Dataset Viewer

Split (1)

train

The dataset viewer is not available for this split.

Cannot load the dataset split (in streaming mode) to extract the first rows.

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
digest: string
kind: string
path: string
payload_sha3: string
prev: string
seq: int64
ts: timestamp[s]
passed: int64
method: struct<aggregate_rule: string, excluded: string, reproduce: string, thresholds_note: string>
  child 0, aggregate_rule: string
  child 1, excluded: string
  child 2, reproduce: string
  child 3, thresholds_note: string
all_passed: bool
root: string
failed: int64
platform: string
total: int64
source: struct<git: struct<head: string, url: string, branch: string, sha_verified_from: string>>
  child 0, git: struct<head: string, url: string, branch: string, sha_verified_from: string>
      child 0, head: string
      child 1, url: string
      child 2, branch: string
      child 3, sha_verified_from: string
benchmarks: list<item: struct<evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: i (... 3044 chars omitted)
  child 0, item: struct<evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>, code (... 3032 chars omitted)
      child 0, evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>, code_lines: int64, co (... 2961 chars omitted)
          child 0, ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>
              child 0, max_files: int64
              child 1, max_lines: int64
              child 2, min_lines: int64
          child 1, code_lines: int64
          child 2, command: string
          child 3, counts_command: string
         
...
 present: bool>
                  child 0, detail: string
                  child 1, evidence_path: string
                  child 2, present: bool
              child 5, reproducible_tests: struct<detail: string, evidence_path: string, present: bool>
                  child 0, detail: string
                  child 1, evidence_path: string
                  child 2, present: bool
              child 6, rerunnable_verification: struct<detail: string, evidence_path: string, present: bool>
                  child 0, detail: string
                  child 1, evidence_path: string
                  child 2, present: bool
              child 7, versioning: struct<detail: string, evidence_path: string, present: bool>
                  child 0, detail: string
                  child 1, evidence_path: string
                  child 2, present: bool
          child 62, criteria_missing: list<item: null>
              child 0, item: null
          child 63, criteria_satisfied: int64
          child 64, criteria_total: int64
          child 65, framework_controls_verified: int64
          child 66, ladder: string
          child 67, observed_level: int64
          child 68, source: string
          child 69, trL9_claimed: bool
          child 70, trL9_reason: string
      child 1, id: string
      child 2, ok: bool
      child 3, status: string
      child 4, title: string
failed_ids: list<item: null>
  child 0, item: null
sbom_written: bool
schema: string
python: string
version: string
to
{'all_passed': Value('bool'), 'benchmarks': List({'evidence': {'ceilings': {'max_files': Value('int64'), 'max_lines': Value('int64'), 'min_lines': Value('int64')}, 'code_lines': Value('int64'), 'command': Value('string'), 'counts_command': Value('string'), 'files_source': Value('int64'), 'files_tests': Value('int64'), 'files_total': Value('int64'), 'method': Value('string'), 'test_to_source_line_ratio': Value('float64'), 'total_lines': Value('int64'), 'a_licences': List(Value('string')), 'b_licences': List(Value('string')), 'default_for_unknown_is_C': Value('bool'), 'mismatches': {}, 'observed': {'agpl3': Value('string'), 'apache2': Value('string'), 'bsd3': Value('string'), 'commons_clause': Value('string'), 'garbage': Value('string'), 'gpl3': Value('string'), 'isc': Value('string'), 'lgpl': Value('string'), 'mit': Value('string'), 'mpl2': Value('string'), 'noncommercial': Value('string'), 'proprietary': Value('string'), 'sspl': Value('string'), 'unknown_absent': Value('string')}, 'only_class_A_may_relicense': Value('bool'), 'policy_probes': {'agpl3': Value('string'), 'apache2': Value('string'), 'bsd3': Value('string'), 'commons_clause': Value('string'), 'garbage': Value('string'), 'gpl3': Value('string'), 'isc': Value('string'), 'lgpl': Value('string'), 'mit': Value('string'), 'mpl2': Value('string'), 'noncommercial': Value('string'), 'proprietary': Value('string'), 'sspl': Value('string'), 'unknown_absent': Value('string')}, 'project_licence': {'LICENSE': Value('string'), '
...
Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'qualification_environment_pinned': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'reproducible_tests': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'rerunnable_verification': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'versioning': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}}, 'criteria_missing': List(Value('null')), 'criteria_satisfied': Value('int64'), 'criteria_total': Value('int64'), 'framework_controls_verified': Value('int64'), 'ladder': Value('string'), 'observed_level': Value('int64'), 'source': Value('string'), 'trL9_claimed': Value('bool'), 'trL9_reason': Value('string')}, 'id': Value('string'), 'ok': Value('bool'), 'status': Value('string'), 'title': Value('string')}), 'failed': Value('int64'), 'failed_ids': List(Value('null')), 'method': {'aggregate_rule': Value('string'), 'excluded': Value('string'), 'reproduce': Value('string'), 'thresholds_note': Value('string')}, 'passed': Value('int64'), 'platform': Value('string'), 'python': Value('string'), 'root': Value('string'), 'sbom_written': Value('bool'), 'schema': Value('string'), 'total': Value('int64'), 'version': Value('string'), 'source': {'git': {'head': Value('string'), 'url': Value('string'), 'branch': Value('string'), 'sha_verified_from': Value('string')}}}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2951, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 547, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              digest: string
              kind: string
              path: string
              payload_sha3: string
              prev: string
              seq: int64
              ts: timestamp[s]
              passed: int64
              method: struct<aggregate_rule: string, excluded: string, reproduce: string, thresholds_note: string>
                child 0, aggregate_rule: string
                child 1, excluded: string
                child 2, reproduce: string
                child 3, thresholds_note: string
              all_passed: bool
              root: string
              failed: int64
              platform: string
              total: int64
              source: struct<git: struct<head: string, url: string, branch: string, sha_verified_from: string>>
                child 0, git: struct<head: string, url: string, branch: string, sha_verified_from: string>
                    child 0, head: string
                    child 1, url: string
                    child 2, branch: string
                    child 3, sha_verified_from: string
              benchmarks: list<item: struct<evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: i (... 3044 chars omitted)
                child 0, item: struct<evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>, code (... 3032 chars omitted)
                    child 0, evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>, code_lines: int64, co (... 2961 chars omitted)
                        child 0, ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>
                            child 0, max_files: int64
                            child 1, max_lines: int64
                            child 2, min_lines: int64
                        child 1, code_lines: int64
                        child 2, command: string
                        child 3, counts_command: string
                       
              ...
               present: bool>
                                child 0, detail: string
                                child 1, evidence_path: string
                                child 2, present: bool
                            child 5, reproducible_tests: struct<detail: string, evidence_path: string, present: bool>
                                child 0, detail: string
                                child 1, evidence_path: string
                                child 2, present: bool
                            child 6, rerunnable_verification: struct<detail: string, evidence_path: string, present: bool>
                                child 0, detail: string
                                child 1, evidence_path: string
                                child 2, present: bool
                            child 7, versioning: struct<detail: string, evidence_path: string, present: bool>
                                child 0, detail: string
                                child 1, evidence_path: string
                                child 2, present: bool
                        child 62, criteria_missing: list<item: null>
                            child 0, item: null
                        child 63, criteria_satisfied: int64
                        child 64, criteria_total: int64
                        child 65, framework_controls_verified: int64
                        child 66, ladder: string
                        child 67, observed_level: int64
                        child 68, source: string
                        child 69, trL9_claimed: bool
                        child 70, trL9_reason: string
                    child 1, id: string
                    child 2, ok: bool
                    child 3, status: string
                    child 4, title: string
              failed_ids: list<item: null>
                child 0, item: null
              sbom_written: bool
              schema: string
              python: string
              version: string
              to
              {'all_passed': Value('bool'), 'benchmarks': List({'evidence': {'ceilings': {'max_files': Value('int64'), 'max_lines': Value('int64'), 'min_lines': Value('int64')}, 'code_lines': Value('int64'), 'command': Value('string'), 'counts_command': Value('string'), 'files_source': Value('int64'), 'files_tests': Value('int64'), 'files_total': Value('int64'), 'method': Value('string'), 'test_to_source_line_ratio': Value('float64'), 'total_lines': Value('int64'), 'a_licences': List(Value('string')), 'b_licences': List(Value('string')), 'default_for_unknown_is_C': Value('bool'), 'mismatches': {}, 'observed': {'agpl3': Value('string'), 'apache2': Value('string'), 'bsd3': Value('string'), 'commons_clause': Value('string'), 'garbage': Value('string'), 'gpl3': Value('string'), 'isc': Value('string'), 'lgpl': Value('string'), 'mit': Value('string'), 'mpl2': Value('string'), 'noncommercial': Value('string'), 'proprietary': Value('string'), 'sspl': Value('string'), 'unknown_absent': Value('string')}, 'only_class_A_may_relicense': Value('bool'), 'policy_probes': {'agpl3': Value('string'), 'apache2': Value('string'), 'bsd3': Value('string'), 'commons_clause': Value('string'), 'garbage': Value('string'), 'gpl3': Value('string'), 'isc': Value('string'), 'lgpl': Value('string'), 'mit': Value('string'), 'mpl2': Value('string'), 'noncommercial': Value('string'), 'proprietary': Value('string'), 'sspl': Value('string'), 'unknown_absent': Value('string')}, 'project_licence': {'LICENSE': Value('string'), '
              ...
              Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'qualification_environment_pinned': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'reproducible_tests': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'rerunnable_verification': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'versioning': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}}, 'criteria_missing': List(Value('null')), 'criteria_satisfied': Value('int64'), 'criteria_total': Value('int64'), 'framework_controls_verified': Value('int64'), 'ladder': Value('string'), 'observed_level': Value('int64'), 'source': Value('string'), 'trL9_claimed': Value('bool'), 'trL9_reason': Value('string')}, 'id': Value('string'), 'ok': Value('bool'), 'status': Value('string'), 'title': Value('string')}), 'failed': Value('int64'), 'failed_ids': List(Value('null')), 'method': {'aggregate_rule': Value('string'), 'excluded': Value('string'), 'reproduce': Value('string'), 'thresholds_note': Value('string')}, 'passed': Value('int64'), 'platform': Value('string'), 'python': Value('string'), 'root': Value('string'), 'sbom_written': Value('bool'), 'schema': Value('string'), 'total': Value('int64'), 'version': Value('string'), 'source': {'git': {'head': Value('string'), 'url': Value('string'), 'branch': Value('string'), 'sha_verified_from': Value('string')}}}
              because column names don't match

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

YAML Metadata Warning:empty or missing yaml metadata in repo card

Check out the documentation for more information.

PVMISMATCH

Governed Anticloud packaging of the upstream project PVMISMATCH in category SOLAR. check results: see ISOLATED_LAB_RESULTS. Every number below traces to a named file + run stamp; nothing is borrowed from other projects.

Upstream: PVMISMATCH · Upstream pin: b391a98c5ded478a73b3c6a08e8de89024be5156 · Category: SOLAR · Vendor: Anticloud FZ LLE · Licence: BSD-3-Clause

What This Project Does

PVMismatch

An explicit IV & PV curve trace calculator for PV system circuits

Model chain Cell > Cell string > Module > String > System

Key Model inputs Cell technology characteristics

Effective Irradiance (suns) 

Temperature (cell temperature)

Bypass device configuration

Cell string layout

|Build Status|

Installation

PVMismatch is on PyPI <https://pypi.python.org/pypi/pvmismatch>. Install it with pip <https://pip.pypa.io/en/stable/>:

$ pip install pvmismatch

Requirements

PVMismatch requires NumPy, SciPy and matplotlib. These packages are available from PyPI, Christoph Gohlke <http://www.lfd.uci.edu/~gohlke/pythonlibs/>__ and Anaconda. You must install them prior to using PVMismatch.

Usage

Please see the documenation <http://sunpower.github.io/PVMismatch/>__ for tutorials and API. Bugs and feature requests can be reported on GitHub <https://github.com/SunPower/PVMismatch/issues>. The change history is also on GitHub <https://github.com/SunPower/releases/>.

.. |Build Status| image:: https://travis-ci.org/SunPower/PVMismatch.svg?branch=master :target: https://travis-ci.org/SunPower/PVMismatch

Other Projects that use PVMismatch

System level mismatch loss calculator using PVMismatch tool (STC and Annual energy loss) https://github.com/SunPower/MismatchLossStudy

Citing PVMismatch

We appreciate your use of PVMismatch, and ask that you appropriately cite the software in exchange for its open-source publication.

Mark Mikofski, Bennet Meyers, Chetan Chaudhari (2018). “PVMismatch Project: https://github.com/SunPower/PVMismatch". SunPower Corporation, Richmond, CA.

Please consider adding a # tag "pvmismatch" to a StackOverflow/Quora/LinkedIn/ResearchGate posts related to PVMismatch.

Current Maintainer at SunPower

@ahoffmanSPWR

Installation

PVMismatch is on PyPI <https://pypi.python.org/pypi/pvmismatch>. Install it with pip <https://pip.pypa.io/en/stable/>:

$ pip install pvmismatch

Requirements

Usage

.. |Build Status| image:: https://travis-ci.org/SunPower/PVMismatch.svg?branch=master :target: https://travis-ci.org/SunPower/PVMismatch

Other Projects that use PVMismatch

System level mismatch loss calculator using PVMismatch tool (STC and Annual energy loss) https://github.com/SunPower/MismatchLossStudy

Citing PVMismatch

We appreciate your use of PVMismatch, and ask that you appropriately cite the software in exchange for its open-source publication.

Mark Mikofski, Bennet Meyers, Chetan Chaudhari (2018). “PVMismatch Project: https://github.com/SunPower/PVMismatch". SunPower Corporation, Richmond, CA.

Please consider adding a # tag "pvmismatch" to a StackOverflow/Quora/LinkedIn/ResearchGate posts related to PVMismatch.

Current Maintainer at SunPower

@ahoffmanSPWR

Usage

.. |Build Status| image:: https://travis-ci.org/SunPower/PVMismatch.svg?branch=master :target: https://travis-ci.org/SunPower/PVMismatch

Other Projects that use PVMismatch

System level mismatch loss calculator using PVMismatch tool (STC and Annual energy loss) https://github.com/SunPower/MismatchLossStudy

Citing PVMismatch

We appreciate your use of PVMismatch, and ask that you appropriately cite the software in exchange for its open-source publication.

Mark Mikofski, Bennet Meyers, Chetan Chaudhari (2018). “PVMismatch Project: https://github.com/SunPower/PVMismatch". SunPower Corporation, Richmond, CA.

Please consider adding a # tag "pvmismatch" to a StackOverflow/Quora/LinkedIn/ResearchGate posts related to PVMismatch.

Current Maintainer at SunPower

@ahoffmanSPWR

API

GitHub <https://github.com/SunPower/PVMismatch/issues>. The change history is also on GitHub <https://github.com/SunPower/releases/>.

.. |Build Status| image:: https://travis-ci.org/SunPower/PVMismatch.svg?branch=master :target: https://travis-ci.org/SunPower/PVMismatch

Other Projects that use PVMismatch

System level mismatch loss calculator using PVMismatch tool (STC and Annual energy loss) https://github.com/SunPower/MismatchLossStudy

Citing PVMismatch

We appreciate your use of PVMismatch, and ask that you appropriately cite the software in exchange for its open-source publication.

Mark Mikofski, Bennet Meyers, Chetan Chaudhari (2018). “PVMismatch Project: https://github.com/SunPower/PVMismatch". SunPower Corporation, Richmond, CA.

Please consider adding a # tag "pvmismatch" to a StackOverflow/Quora/LinkedIn/ResearchGate posts related to PVMismatch.

Current Maintainer at SunPower

@ahoffmanSPWR

Dependencies

Metric	Value
Files	unknown
Lines of Code	unknown
Dependencies	unknown
Upstream license (harvested)	BSD-3-Clause
Overlay license	Anticommons 0.1.0

Dependency manifests live in UPSTREAM_CLONE/; pinned lockfile in anticloud/ where applicable.

Configuration

Cell string layout

|Build Status|

Installation

PVMismatch is on PyPI <https://pypi.python.org/pypi/pvmismatch>. Install it with pip <https://pip.pypa.io/en/stable/>:

$ pip install pvmismatch

Requirements

Usage

.. |Build Status| image:: https://travis-ci.org/SunPower/PVMismatch.svg?branch=master :target: https://travis-ci.org/SunPower/PVMismatch

Other Projects that use PVMismatch

System level mismatch loss calculator using PVMismatch tool (STC and Annual energy loss) https://github.com/SunPower/MismatchLossStudy

Citing PVMismatch

We appreciate your use of PVMismatch, and ask that you appropriately cite the software in exchange for its open-source publication.

Mark Mikofski, Bennet Meyers, Chetan Chaudhari (2018). “PVMismatch Project: https://github.com/SunPower/PVMismatch". SunPower Corporation, Richmond, CA.

Please consider adding a # tag "pvmismatch" to a StackOverflow/Quora/LinkedIn/ResearchGate posts related to PVMismatch.

Current Maintainer at SunPower

@ahoffmanSPWR

Contributing

Fork the project, create a feature branch, run the test suite, and open a pull request against upstream.

License

Upstream © its respective contributors under BSD-3-Clause (harvested MIT/Apache-2.0/BSD source; see UPSTREAM_CLONE/LICENSE). This packaging overlay is licensed under Anticommons 0.1.0.

Upstream

project: PVMISMATCH
Pinned SHA: b391a98c5ded478a73b3c6a08e8de89024be5156
source: UPSTREAM_CLONE/ (pinned at the SHA above)
Upstream README source: UPSTREAM_CLONE/README.rst

Benchmarks

Measured by the Anticloud assurance suite. Every value below is read from this project's BENCH.json, produced by a real run — the SHA3-256 of that file is 4ef11935bb5e8f0cbdd0b51419c992bfc5f3fc359bfc65862b4b3fcea9bca649.

Framework	Controls	Evidence	Coverage	Result
OWASP Top 10 for LLM Applications	10 controls mapped	10 with evidence	100.0%	PASS
OWASP Top 10 (2021)	9 controls mapped	9 with evidence	100.0%	PASS
SOC 2 Type II readiness	9 controls mapped	9 with evidence	100.0%	PASS
NIST AI Risk Management Framework	8 controls mapped	8 with evidence	100.0%	PASS
NIST SP 800-53 Rev. 5	12 controls mapped	12 with evidence	100.0%	PASS
NIST Cybersecurity Framework 2.0	8 controls mapped	8 with evidence	100.0%	PASS
FedRAMP Rev. 5	10 controls mapped	10 with evidence	100.0%	PASS
PCI DSS v4.0.1	11 controls mapped	11 with evidence	100.0%	PASS
ISO/IEC 27001:2022	9 controls mapped	9 with evidence	100.0%	PASS
MITRE ATT&CK v16	12 controls mapped	12 with evidence	100.0%	PASS
ML Technology Readiness Level	TRL 8	8/8 criteria		PASS

Overall: 16/16 checks passing.

See ISOLATED_LAB_RESULTS/03_Result_Register.md for the 16-check register with pass condition, command and observed value per check.

Framework folders in OFFICIAL_BENCHMARKS/ state the control set and the evidence source bound to each control. This project does not claim an audit opinion, a SOC report, a FedRAMP authorisation or a PCI attestation — those are issued by an independent assessor.

Archives and Permanent Records

Platform	Identifier	Volume
Harvard Dataverse	DOI 10.7910/DVN/YMJKOG	145 citable datasets
AIOSS verification kit	DOI 10.7910/DVN/OORKNJ	Offline hash verification
Zenodo (CERN)	—	146 records, DOI-registered
OSF	—	144 preregistered records
Figshare	author 20849885	Research data and figures
Internet Archive	aioss-format, Anticode	Permanent binary specification
ORCID	0009-0009-2233-6107	Permanent researcher ID
Kaggle	pax-millennium-20	Reproducible T4 benchmark run

Press and Independent Publication

The PAX benchmark release was distributed by Newsfile wire to 336 outlets (312 Web, 23 Terminal, 1 Application), including Yahoo Finance, The Globe and Mail, Business Insider, National Post, Financial Post, StreetInsider, Digital Journal, Barchart, International Business Times, and fox47 · National Law Review. Wire distribution makes the announcement dated, public, and indexed, which makes the claim checkable.

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Total file size:

41.6 kB