troubleshoot process range error

Author: ErinWeisbart

documentation/DCP-documentation/troubleshooting_runs.md

@@ -9,7 +9,7 @@
 |   | Nothing happens for a long time after "cellprofiler -c -r " |   |   | 1) Your input directory is set to a folder with a large number of files and CP is trying to read the whole directory before running. 2) You are loading very large images. | 1) In your job file, change the input to a smaller folder. 2) Consider downscaling your images before running them in CP. Or just be more patient. |
 |   | Within a single log there are multiple “cellprofiler -c -r” | Expected output seen. |   | A single job is being processed multiple times.  |  SQS_MESSAGE_VISIBILITY is set too short. See [SQS_Queue_information](SQS_QUEUE_information.md) for more information. |
 |   | “ValueError: no name (Invalid arguments to routine: Bad value)” or “Encountered unrecoverable error in LoadData during startup: No name (no name)”  |   |   | There is a problem with your LoadData.csv. This is usually seen when CSVs are created with a script; accidentally having an extra comma somewhere (looks like ",,") will be invisible in Excel but generate the CP error. If you made your CSVs with pandas to_csv option, you must pass index=False or you will get this error.  |  Find the “,,” in your CSV and remove it. If you made your CSVs with pandas dataframe’s to_csv function, check to make sure you used the index=False parameter. |
-|   | IndexError: index 0 is out of bounds for axis 0 with size 0 |   |   | 1) Metadata values of 0 OR that have leading zeros (ie Metadata_Site=04, rather than Metadata_Site=4) are not handled well by CP. 2) The submitted jobs don’t make sense to CP. 3) DCP is looking for your images in the wrong location. | 1) Change your LoadData.csv so that there are no Metadata values of 0 or with 0 padding. 2) Change your job file so that your jobs match your pipeline’s expected input. 3) If using LoadData, make sure the file paths are correct in your LoadData.csv and the "Base image location" is set correctly in the LoadData module. If using BatchFiles, make sure your BatchFile paths are correct. |
+|   | IndexError: index 0 is out of bounds for axis 0 with size 0 |   |   | 1) Metadata values of 0 OR that have leading zeros (ie Metadata_Site=04, rather than Metadata_Site=4) are not handled well by CP. 2) The submitted jobs don’t make sense to CP. 3) DCP is looking for your images in the wrong location. 4) CellProfiler isn't accessing the rows of your load_data.csv that contain information about the jobs. | 1) Change your LoadData.csv so that there are no Metadata values of 0 or with 0 padding. 2) Change your job file so that your jobs match your pipeline’s expected input. 3) If using LoadData, make sure the file paths are correct in your LoadData.csv and the "Base image location" is set correctly in the LoadData module. If using BatchFiles, make sure your BatchFile paths are correct. 4) Make sure that your LoadData module has "Process just a range of rows?" as No or that the range you have set do not filter out the jobs that you are submitting. |
 |   |   | Pipeline output is not where expected |   | 1) There is a mistake in your ExportToSpreadsheet in your pipeline. 2) There is a mistake in your job file.  | 1) Check that your Output File Location is as expected. Default Output Folder is typical. Default Output Folder sub-folder can cause outputs to be nested in an unusual manner. 2) Check the output path in your job file. |
 |   |  "Empty image set list: no images passed the filtering criteria." |   |   | DCP doesn’t know how to load your image set.|  If you are using a .cppipe and LoadData.csv,  make sure that your pipeline includes the LoadData module. |
 |  Jobs completing(total messages decreasing)  much more quickly than expected. |"==OUT, SUCCESS"| No outcome/saved files on s3 |   |  There is a mismatch in your metadata somewhere. | Check the `Metadata_` columns in your LoadData.csv for typos or a mismatch with your jobs file. The most common sources of mismatch are case and zero padding (e.g. A01 vs a01 vs A1). Check for these mismatches and edit the job file accordingly. If you use pe2loaddata to create your csvs and the plate was imaged multiple times, pay particular attention to the Metadata_Plate column as numbering reflecting this will be automatically passed into the Load_data.csv |