Cache error: TypeError: long() argument must be a string or a number, not 'NoneType'

[johanna-bernal]

When I run the cache function in the terminal of Ubuntu I get this error: TypeError: long() argument must be a string or a number, not 'NoneType'. I do not know how to fix it. I have tried different options like change the job number the total jobs, the locations and directories where I have the .csv, the input images (Landsat 7. Envi BSQ), the folder of the output and also the parameter called prediction. But it has not worked. Thanks in advance for your help

p007r059yaml.txt

(yatsm_venv)ideam@ideam-Precision-WorkStation-T7500:~$ yatsm cache /home/ideam/yatsm/7_59/p007r059/p007r059.yaml 1 8 /home/ideam/yatsm_venv/local/lib/python2.7/site-packages/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment. warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.') Traceback (most recent call last): File "/home/ideam/yatsm_venv/bin/yatsm", line 9, in load_entry_point('yatsm==0.6.1', 'console_scripts', 'yatsm')() File "/home/ideam/yatsm_venv/local/lib/python2.7/site-packages/click/core.py", line 716, in call return self.main(_args, _kwargs) File "/home/ideam/yatsm_venv/local/lib/python2.7/site-packages/click/core.py", line 696, in main rv = self.invoke(ctx) File "/home/ideam/yatsm_venv/local/lib/python2.7/site-packages/click/core.py", line 1060, in invoke return _process_result(sub_ctx.command.invoke(sub_ctx)) File "/home/ideam/yatsm_venv/local/lib/python2.7/site-packages/click/core.py", line 889, in invoke return ctx.invoke(self.callback, _ctx.params) File "/home/ideam/yatsm_venv/local/lib/python2.7/site-packages/click/core.py", line 534, in invoke return callback(_args, _kwargs) File "/home/ideam/yatsm_venv/local/lib/python2.7/site-packages/click/decorators.py", line 17, in new_func return f(get_current_context(), args, *_kwargs) File "/home/ideam/yatsm/yatsm/cli/cache.py", line 108, in cache Y = io.gdal_reader.read_row(df['filename'], job_line) File "/home/ideam/yatsm/yatsm/io/stack_line_readers.py", line 155, in read_row return self._read_row(row) File "/home/ideam/yatsm/yatsm/io/stack_line_readers.py", line 138, in _read_row data[n_b, i, :] = band.ReadAsArray(0, row, self.n_col, 1) TypeError: long() argument must be a string or a number, not 'NoneType'

[ceholden]

Hi Johanna

Not sure off the top of my head what could be causing the error message. Would you mind doing the following to help me track it down?

1. Re-run the command with the "verbose" flag turned on so I can see more messages and post the output:
   • yatsm -v cache /home/ideam/yatsm/7_59/p007r059/p007r059.yaml 1 8
2. Attach the image list that you have referenced in your configuration file -- /home/ideam/yatsm/7_59/p007r059/images.csv

I'll can rule out any obvious problems with those two sources of information. If not, more information about the dataset -- ideally, the dataset itself if it's small enough to zip and transfer over FTP -- would be helpful. It would also rule out issues with the installation of YATSM or its dependencies if you were able to successfully run the program against one of the example datasets or if you were able to make sure the test suite passes on your computer.

Best, Chris

[ceholden]

Whoops -- looking back, I forgot to add the verbose flag. I edited my original reply to be the correct, verbose command

[johanna-bernal]

Thanks for your answer Chris.

I ran what you suggested me (see below). In addition, I ran the cache with the example of the scene p013r030, and it worked. So I have been thinking that maybe could be my images, however, I have been working correctly with my images using TSTools. To prepare them for YATSM and TSTools, I stacked them using ENVI 4.7 and produced BSQ files. But looking in QGIS the metadata of my images I found that the description of the data is different of the example images because it remains calling each band as .tif (I am not sure if it could be affecting the process):

Descripción del conjunto de datos /home/ideam/yatsm/7_59/p007r059/landsat_stack/p007r059/subset/images/LE70070591999233EDC00/LE70070591999233EDC00_stack Band_1=Layer (Band 1:LE70070591999233EDC00_sr_band1.tif) Band_2=Layer (Band 1:LE70070591999233EDC00_sr_band2.tif) Band_3=Layer (Band 1:LE70070591999233EDC00_sr_band3.tif) Band_4=Layer (Band 1:LE70070591999233EDC00_sr_band4.tif) Band_5=Layer (Band 1:LE70070591999233EDC00_sr_band5.tif) Band_6=Layer (Band 1:LE70070591999233EDC00_sr_band7.tif) Band_7=Layer (Band 1:LE70070591999233EDC00_band61.tif) Band_8=Layer (Band 1:LE70070591999233EDC00_cfmask.tif)

(yatsm_venv)ideam@ideam-Precision-WorkStation-T7500:~$ **yatsm -v cache /home/ideam/yatsm/7_59/p007r059/p007r059.yaml 1 8**
/home/ideam/yatsm_venv/local/lib/python2.7/site-packages/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment.
  warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.')
09:12:31:DEBUG:179:config_parser._find_pickle:Using prediction method "LassoCV" from config file (/home/ideam/yatsm/yatsm/regression/pickles/sklearn_LassoCV_n50.pkl)
09:12:31:DEBUG:179:config_parser._find_pickle:Using prediction method "RLM" from config file (/home/ideam/yatsm/yatsm/regression/pickles/rlm_maxiter10.pkl)
09:12:32:DEBUG:45:cache.cache:Responsible for lines: [  0   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
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09:12:32:DEBUG:52:cache.cache:Reading in data from disk using GDAL
09:12:32:DEBUG:72:cache.cache:Caching line 0 to /home/ideam/yatsm/7_59/p007r059/landsat_stack/p007r059/subset/cache/yatsm_r0_n123_b8.npy.npz
09:12:32:DEBUG:107:cache.cache:Reading in data from disk using GDAL
Traceback (most recent call last):
  File "/home/ideam/yatsm_venv/bin/yatsm", line 9, in <module>
    load_entry_point('yatsm==0.6.1', 'console_scripts', 'yatsm')()
  File "/home/ideam/yatsm_venv/local/lib/python2.7/site-packages/click/core.py", line 716, in __call__
    return self.main(*args, **kwargs)
  File "/home/ideam/yatsm_venv/local/lib/python2.7/site-packages/click/core.py", line 696, in main
    rv = self.invoke(ctx)
  File "/home/ideam/yatsm_venv/local/lib/python2.7/site-packages/click/core.py", line 1060, in invoke
    return _process_result(sub_ctx.command.invoke(sub_ctx))
  File "/home/ideam/yatsm_venv/local/lib/python2.7/site-packages/click/core.py", line 889, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/home/ideam/yatsm_venv/local/lib/python2.7/site-packages/click/core.py", line 534, in invoke
    return callback(*args, **kwargs)
  File "/home/ideam/yatsm_venv/local/lib/python2.7/site-packages/click/decorators.py", line 17, in new_func
    return f(get_current_context(), *args, **kwargs)
  File "/home/ideam/yatsm/yatsm/cli/cache.py", line 108, in cache
    Y = io.gdal_reader.read_row(df['filename'], job_line)
  File "/home/ideam/yatsm/yatsm/io/stack_line_readers.py", line 155, in read_row
    return self._read_row(row)
  File "/home/ideam/yatsm/yatsm/io/stack_line_readers.py", line 138, in _read_row
    data[n_b, i, :] = band.ReadAsArray(0, row, self.n_col, 1)
TypeError: long() argument must be a string or a number, not 'NoneType'

imagescsv.xlsx

[ceholden]

Hi Johanna

Thanks for providing the additional information. Unfortunately I'm still at a loss for an explanation. What's really curious to me is that I've tried substituting None into both the assignment (data[n_b, i, :]) and the GDAL call (band.ReadAsArray(0, row, self.n_col, 1)) and putting None into any of the possible argument values never produces the error you've described.

The metadata you see in QGIS is probably okay -- I think it's just information that ENVI has added into the header of its file format to describe what it should show in its user interface. The bands aren't actually TIF files but ENVI keeps track of the names of the TIF files the bands came from.

I have three proposals for continuing to debug this issue:

1. I added some debugging logging statements to the line in question and committed these changes to the branch "johanna". You could use git to retrieve these changes, re-run the same command, and then post the results. If you want to go this route, you would run the following commands (assuming you have the yatsm repository downloaded into your home folder as the TSTools VM does):
   • cd ~/yatsm
   • git fetch --all
   • git checkout johanna
   • pip install -e .
   • yatsm -v cache /home/ideam/yatsm/7_59/p007r059/p007r059.yaml 1 8
   • I didn't change any other code, so it should reach the same failure point. This time, however, there will be even more information to check.
2. It might be easiest to debug if you could send a few of the images to me via FTP. Unfortunately I think our university department's incoming "drop" server is closed for good, but I'd be able to download the images via FTP, Dropbox, Google Drive, or other hosting solutions.
3. If not option 2, then it might be helpful to use the gdalinfo tool to ensure that all of the images you're trying to use were stacked and output by ENVI in the same way. The script checks to make sure that all of the images have the same attributes, like the same number of rows/columns, upper left coordinates, number of bands, etc. If you want to go this route, download the script I've attached (debug_94.txt) and run it as follows:
   • Open the terminal and navigate to the location of the downloaded script
   • bash debug_94.txt /home/ideam/yatsm/7_59/p007r059/landsat_stack/p007r059/subset/images > debug_94.log
   • The > debug_94.log bit of the command will "redirect" the output of the script into a text file instead of showing it in your terminal. When the script completes, you should have a new file, debug_94.log, that holds the results. Upload this in a reply to this ticket

Sorry for the trouble -- wish I had a better way of debugging remotely! If this doesn't work I'll be out of ideas, but I hope we can get you and IDEAM up and running somehow.

debug_94.txt

[ceholden]

@parevalo sorry (or, not sorry?) to drag you in, but you were just at IDEAM and might have some knowledge I don't. Would you mind reading through this thread and comment if you have any other ideas?

[parevalo]

Not sorry at all! I don't have any other ideas to be honest, but I think the obvious next step is to run your debug script and inspect the results to see if we can find something. What's really strange is that I actually saw TS Tools working there normally, so I assume the images must have been fine, but I never really looked at them individually, or their metadata. However, I wonder if it has something to do with not specifying a "reference" output extent when creating the stacks, and then ENVI putting some strange value in those areas, that do not match the "NoData" flag in the metadata.

[johanna-bernal]

Thank you Chris!

I am goning to run the debug and then if it does not work I will share with you the images.

You have been very kind giving me your help.

[johanna-bernal]

Hello Chris:

I ran the debug (see attach) and with the results I think that the problem is with the extent of the images, because they did not have the same size or the same starting point. So, I am going to follow your scripts of pre-processing in order to be sure that the images have the same characteristics. What do you think?

Thanks for your kind help.

debug_94log.txt

[ceholden]

Hi Johanna

Having the extents consistent across the imagery is unfortunately a requirement so far in this version, so it will be progress to alter the extents of your images to match. I'm not exactly sure this will solve the problem that you're encountering, but it's progress in the right direction.

You should be able to just use gdal_translate with the -projwin ulx uly lrx lry argument to fix all of the extents to the same coordinates. It might be easiest to simply pick the coordinates to "stack" from the first image in the series.

Might be something like,

# Borrowed from https://github.com/dwtkns/gdal-cheat-sheet
function gdal_extent() {
    if [ -z "$1" ]; then 
        echo "Missing arguments. Syntax:"
        echo "  gdal_extent <input_raster>"
        return
    fi
    EXTENT=$(gdalinfo $1 |\
        grep "Upper Left\|Lower Right" |\
        sed "s/Upper Left  //g;s/Lower Right //g;s/).*//g" |\
        tr "\n" " " |\
        sed 's/ *$//g' |\
        tr -d "[(,]")
    echo -n "$EXTENT"
}

# GDAL output format and format creation options -- change as you will
OUT_FORMAT=ENVI
OUT_OPTION="INTERLEAVE=BIP"

# Initialize the output extent as an empty string so we can define it with first image in loop
extent=""
# This find command assumes you're in the root directory of the imagery
for img in $(find ./ -name 'L*stack'); do
    # If extent is empty, initialize
    if [ "$extent" == "" ]; then
        extent=$(gdal_extent $img)
        echo "Stacking to extent: $extent"
    fi
    # Define some output name for the corrected images
    out_name=${img}_fixed

    gdal_translate -projwin $extent -of $OUT_FORMAT -co $OUT_OPTION $img $out_name
done

You might get some warnings from GDAL that, Computed -srcwin ... falls partially outside raster extent.. These should be safe to ignore and are to be expected.

I wrote about snippets of code like this a few years ago in the 5th chapter in landsat_preprocess. That tutorial is very out of date, but it might be worth looking at. Please ask any questions you might have in this next step in this thread, however.

Cheers Chris

[johanna-bernal]

The script for adjusting the extent of the stacks worked! Now I have the cache files and I will continue with the other functions of the YATSM code. Thank you Chris.

[parevalo]

Great to hear!

On Mon, Sep 12, 2016 at 5:15 PM, johanna-bernal notifications@github.com wrote:

The script for adjusting the extent of the stacks worked! Now I have the cache files and I will continue with the other functions of the YATSM code. Thank you Chris.

— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub https://github.com/ceholden/yatsm/issues/94#issuecomment-246495984, or mute the thread https://github.com/notifications/unsubscribe-auth/AIrAxySwe2NcPJr6w7GM2rqGuzFubsYSks5qpcDVgaJpZM4Jl1rw .

[ceholden]

@johanna-bernal Hooray!

I should have mentioned earlier, but running yatsm cache before yatsm line isn't strictly a requirement. The yatsm line command will actually cache the time series data when it reads in for the first time, but having the data already cached will speed up reading in the data. yatsm cache is mostly useful if you want to update the cached data when you add new observations or remove any existing observations (if, for instance, you found that the image was very misregistered or the image was filled with clouds the cloud mask missed).

The two commands end up running the same code that was causing the trouble so we've fixed the issue for both commands :)