CALAND.r error man_dead_df$Management

[sbassett]

Error in `[<-.data.frame`(`*tmp*`, man_dead_df$Management == "Afforestation" |  : 
  missing values are not allowed in subscripted assignments of data frames 
4.
stop("missing values are not allowed in subscripted assignments of data frames") 
3.
`[<-.data.frame`(`*tmp*`, man_dead_df$Management == "Afforestation" | 
    man_dead_df$Management == "Reforestation" | man_dead_df$Management == 
    "Restoration" | man_dead_df$Management == "Prescribed_burn" | 
    man_dead_df$Management == "Prescribed_burn_med_slash_util" |  ... at CALAND.r#2106
2.
`[<-`(`*tmp*`, man_dead_df$Management == "Afforestation" | man_dead_df$Management == 
    "Reforestation" | man_dead_df$Management == "Restoration" | 
    man_dead_df$Management == "Prescribed_burn" | man_dead_df$Management == 
    "Prescribed_burn_med_slash_util" | man_dead_df$Management ==  ... at CALAND.r#2106
1.
CALAND(scen_file_arg = "CONM_BAU_v01_testA_rcp85_RCP85.xls", 
    c_file_arg = "2022_01_12_input_conm_testA_rcp85_noOcean.xls", 
    indir = "2022_01_12_input_conm_testA_rcp85_noOcean", outdir = "2022_01_12_output_conm_testA_noOcean", 
    start_year = 2021, end_year = 2051, value_col_dens = 7, ADD_dens = TRUE,  ... 

[aj1s]

dead_frac_in is linearly interpolated over lines 1106 – 1109, but may contain missing value(s) preventing the new value assignments – per []https://stackoverflow.com/questions/23396279/when-trying-to-replace-values-missing-values-are-not-allowed-in-subscripted-as/23396731

[sbassett]

Totally unfounded hypothesis had during park time: These errors were common when we had two different landcat sets. I wonder if there are differences in the landcat sets again. I may have introduced some by including all the future landcat codes that exist in 2100. They are zero in the baseline year, but if the model is trying to match things to all landcats it might throw this.

[aj1s]

If so, I would think it would've thrown an error well before line 2106 ...

[sbassett]

Have reached this error running line by line.

> head(man_dead_df)
  Land_Cat_ID Region Land_Type   Ownership Management man_area man_area_sum tot_area man_area_agg_pre excess_area_pre man_area_agg
1      100002 C08001     Water         DOD       <NA>       NA           NA       NA               NA              NA           NA
2      100003 C08001     Water         FWS       <NA>       NA           NA       NA               NA              NA           NA
3      100004 C08001     Water       Local       <NA>       NA           NA       NA               NA              NA           NA
4      100006 C08001     Water     Private       <NA>       NA           NA       NA               NA              NA           NA
5      100007 C08001     Water State_Other       <NA>       NA           NA       NA               NA              NA           NA
6      100008 C08001     Water State_Trust       <NA>       NA           NA       NA               NA              NA           NA
  man_area_sum_agg_extra excess_sum_area man_area_sum_agg SoilCaccum_frac Above_harvested_frac StandDead_harvested_frac
1                     NA              NA               NA              NA                   NA                       NA
2                     NA              NA               NA              NA                   NA                       NA
3                     NA              NA               NA              NA                   NA                       NA
4                     NA              NA               NA              NA                   NA                       NA
5                     NA              NA               NA              NA                   NA                       NA
6                     NA              NA               NA              NA                   NA                       NA
  Harvested2Wood_frac Harvested2Energy_frac Harvested2SawmillDecay_frac Harvested2Slash_frac Under2Slash_frac DownDead2Slash_frac
1                  NA                    NA                          NA                   NA               NA                  NA
2                  NA                    NA                          NA                   NA               NA                  NA
3                  NA                    NA                          NA                   NA               NA                  NA
4                  NA                    NA                          NA                   NA               NA                  NA
5                  NA                    NA                          NA                   NA               NA                  NA
6                  NA                    NA                          NA                   NA               NA                  NA
  Litter2Slash_frac Slash2Energy_frac Slash2Wood_frac Slash2Burn_frac Slash2Decay_frac Under2DownDead_frac Soil2Atmos_frac
1                NA                NA              NA              NA               NA                  NA              NA
2                NA                NA              NA              NA               NA                  NA              NA
3                NA                NA              NA              NA               NA                  NA              NA
4                NA                NA              NA              NA               NA                  NA              NA
5                NA                NA              NA              NA               NA                  NA              NA
6                NA                NA              NA              NA               NA                  NA              NA
  Above2StandDead_frac Below2Atmos_frac Below2Soil_frac VegCuptake_frac DeadCaccum_frac high_sev_frac med_sev_frac low_sev_frac
1                   NA               NA              NA              NA              NA            NA           NA           NA
2                   NA               NA              NA              NA              NA            NA           NA           NA
3                   NA               NA              NA              NA              NA            NA           NA           NA
4                   NA               NA              NA              NA              NA            NA           NA           NA
5                   NA               NA              NA              NA              NA            NA           NA           NA
6                   NA               NA              NA              NA              NA            NA           NA           NA
  start_urban_forest_fraction current_urban_forest_fraction deadc_frac_in.2021_frac deadc_frac_in.2021_frac.1 adjDeadCfrac.2021_frac
1                          NA                            NA                       0                         0                     NA
2                          NA                            NA                       0                         0                     NA
3                          NA                            NA                       0                         0                     NA
4                          NA                            NA                       0                         0                     NA
5                          NA                            NA                       0                         0                     NA
6                          NA                            NA                       0                         0                     NA
  adjDeadCfrac.2021_frac.1 deadcfracXarea.2021_frac deadcfracXarea.2021_frac.1
1                       NA                       NA                         NA
2                       NA                       NA                         NA
3                       NA                       NA                         NA
4                       NA                       NA                         NA
5                       NA                       NA                         NA
6                       NA                       NA                         NA

> head(man_dead_df$Management)
[1] NA NA NA NA NA NA

> head(man_dead_df$deadcfracXarea)
  2021_frac 2021_frac.1
1        NA          NA
2        NA          NA
3        NA          NA
4        NA          NA
5        NA          NA
6        NA          NA

[sbassett]

trying to replace NAs with 0.0 throw the error. Limited the script to only replace !is.na values with 0.0. Relied on these to get syntax correct: https://stackoverflow.com/questions/51027983/r-error-from-nas-to-0-duplicate-subscripts-for-column-in-data-frame https://stackoverflow.com/questions/13172711/replace-na-with-0-in-a-data-frame-column https://www.statology.org/r-is-not-na/

https://www.tutorialspoint.com/how-to-deal-with-error-undefined-columns-selected-when-subsetting-data-frame-in-r