Bug with the function "mosaic_analyze" when the argument "segment_individuals = TRUE" #16

HelcioDuartePereira · 2024-06-11T02:27:09Z

Hi Tiago

I am using the pliman (latest version) to extract some features about the canopy of citrus plants (area, diameter, etc).
I imported the mosaic and shapefile (made in QGIS) into R without any problem. They are in the same CRS (coordinate reference system).

My mosaic (object orto) looks like this:

print(orto) # 3 camadas: R, G e B
class : SpatRaster
dimensions : 8317, 5725, 3 (nrow, ncol, nlyr)
resolution : 0.01999664, 0.01999765 (x, y)
extent : 252903.9, 253018.4, 7515062, 7515229 (xmin, xmax, ymin, ymax)
coord. ref. : WGS 84 / UTM zone 23S (EPSG:32723)
source : Ortomosaico-citrus-abril-2024.tif
names : red, green, blue

My shapefile (object parcelas) looks like this:

Simple feature collection with 373 features and 3 fields
Geometry type: POLYGON
Dimension: XY
Bounding box: xmin: 252926.2 ymin: 7515102 xmax: 252989.8 ymax: 7515189
Projected CRS: WGS 84 / UTM zone 23S
First 10 features:
fid id Genotype geometry
1 1 1 H4 POLYGON ((252926.7 7515189,...
2 2 2 H6 POLYGON ((252926.4 7515186,...
3 3 3 H10 POLYGON ((252926.4 7515183,...
4 4 4 H39 POLYGON ((252926.9 7515181,...
5 5 5 V3 POLYGON ((252927.1 7515178,...
6 6 6 V6 POLYGON ((252926.8 7515176,...

I am trying to analyze the mosaic with the code below:

mosaic_analyze(mosaic = orto,
r = 1, g = 2, b = 3,
shapefile = parcelas,
include_if = "centroid",
segment_individuals = TRUE,
segment_index = "NGRDI", threshold = 0.08, invert = FALSE,
watershed = TRUE)

However, the following error always happens:

Extracting data from block 1
Error in dplyr::select():
! Can't subset columns that don't exist.
✖ Column block doesn't exist.
Run rlang::last_trace() to see where the error occurred.

If I click on the last message about the error the following is shown:

rlang::last_trace()
<error/vctrs_error_subscript_oob>
Error in dplyr::select():
! Can't subset columns that don't exist.
✖ Column block doesn't exist.

Backtrace:
▆

└─pliman::mosaic_analyze(...)
├─dplyr::select(...)
└─dplyr:::select.data.frame(...)
Run rlang::last_trace(drop = FALSE) to see 18 hidden frames.

rlang::last_trace(drop = FALSE)
<error/vctrs_error_subscript_oob>
Error in dplyr::select():
! Can't subset columns that don't exist.
✖ Column block doesn't exist.

Backtrace:
▆

├─pliman::mosaic_analyze(...)
│ ├─dplyr::select(...)
│ └─dplyr:::select.data.frame(...)
│ └─tidyselect::eval_select(expr(c(...)), data = .data, error_call = error_call)
│ └─tidyselect:::eval_select_impl(...)
│ ├─tidyselect:::with_subscript_errors(...)
│ │ └─rlang::try_fetch(...)
│ │ └─base::withCallingHandlers(...)
│ └─tidyselect:::vars_select_eval(...)
│ └─tidyselect:::walk_data_tree(expr, data_mask, context_mask)
│ └─tidyselect:::eval_c(expr, data_mask, context_mask)
│ └─tidyselect:::reduce_sels(node, data_mask, context_mask, init = init)
│ └─tidyselect:::walk_data_tree(new, data_mask, context_mask)
│ └─tidyselect:::as_indices_sel_impl(...)
│ └─tidyselect:::as_indices_impl(...)
│ └─tidyselect:::chr_as_locations(x, vars, call = call, arg = arg)
│ └─vctrs::vec_as_location(...)
└─vctrs (local) <fn>()
└─vctrs:::stop_subscript_oob(...)
```
└─vctrs:::stop_subscript(...)
```
```
  └─rlang::abort(...)
```

I was thinking that the problem shoud be my shapefile. So, I did a small example of shapefile (on the same mosaic) in plimanshiny and tried to run the same code with the "new" shapefile, but the error was shown again.

Helcio

The text was updated successfully, but these errors were encountered:

TiagoOlivoto · 2024-06-11T12:31:12Z

Hi @HelcioDuartePereira !
This is due the fact that "block" and "plot_id" are mandatory columns (I should include a treatment error for this!). Are you sure your are using the development version of pliman and plimanshiny?

I made a small example, creating the shapefile with plimanshiny and saving it as "lettuce_shp.rds" (why not perform all analyses within plimanshiny?)

library(pliman)
#> |==========================================================|
#> | Tools for Plant Image Analysis (pliman 2.1.0)            |
#> | Author: Tiago Olivoto                                    |
#> | Type `citation('pliman')` to know how to cite pliman     |
#> | Visit 'http://bit.ly/pkg_pliman' for a complete tutorial |
#> |==========================================================|

setwd("D:/testes")
ras <- mosaic_input("05-03-2024_lett.tif")
#> class       : SpatRaster 
#> dimensions  : 3445, 1747, 3  (nrow, ncol, nlyr)
#> resolution  : 0.01, 0.01  (x, y)
#> extent      : 236479.4, 236496.8, 7929163, 7929197  (xmin, xmax, ymin, ymax)
#> coord. ref. : WGS 84 / UTM zone 23S (EPSG:32723) 
#> source      : 05-03-2024_lett.tif 
#> colors RGB  : 1, 2, 3 
#> names       : lettuce_1, lettuce_2, lettuce_3 
#> min values  :         1,         0,         0 
#> max values  :       255,       255,       255

shapefile <- shapefile_input("lettuce_shp.rds")
#>  class       : SpatVector 
#>  geometry    : polygons 
#>  dimensions  : 72, 3  (geometries, attributes)
#>  extent      : 236483.8, 236491.7, 7929167, 7929194  (xmin, xmax, ymin, ymax)
#>  coord. ref. : WGS 84 / UTM zone 23S (EPSG:32723) 
#>  names       : unique_id block plot_id
#>  type        :     <int> <chr>   <chr>
#>  values      :         1   B01   P0001
#>                        2   B01   P0008
#>                        3   B01   P0009

mosaic_analyze(ras,
               shapefile = shapefile,
               plot_index = "GLI",
               segment_index = "GLI",
               segment_individuals = TRUE)
#>  
#> Building the mosaic...
#> Using downsample = 2 so that the number of rendered pixels approximates the `max_pixels`
#>  
#> Computing the indexes...
#>  
#> Extracting data from block 1 
#>  
#> Preparing to plot...
#>  Done!
#> $result_plot
#> Simple feature collection with 72 features and 4 fields
#> Geometry type: POLYGON
#> Dimension:     XY
#> Bounding box:  xmin: 236483.8 ymin: 7929167 xmax: 236491.7 ymax: 7929194
#> Projected CRS: WGS 84 / UTM zone 23S
#> First 10 features:
#>    unique_id block plot_id     mean.GLI                       geometry
#> 1          1   B01   P0001 -0.062621370 POLYGON ((236483.8 7929194,...
#> 2          2   B01   P0008 -0.030286949 POLYGON ((236483.9 7929192,...
#> 3          3   B01   P0009 -0.005732136 POLYGON ((236484 7929191, 2...
#> 4          4   B01   P0016 -0.021559661 POLYGON ((236484.1 7929189,...
#> 5          5   B01   P0017 -0.068187401 POLYGON ((236484.2 7929188,...
#> 6          6   B01   P0024 -0.045827858 POLYGON ((236484.3 7929186,...
#> 7          7   B01   P0025 -0.030057969 POLYGON ((236484.4 7929185,...
#> 8          8   B01   P0032 -0.027310185 POLYGON ((236484.5 7929183,...
#> 9          9   B01   P0033 -0.071393937 POLYGON ((236484.6 7929182,...
#> 10        10   B01   P0040 -0.036239289 POLYGON ((236484.7 7929180,...
#> 
#> $result_plot_summ
#> Simple feature collection with 72 features and 15 fields
#> Geometry type: POLYGON
#> Dimension:     XY
#> Bounding box:  xmin: 236483.8 ymin: 7929167 xmax: 236491.7 ymax: 7929194
#> Projected CRS: WGS 84 / UTM zone 23S
#> # A tibble: 72 × 16
#>    block plot_id     n area_sum   area coverage perimeter length width diam_min
#>    <chr> <chr>   <dbl>    <dbl>  <dbl>    <dbl>     <dbl>  <dbl> <dbl>    <dbl>
#>  1 B01   P0001      15    0.291 0.0194   0.129      0.554  0.172 0.159    0.128
#>  2 B01   P0002      16    0.410 0.0256   0.181      0.635  0.198 0.185    0.152
#>  3 B01   P0003      16    0.573 0.0358   0.253      0.773  0.235 0.220    0.176
#>  4 B01   P0004      16    0.497 0.0311   0.219      0.719  0.221 0.203    0.160
#>  5 B01   P0005      16    0.217 0.0136   0.0958     0.463  0.144 0.135    0.107
#>  6 B01   P0006      16    0.724 0.0453   0.320      0.864  0.260 0.241    0.204
#>  7 B01   P0007      16    0.398 0.0249   0.176      0.622  0.195 0.179    0.147
#>  8 B01   P0008      16    0.534 0.0334   0.236      0.759  0.228 0.205    0.168
#>  9 B01   P0009      16    0.659 0.0412   0.291      0.852  0.259 0.227    0.180
#> 10 B01   P0010      16    0.651 0.0407   0.287      0.823  0.250 0.230    0.194
#> # ℹ 62 more rows
#> # ℹ 6 more variables: diam_mean <dbl>, diam_max <dbl>, unique_id <dbl>,
#> #   mean.GLI <dbl>, plot_area [m^2], geometry <POLYGON [m]>
#> 
#> $result_indiv
#> Simple feature collection with 1139 features and 14 fields
#> Geometry type: POLYGON
#> Dimension:     XY
#> Bounding box:  xmin: 236484.4 ymin: 7929167 xmax: 236491.3 ymax: 7929194
#> Projected CRS: WGS 84 / UTM zone 23S
#> First 10 features:
#>    block plot_id individual        x       y       area perimeter    length
#> 1    B01   P0001        649 236484.9 7929193 0.02978516 0.6994113 0.2159660
#> 2    B01   P0001        663 236484.9 7929193 0.02734375 0.6676955 0.2005139
#> 3    B01   P0001        745 236484.9 7929193 0.02563477 0.6569848 0.1921283
#> 4    B01   P0001        867 236485.1 7929193 0.02197266 0.6028427 0.1801924
#> 5    B01   P0001        872 236485.1 7929193 0.02221680 0.5828427 0.1868534
#> 6    B01   P0001        878 236484.7 7929193 0.02404785 0.6287006 0.1878888
#> 7    B01   P0001        923 236484.7 7929193 0.02221680 0.6028427 0.1843726
#> 8    B01   P0001        971 236485.0 7929193 0.02062988 0.5828427 0.1920252
#> 9    B01   P0001        973 236484.6 7929193 0.01867676 0.5428427 0.1699673
#> 10   B01   P0001        985 236484.5 7929193 0.01574707 0.4945584 0.1555050
#>        width  diam_min diam_mean  diam_max unique_id  mean.GLI
#> 1  0.1989128 0.1630066 0.1963783 0.2263625         1 0.1866175
#> 2  0.1999823 0.1675258 0.1905091 0.2240183         1 0.1895649
#> 3  0.1915655 0.1563362 0.1812418 0.2071473         1 0.1786323
#> 4  0.1614369 0.1383754 0.1680798 0.2033878         1 0.1853317
#> 5  0.1697465 0.1500752 0.1689604 0.1969100         1 0.1869786
#> 6  0.1920182 0.1404371 0.1741295 0.2026813         1 0.1787455
#> 7  0.1691803 0.1228457 0.1687339 0.1982483         1 0.1950610
#> 8  0.1573873 0.1266327 0.1635710 0.2024084         1 0.1650223
#> 9  0.1501876 0.1231384 0.1528330 0.1851201         1 0.1679245
#> 10 0.1413682 0.1203744 0.1429408 0.1714961         1 0.1798203
#>                          geometry
#> 1  POLYGON ((236484.8 7929193,...
#> 2  POLYGON ((236484.9 7929193,...
#> 3  POLYGON ((236484.9 7929193,...
#> 4  POLYGON ((236485 7929193, 2...
#> 5  POLYGON ((236485 7929193, 2...
#> 6  POLYGON ((236484.7 7929193,...
#> 7  POLYGON ((236484.7 7929193,...
#> 8  POLYGON ((236485 7929193, 2...
#> 9  POLYGON ((236484.6 7929193,...
#> 10 POLYGON ((236484.5 7929193,...
#> 
#> $result_individ_map
#> NULL
#> 
#> $map_plot
#> 
#> $map_indiv
#> 
#> $shapefile
#> $shapefile$`1`
#> Simple feature collection with 72 features and 3 fields
#> Geometry type: POLYGON
#> Dimension:     XY
#> Bounding box:  xmin: 236483.8 ymin: 7929167 xmax: 236491.7 ymax: 7929194
#> Projected CRS: WGS 84 / UTM zone 23S
#> First 10 features:
#>    unique_id block plot_id                       geometry
#> 1          1   B01   P0001 POLYGON ((236483.8 7929194,...
#> 2          2   B01   P0008 POLYGON ((236483.9 7929192,...
#> 3          3   B01   P0009 POLYGON ((236484 7929191, 2...
#> 4          4   B01   P0016 POLYGON ((236484.1 7929189,...
#> 5          5   B01   P0017 POLYGON ((236484.2 7929188,...
#> 6          6   B01   P0024 POLYGON ((236484.3 7929186,...
#> 7          7   B01   P0025 POLYGON ((236484.4 7929185,...
#> 8          8   B01   P0032 POLYGON ((236484.5 7929183,...
#> 9          9   B01   P0033 POLYGON ((236484.6 7929182,...
#> 10        10   B01   P0040 POLYGON ((236484.7 7929180,...

^{Created on 2024-06-11 with reprex v2.1.0}

Hope it helps!

HelcioDuartePereira · 2024-06-14T23:58:18Z

Hi @TiagoOlivoto

Thanks a lot for your help!
Now, after adjusting the columns of the shapefile, all the code runs right.

I am using the pliman package frequently, but the app plimanshiny I started these days.
Certainly I will use it more and more.

In this work that I reported the bug, I had already made all the shapefile (373 irregular plots) in QGIS and I would like to take advantage of the work already done.

Thanks.
Helcio

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Bug with the function "mosaic_analyze" when the argument "segment_individuals = TRUE" #16

Bug with the function "mosaic_analyze" when the argument "segment_individuals = TRUE" #16

HelcioDuartePereira commented Jun 11, 2024

TiagoOlivoto commented Jun 11, 2024

HelcioDuartePereira commented Jun 14, 2024

Bug with the function "mosaic_analyze" when the argument "segment_individuals = TRUE" #16

Bug with the function "mosaic_analyze" when the argument "segment_individuals = TRUE" #16

Comments

HelcioDuartePereira commented Jun 11, 2024

TiagoOlivoto commented Jun 11, 2024

HelcioDuartePereira commented Jun 14, 2024