[GRASS-user] v.class.mlR Error
Moritz Lennert
mlennert at club.worldonline.be
Tue Jun 19 02:58:35 PDT 2018
P.S. I'm not sure that for the landscape you are working on (mainly
forest areas) OBIA is the best approach. You might want to also try a
pixel-based approach with i.smap:
#create raster training areas
v.to.rast Training_Ben5 out=training use=attr attrcol=Ecosystem
#create a subgroup with all four bands
i.group WV_Benatimofo subg=sub
in=WV_Benatimofo.1 at haarlooj_Ben_Test,WV_Benatimofo.2 at haarlooj_Ben_Test,WV_Benatimofo.3 at haarlooj_Ben_Test,WV_Benatimofo.4 at haarlooj_Ben_Test
#create signature file
i.gensigset training group=WV_Benatimofo sub=sub
#classify
i.smap group=WV_Benatimofo sub=sub sig=sig out=smap_classified
goodness=smap_goodness
Moritz
On 19/06/18 11:33, Moritz Lennert wrote:
> Hi Jamille,
>
> Testing with the data you sent me offlist (which BTW was a mapset, not a
> location. A location contains at least one mapset named PERMANENT which
> contains the projection info - I just assumed that you are working in
> UTM Zone 21N, created my own location and copied your mapset into that
> location.) and with the following command:
>
> v.class.mlR -i --overwrite
> segments_map=Segments_vector_Stats_Ben_test at haarlooj_Ben_Test
> training_map=Training_Ben5 at haarlooj_Ben_Test
> raster_segments_map=best5_myregion1_at_haarlooj_Ben_Test_rank1 at haarlooj_Ben_Test
> train_class_column=Ecosystem output_class_column=vote
> output_prob_column=prob classifiers=svmRadial,rf,C5.0 folds=5
> partitions=10 tunelength=10 weighting_metric=accuracy
> r_script_file=R-script processes=3
>
> the module runs perfectly fine for me here on GNU/Linux. Note the fact
> that the train_class_column=Ecosystem, not ecosystem. Case matters here.
>
> Could you try with the training class column in the right case ?
>
> Moritz
>
> On 18/06/18 21:51, Jamille Haarloo wrote:
>> Hello Moritz,
>>
>> It looks like I got some results, but I suspect there are still some
>> issues due to the warning messages.
>>
>> I either kept getting that a file couldn't be found or that it had
>> trouble running the R-script.
>> My actions:
>>
>> 1. I found that it was looking in "C:\Program Files\QGIS
>> 2.16.0\apps\Python27\Lib" for certain scripts but I also had another
>> location of the Python27 library "C:\Program Files\GRASS GIS
>> 7.4.0\Python27\Lib". So I tried adding the second location via the
>> black terminal because I figured it needed the GRASS
>> versions/formats (with my lack of experience I am not sure if I
>> succeeded).
>> 2. It was still failing, and I suspected this had to do with the qbwwv
>> voting method (see output). So I unchecked that option and got
>> results. I'am also sending a screenshot of the attribute table with
>> results.
>>
>> Do you have any suggestions for improvement?
>> Soon I will test with a much bigger area for a land-use planning project.
>>
>>
>> /The last 2 command outputs:/
>>
>> Running R now. Following output is R output.
>> During startup - Warning messages:
>> 1: Setting LC_CTYPE=en_US.cp1252 failed
>> 2: Setting LC_COLLATE=en_US.cp1252 failed
>> 3: Setting LC_TIME=en_US.cp1252 failed
>> 4: Setting LC_MONETARY=en_US.cp1252 failed
>> Loading required package: caret
>> Loading required package: lattice
>> Loading required package: ggplot2
>> Loading required package: foreach
>> Loading required package: iterators
>> Loading required package: parallel
>> During startup - Warning messages:
>> 1: Setting LC_CTYPE=en_US.cp1252 failed
>> 2: Setting LC_COLLATE=en_US.cp1252 failed
>> 3: Setting LC_TIME=en_US.cp1252 failed
>> 4: Setting LC_MONETARY=en_US.cp1252 failed
>> During startup - Warning messages:
>> 1: Setting LC_CTYPE=en_US.cp1252 failed
>> 2: Setting LC_COLLATE=en_US.cp1252 failed
>> 3: Setting LC_TIME=en_US.cp1252 failed
>> 4: Setting LC_MONETARY=en_US.cp1252 failed
>> Warning message:
>> In nominalTrainWorkflow(x = x, y = y, wts = weights, info = trainInfo, :
>> There were missing values in resampled performance measures.
>> Error in `$<-.data.frame`(`*tmp*`, vote_qbwwv, value = numeric(0)) :
>> replacement has 0 rows, data has 1965
>> Calls: $<- -> $<-.data.frame
>> Execution halted
>> ERROR: There was an error in the execution of the R script.
>> Please check the R output.
>> (Mon Jun 18 15:36:47 2018) Command finished (1 min 24 sec)
>> (Mon Jun 18 15:50:30 2018)
>> v.class.mlR -i --overwrite
>> segments_map=Segments_vector_Stats_Ben_test at haarlooj_Ben_Test
>> training_map=Training_Ben_Grass at haarlooj_Ben_Test
>> raster_segments_map=best5_myregion1_at_haarlooj_Ben_Test_rank1 at haarlooj_Ben_Test
>> train_class_column=ecosystem output_class_column=vote
>> output_prob_column=prob classifiers=svmRadial,rf,C5.0 folds=5
>> partitions=10 tunelength=10 weighting_metric=accuracy
>> r_script_file=C:\Users\haarlooj\Documents\CELOS\v.class.mIRR_optional_output\Ben_test_mlR-script3
>> processes=2
>> Running R now. Following output is R output.
>> During startup - Warning messages:
>> 1: Setting LC_CTYPE=en_US.cp1252 failed
>> 2: Setting LC_COLLATE=en_US.cp1252 failed
>> 3: Setting LC_TIME=en_US.cp1252 failed
>> 4: Setting LC_MONETARY=en_US.cp1252 failed
>> Loading required package: caret
>> Loading required package: lattice
>> Loading required package: ggplot2
>> Loading required package: foreach
>> Loading required package: iterators
>> Loading required package: parallel
>> During startup - Warning messages:
>> 1: Setting LC_CTYPE=en_US.cp1252 failed
>> 2: Setting LC_COLLATE=en_US.cp1252 failed
>> 3: Setting LC_TIME=en_US.cp1252 failed
>> 4: Setting LC_MONETARY=en_US.cp1252 failed
>> During startup - Warning messages:
>> 1: Setting LC_CTYPE=en_US.cp1252 failed
>> 2: Setting LC_COLLATE=en_US.cp1252 failed
>> 3: Setting LC_TIME=en_US.cp1252 failed
>> 4: Setting LC_MONETARY=en_US.cp1252 failed
>> Warning message:
>> In nominalTrainWorkflow(x = x, y = y, wts = weights, info = trainInfo, :
>> There were missing values in resampled performance measures.
>> Finished running R.
>> Loading results into attribute table
>> (Mon Jun 18 15:51:58 2018) Command finished (1 min 27 sec)
>>
>>
>> Best,
>> Jamille Haarloo
>> Department of Natural Resources and Environmental Assessment (NARENA)
>> Centre for Agricultural Research in Suriname (CELOS)
>> <http://www.celos.sr.org/>
>>
>> Prof. Dr. Ir. Jan Ruinardlaan
>> AdeKUS University campus
>> Phone: 439982
>>
>>
>> On Thu, Jun 14, 2018 at 11:02 AM, Jamille Haarloo <j.r.haarloo at gmail.com
>> <mailto:j.r.haarloo at gmail.com>> wrote:
>>
>> Hello Moritz,
>>
>> Sorry about that. I am sending the zip of the location. The output
>> at the other machine (system cannot find the file specified) was due
>> to location/ directory issues and has been resolved, but also stops
>> executing the R-script saying there were more than 50 errors. Been
>> looking for similar cases online but haven't found many.
>>
>>
>> haarlooj_Ben_Test.zip
>> <https://drive.google.com/file/d/1wQqmreMbbd3oRfoVXWIIGJOG9L63miV6/view?usp=drive_web>
>>
>>
>> On Thu, Jun 14, 2018 at 5:19 AM, Moritz Lennert
>> <mlennert at club.worldonline.be <mailto:mlennert at club.worldonline.be>>
>> wrote:
>>
>> P.S. Your vector data also does not contain any attribute
>> information as this is contained in a separate sqlite file. Just
>> another reason never to touch the contents of a GRASS database
>> directly, but only using dedicated tools. :-)
>>
>>
>> On 14/06/18 10:11, Moritz Lennert wrote:
>>
>> Hi Jamille,
>>
>> Sorry, but I've been hopping from meeting to meeting these
>> days and
>> haven't had the opportunity to look at your data.
>>
>> Actually, the form you transmit them in is very
>> inconvenient. If you
>> want to transmit GRASS data to someone, you should either
>> zip an entire
>> location directory and send that, or export the data with
>> r.pack/v.pack.
>>
>> In this form it is difficult to know which projection is
>> used and I have
>> to handcraft the data by copying the files into different
>> directories.
>>
>> So, please resend your data in a format that I can easily use.
>>
>> Best wishes,
>> Moritz
>>
>> On 11/06/18 20:55, Jamille Haarloo wrote:
>>
>> Hello Moritz,
>>
>> I managed to edit my copy of v.class.mlR with the lines
>> you sent. But I
>> am still getting errors on two different machines.
>> I am sending you the data (hope I didn't miss anything)
>> and the command
>> outputs. I think there is sth wrong with my computer,
>> but also with one
>> of the files because of the error on the other machine.
>>
>> _Computer I normally use:_
>>
>> v.class.mlR -i --overwrite
>> segments_map=Segments_vector_Stats_Ben_test at haarlooj_Ben_Test
>> training_map=Training_Ben5 at haarlooj_Ben_Test
>> raster_segments_map=best5_myregion1_at_haarlooj_Ben_Test_rank1 at haarlooj_Ben_Test
>> train_class_column=Ecosystem output_class_column=vote
>> output_prob_column=prob classifiers=svmRadial,rf,C5.0
>> folds=5
>> partitions=10 tunelength=10 weighting_modes=smv,qbwwv
>> weighting_metric=accuracy
>> Running R now. Following output is R output.
>> During startup - Warning messages:
>> 1: Setting LC_CTYPE=en_US.cp1252 failed
>> 2: Setting LC_COLLATE=en_US.cp1252 failed
>> 3: Setting LC_TIME=en_US.cp1252 failed
>> 4: Setting LC_MONETARY=en_US.cp1252 failed
>> Loading required package: caret
>> Loading required package: lattice
>> Loading required package: ggplot2
>> There were 50 or more warnings (use warnings() to see
>> the first 50)
>> There were 50 or more warnings (use warnings() to see
>> the first 50)
>> Error in `$<-.data.frame`(`*tmp*`, vote_qbwwv, value =
>> numeric(0)) :
>> replacement has 0 rows, data has 1965
>> Calls: $<- -> $<-.data.frame
>> Execution halted
>> ERROR: There was an error in the execution of the R script.
>> Please check the R output.
>>
>>
>> _The output from the other machine:_
>> (Mon Jun 11 13:27:39 2018)
>> v.class.mlR -i --overwrite
>> segments_map=Segments_vector_Stats_Ben_test at haarlooj_Ben_Test
>> training_map=Training_Ben5 at haarlooj_Ben_Test
>> raster_segments_map=best5_myregion1_at_haarlooj_Ben_Test_rank1 at haarlooj_Ben_Test
>> train_class_column=Ecosystem output_class_column=vote
>> output_prob_column=prob classifiers=svmRadial,rf,C5.0
>> folds=5
>> partitions=10 tunelength=10 weighting_metric=accuracy
>> Running R now. Following output is R output.
>> Traceback (most recent call last):
>> File
>> "C:\Users\HaarlooJ\AppData\Roaming\GRASS7\addons/scri
>> pts/v.class.mlR.py <http://v.class.mlR.py>
>> <http://v.class.mlR.py>", line 639, in <module>
>> File
>> "C:\Users\HaarlooJ\AppData\Roaming\GRASS7\addons/scri
>> pts/v.class.mlR.py <http://v.class.mlR.py>
>> <http://v.class.mlR.py>", line 576, in main
>> shutil.copy(r_commands, r_script_file)
>> File "C:\Program Files\GRASS GIS
>> 7.4.0\Python27\lib\subprocess.py", line 537, in check_call
>> retcode = call(*popenargs, **kwargs)
>> File "C:\Program Files\GRASS GIS
>> 7.4.0\Python27\lib\subprocess.py", line 524, in call
>> return Popen(*popenargs, **kwargs).wait()
>> File "C:\Program Files\GRASS GIS
>> 7.4.0\Python27\lib\subprocess.py", line 711, in __init__
>> errread, errwrite)
>> File "C:\Program Files\GRASS GIS
>> 7.4.0\Python27\lib\subprocess.py", line 948, in
>> _execute_child
>> startupinfo)
>> WindowsError: [Error 2] The system cannot find the file
>> specified
>> (Mon Jun 11 13:27:42 2018) Command finished (3 sec)
>>
>>
>> On Mon, Jun 11, 2018 at 5:47 AM, Moritz Lennert
>> <mlennert at club.worldonline.be
>> <mailto:mlennert at club.worldonline.be>
>> <mailto:mlennert at club.worldonline.be
>> <mailto:mlennert at club.worldonline.be>>> wrote:
>>
>> Hi Jamille,
>>
>> Le Fri, 8 Jun 2018 16:14:45 -0300,
>> Jamille Haarloo <j.r.haarloo at gmail.com
>> <mailto:j.r.haarloo at gmail.com>
>> <mailto:j.r.haarloo at gmail.com
>> <mailto:j.r.haarloo at gmail.com>>> a écrit :
>>
>> > Hello Moritz,
>> >
>> > This time I asked a vector to be created with
>> the stats and used this
>> > to extract training polygons in QGIS and
>> imported the training map in
>> > GRASS. I had to do some interventions regarding
>> the column names to
>> > make sure they are the same except for the class.
>> > I still get an error, and the only thing I could
>> trace is the fact
>> > that values are missing in some rows for both
>> vectors. I am not sure
>> > if I should correct this/ retry it all.
>>
>> I haven't seen this before, so yes, please try to
>> eliminate the rows
>> with missing values. How did you get the feature
>> variables and how come
>> there are missing values ?
>>
>> I don't have the time to test this right now, so I
>> prefer not to commit
>> as is, but you could try to edit your copy of
>> v.class.mlR to add the
>> four lines marked with a plus:
>>
>> r_file.write('features <- read.csv("%s",
>> sep="%s", header=TRUE,
>> row.names=1)' % (feature_vars, separator))
>> r_file.write("\n")
>> + r_file.write("features <- na.omit(features)")
>> + r_file.write("\n")
>> r_file.write('training <- read.csv("%s",
>> sep="%s", header=TRUE,
>> row.names=1)' % (training_vars, separator))
>> r_file.write("\n")
>> + r_file.write("training <- na.omit(training)")
>> + r_file.write("\n")
>>
>> This would eliminate all lines that have at least
>> one missing value.
>>
>> Another option would be for you to send me the
>> data (segments
>> and training) privately, so that I can test.
>>
>> Moritz
>>
>>
>> >
>> > This is the command output:
>> >
>> > (Fri Jun 08 15:48:28 2018)
>> >
>> > v.class.mlR -i --overwrite
>> >
>> segments_map=Segments_vector_Stats_Ben_test at haarlooj_Ben_Test
>> > training_map=Training_Ben5 at haarlooj_Ben_Test
>> >
>>
>> raster_segments_map=best5_myregion1_at_haarlooj_Ben_Test_rank1 at haarlooj_Ben_Test
>> > train_class_column=Ecosystem
>> output_class_column=vote
>> > output_prob_column=prob
>> classifiers=svmRadial,rf,C5.0 folds=5
>> > partitions=10 tunelength=10
>> weighting_modes=smv,qbwwv
>> > weighting_metric=accuracy
>> >
>>
>> classification_results=C:\Users\haarlooj\Documents\CELOS\v.class.mIRR_optional_output\Ben_test_Classifier-results
>> >
>>
>> accuracy_file=C:\Users\haarlooj\Documents\CELOS\v.class.mIRR_optional_output\Ben_test_Classifier-accuracy
>> >
>>
>> model_details=C:\Users\haarlooj\Documents\CELOS\v.class.mIRR_optional_output\Ben_test_Classifier-module-runs
>> >
>>
>> bw_plot_file=C:\Users\haarlooj\Documents\CELOS\v.class.mIRR_optional_output\Ben_test_Classifier-performance
>> >
>>
>> r_script_file=C:\Users\haarlooj\Documents\CELOS\v.class.mIRR_optional_output\Ben_test_R_script
>> > processes=3 Running R now. Following output is
>> R output.
>> > During startup - Warning messages:
>> > 1: Setting LC_CTYPE=en_US.cp1252 failed
>> > 2: Setting LC_COLLATE=en_US.cp1252 failed
>> > 3: Setting LC_TIME=en_US.cp1252 failed
>> > 4: Setting LC_MONETARY=en_US.cp1252 failed
>> > Loading required package: caret
>> > Loading required package: lattice
>> > Loading required package: ggplot2
>> > Loading required package: foreach
>> > Loading required package: iterators
>> > Loading required package: parallel
>> > During startup - Warning messages:
>> > 1: Setting LC_CTYPE=en_US.cp1252 failed
>> > 2: Setting LC_COLLATE=en_US.cp1252 failed
>> > 3: Setting LC_TIME=en_US.cp1252 failed
>> > 4: Setting LC_MONETARY=en_US.cp1252 failed
>> > During startup - Warning messages:
>> > 1: Setting LC_CTYPE=en_US.cp1252 failed
>> > 2: Setting LC_COLLATE=en_US.cp1252 failed
>> > 3: Setting LC_TIME=en_US.cp1252 failed
>> > 4: Setting LC_MONETARY=en_US.cp1252 failed
>> > During startup - Warning messages:
>> > 1: Setting LC_CTYPE=en_US.cp1252 failed
>> > 2: Setting LC_COLLATE=en_US.cp1252 failed
>> > 3: Setting LC_TIME=en_US.cp1252 failed
>> > 4: Setting LC_MONETARY=en_US.cp1252 failed
>> > Warning message:
>> > In nominalTrainWorkflow(x = x, y = y, wts =
>> weights, info =
>> > trainInfo, : There were missing values in
>> resampled performance
>> > measures. Error in `$<-.data.frame`(`*tmp*`,
>> vote_qbwwv, value =
>> > numeric(0)) : replacement has 0 rows, data has 1965
>> > Calls: $<- -> $<-.data.frame
>> > Execution halted
>> > ERROR: There was an error in the execution of
>> the R script.
>> > Please check the R output.
>> > (Fri Jun 08 15:49:32 2018) Command finished (1
>> min 4 sec)
>> >
>> >
>> >
>> > Best,
>> > Jamille
>> >
>> >
>> >
>> >
>> > On Thu, Jun 7, 2018 at 11:09 AM, Jamille Haarloo
>> > <j.r.haarloo at gmail.com
>> <mailto:j.r.haarloo at gmail.com>
>> <mailto:j.r.haarloo at gmail.com
>> <mailto:j.r.haarloo at gmail.com>>> wrote:
>> >
>> > > Hello Moritz,
>> > >
>> > > No worries. Thankful these modules are made
>> available for newbies
>> > > in RS like me and also happy these
>> interactions are possible for
>> > > learning. Hope to get back soon after some
>> adjustments.
>> > >
>> > > Best,
>> > > Jamille
>> > >
>> > > On Thu, Jun 7, 2018 at 10:44 AM, Moritz Lennert <
>> > > mlennert at club.worldonline.be
>> <mailto:mlennert at club.worldonline.be>
>> <mailto:mlennert at club.worldonline.be
>> <mailto:mlennert at club.worldonline.be>>> wrote:
>> > >
>> > >> Thanks
>> > >>
>> > >> On 07/06/18 15:17, Jamille Haarloo wrote:
>> > >>
>> > >>> The first 20+ lines of Stats_Training_Ben_test:
>> > >>>
>> > >>>
>> cat,area,perimeter,compact_circle,compact_square,fd,WV_Benat
>> > >>>
>> imofo_1_min,WV_Benatimofo_1_max,WV_Benatimofo_1_range,WV_Ben
>> > >>>
>> atimofo_1_mean,WV_Benatimofo_1_stddev,WV_Benatimofo_1_varia
>> > >>>
>> nce,WV_Benatimofo_1_coeff_var,WV_Benatimofo_1_sum,WV_
>> > >>>
>> Benatimofo_1_first_quart,WV_Benatimofo_1_median,WV_Benatim
>> > >>>
>> ofo_1_third_quart,WV_Benatimofo_2_min,WV_Benatimofo_2_max,
>> > >>>
>> WV_Benatimofo_2_range,WV_Benatimofo_2_mean,WV_Benatimofo_2_
>> > >>>
>> stddev,WV_Benatimofo_2_variance,WV_Benatimofo_2_coeff_var,
>> > >>>
>> WV_Benatimofo_2_sum,WV_Benatimofo_2_first_quart,WV_
>> > >>>
>> Benatimofo_2_median,WV_Benatimofo_2_third_quart,WV_Benatimof
>> > >>>
>> o_3_min,WV_Benatimofo_3_max,WV_Benatimofo_3_range,WV_Benat
>> > >>>
>> imofo_3_mean,WV_Benatimofo_3_stddev,WV_Benatimofo_3_varianc
>> > >>>
>> e,WV_Benatimofo_3_coeff_var,WV_Benatimofo_3_sum,WV_
>> > >>>
>> Benatimofo_3_first_quart,WV_Benatimofo_3_median,WV_Benatim
>> > >>>
>> ofo_3_third_quart,WV_Benatimofo_4_min,WV_Benatimofo_4_max,
>> > >>>
>> WV_Benatimofo_4_range,WV_Benatimofo_4_mean,WV_Benatimofo_4_
>> > >>>
>> stddev,WV_Benatimofo_4_variance,WV_Benatimofo_4_coeff_var,
>> > >>>
>> WV_Benatimofo_4_sum,WV_Benatimofo_4_first_quart,WV_
>> > >>> Benatimofo_4_median,WV_Benatimofo_4_third_quart
>> > >>>
>> 1144,3832.000000,1256.000000,5.723635,0.197144,1.729624,13,7
>> > >>>
>> 6,63,46.4097077244259,9.98454911351384,99.69122100017,21.513
>> > >>>
>> 9237092391,177842,40,47,53,40,138,98,90.2687891440501,15.250
>> > >>>
>> 0825418009,232.565017531741,16.8940812061464,345910,81,92,
>> > >>>
>> 100,15,61,46,40.8582985386221,7.82663897784868,61.2562776895
>> > >>>
>> 802,19.1555675536767,156569,36,42,47,28,124,96,68.42536534
>> > >>>
>>
>> 44676,13.5774536655369,184.347248039801,19.8427200164517,262206,59,68,77
>> > >>>
>> 1145,12092.000000,2282.000000,5.854120,0.192750,1.645226,13,
>> > >>>
>> 94,81,51.386288455177,10.5294376761475,110.869057775874,20.4
>> > >>>
>> 907534532914,621363,45,52,59,21,220,199,114.230731061859,23.
>> > >>>
>> 3590328249442,545.644414516822,20.4489917973953,1381278,101,
>> > >>>
>> 114,128,7,76,69,46.4219318557724,8.42747122371732,71.
>> > >>>
>> 0222712265835,18.1540726264915,561334,42,48,52,17,198,181,
>> > >>>
>> 97.2732385047966,22.492313569247,505.904169697333,23.
>> > >>> 1228176577445,1176228,84,97,110
>> > >>>
>> > >>> [...]
>> > >>
>> > >> ---------------------
>> > >>> All the lines of the output of v.db.select
>> > >>> Training_Ben2 at haarlooj_Ben_Tes t:
>> > >>>
>> > >>> cat|id|Type|code
>> > >>> 1|4|B29|18
>> > >>> 2|5|B31|19
>> > >>> 3|3|B28|17
>> > >>>
>> > >>
>> > >>
>> > >> Again a lack of clear documentation on my
>> side: both the training
>> > >> and the segment info should contain the same
>> attributes, with only
>> > >> additional one column ('code' in your case)
>> present in the
>> > >> training data.
>> > >>
>> > >> It should be possible to do this
>> differently, i.e. provide the
>> > >> module with the features of all segments,
>> and only the id/cat of
>> > >> each training segment with the relevant
>> class and have the module
>> > >> merge the two, but this is not implemented, yet.
>> > >>
>> > >> I also just notice that you have the word
>> 'Training' in both
>> names.
>> > >>
>> > >> The segment_file/segment_map contains the
>> info (cat + all feature
>> > >> variables) of all segments you wish to
>> classify, either in the
>> > >> form of a csv file or in the form of a
>> vector map with the info in
>> > >> the attribute table.
>> > >>
>> > >> The training_file/training_map contains the
>> info (cat + all
>> feature
>> > >> variables + class) of the training data.
>> Often this is an extract
>> > >> of the former, but not necessarily.
>> > >>
>> > >> All columns in the training file have to be
>> present in the segment
>> > >> file, except for the class column (your 'code').
>> > >>
>> > >> Sorry for the lack of docs. This module has
>> mostly been used
>> > >> internally here and so we are not always
>> aware of the unclear and
>> > >> missing parts. Having your feedback has been
>> very useful !
>> > >>
>> > >> Moritz
>> > >>
>> > >>
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