbiaNew
KB
OK
Skeena
Boreal
Omineca
```{r combine all current and working SU in allBGC}
require(DBI) #loads odbc as well
buildSU <- function(db){
correlation <- dbConnect(odbc::odbc(), .connection_string = paste0("Driver={Microsoft Access Driver (*.mdb, *.accdb)}; DBQ=",db , ";"))
all_su <- lapply(setNames(nm = (dbListTables(correlation)%>% str_subset("_SU"))), dbReadTable, conn = correlation)
dbDisconnect(correlation)
SU <- do.call(rbind.data.frame, all_su)
SU <- SU %>% mutate(bgc = substr(SiteUnit,1,9)) %>% drop_na() %>% distinct(PlotNumber, .keep_all = TRUE) %>%
filter(!grepl('poor|low|[$]|add|nudum|_[[:alpha:]]|X|omit|unplaced', SiteUnit)) %>%
arrange(desc(PlotNumber))
SU2 <- SU %>% dplyr::select(PlotNumber, SiteUnit)
return(SU)
}
CariboonewSU <- buildSU(db = "D:/BC_Correlation2_Vpro_2023/Cariboo_SUs.accdb")
CassiarnewSU <- buildSU(db = "D:/BC_Correlation2_Vpro_2023/Cassiar_SUs.accdb")
CoastnewSU <- buildSU(db = "D:/BC_Correlation2_Vpro_2023/CoastGuide_Forested.accdb")
ColumbianewSU <- buildSU(db = "D:/BC_Correlation2_Vpro_2023/Columbia_FG_draft.accdb")
KBSU <- buildSU(db = "D:/BC_Correlation2_Vpro_2023/published_sorts/KootenayBoundary_Sorts.accdb")
OKSU <- buildSU(db = "D:/BC_Correlation2_Vpro_2023/published_sorts/ThompsonOK_Sorts.accdb")
SkeenaSU <- buildSU(db = "D:/BC_Correlation2_Vpro_2023/published_sorts/Skeena_LMH26_Sorts.accdb")
BorealSU <- buildSU(db = "D:/BC_Correlation2_Vpro_2023/published_sorts/LMH65_Boreal_Sorts.accdb")
OminecaSU <- buildSU(db = "D:/BC_Correlation2_Vpro_2023/published_sorts/OminecaPeace_SU_Tables.accdb")
AllBGC_SU <- rbind(CariboonewSU, CassiarnewSU, CoastnewSU, KBSU, OKSU, SkeenaSU, BorealSU, OminecaSU)
##need to build a check for duplicates in here
AllBGC_SU <- AllBGC_SU %>% distinct(PlotNumber, .keep_all = TRUE) %>% arrange(desc(PlotNumber))
master_su <- dbConnect(odbc::odbc(), .connection_string = "Driver={Microsoft Access Driver (*.mdb, *.accdb)};
DBQ=D:/BC_Correlation2_Vpro_2023/All_BC_Correlation.accdb;")
dbWriteTable(master_su, "All_BGC12DEC2024_SU", AllBGC_SU, overwrite = TRUE, batch_rows = 1, row.names = FALSE)
dbDisconnect(master_su)
```
### New Columbia Guide
```{r}
correlation <- dbConnect(odbc::odbc(), .connection_string = "Driver={Microsoft Access Driver (*.mdb, *.accdb)};
DBQ=D:/BC_Correlation2_Vpro_2023/Columbia_FG_draft.accdb;")
all_su <- lapply(setNames(nm = (dbListTables(correlation)%>% str_subset("_SU"))), dbReadTable, conn = correlation)
dbDisconnect(correlation)
SU <- do.call(rbind.data.frame, all_su)
SU <- SU %>% mutate(bgc = substr(SiteUnit,1,9)) %>% drop_na() %>% distinct(PlotNumber, .keep_all = TRUE) %>%
arrange(desc(PlotNumber))
ss.unique <- SU %>% select(SiteUnit) %>% distinct
SU2 <- SU %>% dplyr::select(PlotNumber, SiteUnit)
master_su <- dbConnect(odbc::odbc(), .connection_string = "Driver={Microsoft Access Driver (*.mdb, *.accdb)};
DBQ=D:/BC_Correlation2_Vpro_2023/Columbia_FG_draft.accdb;")
dbWriteTable(master_su, "All_Columbia_FG_SU", SU2, overwrite = TRUE, batch_rows = 1, row.names = FALSE)
dbDisconnect(master_su)
```
## Import SU table and BECdb for current BGC units and site series. Look for missing units. Create complete SU
###COAST
```{r import SU tables and look for errors}
require(DBI) #loads odbc as well
correlation <- dbConnect(odbc::odbc(), .connection_string = "Driver={Microsoft Access Driver (*.mdb, *.accdb)};
DBQ=D:/BC_Correlation2_Vpro_2023/CoastGuide_Forested.accdb;")
all_su <- lapply(setNames(nm = (dbListTables(correlation)%>% str_subset("_SU"))), dbReadTable, conn = correlation)
dbDisconnect(correlation)
SU <- do.call(rbind.data.frame, all_su)
SU <- SU %>% mutate(bgc = substr(SiteUnit,1,9)) %>% drop_na() %>% distinct(PlotNumber, .keep_all = TRUE) %>%
arrange(desc(PlotNumber))
ss.unique <- SU %>% select(SiteUnit) %>% distinct
SU2 <- SU %>% dplyr::select(PlotNumber, SiteUnit)
## *** The field length of plotnumber is changed to 255 in the exported database table. This causes a fail in veg summary reporting from the hierarchy. need to change the Plot Number field length back to 7 **************
master_su <- dbConnect(odbc::odbc(), .connection_string = "Driver={Microsoft Access Driver (*.mdb, *.accdb)};
DBQ=D:/BC_Correlation2_Vpro_2023/CoastGuide_Hierarchy.accdb;")
dbWriteTable(master_su, "All_Coast_Forest_2024v8_SU", SU2, overwrite = TRUE, batch_rows = 1, row.names = FALSE)
dbDisconnect(master_su)
#%>% mutate(PlotNumber = paste0("'",PlotNumber))
#fwrite(SU, "./clean_tabs/CoastGuide_All_BGC_Forest_SU.csv")
###remove phases and seral units
SU_siteseries <- SU %>%
filter(!str_detect(SiteUnit, '[$]'))
##phases = c("a", "b", "c")
SU_siteseries$SiteUnit <- str_replace(SU_siteseries$SiteUnit, "[abc]$", "")
fwrite(SU_siteseries, "./clean_tabs/CoastGuide_All_BGC_Forest_SS.csv")
SU_coast <- SU_siteseries
###Check that there is plot data for all
missingplots <- anti_join(SU_coast, plot.env)
plots <- right_join(SU_coast, plot.env)
### Check for duplicate plot usage
usemorethanone <- SU_coast %>% dplyr::group_by(PlotNumber) %>% dplyr::mutate(dups = n()) %>% filter(dups >1) %>% ungroup() %>% arrange(PlotNumber)
fwrite(usemorethanone, "./review_outputs/Coast_Plots_Used_Morethan_Once.csv")
###Summaries by BGC and by SS
plots_bgc <- SU_coast %>% group_by(bgc) %>% dplyr::summarise(plots = n())
plots_SS <- SU_coast %>% group_by(SiteUnit) %>% dplyr::summarise(plots = n())
SS_count <- length(unique(SU_coast$SiteUnit))
siteunits_toofew <- plots_SS %>% filter(plots <5) #%>% dplyr::select(- PlotNumber) %>% distinct
fwrite(siteunits_toofew, "./review_outputs/Coast_SiteUnits_w_lessthan5plots.csv")
all_zonals <- SU2 %>% filter(str_detect(SiteUnit, "101|/01"))
zonal_su <- dbConnect(odbc::odbc(), .connection_string = "Driver={Microsoft Access Driver (*.mdb, *.accdb)};
DBQ=D:/BC_Correlation2_Vpro_2023/CoastGuide_Hierarchy.accdb;")
dbWriteTable(zonal_su, "Coast_Zonals_SU", all_zonals, overwrite = TRUE, batch_rows = 1, row.names = FALSE)
dbDisconnect(zonal_su)
```
###SOUTHERN INTERIOR Forested
```{r import SU tables and look for errors}
require(DBI) #loads odbc as well
correlation <- dbConnect(odbc::odbc(), .connection_string = "Driver={Microsoft Access Driver (*.mdb, *.accdb)};
DBQ=D:/BC_Correlation2_Vpro_2023/SIFR_LMH_SU.accdb;")
all_su <- lapply(setNames(nm = (dbListTables(correlation)%>% str_subset("_SU"))), dbReadTable, conn = correlation)
dbDisconnect(correlation)
SU <- do.call(rbind.data.frame, all_su)
SU <- SU %>% mutate(bgc = substr(SiteUnit,1,9)) %>% drop_na() %>% distinct(PlotNumber, .keep_all = TRUE) %>%
arrange(desc(PlotNumber))
SU2 <- SU %>% dplyr::select(PlotNumber, SiteUnit)
require(DBI) #loads odbc as well
correlation <- dbConnect(odbc::odbc(), .connection_string = "Driver={Microsoft Access Driver (*.mdb, *.accdb)};
DBQ=D:/BC_Correlation2_Vpro_2023/Columbia_FG_draft.accdb;")
all_su <- lapply(setNames(nm = (dbListTables(correlation)%>% str_subset("_SU"))), dbReadTable, conn = correlation)
dbDisconnect(correlation)
SU_draft <- do.call(rbind.data.frame, all_su)
SU_draft <- SU_draft %>% mutate(bgc = substr(SiteUnit,1,9)) %>% drop_na() %>% distinct(PlotNumber, .keep_all = TRUE) %>%
arrange(desc(PlotNumber))
SU_draft2 <- SU_draft %>% dplyr::select(PlotNumber, SiteUnit)
SU <- rbind(SU,SU_draft) %>% distinct(PlotNumber, .keep_all = TRUE) %>% arrange(desc(PlotNumber))
#%>% mutate(PlotNumber = paste0("'",PlotNumber))
#fwrite(SU, "./clean_tabs/CoastGuide_All_BGC_Forest_SU.csv")
###remove phases and seral units
SU_siteseries <- SU %>%
filter(!str_detect(SiteUnit, '[$]'))%>% filter(!str_detect(SiteUnit, "/W|/R|/G|/F|/A|/V")) %>% filter(!str_detect(SiteUnit, fixed("(G")))
phases = c("a", "b", "c")
SU_siteseries$SiteUnit <- str_replace(SU_siteseries$SiteUnit, "a$|b$", "")
SU_siteseries2 <- SU_siteseries %>% dplyr::select(-bgc)
fwrite(SU_siteseries, "./clean_tabs/SIFR_Guide_All_BGC_Forest_SS.csv")
SU_zonals <- SU_siteseries2 %>% filter(str_detect(SiteUnit, "101|/01"))
###write combined SU to database
master_su <- dbConnect(odbc::odbc(), .connection_string = "Driver={Microsoft Access Driver (*.mdb, *.accdb)};
DBQ=D:/BC_Correlation2_Vpro_2023/SIFR_Hierarchy.accdb;")
dbWriteTable(master_su, "All_SIFR_Forest_SU", SU_siteseries2, overwrite = TRUE, batch_rows = 1)
dbWriteTable(master_su, "All_SIFR_Zonals_SU", SU_zonals, overwrite = TRUE, batch_rows = 1)
dbDisconnect(master_su)
SU_SIFR <- SU_siteseries
###Check that there is plot data for all
missingplots <- anti_join(SU_SIFR, plot.env)
plots <- right_join(SU_SIFR, plot.env)
### Check for duplicate plot usage
usemorethanone <- SU_SIFR %>% dplyr::group_by(PlotNumber) %>% dplyr::mutate(dups = n()) %>% filter(dups >1) %>% ungroup() %>% arrange(PlotNumber)
fwrite(usemorethanone, "./outputs/SIFR_Plots_Used_Morethan_Once.csv")
###Summaries by BGC and by SS
plots_bgc <- SU_SIFR %>% group_by(bgc) %>% dplyr::summarise(plots = n())
plots_SS <- SU_SIFR %>% group_by(SiteUnit) %>% dplyr::summarise(plots = n())
SS_count <- length(unique(SU_SIFR$SiteUnit))
siteunits_toofew <- plots_SS %>% filter(plots <5) #%>% dplyr::select(- PlotNumber) %>% distinct
fwrite(siteunits_toofew, "./outputs/SIFR_SiteUnits_w_lessthan5plots.csv")
```
###Northern INTERIOR Forested
```{r import SU tables and look for errors}
require(DBI) #loads odbc as well
correlation <- dbConnect(odbc::odbc(), .connection_string = "Driver={Microsoft Access Driver (*.mdb, *.accdb)};
DBQ=D:/BC_Correlation2_Vpro_2023/NIFR_SU_Tables.accdb;")
all_su <- lapply(setNames(nm = (dbListTables(correlation)%>% str_subset("_SU"))), dbReadTable, conn = correlation)
dbDisconnect(correlation)
SU <- do.call(rbind.data.frame, all_su)
SU <- SU %>% mutate(bgc = substr(SiteUnit,1,9)) %>% drop_na() %>% distinct(PlotNumber, .keep_all = TRUE) %>%
arrange(desc(PlotNumber))
SU2 <- SU %>% dplyr::select(PlotNumber, SiteUnit)
####Draft units
# require(DBI) #loads odbc as well
# correlation <- dbConnect(odbc::odbc(), .connection_string = "Driver={Microsoft Access Driver (*.mdb, *.accdb)};
# DBQ=D:/BC_Correlation2_Vpro_2023/Zonal_Cassiar_2022.accdb;")
# all_su <- lapply(setNames(nm = (dbListTables(correlation)%>% str_subset("_SU"))), dbReadTable, conn = correlation)
# dbDisconnect(correlation)
# SU_draft <- do.call(rbind.data.frame, all_su)
# SU_draft <- SU_draft %>% mutate(bgc = substr(SiteUnit,1,9)) %>% drop_na() %>% distinct(PlotNumber, .keep_all = TRUE) %>%
# arrange(desc(PlotNumber))
# SU_draft2 <- SU_draft %>% dplyr::select(PlotNumber, SiteUnit)
#
#
# SU <- rbind(SU,SU_draft)
#%>% mutate(PlotNumber = paste0("'",PlotNumber))
#fwrite(SU, "./clean_tabs/CoastGuide_All_BGC_Forest_SU.csv")
###remove phases and seral units
SU_siteseries <- SU %>%
filter(!str_detect(SiteUnit, '[$]'))%>% filter(!str_detect(SiteUnit, "/W|/R|/G|/F|/A|/V")) %>% filter(!str_detect(SiteUnit, fixed("(G")))
phases = c("a", "b", "c")
SU_siteseries$SiteUnit <- str_replace(SU_siteseries$SiteUnit, "a$|b$", "")
SU_siteseries2 <- SU_siteseries %>% dplyr::select(-bgc)
fwrite(SU_siteseries, "./clean_tabs/NIFR_Guide_All_BGC_Forest_SS.csv")
SU_zonals <- SU_siteseries2 %>% filter(str_detect(SiteUnit, "101|/01"))
###write combined SU to database
master_su <- dbConnect(odbc::odbc(), .connection_string = "Driver={Microsoft Access Driver (*.mdb, *.accdb)};
DBQ=D:/BC_Correlation2_Vpro_2023/NIFR_Hierarchy.accdb;")
dbWriteTable(master_su, "All_NIFR_Forest_SU", SU_siteseries2, overwrite = TRUE, batch_rows = 1)
dbWriteTable(master_su, "All_NIFR_Zonals_SU", SU_zonals, overwrite = TRUE, batch_rows = 1)
dbDisconnect(master_su)
SU_NIFR <- SU_siteseries
###Check that there is plot data for all
missingplots <- anti_join(SU_NIFR, plot.env)
plots <- right_join(SU_NIFR, plot.env)
### Check for duplicate plot usage
usemorethanone <- SU_NIFR %>% dplyr::group_by(PlotNumber) %>% dplyr::mutate(dups = n()) %>% filter(dups >1) %>% ungroup() %>% arrange(PlotNumber)
fwrite(usemorethanone, "./outputs/NIFR_Plots_Used_Morethan_Once.csv")
###Summaries by BGC and by SS
plots_bgc <- SU_NIFR %>% group_by(bgc) %>% dplyr::summarise(plots = n())
plots_SS <- SU_NIFR %>% group_by(SiteUnit) %>% dplyr::summarise(plots = n())
SS_count <- length(unique(SU_NIFR$SiteUnit))
siteunits_toofew <- plots_SS %>% filter(plots <5) #%>% dplyr::select(- PlotNumber) %>% distinct
fwrite(siteunits_toofew, "./outputs/NIFR_SiteUnits_w_lessthan5plots.csv")
```
```{r write combined SU for province}
all_SS <- rbind(SU_coast, SU_SIFR, SU_NIFR)
all_SS$bgc <- str_replace_all(all_SS$bgc, " ", "")
all_SS <- left_join(all_SS, BGCs, by = c("bgc" = "BGC_NoSpace")) %>% dplyr::select(PlotNumber, SiteUnit, bgc)
SS_notBECdb <- anti_join(all_SS, BGCs, by = c("bgc" = "BGC_NoSpace"))
BECdb_noSS <- anti_join(BGCs, all_SS, by = c("BGC_NoSpace" = "bgc"))
all_SS2 <- all_SS %>% select(PlotNumber, SiteUnit)
all_SS_dups <- all_SS2 %>% filter(duplicated(.[["PlotNumber"]])) %>% select(PlotNumber) %>% distinct
Plots_dups <- all_SS2 %>% filter(PlotNumber %in% all_SS_dups$PlotNumber)
fwrite(Plots_dups, "./outputs/PlotsUsedTwice.csv")
all_zonals <- all_SS2 %>% filter(str_detect(SiteUnit, "101|/01"))
all_su <- dbConnect(odbc::odbc(), .connection_string = "Driver={Microsoft Access Driver (*.mdb, *.accdb)};
DBQ=D:/BC_Correlation2_Vpro_2023/All_BC_Correlation.accdb;")
dbWriteTable(all_su, "All_BC_BGCs_SU", all_SS, overwrite = TRUE, batch_rows = 1, row.names = FALSE)
dbWriteTable(all_su, "All_BC_zonals_SU", all_zonals, overwrite = TRUE, batch_rows = 1, row.names = FALSE)
dbDisconnect(all_su)
```
###Drafts
```{r import SU tables and look for errors}
# require(DBI) #loads odbc as well
# correlation <- dbConnect(odbc::odbc(), .connection_string = "Driver={Microsoft Access Driver (*.mdb, *.accdb)};
# DBQ=D:/BC_Correlation2_Vpro_2023/InteriorGuides_Forested.accdb;")
# all_su <- lapply(setNames(nm = (dbListTables(correlation)%>% str_subset("_SU"))), dbReadTable, conn = correlation)
# dbDisconnect(correlation)
# SU <- do.call(rbind.data.frame, all_su)
# SU <- SU %>% mutate(bgc = substr(SiteUnit,1,9)) %>% drop_na() %>% distinct(PlotNumber, .keep_all = TRUE) %>%
# arrange(desc(PlotNumber))
# SU2 <- SU %>% dplyr::select(PlotNumber, SiteUnit)
#
#
# #%>% mutate(PlotNumber = paste0("'",PlotNumber))
# #fwrite(SU, "./clean_tabs/CoastGuide_All_BGC_Forest_SU.csv")
# ###remove phases and seral units
# SU_siteseries <- SU %>%
# filter(!str_detect(SiteUnit, '[$]'))%>% filter(!str_detect(SiteUnit, "/W|/R|/G|/F|/A|/V")) %>% filter(!str_detect(SiteUnit, fixed("(G")))
# phases = c("a", "b", "c")
# SU_siteseries$SiteUnit <- str_replace(SU_siteseries$SiteUnit, "a$|b$", "")
# SU_siteseries2 <- SU_siteseries %>% dplyr::select(-bgc)
# fwrite(SU_siteseries, "./clean_tabs/SIFR_Guide_All_BGC_Forest_SS.csv")
# ###write combined SU to database
# master_su <- dbConnect(odbc::odbc(), .connection_string = "Driver={Microsoft Access Driver (*.mdb, *.accdb)};
# DBQ=D:/BC_Correlation2_Vpro_2023/SIFR_Hierarchy.accdb;")
# dbWriteTable(master_su, "All_SIFR_Forest_SU", SU_siteseries2, overwrite = TRUE, batch_rows = 1)
# dbDisconnect(master_su)
#
# SU <- SU_siteseries
# ###Check that there is plot data for all
# missingplots <- anti_join(SU, plot.env)
# plots <- right_join(SU, plot.env)
# ### Check for duplicate plot usage
# usemorethanone <- SU %>% dplyr::group_by(PlotNumber) %>% dplyr::mutate(dups = n()) %>% filter(dups >1) %>% ungroup() %>% arrange(PlotNumber)
# fwrite(usemorethanone, "./outputs/SIFR_Plots_Used_Morethan_Once.csv")
# ###Summaries by BGC and by SS
# plots_bgc <- SU %>% group_by(bgc) %>% dplyr::summarise(plots = n())
# plots_SS <- SU %>% group_by(SiteUnit) %>% dplyr::summarise(plots = n())
# SS_count <- length(unique(SU$SiteUnit))
# siteunits_toofew <- plots_SS %>% filter(plots <5) #%>% dplyr::select(- PlotNumber) %>% distinct
#
# fwrite(siteunits_toofew, "./outputs/SIFR_SiteUnits_w_lessthan5plots.csv")
```
Site unit statistics
```{r}
###some evaluative stats for units
# temp2 <- temp[,c(1,5)]
# VegUnits <- unique(temp2)# number of plots per unit
# numspp <- ddply(temp,~Group,summarise,sppcount=length(unique(Species))) # number of species per unit
# VegUnits2 <-merge(VegUnits, numspp, by= "Group" )
# numspp2<-ddply(temp[temp$Constancy > 20,],~Group,summarise,sppcount=length(unique(Species))) # number of non-accidental species per unit
# VegUnits2 <-merge(VegUnits2, numspp2, by= "Group" )
# constspp <-ddply(temp[temp$Constancy > 59,],~Group,summarise,sppcount=length(unique(Species))) # number of constant species per unit
# VegUnits2 <-merge(VegUnits2, constspp, by= "Group" )
# colnames(VegUnits2)[3:5] <- c("TotalSpp","NonrareSpp","ConstSpp")
# VegUnits2$Poor <- ifelse(VegUnits2$NoPlots < 5 | VegUnits2$ConstSpp<5, "Poor", "OK")
# write.csv(VegUnits2, "GrasslandsUnitSpeciesTotals.csv")
```
### Compare BGCv12 and Hierarchy SU
```{r check for inclusion of classification units}
# Hierarchy <- fread("./inputs/AllForestHier.csv", stringsAsFactors = FALSE)
# colnames(Hierarchy )[1:12]=c("PlotNumber", "Region", "Class", "Order", "SubOrder", "Alliance", "SubAlliance", "Association", "SubAssociation", "Facies", "Working", "SiteUnit")
# #Create lowest working hierarchical units
# Hierarchy$SubAssociation <- ifelse(Hierarchy$SubAssociation == "",Hierarchy$Association,Hierarchy$SubAssociation) ##if SubAssoc blank, fill with Association
# Hierarchy$SubOrder <- ifelse(Hierarchy$SubOrder == "",Hierarchy$Order,Hierarchy$SubOrder)
# Hierarchy$SubAlliance <- ifelse(Hierarchy$SubAlliance == "",Hierarchy$Alliance,Hierarchy$SubAlliance)
#
# write.csv(Hierarchy, "AllForestHier_filled.csv")
#
# BGCv12inHier <- left_join(BGCv12_nplots, Hierarchy)
```
`