7293664 report - OSSR Reports

Repository Information

Repository Name: IndexedConv/IndexedConv: v1.3.2
Record ID: 7293664
Repository URL: git+https://github.com/IndexedConv/IndexedConv.git
Tool Type: SoftwareSourceCode
Version: 1.3.2

Results

Indicator	generated by	evidence	Value	Run Status	Check passed
https://w3id.org/everse/i/indicators/codemeta_completeness	Codemeta Completeness Tool	Codemeta completeness = 32.4%, minimal threshold to consider this check to pass is set to 20.0%. Found ['codeRepository', 'programmingLanguage', 'applicationCategory', 'downloadUrl', 'softwareVersion', 'author', 'dateCreated', 'dateModified', 'datePublished', 'funder', 'keywords', 'license', 'version', 'isPartOf', 'description', 'identifier', 'name', 'identifier', 'name', 'maintainer', 'contIntegration', 'funding', 'issueTracker', 'readme'] keys in codemeta file.	0.32432432432432434	✅	✅
https://w3id.org/everse/i/indicators/codemeta_completeness	Codemeta Completeness Tool	Codemeta completeness = 32.4%, minimal threshold to consider this check to pass is set to 50.0%. Found ['codeRepository', 'programmingLanguage', 'applicationCategory', 'downloadUrl', 'softwareVersion', 'author', 'dateCreated', 'dateModified', 'datePublished', 'funder', 'keywords', 'license', 'version', 'isPartOf', 'description', 'identifier', 'name', 'identifier', 'name', 'maintainer', 'contIntegration', 'funding', 'issueTracker', 'readme'] keys in codemeta file.	0.32432432432432434	✅	❌
https://w3id.org/everse/i/indicators/doi_presence	SOMEF	DOI not found in SOMEF output. Confidence: 0.0%		❌	❌
https://w3id.org/everse/i/indicators/codemeta_discrepancy	SOMEF, Codemeta Completeness Tool	Comparison value: 0.6764705882352942, Threshold: 0.5, Status: True	0.6764705882352942	❌	✅

Results Output

https://w3id.org/everse/i/indicators/codemeta_completeness

Status: CompletedActionStatus
Value: 0.32
Evidence: Codemeta completeness = 32.4%, minimal threshold to consider this check to pass is set to 20.0%. Found ['codeRepository', 'programmingLanguage', 'applicationCategory', 'downloadUrl', 'softwareVersion', 'author', 'dateCreated', 'dateModified', 'datePublished', 'funder', 'keywords', 'license', 'version', 'isPartOf', 'description', 'identifier', 'name', 'identifier', 'name', 'maintainer', 'contIntegration', 'funding', 'issueTracker', 'readme'] keys in codemeta file.
Output:

{"pass": true, "value": 0.32432432432432434, "codemeta_dict": {"@context": "https://doi.org/10.5063/schema/codemeta-2.0", "@type": "SoftwareSourceCode", "license": "https://spdx.org/licenses/MIT", "codeRepository": "git+https://github.com/IndexedConv/IndexedConv.git", "contIntegration": "https://github.com/IndexedConv/IndexedConv/actions", "dateCreated": "2018-12-05", "datePublished": "2019-01-14", "dateModified": "2022-01-20", "downloadUrl": "https://zenodo.org/record/5884046/files/IndexedConv/IndexedConv-v1.3.1.zip", "issueTracker": "https://github.com/IndexedConv/IndexedConv/issues", "name": "IndexedConv", "version": "1.3.2", "softwareVersion": "1.3.2", "maintainer": {"@type": "Person", "givenName": "Mikael", "familyName": "Jacquemont", "@id": "https://orcid.org/0000-0002-4012-6930", "email": "jacquemont@lapp.in2p3.fr", "affiliation": {"@type": "Organization", "name": "Univ. Savoie Mont-Blanc, CNRS, LAPP"}}, "readme": "https://raw.githubusercontent.com/IndexedConv/IndexedConv/master/README.rst", "identifier": "10.5281/zenodo.2542651", "description": "The indexed operations allow the user to perform convolution and pooling on non-Euclidian grids of data given that the neighbors pixels of each pixel is known and provided.\n\nIt gives an alternative to masking or resampling the data in order to apply standard Euclidian convolution. This solution has been developed in order to apply convolutional neural networks to data from physics experiments that propose specific pixels arrangements.\n\nIt is used in the GammaLearn project for the Cherenkov Telescope Array.\n\nHere you will find the code for the indexed operations as well as applied examples. The current implementation has been done for pytorch.", "applicationCategory": "deep learning", "funding": "ESCAPE 824064, ASTERICS 653477", "isPartOf": "https://purl.org/gammalearn", "funder": {"@type": "Organization", "name": "European Union's Horizon 2020 research and innovation programme"}, "keywords": ["CTA"], "programmingLanguage": ["Python 3"], "author": [{"@type": "Person", "givenName": "Thomas", "familyName": "Vuillaume", "@id": "https://orcid.org/0000-0002-5686-2078", "email": "thomas.vuillaume@lapp.in2p3.fr", "affiliation": {"@type": "Organization", "name": "Univ. Savoie Mont-Blanc, CNRS, LAPP"}}, {"@type": "Person", "givenName": "Mikael", "familyName": "Jacquemont", "@id": "https://orcid.org/0000-0002-4012-6930", "email": "jacquemont@lapp.in2p3.fr", "affiliation": {"@type": "Organization", "name": "Univ. Savoie Mont-Blanc, CNRS, LAPP"}}, {"@type": "Person", "givenName": "Antiga", "familyName": "Luca", "affiliation": {"@type": "Organization", "name": "Orobix"}}]}, "threshold": 0.2}

https://w3id.org/everse/i/indicators/codemeta_completeness

Status: CompletedActionStatus
Value: 0.32
Evidence: Codemeta completeness = 32.4%, minimal threshold to consider this check to pass is set to 50.0%. Found ['codeRepository', 'programmingLanguage', 'applicationCategory', 'downloadUrl', 'softwareVersion', 'author', 'dateCreated', 'dateModified', 'datePublished', 'funder', 'keywords', 'license', 'version', 'isPartOf', 'description', 'identifier', 'name', 'identifier', 'name', 'maintainer', 'contIntegration', 'funding', 'issueTracker', 'readme'] keys in codemeta file.
Output:

{"pass": false, "value": 0.32432432432432434, "codemeta_dict": {"@context": "https://doi.org/10.5063/schema/codemeta-2.0", "@type": "SoftwareSourceCode", "license": "https://spdx.org/licenses/MIT", "codeRepository": "git+https://github.com/IndexedConv/IndexedConv.git", "contIntegration": "https://github.com/IndexedConv/IndexedConv/actions", "dateCreated": "2018-12-05", "datePublished": "2019-01-14", "dateModified": "2022-01-20", "downloadUrl": "https://zenodo.org/record/5884046/files/IndexedConv/IndexedConv-v1.3.1.zip", "issueTracker": "https://github.com/IndexedConv/IndexedConv/issues", "name": "IndexedConv", "version": "1.3.2", "softwareVersion": "1.3.2", "maintainer": {"@type": "Person", "givenName": "Mikael", "familyName": "Jacquemont", "@id": "https://orcid.org/0000-0002-4012-6930", "email": "jacquemont@lapp.in2p3.fr", "affiliation": {"@type": "Organization", "name": "Univ. Savoie Mont-Blanc, CNRS, LAPP"}}, "readme": "https://raw.githubusercontent.com/IndexedConv/IndexedConv/master/README.rst", "identifier": "10.5281/zenodo.2542651", "description": "The indexed operations allow the user to perform convolution and pooling on non-Euclidian grids of data given that the neighbors pixels of each pixel is known and provided.\n\nIt gives an alternative to masking or resampling the data in order to apply standard Euclidian convolution. This solution has been developed in order to apply convolutional neural networks to data from physics experiments that propose specific pixels arrangements.\n\nIt is used in the GammaLearn project for the Cherenkov Telescope Array.\n\nHere you will find the code for the indexed operations as well as applied examples. The current implementation has been done for pytorch.", "applicationCategory": "deep learning", "funding": "ESCAPE 824064, ASTERICS 653477", "isPartOf": "https://purl.org/gammalearn", "funder": {"@type": "Organization", "name": "European Union's Horizon 2020 research and innovation programme"}, "keywords": ["CTA"], "programmingLanguage": ["Python 3"], "author": [{"@type": "Person", "givenName": "Thomas", "familyName": "Vuillaume", "@id": "https://orcid.org/0000-0002-5686-2078", "email": "thomas.vuillaume@lapp.in2p3.fr", "affiliation": {"@type": "Organization", "name": "Univ. Savoie Mont-Blanc, CNRS, LAPP"}}, {"@type": "Person", "givenName": "Mikael", "familyName": "Jacquemont", "@id": "https://orcid.org/0000-0002-4012-6930", "email": "jacquemont@lapp.in2p3.fr", "affiliation": {"@type": "Organization", "name": "Univ. Savoie Mont-Blanc, CNRS, LAPP"}}, {"@type": "Person", "givenName": "Antiga", "familyName": "Luca", "affiliation": {"@type": "Organization", "name": "Orobix"}}]}, "threshold": 0.5}

https://w3id.org/everse/i/indicators/codemeta_discrepancy

Status: FailedActionStatus
Value: 0.68
Evidence: Comparison value: 0.6764705882352942, Threshold: 0.5, Status: True
Output:

{"pass": true, "value": 0.6764705882352942, "threshold": 0.5, "results": {"completeness_1": 0.32432432432432434, "codemeta_version_1": "codemeta-2.0", "codemeta_version_2": "codemeta-3.0", "completeness_2": 0.0, "missing_keys_1": ["runtimePlatform", "targetProduct", "applicationSubCategory", "fileSize", "installUrl", "memoryRequirements", "operatingSystem", "permissions", "processorRequirements", "releaseNotes", "softwareHelp", "softwareRequirements", "storageRequirements", "supportingData", "citation", "contributor", "copyrightHolder", "copyrightYear", "editor", "encoding", "fileFormat", "producer", "provider", "publisher", "sponsor", "isAccessibleForFree", "hasPart", "position", "sameAs", "url", "relatedLink", "givenName", "familyName", "email", "affiliation", "address", "", "", "softwareSuggestions", "buildInstructions", "developmentStatus", "embargoDate", "referencePublication", "creator", "", "", "", "endDate", "roleName", "startDate"], "missing_keys_2": ["codeRepository", "programmingLanguage", "runtimePlatform", "targetProduct", "applicationCategory", "applicationSubCategory", "downloadUrl", "fileSize", "installUrl", "memoryRequirements", "operatingSystem", "permissions", "processorRequirements", "releaseNotes", "softwareHelp", "softwareRequirements", "softwareVersion", "storageRequirements", "supportingData", "author", "citation", "contributor", "copyrightHolder", "copyrightYear", "dateCreated", "dateModified", "datePublished", "editor", "encoding", "fileFormat", "funder", "keywords", "license", "producer", "provider", "publisher", "sponsor", "version", "isAccessibleForFree", "isPartOf", "hasPart", "position", "description", "identifier", "name", "sameAs", "url", "relatedLink", "givenName", "familyName", "email", "affiliation", "identifier", "name", "address", "", "", "softwareSuggestions", "maintainer", "continuousIntegration", "buildInstructions", "developmentStatus", "embargoEndDate", "funding", "issueTracker", "referencePublication", "readme", "creator", "review", "reviewAspect", "reviewBody", "endDate", "roleName", "startDate"], "existing_keys_1": ["codeRepository", "programmingLanguage", "applicationCategory", "downloadUrl", "softwareVersion", "author", "dateCreated", "dateModified", "datePublished", "funder", "keywords", "license", "version", "isPartOf", "description", "identifier", "name", "identifier", "name", "maintainer", "contIntegration", "funding", "issueTracker", "readme"], "existing_keys_2": [], "differences": {"codeRepository": {"value_in_1": "git+https://github.com/IndexedConv/IndexedConv.git", "value_in_2": null}, "programmingLanguage": {"value_in_1": ["Python 3"], "value_in_2": null}, "applicationCategory": {"value_in_1": "deep learning", "value_in_2": null}, "downloadUrl": {"value_in_1": "https://zenodo.org/record/5884046/files/IndexedConv/IndexedConv-v1.3.1.zip", "value_in_2": null}, "softwareVersion": {"value_in_1": "1.3.2", "value_in_2": null}, "author": {"value_in_1": [{"@type": "Person", "givenName": "Thomas", "familyName": "Vuillaume", "@id": "https://orcid.org/0000-0002-5686-2078", "email": "thomas.vuillaume@lapp.in2p3.fr", "affiliation": {"@type": "Organization", "name": "Univ. Savoie Mont-Blanc, CNRS, LAPP"}}, {"@type": "Person", "givenName": "Mikael", "familyName": "Jacquemont", "@id": "https://orcid.org/0000-0002-4012-6930", "email": "jacquemont@lapp.in2p3.fr", "affiliation": {"@type": "Organization", "name": "Univ. Savoie Mont-Blanc, CNRS, LAPP"}}, {"@type": "Person", "givenName": "Antiga", "familyName": "Luca", "affiliation": {"@type": "Organization", "name": "Orobix"}}], "value_in_2": null}, "dateCreated": {"value_in_1": "2018-12-05", "value_in_2": null}, "dateModified": {"value_in_1": "2022-01-20", "value_in_2": null}, "datePublished": {"value_in_1": "2019-01-14", "value_in_2": null}, "funder": {"value_in_1": {"@type": "Organization", "name": "European Union's Horizon 2020 research and innovation programme"}, "value_in_2": null}, "keywords": {"value_in_1": ["CTA"], "value_in_2": null}, "license": {"value_in_1": "https://spdx.org/licenses/MIT", "value_in_2": null}, "version": {"value_in_1": "1.3.2", "value_in_2": null}, "isPartOf": {"value_in_1": "https://purl.org/gammalearn", "value_in_2": null}, "description": {"value_in_1": "The indexed operations allow the user to perform convolution and pooling on non-Euclidian grids of data given that the neighbors pixels of each pixel is known and provided.\n\nIt gives an alternative to masking or resampling the data in order to apply standard Euclidian convolution. This solution has been developed in order to apply convolutional neural networks to data from physics experiments that propose specific pixels arrangements.\n\nIt is used in the GammaLearn project for the Cherenkov Telescope Array.\n\nHere you will find the code for the indexed operations as well as applied examples. The current implementation has been done for pytorch.", "value_in_2": null}, "identifier": {"value_in_1": "10.5281/zenodo.2542651", "value_in_2": null}, "name": {"value_in_1": "IndexedConv", "value_in_2": null}, "maintainer": {"value_in_1": {"@type": "Person", "givenName": "Mikael", "familyName": "Jacquemont", "@id": "https://orcid.org/0000-0002-4012-6930", "email": "jacquemont@lapp.in2p3.fr", "affiliation": {"@type": "Organization", "name": "Univ. Savoie Mont-Blanc, CNRS, LAPP"}}, "value_in_2": null}, "contIntegration": {"value_in_1": "https://github.com/IndexedConv/IndexedConv/actions", "value_in_2": null}, "funding": {"value_in_1": "ESCAPE 824064, ASTERICS 653477", "value_in_2": null}, "issueTracker": {"value_in_1": "https://github.com/IndexedConv/IndexedConv/issues", "value_in_2": null}, "readme": {"value_in_1": "https://raw.githubusercontent.com/IndexedConv/IndexedConv/master/README.rst", "value_in_2": null}}, "equivalences": {"runtimePlatform": null, "targetProduct": null, "applicationSubCategory": null, "fileSize": null, "installUrl": null, "memoryRequirements": null, "operatingSystem": null, "permissions": null, "processorRequirements": null, "releaseNotes": null, "softwareHelp": null, "softwareRequirements": null, "storageRequirements": null, "supportingData": null, "citation": null, "contributor": null, "copyrightHolder": null, "copyrightYear": null, "editor": null, "encoding": null, "fileFormat": null, "producer": null, "provider": null, "publisher": null, "sponsor": null, "isAccessibleForFree": null, "hasPart": null, "position": null, "sameAs": null, "url": null, "relatedLink": null, "givenName": null, "familyName": null, "email": null, "affiliation": null, "address": null, "": null, "softwareSuggestions": null, "buildInstructions": null, "developmentStatus": null, "embargoDate": null, "referencePublication": null, "creator": null, "endDate": null, "roleName": null, "startDate": null}}}

Logs

Log File: docs/records/7293664/7293664_somef_log.txt

Running SOMEF on repository: https://github.com/IndexedConv/IndexedConv
SOftware Metadata Extraction Framework (SOMEF) Command Line Interface

Error: Please provide a config.json file or run somef configure.

[Somef Tool] Error occurred while processing record ID 7293664: somef file docs/records/7293664/7293664_somef.json does not exist

Log File: docs/records/7293664/7293664_codemeta_completeness_tool_log.txt

[codemeta completeness tool] Running Codemeta Completeness Tool on record ID: 7293664

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