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Created May 23, 2024 09:55
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(partial) EasyBuild log for failed build of /tmp/eb-icrv8ens/files_pr19684/p/pyTME/pyTME-0.2.0-foss-2023a-CUDA-12.1.1.eb (PR(s) #19684)
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pyTME-0.2.0-foss-2023a-CUDA-12.1.1_partial.log
How values passed to --lowpass and --highpass should be interpreted. By default, they are assumed to be in units of sampling rate, e.g. ngstrom.
--whiten_spectrum Apply spectral whitening to template and target based on target spectrum.
--wedge_axes WEDGE_AXES
Indices of wedge opening and tilt axis, e.g. 0,2 for a wedge that is open in z-direction and tilted over the x axis.
--tilt_angles TILT_ANGLES
Path to a tab-separated file containing the column angles and optionally weights, or comma separated start and stop stage tilt angle, e.g. 50,45, which yields a continuous wedge mask. Alternatively, a tilt step size can be specified like
50,45:5.0 to sample 5.0 degree tilt angle steps.
--tilt_weighting {angle,relion,grigorieff}
Weighting scheme used to reweight individual tilts. Available options: angle (cosine based weighting), relion (relion formalism for wedge weighting) requires,grigorieff (exposure filter as defined in Grant and Grigorieff 2015).relion and
grigorieff require electron doses in --tilt_angles weights column.
--reconstruction_filter {ram-lak,ramp,shepp-logan,cosine,hamming}
Filter applied when reconstructing (N+1)-D from N-D filters.
Performance:
--cutoff_target CUTOFF_TARGET
Target contour level (used for cropping).
--cutoff_template CUTOFF_TEMPLATE
Template contour level (used for cropping).
--no_centering Assumes the template is already centered and omits centering.
--no_edge_padding Whether to not pad the edges of the target. Can be set if the target has a well defined bounding box, e.g. a masked reconstruction.
--no_fourier_padding Whether input arrays should not be zero-padded to full convolution shape for numerical stability. When working with very large targets, e.g. tomograms, it is safe to use this flag and benefit from the performance gain.
--interpolation_order INTERPOLATION_ORDER
Spline interpolation used for template rotations. If less than zero no interpolation is performed.
--use_mixed_precision
Use float16 for real values operations where possible.
--use_memmap Use memmaps to offload large data objects to disk. Particularly useful for large inputs in combination with --use_gpu.
Analyzer:
--score_threshold SCORE_THRESHOLD
Minimum template matching scores to consider for analysis.
== 2024-05-23 11:52:11,367 run.py:725 DEBUG Using default regular expression: (?<![(,-]|\w)(?:error|segmentation fault|failed)(?![(,-]|\.?\w)
== 2024-05-23 11:52:11,367 easyblock.py:3640 INFO sanity check command match_template.py --help ran successfully! (output: usage: match_template.py [-h] -m TARGET [--target_mask TARGET_MASK] -i TEMPLATE [--template_mask TEMPLATE_MASK] [-o OUTPUT] [--invert_target_contrast] [--scramble_phases] [-s {CC,LCC,CORR,CAM,FLCSphericalMask,FLC,FLC2,MCC}] [-p]
(-a ANGULAR_SAMPLING | --cone_angle CONE_ANGLE) [--cone_sampling CONE_SAMPLING] [--axis_angle AXIS_ANGLE] [--axis_sampling AXIS_SAMPLING] [--axis_symmetry AXIS_SYMMETRY] [--no_use_optimized_set] [-n CORES] [--use_gpu] [--gpu_indices GPU_INDICES]
[-r MEMORY] [--memory_scaling MEMORY_SCALING] [--temp_directory TEMP_DIRECTORY] [--lowpass LOWPASS] [--highpass HIGHPASS] [--no_pass_smooth] [--pass_format {sampling_rate,voxel,frequency}] [--whiten_spectrum] [--wedge_axes WEDGE_AXES]
[--tilt_angles TILT_ANGLES] [--tilt_weighting {angle,relion,grigorieff}] [--reconstruction_filter {ram-lak,ramp,shepp-logan,cosine,hamming}] [--cutoff_target CUTOFF_TARGET] [--cutoff_template CUTOFF_TEMPLATE] [--no_centering] [--no_edge_padding]
[--no_fourier_padding] [--interpolation_order INTERPOLATION_ORDER] [--use_mixed_precision] [--use_memmap] [--score_threshold SCORE_THRESHOLD]
Perform template matching.
options:
-h, --help show this help message and exit
Input / Output:
-m TARGET, --target TARGET
Path to a target in CCP4/MRC, EM, H5 or another format supported by tme.density.Density.from_file https://kosinskilab.github.io/pyTME/reference/api/tme.density.Density.from_file.html
--target_mask TARGET_MASK
Path to a mask for the target in a supported format (see target).
-i TEMPLATE, --template TEMPLATE
Path to a template in PDB/MMCIF or other supported formats (see target).
--template_mask TEMPLATE_MASK
Path to a mask for the template in a supported format (see target).
-o OUTPUT, --output OUTPUT
Path to the output pickle file.
--invert_target_contrast
Invert the target's contrast and rescale linearly between zero and one. This option is intended for targets where templates to-be-matched have negative values, e.g. tomograms.
--scramble_phases Phase scramble the template to generate a noise score background.
Scoring:
-s {CC,LCC,CORR,CAM,FLCSphericalMask,FLC,FLC2,MCC}
Template matching scoring function.
-p Perform peak calling instead of score aggregation.
Angular Sampling:
-a ANGULAR_SAMPLING Angular sampling rate using optimized rotational sets.A lower number yields more rotations. Values >= 180 sample only the identity.
--cone_angle CONE_ANGLE
Half-angle of the cone to be sampled in degrees. Allows to sample a narrow interval around a known orientation, e.g. for surface oversampling.
--cone_sampling CONE_SAMPLING
Sampling rate of the cone in degrees.
--axis_angle AXIS_ANGLE
Sampling angle along the z-axis of the cone. Defaults to 360.
--axis_sampling AXIS_SAMPLING
Sampling rate along the z-axis of the cone. Defaults to --cone_sampling.
--axis_symmetry AXIS_SYMMETRY
N-fold symmetry around z-axis of the cone.
--no_use_optimized_set
Whether to use random uniform instead of optimized rotation sets.
Computation:
-n CORES Number of cores used for template matching.
--use_gpu Whether to perform computations on the GPU.
--gpu_indices GPU_INDICES
Comma-separated list of GPU indices to use. For example, 0,1 for the first and second GPU. Only used if --use_gpu is set. If not provided but --use_gpu is set, CUDA_VISIBLE_DEVICES will be respected.
-r MEMORY, --ram MEMORY
Amount of memory that can be used in bytes.
--memory_scaling MEMORY_SCALING
Fraction of available memory that can be used. Defaults to 0.85 and is ignored if --ram is set
--temp_directory TEMP_DIRECTORY
Directory for temporary objects. Faster I/O improves runtime.
Filters:
--lowpass LOWPASS Resolution to lowpass filter template and target to in the same unit as the sampling rate of template and target (typically ngstrom).
--highpass HIGHPASS Resolution to highpass filter template and target to in the same unit as the sampling rate of template and target (typically ngstrom).
--no_pass_smooth Whether a hard edge filter should be used for --lowpass and --highpass.
--pass_format {sampling_rate,voxel,frequency}
How values passed to --lowpass and --highpass should be interpreted. By default, they are assumed to be in units of sampling rate, e.g. ngstrom.
--whiten_spectrum Apply spectral whitening to template and target based on target spectrum.
--wedge_axes WEDGE_AXES
Indices of wedge opening and tilt axis, e.g. 0,2 for a wedge that is open in z-direction and tilted over the x axis.
--tilt_angles TILT_ANGLES
Path to a tab-separated file containing the column angles and optionally weights, or comma separated start and stop stage tilt angle, e.g. 50,45, which yields a continuous wedge mask. Alternatively, a tilt step size can be specified like
50,45:5.0 to sample 5.0 degree tilt angle steps.
--tilt_weighting {angle,relion,grigorieff}
Weighting scheme used to reweight individual tilts. Available options: angle (cosine based weighting), relion (relion formalism for wedge weighting) requires,grigorieff (exposure filter as defined in Grant and Grigorieff 2015).relion and
grigorieff require electron doses in --tilt_angles weights column.
--reconstruction_filter {ram-lak,ramp,shepp-logan,cosine,hamming}
Filter applied when reconstructing (N+1)-D from N-D filters.
Performance:
--cutoff_target CUTOFF_TARGET
Target contour level (used for cropping).
--cutoff_template CUTOFF_TEMPLATE
Template contour level (used for cropping).
--no_centering Assumes the template is already centered and omits centering.
--no_edge_padding Whether to not pad the edges of the target. Can be set if the target has a well defined bounding box, e.g. a masked reconstruction.
--no_fourier_padding Whether input arrays should not be zero-padded to full convolution shape for numerical stability. When working with very large targets, e.g. tomograms, it is safe to use this flag and benefit from the performance gain.
--interpolation_order INTERPOLATION_ORDER
Spline interpolation used for template rotations. If less than zero no interpolation is performed.
--use_mixed_precision
Use float16 for real values operations where possible.
--use_memmap Use memmaps to offload large data objects to disk. Particularly useful for large inputs in combination with --use_gpu.
Analyzer:
--score_threshold SCORE_THRESHOLD
Minimum template matching scores to consider for analysis.
)
== 2024-05-23 11:52:11,372 run.py:221 DEBUG run_cmd: running cmd postprocess --help (in /kyukon/scratch/gent/vo/000/gvo00002/vsc40023/easybuild_REGTEST/RHEL8/cascadelake-volta-ib/software/pyTME/0.2.0-foss-2023a-CUDA-12.1.1)
== 2024-05-23 11:52:11,372 run.py:247 INFO running cmd: postprocess --help
== 2024-05-23 11:52:33,472 run.py:689 DEBUG cmd "postprocess --help" exited with exit code 0 and output:
usage: postprocess [-h] --input_file INPUT_FILE [INPUT_FILE ...] [--target_mask TARGET_MASK] [--orientations ORIENTATIONS] --output_prefix OUTPUT_PREFIX [--output_format {orientations,alignment,extraction,relion,backmapping,average}]
[--peak_caller {PeakCallerSort,PeakCallerMaximumFilter,PeakCallerFast,PeakCallerRecursiveMasking,PeakCallerScipy}] [--minimum_score MINIMUM_SCORE] [--maximum_score MAXIMUM_SCORE] [--min_distance MIN_DISTANCE]
[--min_boundary_distance MIN_BOUNDARY_DISTANCE] [--mask_edges] [--number_of_peaks NUMBER_OF_PEAKS] [--peak_oversampling PEAK_OVERSAMPLING] [--subtomogram_box_size SUBTOMOGRAM_BOX_SIZE] [--mask_subtomograms] [--invert_target_contrast]
[--wedge_mask WEDGE_MASK] [--n_false_positives N_FALSE_POSITIVES]
Peak Calling for Template Matching Outputs
options:
-h, --help show this help message and exit
Input:
--input_file INPUT_FILE [INPUT_FILE ...]
Path to the output of match_template.py.
--target_mask TARGET_MASK
Path to an optional mask applied to template matching scores.
--orientations ORIENTATIONS
Path to file generated using output_format orientations. Can be filtered to exclude false-positive peaks. If this file is provided, peak calling is skipped and corresponding parameters ignored.
Output:
--output_prefix OUTPUT_PREFIX
Output filename, extension will be added based on output_format.
--output_format {orientations,alignment,extraction,relion,backmapping,average}
Available output formats:orientations (translation, rotation, and score), alignment (aligned template to target based on orientations), extraction (extract regions around peaks from targets, i.e. subtomograms), relion (perform extraction step and
generate corresponding star files), backmapping (map template to target using identified peaks),average (extract matched regions from target and average them).
Peak Calling:
--peak_caller {PeakCallerSort,PeakCallerMaximumFilter,PeakCallerFast,PeakCallerRecursiveMasking,PeakCallerScipy}
Peak caller for local maxima identification.
--minimum_score MINIMUM_SCORE
Minimum score from which peaks will be considered.
--maximum_score MAXIMUM_SCORE
Maximum score until which peaks will be considered.
--min_distance MIN_DISTANCE
Minimum distance between peaks.
--min_boundary_distance MIN_BOUNDARY_DISTANCE
Minimum distance of peaks to target edges.
--mask_edges Whether candidates should not be identified from scores that were computed from padded densities. Superseded by min_boundary_distance.
--number_of_peaks NUMBER_OF_PEAKS
Upper limit of peaks to call, subject to filtering parameters. Default 1000. If minimum_score is provided all peaks scoring higher will be reported.
--peak_oversampling PEAK_OVERSAMPLING
1 / factor equals voxel precision, e.g. 2 detects half voxel translations. Useful for matching structures to electron density maps.
Additional Parameters:
--subtomogram_box_size SUBTOMOGRAM_BOX_SIZE
Subtomogram box size, by default equal to the centered template. Will be padded to even values if output_format is relion.
--mask_subtomograms Whether to mask subtomograms using the template mask. The mask will be rotated according to determined angles.
--invert_target_contrast
Whether to invert the target contrast.
--wedge_mask WEDGE_MASK
Path to file used as ctf_mask for output_format relion.
--n_false_positives N_FALSE_POSITIVES
Number of accepted false-positives picks to determine minimum score.
== 2024-05-23 11:52:33,472 run.py:725 DEBUG Using default regular expression: (?<![(,-]|\w)(?:error|segmentation fault|failed)(?![(,-]|\.?\w)
== 2024-05-23 11:52:33,472 easyblock.py:3640 INFO sanity check command postprocess --help ran successfully! (output: usage: postprocess [-h] --input_file INPUT_FILE [INPUT_FILE ...] [--target_mask TARGET_MASK] [--orientations ORIENTATIONS] --output_prefix OUTPUT_PREFIX [--output_format {orientations,alignment,extraction,relion,backmapping,average}]
[--peak_caller {PeakCallerSort,PeakCallerMaximumFilter,PeakCallerFast,PeakCallerRecursiveMasking,PeakCallerScipy}] [--minimum_score MINIMUM_SCORE] [--maximum_score MAXIMUM_SCORE] [--min_distance MIN_DISTANCE]
[--min_boundary_distance MIN_BOUNDARY_DISTANCE] [--mask_edges] [--number_of_peaks NUMBER_OF_PEAKS] [--peak_oversampling PEAK_OVERSAMPLING] [--subtomogram_box_size SUBTOMOGRAM_BOX_SIZE] [--mask_subtomograms] [--invert_target_contrast]
[--wedge_mask WEDGE_MASK] [--n_false_positives N_FALSE_POSITIVES]
Peak Calling for Template Matching Outputs
options:
-h, --help show this help message and exit
Input:
--input_file INPUT_FILE [INPUT_FILE ...]
Path to the output of match_template.py.
--target_mask TARGET_MASK
Path to an optional mask applied to template matching scores.
--orientations ORIENTATIONS
Path to file generated using output_format orientations. Can be filtered to exclude false-positive peaks. If this file is provided, peak calling is skipped and corresponding parameters ignored.
Output:
--output_prefix OUTPUT_PREFIX
Output filename, extension will be added based on output_format.
--output_format {orientations,alignment,extraction,relion,backmapping,average}
Available output formats:orientations (translation, rotation, and score), alignment (aligned template to target based on orientations), extraction (extract regions around peaks from targets, i.e. subtomograms), relion (perform extraction step and
generate corresponding star files), backmapping (map template to target using identified peaks),average (extract matched regions from target and average them).
Peak Calling:
--peak_caller {PeakCallerSort,PeakCallerMaximumFilter,PeakCallerFast,PeakCallerRecursiveMasking,PeakCallerScipy}
Peak caller for local maxima identification.
--minimum_score MINIMUM_SCORE
Minimum score from which peaks will be considered.
--maximum_score MAXIMUM_SCORE
Maximum score until which peaks will be considered.
--min_distance MIN_DISTANCE
Minimum distance between peaks.
--min_boundary_distance MIN_BOUNDARY_DISTANCE
Minimum distance of peaks to target edges.
--mask_edges Whether candidates should not be identified from scores that were computed from padded densities. Superseded by min_boundary_distance.
--number_of_peaks NUMBER_OF_PEAKS
Upper limit of peaks to call, subject to filtering parameters. Default 1000. If minimum_score is provided all peaks scoring higher will be reported.
--peak_oversampling PEAK_OVERSAMPLING
1 / factor equals voxel precision, e.g. 2 detects half voxel translations. Useful for matching structures to electron density maps.
Additional Parameters:
--subtomogram_box_size SUBTOMOGRAM_BOX_SIZE
Subtomogram box size, by default equal to the centered template. Will be padded to even values if output_format is relion.
--mask_subtomograms Whether to mask subtomograms using the template mask. The mask will be rotated according to determined angles.
--invert_target_contrast
Whether to invert the target contrast.
--wedge_mask WEDGE_MASK
Path to file used as ctf_mask for output_format relion.
--n_false_positives N_FALSE_POSITIVES
Number of accepted false-positives picks to determine minimum score.
)
== 2024-05-23 11:52:33,477 run.py:221 DEBUG run_cmd: running cmd postprocess.py --help (in /kyukon/scratch/gent/vo/000/gvo00002/vsc40023/easybuild_REGTEST/RHEL8/cascadelake-volta-ib/software/pyTME/0.2.0-foss-2023a-CUDA-12.1.1)
== 2024-05-23 11:52:33,477 run.py:247 INFO running cmd: postprocess.py --help
== 2024-05-23 11:52:54,927 run.py:689 DEBUG cmd "postprocess.py --help" exited with exit code 0 and output:
usage: postprocess.py [-h] --input_file INPUT_FILE [INPUT_FILE ...] [--target_mask TARGET_MASK] [--orientations ORIENTATIONS] --output_prefix OUTPUT_PREFIX [--output_format {orientations,alignment,extraction,relion,backmapping,average}]
[--peak_caller {PeakCallerSort,PeakCallerMaximumFilter,PeakCallerFast,PeakCallerRecursiveMasking,PeakCallerScipy}] [--minimum_score MINIMUM_SCORE] [--maximum_score MAXIMUM_SCORE] [--min_distance MIN_DISTANCE]
[--min_boundary_distance MIN_BOUNDARY_DISTANCE] [--mask_edges] [--number_of_peaks NUMBER_OF_PEAKS] [--peak_oversampling PEAK_OVERSAMPLING] [--subtomogram_box_size SUBTOMOGRAM_BOX_SIZE] [--mask_subtomograms] [--invert_target_contrast]
[--wedge_mask WEDGE_MASK] [--n_false_positives N_FALSE_POSITIVES]
Peak Calling for Template Matching Outputs
options:
-h, --help show this help message and exit
Input:
--input_file INPUT_FILE [INPUT_FILE ...]
Path to the output of match_template.py.
--target_mask TARGET_MASK
Path to an optional mask applied to template matching scores.
--orientations ORIENTATIONS
Path to file generated using output_format orientations. Can be filtered to exclude false-positive peaks. If this file is provided, peak calling is skipped and corresponding parameters ignored.
Output:
--output_prefix OUTPUT_PREFIX
Output filename, extension will be added based on output_format.
--output_format {orientations,alignment,extraction,relion,backmapping,average}
Available output formats:orientations (translation, rotation, and score), alignment (aligned template to target based on orientations), extraction (extract regions around peaks from targets, i.e. subtomograms), relion (perform extraction step and
generate corresponding star files), backmapping (map template to target using identified peaks),average (extract matched regions from target and average them).
Peak Calling:
--peak_caller {PeakCallerSort,PeakCallerMaximumFilter,PeakCallerFast,PeakCallerRecursiveMasking,PeakCallerScipy}
Peak caller for local maxima identification.
--minimum_score MINIMUM_SCORE
Minimum score from which peaks will be considered.
--maximum_score MAXIMUM_SCORE
Maximum score until which peaks will be considered.
--min_distance MIN_DISTANCE
Minimum distance between peaks.
--min_boundary_distance MIN_BOUNDARY_DISTANCE
Minimum distance of peaks to target edges.
--mask_edges Whether candidates should not be identified from scores that were computed from padded densities. Superseded by min_boundary_distance.
--number_of_peaks NUMBER_OF_PEAKS
Upper limit of peaks to call, subject to filtering parameters. Default 1000. If minimum_score is provided all peaks scoring higher will be reported.
--peak_oversampling PEAK_OVERSAMPLING
1 / factor equals voxel precision, e.g. 2 detects half voxel translations. Useful for matching structures to electron density maps.
Additional Parameters:
--subtomogram_box_size SUBTOMOGRAM_BOX_SIZE
Subtomogram box size, by default equal to the centered template. Will be padded to even values if output_format is relion.
--mask_subtomograms Whether to mask subtomograms using the template mask. The mask will be rotated according to determined angles.
--invert_target_contrast
Whether to invert the target contrast.
--wedge_mask WEDGE_MASK
Path to file used as ctf_mask for output_format relion.
--n_false_positives N_FALSE_POSITIVES
Number of accepted false-positives picks to determine minimum score.
== 2024-05-23 11:52:54,927 run.py:725 DEBUG Using default regular expression: (?<![(,-]|\w)(?:error|segmentation fault|failed)(?![(,-]|\.?\w)
== 2024-05-23 11:52:54,927 easyblock.py:3640 INFO sanity check command postprocess.py --help ran successfully! (output: usage: postprocess.py [-h] --input_file INPUT_FILE [INPUT_FILE ...] [--target_mask TARGET_MASK] [--orientations ORIENTATIONS] --output_prefix OUTPUT_PREFIX [--output_format {orientations,alignment,extraction,relion,backmapping,average}]
[--peak_caller {PeakCallerSort,PeakCallerMaximumFilter,PeakCallerFast,PeakCallerRecursiveMasking,PeakCallerScipy}] [--minimum_score MINIMUM_SCORE] [--maximum_score MAXIMUM_SCORE] [--min_distance MIN_DISTANCE]
[--min_boundary_distance MIN_BOUNDARY_DISTANCE] [--mask_edges] [--number_of_peaks NUMBER_OF_PEAKS] [--peak_oversampling PEAK_OVERSAMPLING] [--subtomogram_box_size SUBTOMOGRAM_BOX_SIZE] [--mask_subtomograms] [--invert_target_contrast]
[--wedge_mask WEDGE_MASK] [--n_false_positives N_FALSE_POSITIVES]
Peak Calling for Template Matching Outputs
options:
-h, --help show this help message and exit
Input:
--input_file INPUT_FILE [INPUT_FILE ...]
Path to the output of match_template.py.
--target_mask TARGET_MASK
Path to an optional mask applied to template matching scores.
--orientations ORIENTATIONS
Path to file generated using output_format orientations. Can be filtered to exclude false-positive peaks. If this file is provided, peak calling is skipped and corresponding parameters ignored.
Output:
--output_prefix OUTPUT_PREFIX
Output filename, extension will be added based on output_format.
--output_format {orientations,alignment,extraction,relion,backmapping,average}
Available output formats:orientations (translation, rotation, and score), alignment (aligned template to target based on orientations), extraction (extract regions around peaks from targets, i.e. subtomograms), relion (perform extraction step and
generate corresponding star files), backmapping (map template to target using identified peaks),average (extract matched regions from target and average them).
Peak Calling:
--peak_caller {PeakCallerSort,PeakCallerMaximumFilter,PeakCallerFast,PeakCallerRecursiveMasking,PeakCallerScipy}
Peak caller for local maxima identification.
--minimum_score MINIMUM_SCORE
Minimum score from which peaks will be considered.
--maximum_score MAXIMUM_SCORE
Maximum score until which peaks will be considered.
--min_distance MIN_DISTANCE
Minimum distance between peaks.
--min_boundary_distance MIN_BOUNDARY_DISTANCE
Minimum distance of peaks to target edges.
--mask_edges Whether candidates should not be identified from scores that were computed from padded densities. Superseded by min_boundary_distance.
--number_of_peaks NUMBER_OF_PEAKS
Upper limit of peaks to call, subject to filtering parameters. Default 1000. If minimum_score is provided all peaks scoring higher will be reported.
--peak_oversampling PEAK_OVERSAMPLING
1 / factor equals voxel precision, e.g. 2 detects half voxel translations. Useful for matching structures to electron density maps.
Additional Parameters:
--subtomogram_box_size SUBTOMOGRAM_BOX_SIZE
Subtomogram box size, by default equal to the centered template. Will be padded to even values if output_format is relion.
--mask_subtomograms Whether to mask subtomograms using the template mask. The mask will be rotated according to determined angles.
--invert_target_contrast
Whether to invert the target contrast.
--wedge_mask WEDGE_MASK
Path to file used as ctf_mask for output_format relion.
--n_false_positives N_FALSE_POSITIVES
Number of accepted false-positives picks to determine minimum score.
)
== 2024-05-23 11:52:54,932 run.py:221 DEBUG run_cmd: running cmd preprocess --help (in /kyukon/scratch/gent/vo/000/gvo00002/vsc40023/easybuild_REGTEST/RHEL8/cascadelake-volta-ib/software/pyTME/0.2.0-foss-2023a-CUDA-12.1.1)
== 2024-05-23 11:52:54,932 run.py:247 INFO running cmd: preprocess --help
== 2024-05-23 11:53:16,173 run.py:689 DEBUG cmd "preprocess --help" exited with exit code 0 and output:
usage: preprocess [-h] -i INPUT_FILE -y YAML_FILE -o OUTPUT_FILE [--compress]
Apply preprocessing to an input file based on a provided YAML configuration.
Expected YAML file format:
```yaml
<method_name>:
<parameter1>: <value1>
<parameter2>: <value2>
...
```
options:
-h, --help show this help message and exit
-i INPUT_FILE, --input_file INPUT_FILE
Path to the input data file in CCP4/MRC format.
-y YAML_FILE, --yaml_file YAML_FILE
Path to the YAML configuration file.
-o OUTPUT_FILE, --output_file OUTPUT_FILE
Path to output file in CPP4/MRC format..
--compress Compress the output file using gzip.
== 2024-05-23 11:53:16,173 run.py:725 DEBUG Using default regular expression: (?<![(,-]|\w)(?:error|segmentation fault|failed)(?![(,-]|\.?\w)
== 2024-05-23 11:53:16,173 easyblock.py:3640 INFO sanity check command preprocess --help ran successfully! (output: usage: preprocess [-h] -i INPUT_FILE -y YAML_FILE -o OUTPUT_FILE [--compress]
Apply preprocessing to an input file based on a provided YAML configuration.
Expected YAML file format:
```yaml
<method_name>:
<parameter1>: <value1>
<parameter2>: <value2>
...
```
options:
-h, --help show this help message and exit
-i INPUT_FILE, --input_file INPUT_FILE
Path to the input data file in CCP4/MRC format.
-y YAML_FILE, --yaml_file YAML_FILE
Path to the YAML configuration file.
-o OUTPUT_FILE, --output_file OUTPUT_FILE
Path to output file in CPP4/MRC format..
--compress Compress the output file using gzip.
)
== 2024-05-23 11:53:16,178 run.py:221 DEBUG run_cmd: running cmd preprocess.py --help (in /kyukon/scratch/gent/vo/000/gvo00002/vsc40023/easybuild_REGTEST/RHEL8/cascadelake-volta-ib/software/pyTME/0.2.0-foss-2023a-CUDA-12.1.1)
== 2024-05-23 11:53:16,178 run.py:247 INFO running cmd: preprocess.py --help
== 2024-05-23 11:53:38,406 run.py:689 DEBUG cmd "preprocess.py --help" exited with exit code 0 and output:
usage: preprocess.py [-h] -i INPUT_FILE -y YAML_FILE -o OUTPUT_FILE [--compress]
Apply preprocessing to an input file based on a provided YAML configuration.
Expected YAML file format:
```yaml
<method_name>:
<parameter1>: <value1>
<parameter2>: <value2>
...
```
options:
-h, --help show this help message and exit
-i INPUT_FILE, --input_file INPUT_FILE
Path to the input data file in CCP4/MRC format.
-y YAML_FILE, --yaml_file YAML_FILE
Path to the YAML configuration file.
-o OUTPUT_FILE, --output_file OUTPUT_FILE
Path to output file in CPP4/MRC format..
--compress Compress the output file using gzip.
== 2024-05-23 11:53:38,406 run.py:725 DEBUG Using default regular expression: (?<![(,-]|\w)(?:error|segmentation fault|failed)(?![(,-]|\.?\w)
== 2024-05-23 11:53:38,406 easyblock.py:3640 INFO sanity check command preprocess.py --help ran successfully! (output: usage: preprocess.py [-h] -i INPUT_FILE -y YAML_FILE -o OUTPUT_FILE [--compress]
Apply preprocessing to an input file based on a provided YAML configuration.
Expected YAML file format:
```yaml
<method_name>:
<parameter1>: <value1>
<parameter2>: <value2>
...
```
options:
-h, --help show this help message and exit
-i INPUT_FILE, --input_file INPUT_FILE
Path to the input data file in CCP4/MRC format.
-y YAML_FILE, --yaml_file YAML_FILE
Path to the YAML configuration file.
-o OUTPUT_FILE, --output_file OUTPUT_FILE
Path to output file in CPP4/MRC format..
--compress Compress the output file using gzip.
)
== 2024-05-23 11:53:38,411 run.py:221 DEBUG run_cmd: running cmd preprocessor_gui.py --help (in /kyukon/scratch/gent/vo/000/gvo00002/vsc40023/easybuild_REGTEST/RHEL8/cascadelake-volta-ib/software/pyTME/0.2.0-foss-2023a-CUDA-12.1.1)
== 2024-05-23 11:53:38,411 run.py:247 INFO running cmd: preprocessor_gui.py --help
== 2024-05-23 11:54:16,497 run.py:689 DEBUG cmd "preprocessor_gui.py --help" exited with exit code 0 and output:
usage: preprocessor_gui.py [-h]
GUI for preparing and analyzing template matching runs.
options:
-h, --help show this help message and exit
== 2024-05-23 11:54:16,497 run.py:725 DEBUG Using default regular expression: (?<![(,-]|\w)(?:error|segmentation fault|failed)(?![(,-]|\.?\w)
== 2024-05-23 11:54:16,497 easyblock.py:3640 INFO sanity check command preprocessor_gui.py --help ran successfully! (output: usage: preprocessor_gui.py [-h]
GUI for preparing and analyzing template matching runs.
options:
-h, --help show this help message and exit
)
== 2024-05-23 11:54:16,502 run.py:221 DEBUG run_cmd: running cmd napari --plugin-info|grep napari-density-io (in /kyukon/scratch/gent/vo/000/gvo00002/vsc40023/easybuild_REGTEST/RHEL8/cascadelake-volta-ib/software/pyTME/0.2.0-foss-2023a-CUDA-12.1.1)
== 2024-05-23 11:54:16,502 run.py:247 INFO running cmd: napari --plugin-info|grep napari-density-io
== 2024-05-23 11:54:53,931 run.py:689 DEBUG cmd "napari --plugin-info|grep napari-density-io" exited with exit code 0 and output:
napari-density-io 0.0.1 commands (7), readers (1), writers (2), widgets (3), sample_data (1)
== 2024-05-23 11:54:53,931 run.py:725 DEBUG Using default regular expression: (?<![(,-]|\w)(?:error|segmentation fault|failed)(?![(,-]|\.?\w)
== 2024-05-23 11:54:53,931 easyblock.py:3640 INFO sanity check command napari --plugin-info|grep napari-density-io ran successfully! (output: napari-density-io 0.0.1 commands (7), readers (1), writers (2), widgets (3), sample_data (1)
)
== 2024-05-23 11:54:53,934 environment.py:93 INFO Environment variable PYTHONNOUSERSITE set to 1 (previously undefined)
== 2024-05-23 11:54:53,934 pythonpackage.py:972 INFO Detection of downloaded depenencies enabled, checking output of installation command...
== 2024-05-23 11:54:53,934 pythonpackage.py:229 INFO Determining pip version...
== 2024-05-23 11:54:53,934 run.py:221 DEBUG run_cmd: running cmd /user/gent/400/vsc40023/eb_scratch/RHEL8/cascadelake-volta-ib/software/Python/3.11.3-GCCcore-12.3.0/bin/python -m pip --version (in /kyukon/scratch/gent/vo/000/gvo00002/vsc40023/easybuild_REGTEST/RHEL8/cascadelake-volta-ib/software/pyTME/0.2.0-foss-2023a-CUDA-12.1.1)
== 2024-05-23 11:54:53,934 run.py:247 INFO running cmd: /user/gent/400/vsc40023/eb_scratch/RHEL8/cascadelake-volta-ib/software/Python/3.11.3-GCCcore-12.3.0/bin/python -m pip --version
== 2024-05-23 11:54:58,963 run.py:689 DEBUG cmd "/user/gent/400/vsc40023/eb_scratch/RHEL8/cascadelake-volta-ib/software/Python/3.11.3-GCCcore-12.3.0/bin/python -m pip --version" exited with exit code 0 and output:
pip 23.1.2 from /user/gent/400/vsc40023/eb_scratch/RHEL8/cascadelake-volta-ib/software/Python/3.11.3-GCCcore-12.3.0/lib/python3.11/site-packages/pip (python 3.11)
== 2024-05-23 11:54:58,963 run.py:725 DEBUG Using default regular expression: (?<![(,-]|\w)(?:error|segmentation fault|failed)(?![(,-]|\.?\w)
== 2024-05-23 11:54:58,963 pythonpackage.py:237 INFO Found pip version: 23.1.2
== 2024-05-23 11:54:58,964 run.py:180 DEBUG run_cmd: Output of "/user/gent/400/vsc40023/eb_scratch/RHEL8/cascadelake-volta-ib/software/Python/3.11.3-GCCcore-12.3.0/bin/python -m pip check" will be logged to /tmp/eb-icrv8ens/easybuild-run_cmd-8cyyr51t.log
== 2024-05-23 11:54:58,967 run.py:221 DEBUG run_cmd: running cmd /user/gent/400/vsc40023/eb_scratch/RHEL8/cascadelake-volta-ib/software/Python/3.11.3-GCCcore-12.3.0/bin/python -m pip check (in /kyukon/scratch/gent/vo/000/gvo00002/vsc40023/easybuild_REGTEST/RHEL8/cascadelake-volta-ib/software/pyTME/0.2.0-foss-2023a-CUDA-12.1.1)
== 2024-05-23 11:54:58,967 run.py:247 INFO running cmd: /user/gent/400/vsc40023/eb_scratch/RHEL8/cascadelake-volta-ib/software/Python/3.11.3-GCCcore-12.3.0/bin/python -m pip check
== 2024-05-23 11:55:05,770 run.py:725 DEBUG Using default regular expression: (?<![(,-]|\w)(?:error|segmentation fault|failed)(?![(,-]|\.?\w)
== 2024-05-23 11:55:05,770 pythonpackage.py:558 INFO Running command '/user/gent/400/vsc40023/eb_scratch/RHEL8/cascadelake-volta-ib/software/Python/3.11.3-GCCcore-12.3.0/bin/python -m pip list --isolated --disable-pip-version-check --format json'
== 2024-05-23 11:55:07,344 pythonpackage.py:567 DEBUG Command '/user/gent/400/vsc40023/eb_scratch/RHEL8/cascadelake-volta-ib/software/Python/3.11.3-GCCcore-12.3.0/bin/python -m pip list --isolated --disable-pip-version-check --format json' returned with 0: stdout: [{"name": "aiohttp", "version": "3.8.5"}, {"name": "aiosignal", "version": "1.3.1"}, {"name": "alabaster", "version": "0.7.13"}, {"name": "alembic", "version": "1.11.3"}, {"name": "annotated-types", "version": "0.6.0"}, {"name": "anyio", "version": "3.7.1"}, {"name": "app-model", "version": "0.2.4"}, {"name": "appdirs", "version": "1.4.4"}, {"name": "argon2-cffi", "version": "23.1.0"}, {"name": "argon2-cffi-bindings", "version": "21.2.0"}, {"name": "arrow", "version": "1.2.3"}, {"name": "asn1crypto", "version": "1.5.1"}, {"name": "asttokens", "version": "2.2.1"}, {"name": "async-generator", "version": "1.10"}, {"name": "async-lru", "version": "2.0.4"}, {"name": "async-timeout", "version": "4.0.2"}, {"name": "atomicwrites", "version": "1.4.1"}, {"name": "attrs", "version": "23.1.0"}, {"name": "Babel", "version": "2.12.1"}, {"name": "backcall", "version": "0.2.0"}, {"name": "backports.entry-points-selectable", "version": "1.2.0"}, {"name": "backports.functools-lru-cache", "version": "1.6.5"}, {"name": "batchspawner", "version": "1.2.0"}, {"name": "bcrypt", "version": "4.0.1"}, {"name": "beautifulsoup4", "version": "4.12.2"}, {"name": "beniget", "version": "0.4.1"}, {"name": "bitstring", "version": "4.0.2"}, {"name": "bleach", "version": "6.0.0"}, {"name": "blist", "version": "1.3.6"}, {"name": "bokeh", "version": "3.2.2"}, {"name": "Bottleneck", "version": "1.3.7"}, {"name": "build", "version": "0.10.0"}, {"name": "CacheControl", "version": "0.12.14"}, {"name": "cachey", "version": "0.2.1"}, {"name": "cachy", "version": "0.3.0"}, {"name": "certifi", "version": "2023.5.7"}, {"name": "certipy", "version": "0.1.3"}, {"name": "cffi", "version": "1.15.1"}, {"name": "chardet", "version": "5.1.0"}, {"name": "charset-normalizer", "version": "3.1.0"}, {"name": "cleo", "version": "2.0.1"}, {"name": "click", "version": "8.1.3"}, {"name": "cloudpickle", "version": "2.2.1"}, {"name": "colorama", "version": "0.4.6"}, {"name": "comm", "version": "0.1.4"}, {"name": "commonmark", "version": "0.9.1"}, {"name": "contourpy", "version": "1.0.7"}, {"name": "crashtest", "version": "0.4.1"}, {"name": "cryptography", "version": "41.0.1"}, {"name": "cupy", "version": "13.0.0"}, {"name": "cycler", "version": "0.11.0"}, {"name": "Cython", "version": "0.29.35"}, {"name": "dask", "version": "2023.9.2"}, {"name": "dask-jobqueue", "version": "0.8.2"}, {"name": "dask-mpi", "version": "2022.4.0"}, {"name": "deap", "version": "1.4.0"}, {"name": "debugpy", "version": "1.6.7.post1"}, {"name": "decorator", "version": "5.1.1"}, {"name": "defusedxml", "version": "0.7.1"}, {"name": "deprecation", "version": "2.1.0"}, {"name": "distlib", "version": "0.3.6"}, {"name": "distributed", "version": "2023.9.2"}, {"name": "distro", "version": "1.8.0"}, {"name": "docopt", "version": "0.6.2"}, {"name": "docrep", "version": "0.3.2"}, {"name": "docstring-parser", "version": "0.15"}, {"name": "docutils", "version": "0.20.1"}, {"name": "doit", "version": "0.36.0"}, {"name": "dulwich", "version": "0.21.5"}, {"name": "ecdsa", "version": "0.18.0"}, {"name": "editables", "version": "0.3"}, {"name": "exceptiongroup", "version": "1.1.1"}, {"name": "execnet", "version": "1.9.0"}, {"name": "executing", "version": "1.2.0"}, {"name": "expecttest", "version": "0.1.5"}, {"name": "fastjsonschema", "version": "2.18.0"}, {"name": "fastrlock", "version": "0.8.2"}, {"name": "filelock", "version": "3.12.2"}, {"name": "flit_core", "version": "3.9.0"}, {"name": "fonttools", "version": "4.42.0"}, {"name": "freetype-py", "version": "2.4.0"}, {"name": "frozenlist", "version": "1.4.0"}, {"name": "fsspec", "version": "2023.6.0"}, {"name": "future", "version": "0.18.3"}, {"name": "gast", "version": "0.5.4"}, {"name": "glob2", "version": "0.7"}, {"name": "gmpy2", "version": "2.1.5"}, {"name": "greenlet", "version": "2.0.2"}, {"name": "h5py", "version": "3.9.0"}, {"name": "hatch-fancy-pypi-readme", "version": "23.1.0"}, {"name": "hatch-jupyter-builder", "version": "0.8.3"}, {"name": "hatch-nodejs-version", "version": "0.3.1"}, {"name": "hatch-vcs", "version": "0.3.0"}, {"name": "hatchling", "version": "1.18.0"}, {"name": "HeapDict", "version": "1.0.1"}, {"name": "hsluv", "version": "5.0.3"}, {"name": "html5lib", "version": "1.1"}, {"name": "idna", "version": "3.4"}, {"name": "imageio", "version": "2.33.1"}, {"name": "imagesize", "version": "1.4.1"}, {"name": "importlib-metadata", "version": "6.7.0"}, {"name": "importlib-resources", "version": "5.12.0"}, {"name": "imread", "version": "0.7.4"}, {"name": "in-n-out", "version": "0.1.9"}, {"name": "iniconfig", "version": "2.0.0"}, {"name": "installer", "version": "0.7.0"}, {"name": "intervaltree", "version": "3.1.0"}, {"name": "intreehooks", "version": "1.0"}, {"name": "ipaddress", "version": "1.0.23"}, {"name": "ipykernel", "version": "6.25.1"}, {"name": "ipython", "version": "8.14.0"}, {"name": "ipython-genutils", "version": "0.2.0"}, {"name": "ipywidgets", "version": "8.1.0"}, {"name": "jaraco.classes", "version": "3.2.3"}, {"name": "jedi", "version": "0.19.0"}, {"name": "jeepney", "version": "0.8.0"}, {"name": "Jinja2", "version": "3.1.2"}, {"name": "joblib", "version": "1.2.0"}, {"name": "json5", "version": "0.9.14"}, {"name": "jsonschema", "version": "4.17.3"}, {"name": "jsonschema-specifications", "version": "2023.7.1"}, {"name": "jupyter_client", "version": "8.3.0"}, {"name": "jupyter_core", "version": "5.3.1"}, {"name": "jupyter-events", "version": "0.7.0"}, {"name": "jupyter-lsp", "version": "2.2.0"}, {"name": "jupyter_packaging", "version": "0.12.3"}, {"name": "jupyter-resource-usage", "version": "1.0.0"}, {"name": "jupyter_server", "version": "2.7.2"}, {"name": "jupyter_server_proxy", "version": "4.0.0"}, {"name": "jupyter_server_terminals", "version": "0.4.4"}, {"name": "jupyter-telemetry", "version": "0.1.0"}, {"name": "jupyterhub", "version": "4.0.2"}, {"name": "jupyterhub-jwtauthenticator-v2", "version": "2.0.3"}, {"name": "jupyterhub-ldapauthenticator", "version": "1.3.2"}, {"name": "jupyterhub-nativeauthenticator", "version": "1.2.0"}, {"name": "jupyterhub-simplespawner", "version": "0.1"}, {"name": "jupyterhub-systemdspawner", "version": "1.0.1"}, {"name": "jupyterlab", "version": "4.0.5"}, {"name": "jupyterlab-pygments", "version": "0.2.2"}, {"name": "jupyterlab_server", "version": "2.24.0"}, {"name": "jupyterlab-widgets", "version": "3.0.8"}, {"name": "jupyterlmod", "version": "4.0.3"}, {"name": "keyring", "version": "23.13.1"}, {"name": "keyrings.alt", "version": "4.2.0"}, {"name": "kiwisolver", "version": "1.4.4"}, {"name": "lazy_loader", "version": "0.3"}, {"name": "ldap3", "version": "2.9.1"}, {"name": "liac-arff", "version": "2.5.0"}, {"name": "locket", "version": "1.0.0"}, {"name": "lockfile", "version": "0.12.2"}, {"name": "lxml", "version": "4.9.2"}, {"name": "magicgui", "version": "0.8.1"}, {"name": "Mako", "version": "1.2.4"}, {"name": "markdown-it-py", "version": "3.0.0"}, {"name": "MarkupSafe", "version": "2.1.3"}, {"name": "matplotlib", "version": "3.7.2"}, {"name": "matplotlib-inline", "version": "0.1.6"}, {"name": "mdurl", "version": "0.1.2"}, {"name": "meson", "version": "1.1.1"}, {"name": "meson-python", "version": "0.13.2"}, {"name": "mistune", "version": "3.0.1"}, {"name": "mock", "version": "5.0.2"}, {"name": "more-itertools", "version": "9.1.0"}, {"name": "mpi4py", "version": "3.1.4"}, {"name": "mpmath", "version": "1.3.0"}, {"name": "mrcfile", "version": "1.5.0"}, {"name": "msgpack", "version": "1.0.5"}, {"name": "multidict", "version": "6.0.4"}, {"name": "mypy-extensions", "version": "1.0.0"}, {"name": "napari", "version": "0.4.19.post1"}, {"name": "napari-console", "version": "0.0.9"}, {"name": "napari-density-io", "version": "0.0.1"}, {"name": "napari-plugin-engine", "version": "0.2.0"}, {"name": "napari-svg", "version": "0.1.10"}, {"name": "nbclassic", "version": "1.0.0"}, {"name": "nbclient", "version": "0.8.0"}, {"name": "nbconvert", "version": "7.7.4"}, {"name": "nbformat", "version": "5.9.2"}, {"name": "nest-asyncio", "version": "1.5.7"}, {"name": "netaddr", "version": "0.8.0"}, {"name": "netifaces", "version": "0.11.0"}, {"name": "networkx", "version": "3.1"}, {"name": "notebook", "version": "7.0.2"}, {"name": "notebook_shim", "version": "0.2.3"}, {"name": "npe2", "version": "0.7.4"}, {"name": "numexpr", "version": "2.8.4"}, {"name": "numpy", "version": "1.25.1"}, {"name": "numpydoc", "version": "1.6.0"}, {"name": "oauthlib", "version": "3.2.2"}, {"name": "onetimepass", "version": "1.0.1"}, {"name": "overrides", "version": "7.4.0"}, {"name": "packaging", "version": "23.1"}, {"name": "pamela", "version": "1.1.0"}, {"name": "pandas", "version": "2.0.3"}, {"name": "pandocfilters", "version": "1.5.0"}, {"name": "parso", "version": "0.8.3"}, {"name": "partd", "version": "1.4.0"}, {"name": "pastel", "version": "0.2.1"}, {"name": "pathlib2", "version": "2.3.7.post1"}, {"name": "pathspec", "version": "0.11.1"}, {"name": "pbr", "version": "5.11.1"}, {"name": "pexpect", "version": "4.8.0"}, {"name": "pickleshare", "version": "0.7.5"}, {"name": "Pillow", "version": "9.5.0"}, {"name": "Pint", "version": "0.23"}, {"name": "pip", "version": "23.1.2"}, {"name": "pkginfo", "version": "1.9.6"}, {"name": "platformdirs", "version": "3.8.0"}, {"name": "pluggy", "version": "1.2.0"}, {"name": "ply", "version": "3.11"}, {"name": "poetry", "version": "1.5.1"}, {"name": "poetry-core", "version": "1.6.1"}, {"name": "poetry-plugin-export", "version": "1.4.0"}, {"name": "pooch", "version": "1.7.0"}, {"name": "prometheus-client", "version": "0.17.1"}, {"name": "prompt-toolkit", "version": "3.0.39"}, {"name": "protobuf", "version": "4.24.0"}, {"name": "psutil", "version": "5.9.5"}, {"name": "psygnal", "version": "0.9.5"}, {"name": "ptyprocess", "version": "0.7.0"}, {"name": "pure-eval", "version": "0.2.2"}, {"name": "py", "version": "1.11.0"}, {"name": "py-expression-eval", "version": "0.3.14"}, {"name": "pyasn1", "version": "0.5.0"}, {"name": "pybind11", "version": "2.11.1"}, {"name": "pycparser", "version": "2.21"}, {"name": "pycryptodome", "version": "3.18.0"}, {"name": "pycurl", "version": "7.45.2"}, {"name": "pydantic", "version": "2.5.3"}, {"name": "pydantic-compat", "version": "0.1.2"}, {"name": "pydantic_core", "version": "2.14.6"}, {"name": "pydevtool", "version": "0.3.0"}, {"name": "pyFFTW", "version": "0.13.1"}, {"name": "Pygments", "version": "2.15.1"}, {"name": "PyJWT", "version": "2.8.0"}, {"name": "pylev", "version": "1.4.0"}, {"name": "PyNaCl", "version": "1.5.0"}, {"name": "PyOpenGL", "version": "3.1.7"}, {"name": "PyOpenGL-accelerate", "version": "3.1.7"}, {"name": "pyOpenSSL", "version": "23.2.0"}, {"name": "pyparsing", "version": "3.1.0"}, {"name": "pyproject_hooks", "version": "1.0.0"}, {"name": "pyproject-metadata", "version": "0.7.1"}, {"name": "PyQt5", "version": "5.15.10"}, {"name": "PyQt5-sip", "version": "12.13.0"}, {"name": "PyQtWebEngine", "version": "5.15.6"}, {"name": "pyrsistent", "version": "0.19.3"}, {"name": "pytest", "version": "7.4.0"}, {"name": "pytest-xdist", "version": "3.3.1"}, {"name": "python-dateutil", "version": "2.8.2"}, {"name": "python-json-logger", "version": "2.0.7"}, {"name": "pythran", "version": "0.13.1"}, {"name": "pytme", "version": "0.2.0"}, {"name": "pytoml", "version": "0.1.21"}, {"name": "pytz", "version": "2023.3"}, {"name": "PyWavelets", "version": "1.4.1"}, {"name": "PyYAML", "version": "6.0"}, {"name": "pyzmq", "version": "25.1.1"}, {"name": "qtconsole", "version": "5.5.1"}, {"name": "QtPy", "version": "2.4.1"}, {"name": "rapidfuzz", "version": "2.15.1"}, {"name": "referencing", "version": "0.30.2"}, {"name": "regex", "version": "2023.6.3"}, {"name": "requests", "version": "2.31.0"}, {"name": "requests-toolbelt", "version": "1.0.0"}, {"name": "rfc3339-validator", "version": "0.1.4"}, {"name": "rfc3986-validator", "version": "0.1.1"}, {"name": "rich", "version": "13.7.1"}, {"name": "rich-click", "version": "1.6.1"}, {"name": "rpds-py", "version": "0.9.2"}, {"name": "ruamel.yaml", "version": "0.17.32"}, {"name": "ruamel.yaml.clib", "version": "0.2.7"}, {"name": "scandir", "version": "1.10.0"}, {"name": "scikit-image", "version": "0.22.0"}, {"name": "scikit-learn", "version": "1.3.1"}, {"name": "scipy", "version": "1.11.1"}, {"name": "SecretStorage", "version": "3.3.3"}, {"name": "semantic-version", "version": "2.10.0"}, {"name": "Send2Trash", "version": "1.8.2"}, {"name": "setuptools", "version": "67.7.2"}, {"name": "setuptools-scm", "version": "7.1.0"}, {"name": "shellingham", "version": "1.5.0"}, {"name": "simpervisor", "version": "1.0.0"}, {"name": "simplegeneric", "version": "0.8.1"}, {"name": "simplejson", "version": "3.19.1"}, {"name": "six", "version": "1.16.0"}, {"name": "sklearn", "version": "0.0"}, {"name": "sniffio", "version": "1.3.0"}, {"name": "snowballstemmer", "version": "2.2.0"}, {"name": "sortedcontainers", "version": "2.4.0"}, {"name": "soupsieve", "version": "2.4.1"}, {"name": "Sphinx", "version": "7.0.1"}, {"name": "sphinx-bootstrap-theme", "version": "0.8.1"}, {"name": "sphinxcontrib-applehelp", "version": "1.0.4"}, {"name": "sphinxcontrib-devhelp", "version": "1.0.2"}, {"name": "sphinxcontrib-htmlhelp", "version": "2.0.1"}, {"name": "sphinxcontrib-jsmath", "version": "1.0.1"}, {"name": "sphinxcontrib-qthelp", "version": "1.0.3"}, {"name": "sphinxcontrib-serializinghtml", "version": "1.1.5"}, {"name": "sphinxcontrib-websupport", "version": "1.2.4"}, {"name": "SQLAlchemy", "version": "2.0.20"}, {"name": "stack-data", "version": "0.6.2"}, {"name": "superqt", "version": "0.6.1"}, {"name": "sympy", "version": "1.12"}, {"name": "tabulate", "version": "0.9.0"}, {"name": "tblib", "version": "2.0.0"}, {"name": "terminado", "version": "0.17.1"}, {"name": "threadpoolctl", "version": "3.1.0"}, {"name": "tifffile", "version": "2023.7.18"}, {"name": "tinycss2", "version": "1.2.1"}, {"name": "toml", "version": "0.10.2"}, {"name": "tomli", "version": "2.0.1"}, {"name": "tomli_w", "version": "1.0.0"}, {"name": "tomlkit", "version": "0.11.8"}, {"name": "toolz", "version": "0.12.0"}, {"name": "torch", "version": "2.1.2"}, {"name": "tornado", "version": "6.3.2"}, {"name": "tqdm", "version": "4.66.1"}, {"name": "traitlets", "version": "5.9.0"}, {"name": "trove-classifiers", "version": "2023.5.24"}, {"name": "typer", "version": "0.9.0"}, {"name": "typing_extensions", "version": "4.6.3"}, {"name": "tzdata", "version": "2023.3"}, {"name": "ujson", "version": "5.8.0"}, {"name": "urllib3", "version": "1.26.16"}, {"name": "versioneer", "version": "0.29"}, {"name": "virtualenv", "version": "20.23.1"}, {"name": "vispy", "version": "0.14.1"}, {"name": "wcwidth", "version": "0.2.6"}, {"name": "webencodings", "version": "0.5.1"}, {"name": "websocket-client", "version": "1.6.1"}, {"name": "wheel", "version": "0.40.0"}, {"name": "widgetsnbextension", "version": "4.0.8"}, {"name": "wrapt", "version": "1.15.0"}, {"name": "xlrd", "version": "2.0.1"}, {"name": "xyzservices", "version": "2023.7.0"}, {"name": "yarl", "version": "1.9.2"}, {"name": "zict", "version": "3.0.0"}, {"name": "zipfile36", "version": "0.1.3"}, {"name": "zipp", "version": "3.15.0"}]
; stderr:
== 2024-05-23 11:55:07,344 pythonpackage.py:1066 INFO Found 0 invalid packages out of 340 packages
== 2024-05-23 11:55:07,543 build_log.py:171 ERROR EasyBuild crashed with an error (at easybuild/easybuild-framework/easybuild/base/exceptions.py:126 in __init__): `/user/gent/400/vsc40023/eb_scratch/RHEL8/cascadelake-volta-ib/software/Python/3.11.3-GCCcore-12.3.0/bin/python -m pip check` failed:
npe2 0.7.4 has requirement build>=1, but you have build 0.10.0.
jupyter-events 0.7.0 has requirement jsonschema[format-nongpl]>=4.18.0, but you have jsonschema 4.17.3.
(at easybuild/easybuild-easyblocks/easybuild/easyblocks/generic/pythonpackage.py:1079 in sanity_check_step)
== 2024-05-23 11:55:07,543 build_log.py:267 INFO ... (took 4 mins 39 secs)
== 2024-05-23 11:55:07,546 config.py:699 DEBUG software install path as specified by 'installpath' and 'subdir_software': /user/gent/400/vsc40023/eb_scratch/RHEL8/cascadelake-volta-ib/software
== 2024-05-23 11:55:07,546 filetools.py:2013 INFO Removing lock /user/gent/400/vsc40023/eb_scratch/RHEL8/cascadelake-volta-ib/software/.locks/_user_gent_400_vsc40023_eb_scratch_RHEL8_cascadelake-volta-ib_software_pyTME_0.2.0-foss-2023a-CUDA-12.1.1.lock...
== 2024-05-23 11:55:07,548 filetools.py:383 INFO Path /user/gent/400/vsc40023/eb_scratch/RHEL8/cascadelake-volta-ib/software/.locks/_user_gent_400_vsc40023_eb_scratch_RHEL8_cascadelake-volta-ib_software_pyTME_0.2.0-foss-2023a-CUDA-12.1.1.lock successfully removed.
== 2024-05-23 11:55:07,548 filetools.py:2017 INFO Lock removed: /user/gent/400/vsc40023/eb_scratch/RHEL8/cascadelake-volta-ib/software/.locks/_user_gent_400_vsc40023_eb_scratch_RHEL8_cascadelake-volta-ib_software_pyTME_0.2.0-foss-2023a-CUDA-12.1.1.lock
== 2024-05-23 11:55:07,548 easyblock.py:4291 WARNING build failed (first 300 chars): `/user/gent/400/vsc40023/eb_scratch/RHEL8/cascadelake-volta-ib/software/Python/3.11.3-GCCcore-12.3.0/bin/python -m pip check` failed:
npe2 0.7.4 has requirement build>=1, but you have build 0.10.0.
jupyter-events 0.7.0 has requirement jsonschema[format-nongpl]>=4.18.0, but you have jsonschema 4.17.3
== 2024-05-23 11:55:07,549 easyblock.py:328 INFO Closing log for application name pyTME version 0.2.0
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