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0.0.3 synthetic_data_metrics-0.0.3-py3-none-any.whl

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Project: synthetic-data-metrics
Version: 0.0.3
Filename: synthetic_data_metrics-0.0.3-py3-none-any.whl
Download: [link]
Size: 14157
MD5: 3dbce6bf8becc84f4a4a5128438857d4
SHA256: f5d4d8ac07c136cdec49547c23ce20c4515f38822967fb9dde023f6207ac5c99
Uploaded: 2023-03-17 08:51:57 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt

METADATA

Metadata-Version: 2.1
Name: synthetic-data-metrics
Version: 0.0.3
Summary: Synthetic Data Metrics is a Python library for evaluating synthetic data quality across a wide range of data types (image, tabular, time series, language) and approaches to evaluation.
Author: K.Court
Author-Email: kate.court[at]ncl.ac.uk
Home-Page: https://github.com/NewcastleRSE/synthetic_data_metrics/tree/dev
Classifier: Programming Language :: Python :: 3.10
Classifier: License :: OSI Approved :: MIT License
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Description-Content-Type: text/markdown
[Description omitted; length: 3590 characters]

WHEEL

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RECORD

Path Digest Size
synthetic_data_metrics/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
synthetic_data_metrics/datasets.py sha256=HC5RuMP1n8V5XWF6PpsnRGn-A3xHs8S1dfw3Sqdlq8I 3425
synthetic_data_metrics/evaluator.py sha256=5XHBR0Kf3B3q9my7qhBCeQJyDyJhp-n_uL4g-ihTaKQ 10957
synthetic_data_metrics/plot.py sha256=tnHmtKJFkwAK5bluPaUfXICRubDEvzhZ2FGxNXOy4KU 5029
synthetic_data_metrics/utils.py sha256=f42rBd0tgqajojEDytaVFDUJheDV1FjQEHr2YCffy0E 9193
synthetic_data_metrics/metrics/__init__.py sha256=yR7fZ8AlAfqITSA1rkR7b3HGq0gFamZzwu4PcJ1p5tA 214
synthetic_data_metrics/metrics/image_metrics.py sha256=w0P6HW21xl5o2i1VU3FwgQSA7_ouSG4tc2jpJQ5Y1uo 2757
synthetic_data_metrics/metrics/ts_metrics.py sha256=WRG-B67RYbwG3yhCnOhq8kpR_q9g3Hn8fBYwhuJixbo 1968
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synthetic_data_metrics-0.0.3.dist-info/WHEEL sha256=G16H4A3IeoQmnOrYV4ueZGKSjhipXx8zc8nu9FGlvMA 92
synthetic_data_metrics-0.0.3.dist-info/top_level.txt sha256=P6O6ry3PZJ-Z_zdD1PV8fGdgbcrhec_Yi_oF-cqsC5U 23
synthetic_data_metrics-0.0.3.dist-info/RECORD — —

top_level.txt

synthetic_data_metrics