Running 'testthat.R' [67s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
  > # nolint start
  > library(testthat)
  > library(pavo)
  > # nolint end
  > 
  > test_check("pavo")
  Colorspace & visual model options:
   * Colorspace: trispace 
   * Quantal catch: Qi 
   * Visual system, chromatic: cie10 
   * Visual system, achromatic: none 
   * Illuminant: ideal, scale = 1 (von Kries colour correction applied) 
   * Background: ideal 
   * Relative: TRUE 
   * Max possible chromatic volume: NA 
  
  Colorspace & visual model options:
   * Colorspace: tcs 
   * Quantal catch: Qi 
   * Visual system, chromatic: avg.uv 
   * Visual system, achromatic: none 
   * Illuminant: ideal, scale = 1 (von Kries colour correction not applied) 
   * Background: ideal 
   * Relative: TRUE 
   * Max possible chromatic volume: 0.215735 
  
  'avalue' automatically set to 1.8275e-01
  wavelengths found in column 1
  wavelengths found in column 1
  wavelengths found in column 1
  The spectral data contain 819 negative value(s),
   which may produce unexpected results if used in models.
  Consider using procspec() to correct them.
  wavelengths found in column 1
  The spectral data contain 1212 negative value(s),
   which may produce unexpected results if used in models.
  Consider using procspec() to correct them.
  wavelengths found in column 1
  The spectral data contain 410 negative value(s),
   which may produce unexpected results if used in models.
  Consider using procspec() to correct them.
  wavelengths found in column 1
  The spectral data contain 410 negative value(s),
   which may produce unexpected results if used in models.
  Consider using procspec() to correct them.
  wavelengths found in column 1
  The spectral data contain 607 negative value(s),
   which may produce unexpected results if used in models.
  Consider using procspec() to correct them.
  wavelengths found in column 1
  The spectral data contain 607 negative value(s),
   which may produce unexpected results if used in models.
  Consider using procspec() to correct them.
  The spectral data contain 604 negative value(s),
   which may produce unexpected results if used in models.
  Consider using procspec() to correct them.
  The spectral data contain 607 negative value(s),
   which may produce unexpected results if used in models.
  Consider using procspec() to correct them.
  The spectral data contain 411 negative value(s),
   which may produce unexpected results if used in models.
  Consider using procspec() to correct them.
  The spectral data contain 1212 negative value(s),
   which may produce unexpected results if used in models.
  Consider using procspec() to correct them.
  wavelengths found in column 1
  The spectral data contain 818 negative value(s),
   which may produce unexpected results if used in models.
  Consider using procspec() to correct them.
  wavelengths found in column 1
  The spectral data contain 815 negative value(s),
   which may produce unexpected results if used in models.
  Consider using procspec() to correct them.
  The spectral data contain 3 NA's(s), which should be reviewed closely.
  The spectral data contain 607 negative value(s),
   which may produce unexpected results if used in models.
  Consider using procspec() to correct them.
  Calculating noise-weighted Euclidean distances
  Quantum catch are relative, distances may not be meaningful
  Number of cones assumed to be 4
  Quantum catch are relative, distances may not be meaningful
  Quantum catch are relative, distances may not be meaningful
  Quantum catch are relative, distances may not be meaningful
  Calculating noise-weighted Euclidean distances and noise-weighted luminance contrasts
  Calculating noise-weighted Euclidean distances
  Calculating noise-weighted Euclidean distances
  Quantum catch are relative, distances may not be meaningful
  Calculating noise-weighted Euclidean distances
  Calculating noise-weighted Euclidean distances
  Calculating noise-weighted Euclidean distances
  Calculating noise-weighted Euclidean distances
  Calculating noise-weighted Euclidean distances
  Quantum catch are relative, distances may not be meaningful
  Calculating noise-weighted Euclidean distances
  Calculating noise-weighted Euclidean distances
  Quantum catch are relative, distances may not be meaningful
  Calculating noise-weighted Euclidean distances
  Quantum catch are relative, distances may not be meaningful
  Calculating noise-weighted Euclidean distances
  Calculating CIE2000 distances
  Calculating CIE2000 distances
  Calculating noise-weighted Euclidean distances and noise-weighted luminance contrasts
  Quantum catch are relative, distances may not be meaningful
  Calculating noise-weighted Euclidean distances
  Quantum catch are relative, distances may not be meaningful
  Calculating noise-weighted Euclidean distances
  Input is not a "vismodel" object and argument "qcatch" is undefined; assuming quantum catch are not transformed (i.e. qcatch = "Qi")
  Quantum catch are relative, distances may not be meaningful
  Calculating unweighted Euclidean distances
  Input is not a "vismodel" object and argument "qcatch" is undefined; assuming quantum catch are not transformed (i.e. qcatch = "Qi")
  Quantum catch are relative, distances may not be meaningful
  Calculating unweighted Euclidean distances
  Input is not a "vismodel" object and argument "qcatch" is undefined; assuming quantum catch are not transformed (i.e. qcatch = "Qi")
  Quantum catch are relative, distances may not be meaningful
  Calculating unweighted Euclidean distances
  Quantum catch are relative, distances may not be meaningful
  Calculating noise-weighted Euclidean distances and noise-weighted luminance contrasts
  Quantum catch are relative, distances may not be meaningful
  Calculating noise-weighted Euclidean distances and noise-weighted luminance contrasts
  Quantum catch are relative, distances may not be meaningful
  Calculating noise-weighted Euclidean distances and noise-weighted luminance contrasts
  Colorspace & visual model options:
   * Colorspace: tcs 
   * Quantal catch: Qi 
   * Visual system, chromatic: user-defined 
   * Visual system, achromatic: none 
   * Illuminant: ideal, scale = 1 (von Kries colour correction not applied) 
   * Background: ideal 
   * Relative: TRUE 
   * Max possible chromatic volume: 0.1294362 
  
  Input is not a "vismodel" object and argument "qcatch" is undefined; assuming quantum catch are not transformed (i.e. qcatch = "Qi")
  Input is not a "vismodel" object and argument "qcatch" is undefined; assuming quantum catch are not transformed (i.e. qcatch = "Qi")
  Input is not a "vismodel" object and argument "qcatch" is undefined; assuming quantum catch are not transformed (i.e. qcatch = "Qi")
  Input is not a "vismodel" object and argument "qcatch" is undefined; assuming quantum catch are not transformed (i.e. qcatch = "Qi")
  Input is not a "vismodel" object and argument "qcatch" is undefined; assuming quantum catch are not transformed (i.e. qcatch = "Qi")
  Input is not a "vismodel" object and argument "qcatch" is undefined; assuming quantum catch are not transformed (i.e. qcatch = "Qi")
  Using custom visual system to estimate cie neutral point
  Using custom illuminant to estimate cie neutral point
  Input is not a "vismodel" object and argument "qcatch" is undefined; assuming quantum catch are not transformed (i.e. qcatch = "Qi")
  Input is not a "vismodel" object and argument "qcatch" is undefined; assuming quantum catch are not transformed (i.e. qcatch = "Qi")
  Input is not a "vismodel" object and argument "qcatch" is undefined; assuming quantum catch are not transformed (i.e. qcatch = "Qi")
  Input is not a "vismodel" object and argument "qcatch" is undefined; assuming quantum catch are not transformed (i.e. qcatch = "Qi")
  Rescaling values to [0,1]
  Rescaling values to [0,1]
  Rescaling values to [0,1]
  Rescaling values to [0,1]
  Rescaling values to [0,1]
  Image classification in progress...
  Image classification in progress...
  Image classification in progress...
  Attempting to coerce image to class rimg.
  Attempting to coerce image to class rimg.
  Attempting to coerce image to class rimg.
  Attempting to coerce image to class rimg.
  Attempting to coerce image to class rimg.
  One or more images are not of class 'rimg'; attempting to coerce.
  Image classification in progress...
  One or more images are not of class 'rimg'; attempting to coerce.
  Image classification in progress...
  One or more images are not of class 'rimg'; attempting to coerce.
  Image classification in progress...
  Image classification in progress...
  Image classification in progress...
  Image classification in progress...
  Image classification in progress...
  Image classification in progress...
  One or more image matrices are not of class 'rimg'; attempting to coerce.
  Using single set of coldists for all images.
  Specified grid-sampling density exceeds dimensions of at least one image. Overwriting xpts to equal the smallest dimension in the image set.
  Using single set of coldists for all images.
  Using single set of hsl values for all images.
  Using single set of coldists for all images.
  Using single set of hsl values for all images.
  Image classification in progress...
  One or more image matrices are not of class 'rimg'; attempting to coerce.
  Specified grid-sampling density exceeds dimensions of at least one image. Overwriting xpts to equal the smallest dimension in the image set.
  Image classification in progress...
  Image classification in progress...
  Using single set of coldists for all images.
  Using single set of hsl values for all images.
  Image classification in progress...
  4 files found; importing spectra:
  1 files found; importing spectra:
  6 files found; importing spectra:
  5 files found; importing spectra:
  processing options applied:
  smoothing spectra with a span of 0.25
  processing options applied:
  smoothing spectra with a span of 0.1
  processing options applied:
  smoothing spectra with a span of 30
  processing options applied:
  smoothing spectra with a span of 0.1
  processing options applied:
  smoothing spectra with a span of 50
  processing options applied:
  binned spectra to 17-nm intervals
  processing options applied:
  binned spectra to 12-nm intervals
  processing options applied:
  Scaling spectra to a maximum value of 1
  processing options applied:
  Scaling spectra to a minimum value of zero
  processing options applied:
  Scaling spectra to a minimum value of zero
  Scaling spectra to a maximum value of 1
  processing options applied:
  Scaling spectra to a total area of 1
  processing options applied:
  Centering spectra to a mean of zero
  processing options applied:
  Negative value correction: converted negative values to zero
  processing options applied:
  Negative value correction: added min to all reflectance
  processing options applied:
  Scaling spectra to a minimum value of zero
  Scaling spectra to a maximum value of 1
  Scaling spectra to a total area of 1
  Centering spectra to a mean of zero
  binned spectra to 17-nm intervals
  4 files found; importing spectra:
  processing options applied:
  smoothing spectra with a span of 0.1
  NULL
  Quantum catch are relative, distances may not be meaningful
  Calculating noise-weighted Euclidean distances
  Calculating noise-weighted Euclidean distances and noise-weighted luminance contrasts
  Quantum catch are relative, distances may not be meaningful
  Calculating unweighted Euclidean distances and Weber luminance contrast
  Quantum catch are relative, distances may not be meaningful
  Calculating unweighted Euclidean distances and Weber luminance contrast
  Calculating unweighted Euclidean distances and simple luminance contrast
  Quantum catch are relative, distances may not be meaningful
  Calculating unweighted Euclidean distances and Michelson luminance contrast
  Calculating CIE2000 distances
  Number of cones assumed to be 4 (last column ignored for chromatic contrast, used only for achromatic contrast)
  Calculating noise-weighted Euclidean distances and noise-weighted luminance contrasts
  Quantum catch are relative, distances may not be meaningful
  Calculating noise-weighted Euclidean distances and noise-weighted luminance contrasts
  2 files found; importing images.
  The length of argument 'sensnames' does not equal the number of curves specified by 'peaksens'. Reverting to default names.
  wavelengths found in column 1
  The spectral data contain 401 negative value(s),
   which may produce unexpected results if used in models.
  Consider using procspec() to correct them.
  wavelengths found in column 1
  wavelengths found in column 1
  [ FAIL 3 | WARN 54 | SKIP 2 | PASS 468 ]
  
  ══ Skipped tests (2) ═══════════════════════════════════════════════════════════
  • On CRAN (2): 'test-processing.R:63:3', 'test-voloverlap.R:107:3'
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Failure ('test-import.R:17:3'): getspec ─────────────────────────────────────
  `proc` is not an S3 object
  ── Failure ('test-import.R:18:3'): getspec ─────────────────────────────────────
  `proc` has length 0, not length 5.
  ── Failure ('test-import.R:22:3'): getspec ─────────────────────────────────────
  `proccase` has length 0, not length 5.
  
  [ FAIL 3 | WARN 54 | SKIP 2 | PASS 468 ]
  Error: Test failures
  Execution halted