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72 lines (71 loc) · 4.07 KB
Upload Errors:
  TSV Errors:
    examples/dataset-examples/bad-tsv-formats/upload/codex-metadata.tsv, column 'contributors_path', value 'contributors.tsv':
    - 'File has no data rows: examples/dataset-examples/bad-tsv-formats/upload/contributors.tsv.'
    examples/dataset-examples/bad-tsv-formats/upload/codex-metadata.tsv, column 'antibodies_path', value 'antibodies.tsv':
    - 'File does not exist: examples/dataset-examples/bad-tsv-formats/upload/antibodies.tsv.'
  Directory Errors:
    examples/dataset-examples/bad-tsv-formats/upload/codex-metadata.tsv, column 'data_path', value 'dataset-1/':
      examples/dataset-examples/bad-tsv-formats/upload/dataset-1 (as codex-v1-with-dataset-json):
        Not allowed:
        - channelnames.txt.
        - cyc002_reg001_200216_112537/1_00001_Z001_CH1.tif.
        - experiment.json.
        - exposure_times.txt.
        - segmentation.json.
        Required but missing:
        - (processed|drv_[^/]*)/.*.
        - (raw|src_.*)/.*.
        - (raw|src_.*)/[cC]yc.*_reg.*/.*_Z.*_CH.*\.tif.
        - (raw|src_[^/]*)/dataset\.json.
        - extras/dir-schema-v1-with-dataset-json.
Metadata TSV Validation Errors:
  Local Validation Errors:
    examples/dataset-examples/bad-tsv-formats/upload/codex-metadata.tsv (as codex-v0):
    - 'On row 2, column "donor_id", value "not-uuid" fails because it does not match
      the expected pattern. Example: ABC123'
    - 'On row 2, column "tissue_id", value "not-uuid" fails because it does not match
      the expected pattern. Example: ABC123-BL-1-2-3_456'
    - On row 2, column "execution_datetime", value "not-time" fails because it is
      not in the format YYYY-MM-DD Hour:Minute.
    - On row 2, column "protocols_io_doi", value "10\.17504/protocols.io.menc3de"
      fails because it does not match the expected pattern.
    - 'On row 2, column "analyte_class", value "analyte_class" fails because it is
      not one of these: "protein".'
    - On row 2, column "is_targeted", value "is_targeted" fails because it is neither
      true nor false.
    - 'On row 2, column "acquisition_instrument_vendor", value "acquisition_instrument_vendor"
      fails because it is not one of these: "Keyence", "Zeiss".'
    - 'On row 2, column "acquisition_instrument_model", value "acquisition_instrument_model"
      fails because it is not one of these: "BZ-X800", "BZ-X710", "Axio Observer Z1".'
    - On row 2, column "resolution_x_value", value "forty-two" fails because it is
      not in numerical form.
    - 'On row 2, column "resolution_x_unit", value "inches" fails because it is not
      one of these: "mm", "um", "nm".'
    - On row 2, column "resolution_y_value", value "forty-two" fails because it is
      not in numerical form.
    - 'On row 2, column "resolution_y_unit", value "inches" fails because it is not
      one of these: "mm", "um", "nm".'
    - On row 2, column "resolution_z_value", value "forty-two" fails because it is
      not in numerical form.
    - 'On row 2, column "resolution_z_unit", value "inches" fails because it is not
      one of these: "mm", "um", "nm".'
    - 'On row 2, column "preparation_instrument_vendor", value "preparation_instrument_vendor"
      fails because it is not one of these: "CODEX".'
    - 'On row 2, column "preparation_instrument_model", value "preparation_instrument_model"
      fails because it is not one of these: "version 1 robot", "prototype robot -
      Stanford/Nolan Lab".'
    - On row 2, column "number_of_antibodies", value "0.5" fails because it is not
      an integer.
    - On row 2, column "number_of_channels", value "0.5" fails because it is not an
      integer.
    - On row 2, column "number_of_cycles", value "0.5" fails because it is not an
      integer.
    - On row 2, column "section_prep_protocols_io_doi", value "not-doi" fails because
      it does not match the expected pattern.
    - On row 2, column "reagent_prep_protocols_io_doi", value "not-doi" fails because
      it does not match the expected pattern.
Hint: 'If validation fails because of extra whitespace in the TSV, try:

  src/cleanup_whitespace.py --tsv_in original.tsv --tsv_out clean.tsv.'